Final Year IEEE Project 2013-2014 - Grid Computing Project Title and Abstract

Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad |

Pondicherry | Trivandrum | Salem | Erode | Tirunelveli

http://www.elysiumtechnologies.com, [email protected]

13 Years of Experience

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Kerala & Karnataka.

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Around 250 Developers & 20

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227-230 Church Road, Anna Nagar, Madurai – 625020.

0452-4390702, 4392702, + 91-9944793398.

[email protected], [email protected]

S.P.Towers, No.81 Valluvar Kottam High Road, Nungambakkam,

Chennai - 600034. 044-42072702, +91-9600354638,

[email protected]

15, III Floor, SI Towers, Melapudur main Road, Trichy – 620001.

0431-4002234, + 91-9790464324.

[email protected]

577/4, DB Road, RS Puram, Opp to KFC, Coimbatore – 641002

0422- 4377758, +91-9677751577.

[email protected]

mailto:[email protected]

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Plot No: 4, C Colony, P&T Extension, Perumal puram, Tirunelveli-

627007. 0462-2532104, +919677733255,

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1st Floor, A.R.IT Park, Rasi Color Scan Building, Ramanathapuram

- 623501. 04567-223225,

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Road, Opp. Bus stand, Erode-638 011. 0424-4030055, +91-

9677748477 [email protected]

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4200640 +91-9677704822

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TNHB A-Block, D.no.10, Opp: Hotel Ganesh Near Busstand. Salem

– 636007, 0427-4042220, +91-9894444716.

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ETPL

GC-001

Smart Grid Last-Mile Communications Model and Its Application to the Study of

Leased Broadband Wired-Access

Abstract: This paper addresses the modeling of specific Smart Grid (SG) communication requirements from

a data networking research perspective, as a general approach to the study of different access technologies

suitable for the last mile (LM). SGLM networks serve customers' Energy Services Interfaces. From

functional descriptions of SG, a traffic model is developed. It is then applied to the study of an access

architecture based on leased lines from local broadband access providers. This permits consideration of the

potential starvation of domestic traffic, which is avoided by applying well-known traffic management

techniques. From previous results obtained for a purpose-built WiMAX SGLM network, the intuition that a

leased broadband access yields lower latencies is verified. In general, the proposed traffic model simplifies

the design of benchmarks for the comparison of candidate access technologies.

ETPL

GC-002

Performance Analysis of Multiuser Selection Scheme in Dynamic Home Area Networks

for Smart Grid Communications

In this paper, multiuser selection scheme is employed in dynamic home area networks (HANs) for smart

grid communications, to reduce the effects of fading at the receiver part of smart meter. The performance of

multiuser selection scheme is evaluated in two cases: in the absence of interference and in the presence of

multiuser interference (MUI). In the former case, the closed-form capacity outage probability as well as the

numerical values of the bit error rate (BER) are obtained via the probability density function (PDF) of signal

to noise ratio (SNR) that is derived from the amplitude distribution property of the classic indoor Saleh-

Valenzuela (S-V) channel. In the latter case, the multiuser interference cancellation coefficient as a random

variable is added for the calculation of signal to interference noise ratio (SINR). In addition, due to free

space path loss and log-normal shadowing, the sum of MUI is treated as another log-normal-distributed

random variable by exploiting central limit theorem. Numerical results show that the performance of

multiuser selection scheme in HANs of smart grid is due to several factors, i.e., total number of devices in

HANs, traffic intensity, modulation scheme, and multiuser interference cancellation coefficient, etc.

ETPL

GC-003

Optimizations of Power Consumption and Supply in the Smart Grid: Analysis of the

Impact of Data Communication Reliability

Abstract: Data communications infrastructure will play an important role to transfer various information in

smart grid. In this paper, we consider the reliability of the smart grid data communications infrastructure and

its impact on the power consumption and supply optimizations. For optimizing the power consumption, we

consider a deferrable load scheduling method which is modeled by using a constrained Markov decision

process (CMDP) model, taking into account the unavailability of the home area network (HAN) and

neighborhood area network (NAN) gateways. For optimizing the power supply, we consider an economic

dispatch method which is modeled by using stochastic programming (SP), taking into account the

unavailability of the exact power demand and supply information. The power consumption and supply costs

are analyzed. In addition, we show how these costs can be reduced through the deployment of component

redundancy in the smart grid data communications infrastructure.

ETPL

GC-004 Smart Grid Communication: Its Challenges and Opportunities

The necessity to promote smart grid (SG) has been recognized with a strong consensus. The SG integrates

electrical grids and communication infrastructures and forms an intelligent electricity network working with



http://www.elysiumtechnologies.com, [email protected] all connected components to deliver sustainable electricity supplies. Many advanced communication

technologies have been identified for SG applications with a potential to significantly enhance the overall

efficiency of power grids. In this paper, the challenges and applications of communication technologies in

SG are discussed. In particular, we identify three major challenges to implement SG communication

systems, including standards interoperability, cognitive access to unlicensed radio spectra, and cyber

security. The issues to implement SG communications on an evolutional path and its future trends are also

addressed. The aim of this paper is to offer a comprehensive review of state-of-the-art researches on SG

communications.

ETPL

GC-005 Scalable Solutions of Markov Games for Smart-Grid Infrastructure Protection

Abstract: The anticipated proliferation of cyber components for collecting information and controlling

operations of smart grids increases their vulnerability to a variety of cyber attacks. For instance, a large-scale

simultaneous attack on smart meters to destabilize the grid could be feasible via cyber means, which is not

viable via physical attacks alone. The interactions between the providers and attackers of the smart grid and

their optimal strategies can be modeled as a Markov game. However, the computational complexity of such

a game grows exponentially with the size of the infrastructure, making it impractical for smart grids of

reasonable sizes. In this paper, we show that when the players' current interest is a subset of the states only

and they are willing to accept small inaccuracies in the game solutions, many Markov game states can be

pruned. We present a pruning algorithm in which a threshold parameter is used to control qualitatively the

tradeoff between computation time and solution accuracy. The algorithm is iterative with decoupled state

values in each iteration, and we parallelize the state estimations to reduce the overall computation time. We

illustrate with examples that the pruning algorithm reduces the computation time greatly without losing

much precision in the game solutions, and that parallelization further reduces the computation time.

ETPL

GC-006

A Communication-Based Appliance Scheduling Scheme for Consumer-Premise Energy

Management Systems

Abstract: In this paper, a communication-based load scheduling protocol is proposed for in-home appliances

connected over a home area network. Specifically, a joint access and scheduling approach for appliances is

developed to enable in-home appliances to coordinate power usage so that the total energy demand for the

home is kept below a target value. The proposed protocol considers both “schedulable” appliances which

have delay flexibility, and “critical” appliances which consume power as they desire. An optimization

problem is formulated for the energy management controller to decide the target values for each time slot,

by incorporating the variation of electricity prices and distributed wind power uncertainty. We model the

evolution of the protocol as a two-dimensional Markov chain, and derive the steady-state distribution, by

which the average delay of an appliance is then obtained. Simulation results verify the analysis and show

cost saving to customers using the proposed scheme.

ETPL

GC-007

Decentralized Controls and Communications for Autonomous Distribution Networks

in Smart Grid

Abstract: The traditional power grid system was constructed in a centralized and radial topology where

power is generated and delivered from one end to the other. Conventional methods for unidirectional power

flow analysis will no longer be effective to control renewable energy sources implemented at the

consumption sector efficiently; new strategies are called for to facilitate the bidirectional flow incurred by



http://www.elysiumtechnologies.com, [email protected] power production of the distributed energy resource units. The transformation will require intelligent

distribution automation by means of decentralized power management as well as information and

communications technologies to actualize smart grid modernization. In this paper, we design autonomous

distribution networks that take scalability into account by dividing the legacy distribution network into a set

of subnetworks. We tackle the power flow and power balance issues individually in parallel to optimize the

global distribution operation by our proposed power-control method. Meanwhile, we propose an overlay

multi-tier communications infrastructure for the underlying power network to analyze the traffic of data

information and control message required for associated power flow operation. Based on the proposed

schemes, we show that we can potentially improve the utilization of renewable energy production and

achieve data traffic reduction under decentralized operations as compared to legacy centralized management.

ETPL

GC-008

Priority-Based Traffic Scheduling and Utility Optimization for Cognitive Radio

Communication Infrastructure-Based Smart Grid

Abstract: Smart grid can be visualized as an intelligent control system over sensors and communication

platforms. Recently, wireless multimedia sensor networks (WMSNs) have shown its advantages for smart

grid by providing rich surveillance information for grid failure detection and recovery, energy source

monitoring, asset management, security, etc. On the other hand, cognitive radio (CR) networks have been

identified as a key wireless technology to reduce the communication interferences and improve the

bandwidth efficiency for smart grid communication. There is an essential need to use the CR communication

platform to support large-size and time-sensitive multimedia delivery for future smart grid system. In this

paper, we consider the heterogeneous characteristics of smart grid traffic including multimedia and propose

a priority-based traffic scheduling approach for CR communication infrastructure based smart grid system

according to the various traffic types of smart grid such as control commands, multimedia sensing data and

meter readings. Specifically, we develop CR channel allocation and traffic scheduling schemes taking into

consideration of channel switch and spectrum sensing errors, and solve a system utility optimization

problem for smart grid communication system. Our solutions are demonstrated through both analyzes and

simulations. This research opens a new vista of future smart grid communications.

ETPL

GC-009 Time Synchronization Attack in Smart Grid: Impact and Analysis

Abstract: Many operations in power grids, such as fault detection and event location estimation, depend on

precise timing information. In this paper, a novel Time Synchronization Attack (TSA) is proposed to attack

the timing information in smart grid. Since many applications in smart grid utilize synchronous

measurements and most of the measurement devices are equipped with global positioning system (GPS) for

precise timing, it is highly probable to attack the measurement system by spoofing the GPS. The

effectiveness of TSA is demonstrated for three applications of phasor measurement unit (PMU) in smart

grid, namely transmission line fault detection, voltage stability monitoring and event locationing. The

validity of TSA is demonstrated by numerical simulations.

ETPL

GC-010

Toward SWSs Discovery: Mapping from WSDL to OWL-S Based on Ontology Search

and Standardization Engine

Abstract: Semantic Web Services (SWSs) represent the most recent and revolutionary technology developed

for machine-to-machine interaction on the web 3.0. As for the conventional web services, the problem of

discovering and selecting the most suitable web service represents a challenge for SWSs to be widely used.



http://www.elysiumtechnologies.com, [email protected] In this paper, we propose a mapping algorithm that facilitates the redefinition of the conventional web

services annotations (i.e., WSDL) using semantic annotations (i.e., OWL-S). This algorithm will be a part of

a new discovery mechanism that relies on the semantic annotations of the web services to perform its task.

The “local ontology repository” and “ontology search and standardization

engine” are the backbone of this algorithm. Both of them target to define any data type in the

system using a standard ontology-based concept. The originality of the proposed mapping algorithm is its

applicability and consideration of the standardization problem. The proposed algorithm is implemented and

its components are validated using some test collections and real examples. An experimental test of the

proposed techniques is reported, showing the impact of the proposed algorithm in decreasing the time and

the effort of the mapping process. Moreover, the experimental results promise that the proposed algorithm

will have a positive impact on the discovery process as a whole.

ETPL

GC-011 Battery Status-aware Authentication Scheme for V2G Networks in Smart Grid

Abstract: Vehicle-to-grid (V2G) is emerging as an attractive paradigm in smart grid, and provides power and

information services by periodically collecting power status of battery vehicles (BVs). During a BV's

interaction with power grid, it may be in one of the following states: charging, fully-charged (FC), and

discharging. In this paper, we identify that there are unique security challenges in a BV's different battery

states. Accordingly, we propose a battery status-aware authentication scheme (BASA) to address the issue

for V2G networks. In BASA, 1) an aggregated-identifier is proposed during the charging-to-FC state

transition to ensure that BVs can be authenticated without disclosing their real identities; 2) selective

disclosure based challenge-response authentication is presented during the FC-to-discharging phase to

realize anonymous data transmission; 3) an aggregated-status is reported during the discharging-to-charging

transition in order to hide a BV's power level from an aggregator. In addition, we perform comprehensive

security analysis, which shows that BASA achieves both privacy preservation and security protection during

battery state transitions. The analysis also indicates that battery status awareness is crucial for BVs' secure

operations for V2G networks in smart grid.

ETPL

GC-012

Dependable Demand Response Management in the Smart Grid: A Stackelberg Game

Approach

Abstract: Demand Response Management (DRM) is a key component in the smart grid to effectively reduce

power generation costs and user bills. However, it has been an open issue to address the DRM problem in a

network of multiple utility companies and consumers where every entity is concerned about maximizing its

own benefit. In this paper, we propose a Stackelberg game between utility companies and end-users to

maximize the revenue of each utility company and the payoff of each user. We derive analytical results for

the Stackelberg equilibrium of the game and prove that a unique solution exists. We develop a distributed

algorithm which converges to the equilibrium with only local information available for both utility

companies and end-users. Though DRM helps to facilitate the reliability of power supply, the smart grid can

be succeptible to privacy and security issues because of communication links between the utility companies

and the consumers. We study the impact of an attacker who can manipulate the price information from the

utility companies. We also propose a scheme based on the concept of shared reserve power to improve the

grid reliability and ensure its dependability




ETPL

GC-013 A Generic Query Model for the Unified Discovery of Heterogeneous Services

Abstract: In this paper, we propose Proteus, a generic query model for the discovery of operations offered by

heterogeneous services. We demonstrate the need for such a model, and show how it unifies the task of

service discovery through abstractions, which allow for the technology-independent formulation of service

advertisements, queries, and query responses. On top of these generic elements, we build an intuitive, fuzzy-

based query evaluation mechanism that supports the service matchmaking process by employing and

appropriately combining existing similarity metrics. Thanks to the generality of Proteus, it is possible to

seamlessly accommodate the discovery of operations provided by various types of services without the need

of changing the existing service infrastructure. Thus, our approach is applicable to a variety of settings

ranging from traditional web services to service-oriented grids, peer-to-peer networks, geospatial

information systems, and so on. Overall, compared to the existing query models supported by standard

service discovery technologies, our approach is marked by openness, flexibility, and improved performance

in terms of precision and recall. The feasibility and efficiency of Proteus are verified by a series of

experiments.

ETPL

GC-014 Reliable Wireless Communication Networks for Demand Response Control

Abstract: This paper presents methodologies for deriving reliability performance of wireless communication

networks to support demand response (DR) control. First, the impact of communication impairments on a

direct DR control program is investigated. Second, the outage probability of a wireless link is modelled and

quantified, considering the multipath fading, shadowing, and random path loss given the location

distribution of smart meters. Third, the distributions of packet delivery ratio are derived for two wireless

network architectures: the single-hop infrastructure-based network and the multi-hop mesh network.

Simulation results verify the above reliability models and provide important insights on the coverage of

wireless communication networks considering the reliability requirements of DR programs.

ETPL

GC-015 UDP: Usage-Based Dynamic Pricing With Privacy Preservation for Smart Grid

Abstract: Smart sensing and wireless communication technologies enable the electric power grid system to

deliver electricity more efficiently through the dynamic analysis of the electricity demand and supply. The

current solution is to extend the traditional static electricity pricing strategy to a time-based one where peak-

time prices are defined to influence electricity usage behavior of customers. However, the time-based

pricing strategy is not truly dynamic and the electricity resource cannot be optimally utilized in real time. In

this paper, we propose a usage-based dynamic pricing (UDP) scheme for smart grid in a community

environment, which enables the electricity price to correspond to the electricity usage in real time. In the

UDP scheme, to simplify price management and reduce communication overhead, we introduce distributed

community gateways as proxies of the utility company to timely respond to the price enquiries from the

community customers. We consider both community-wide electricity usage and individual electricity usage

as factors into price management: a customer gets higher electricity unit price if its own electricity usage

becomes larger under certain conditions of the community-wide collective electricity usage. Additionally,

we protect the privacy of the customers by restricting the disclosure of the individual electricity usage to the

community gateways. Lastly, we provide privacy and performance analysis to demonstrate that the UDP



http://www.elysiumtechnologies.com, [email protected] scheme supports real-time dynamic pricing in an efficient and privacy-preserving manner.

ETPL

GC-016

Detecting Critical Nodes in Interdependent Power Networks for Vulnerability

Assessment

Abstract: Power networks and information systems become more and more interdependent to ensure better

supports for the functionality as well as improve the economy. However, power networks also tend to be

more vulnerable due to the cascading failures from their interdependent information systems, i.e., the

failures in the information systems can cause the failures of the coupled portion in power networks.

Therefore, the accurate vulnerability assessment of interdependent power networks is of great importance in

the presence of unexpected disruptive events or adversarial attacks targeting on critical network nodes. In

this paper, we study the Interdependent Power Network Disruptor (IPND) optimization problem to identify

critical nodes in an interdependent power network whose removals maximally destroy its functions due to

both malfunction of these nodes and the cascading failures of its interdependent communication network.

First, we show the IPND problem is NP-hard to be approximated within the factor of (2-ε) . Despite its

intractability, we propose a greedy framework with novel centrality functions based on the networks'

interdependencies, to efficiently solve this problem in a timely manner. An extensive experiment not only

illustrates the effectiveness of our approach on networks with different topologies and interdependencies,

but also highlights some important observations which help to sharpen the robustness of interdependent

networks in the future.

ETPL

GC-017 Proactive and Reactive Runtime Service Discovery: A Framework and Its Evaluation

Abstract: The identification of services during the execution of service-based applications to replace services

in them that are no longer available and/or fail to satisfy certain requirements is an important issue. In this

paper, we present a framework to support runtime service discovery. This framework can execute service

discovery queries in pull and push mode. In pull mode, it executes queries when a need for finding a

replacement service arises. In push mode, queries are subscribed to the framework to be executed

proactively and, in parallel with the operation of the application, to identify adequate services that could be

used if the need for replacing a service arises. Hence, the proactive (push) mode of query execution makes it

more likely to avoid interruptions in the operation of service-based applications when a service in them

needs to be replaced at runtime. In both modes of query execution, the identification of services relies on

distance-based matching of structural, behavioral, quality, and contextual characteristics of services and

applications. A prototype implementation of the framework has been developed and an evaluation was

carried out to assess the performance of the framework. This evaluation has shown positive results, which

are discussed in the paper.

ETPL

GC-018

Bad Data Injection Attack and Defense in Electricity Market Using Game Theory

Study

Abstract: Applications of cyber technologies improve the quality of monitoring and decision making in

smart grid. These cyber technologies are vulnerable to malicious attacks, and compromising them can have

serious technical and economical problems. This paper specifies the effect of compromising each

measurement on the price of electricity, so that the attacker is able to change the prices in the desired

direction (increasing or decreasing). Attacking and defending all measurements are impossible for the



http://www.elysiumtechnologies.com, [email protected] attacker and defender, respectively. This situation is modeled as a zero-sum game between the attacker and

defender. The game defines the proportion of times that the attacker and defender like to attack and defend

different measurements, respectively. From the simulation results based on the PJM 5-Bus test system, we

can show the effectiveness and properties of the studied game.

ETPL

GC-019

An Empirical Study of Communication Infrastructures Towards the Smart Grid:

Design, Implementation, and Evaluation,

Abstract: The smart grid features ubiquitous interconnections of power equipments to enable two-way flows

of electricity and information for various intelligent power management applications, such as accurate relay

protection and timely demand response. To fulfill such pervasive equipment interconnects, a full-fledged

communication infrastructure is of great importance in the smart grid. There have been extensive works on

disparate layouts of communication infrastructures in the smart grid by surveying feasible wired or wireless

communication technologies, such as power line communications and cellular networks. Nevertheless,

towards an operable, cost-efficient and backward-compatible communication solution, more comprehensive

and practical understandings are still urgently needed regarding communication requirements, applicable

protocols, and system performance. Through such comprehensive understandings, we are prone to answer a

fundamental question, how to design, implement and integrate communication infrastructures with power

systems. In this paper, we address this issue in a case study of a smart grid demonstration project, the Future

Renewable Electric Energy Delivery and Management (FREEDM) systems. By investigating

communication scenarios, we first clarify communication requirements implied in FREEDM use cases.

Then, we adopt a predominant protocol framework, Distributed Network Protocol 3.0 over TCP/IP (DNP3

over TCP/IP), to practically establish connections between electric devices for data exchanges in a small-

scale FREEDM system setting, Green Hub. Within the real-setting testbed, we measure the message

delivery performance of the DNP3-based communication infrastructure. Our results reveal that diverse

timing requirements of message deliveries are arguably primary concerns in a way that dominates viabilities

of protocols or schemes in the communication infrastructure of the smart grid. Accordingly, although DNP3

over TCP/IP is widely considered as a smart grid co- munication solution, it cannot satisfy communication

requirements in some time-critical scenarios, such as relay protections, which claim a further optimization

on the protocol efficiency of DNP3.

ETPL

GC-020 Trust System Design Optimization in Smart Grid Network Infrastructure

Abstract: The imposed communication network brings more vulnerabilities to the evolving smart grid.

Therefore, defensive techniques such as intrusion detection will need to be deployed in this already

complicated system. Deployment and runtime cost due to the defensive trust systems will affect the original

function of smart grid system without careful planning and design. This paper is an effort to address this

important issue. In particular, the set packing algorithm is used to optimize the placement of the trust nodes

of the defensive system in the multiple layer architecture of the smart grid. After the trust nodes are placed, a

trust node aware optimal routing algorithm is used to find the least cost routing in the communications of the

nodes. Also, an algorithm to identify new trust node(s) is presented to address the fault tolerance

requirement of the smart grid system. Simulation results demonstrate that our approach is promising by

providing secure, efficient, and reliable communications in the smart grid network.




ETPL

GC-021

A Decentralized Security Framework for Data Aggregation and Access Control in

Smart Grids

Abstract: We propose a decentralized security framework for smart grids that supports data aggregation and

access control. Data can be aggregated by home area network (HAN), building area network (BAN), and

neighboring area network (NAN) in such a way that the privacy of customers is protected. We use

homomorphic encryption technique to achieve this. The consumer data that is collected is sent to the

substations where it is monitored by remote terminal units (RTU). The proposed access control mechanism

uses attribute-based encryption (ABE) which gives selective access to consumer data stored in data

repositories and used by different smart grid users. RTUs and users have attributes and cryptographic keys

distributed by several key distribution centers (KDC). RTUs send data encrypted under a set of attributes.

Since RTUs are maintained in the substations they are well protected in control rooms and are assumed to be

trusted. Users can decrypt information provided they have valid attributes. The access control scheme is

distributed in nature and does not rely on a single KDC to distribute the keys which makes the approach

robust. To the best of our knowledge, ours is the first work on smart grids, which integrates these two

important security components (privacy preserving data aggregation and access control) and the first paper

which addresses access control in smart grids.

ETPL

GC-022 Reliability Analysis of Substation Automation System Functions Using PRMs

Abstract: The current trend for building an ontology-based data management system (DMS) is to capitalize

on efforts made to design a preexisting well-established DMS (a reference system). The method amounts to

extracting from the reference DMS a piece of schema relevant to the new application needs-a module-,

possibly personalizing it with extra constraints w.r.t. the application under construction, and then managing

a data set using the resulting schema. In this paper, we extend the existing definitions of modules and we

introduce novel properties of robustness that provide means for checking easily that a robust module-based

DMS evolves safely w.r.t. both the schema and the data of the reference DMS. We carry out our

investigations in the setting of description logics which underlie modern ontology languages, like RDFS,

OWL, and OWL2 from W3C. Notably, we focus on the DL-liteA dialect of the DL-lite family, which

encompasses the foundations of the QL profile of OWL2 (i.e., DL-liteR): the W3C recommendation for

efficiently managing large data sets.

ETPL

GC-023 Efficient Service Skyline Computation for Composite Service Selection

Abstract: This paper presents the application of a framework for reliability analysis of substation automation

(SA) system functions. The framework is based on probabilistic relational models which combines

probabilistic reasoning offered by Bayesian networks together with architecture models in form of entity

relationship diagrams. In the analysis, both the physical infrastructure, and the logical structure of the

system, is regarded in terms of qualitative modeling and quantitative analysis. Moreover, the framework

treats the aspect of failures caused by software. An example is detailed with the framework applied to an

IEC 61850-based SA system. The logical structure, including functions and their relations, is modeled in

accordance with Pieces of Information for COMmunication (PICOM) defined in the IEC 61850 standard.

By applying PICOMs as frame of reference when modeling functions the model instantiation becomes more

standardized compared to subjectively defining functions. A quantitative reliability analysis is performed on



http://www.elysiumtechnologies.com, [email protected] a function for tipping a circuit breaker in case of mismatch between currents. The result is presented both in

terms of a qualitative architecture model and a quantitative result showing the probability of successful

operation during a period of one year.

ETPL

GC-024 Exploring Malicious Meter Inspection in Neighborhood Area Smart Grids

Abstract: In smart grids, smart meters may potentially be attacked or compromised to cause certain security

risks. It is challenging to identify malicious meters when there are a large number of users. In this paper, we

explore the malicious meter inspection (MMI) problem in neighborhood area smart grids. We propose a

suite of inspection algorithms in a progressive manner. First, we present a basic scanning method, which

takes linear time to accomplish inspection. The scanning method is efficient when the malicious meter ratio

is high. Then, we propose a binary-tree-based inspection algorithm, which performs better than scanning

when the malicious meter ratio is low. Finally, we employ an adaptive-tree-based algorithm, which

leverages advantages of both the scanning and binary-tree inspections. Our approaches are tailored to fit

both static and dynamic situations. The theoretical and experimental results have shown the effectiveness of

the adaptive tree approach.

ETPL

GC-025 Real-Time Opportunistic Scheduling for Residential Demand Response

Abstract: Demand response is a key feature of the smart grid. The addition of bidirectional communication

to today's power grid can provide real-time pricing (RTP) to customers via smart meters. A growing number

of appliance companies have started to design and produce smart appliances which embed intelligent control

modules to implement residential demand response based on RTP. However, most of the current residential

load scheduling schemes is centralized and based on either day-ahead pricing (DAP) or predicted price,

which can deviate significantly from the RTP. In this paper, we propose an opportunistic scheduling scheme

based on the optimal stopping rule as a real-time distributed scheduling algorithm for smart appliances'

automation control. It determines the best time for appliances' operation to balance electricity bill reduction

and inconvenience resulting from the operation delay. It is shown that our scheme is a distributed threshold

policy when no constraint is considered. When a total power constraint exists, the proposed scheduling

algorithm can be implemented in either a centralized or distributed fashion. Our scheme has low complexity

and can be easily implemented. Simulation results validate proposed scheduling scheme shifts the operation

to off-peak times and consequently leads to significant electricity bill saving with reasonable waiting time.

ETPL

GC-026

Modeling Cyber-Physical Vulnerability of the Smart Grid With Incomplete

Information

Abstract: This paper addresses the attack modeling using vulnerability of information, communication and

electric grid network. Vulnerability of electric grid with incomplete information has been analyzed using

graph theory based approach. Vulnerability of information and communication (cyber) network has been

modeled utilizing concepts of discovery, access, feasibility, communication speed and detection threat.

Common attack vector based on vulnerability of cyber and physical system have been utilized to operate

breakers associated with generating resources to model aurora-like event. Real time simulations for modified

IEEE 14 bus test case system and graph theory analysis for IEEE 118 bus system have been presented. Test

case results show the possible impact on smart grid caused by integrated cyber-physical attack.




ETPL

GC-027 Outage-Storage Tradeoff in Frequency Regulation for Smart Grid With Renewables

Abstract: Future power grid systems are envisioned to be integrated with many distributed renewable energy

sources (DRES). Energy storage is a key technology to enable reliable and cost-effective renewable energy.

Given the fact that a large-scale energy storage device is usually costly to install and operate, we are

naturally led to the following question: How much storage is necessary to guarantee the stability of a power

grid network with DRESs? This paper represents a first step in systematically exploring the tradeoff between

the capacity of energy storage devices and the outage probability, i.e., the probability of the occurrence of

imbalance between the supply and demand. We first propose a secure scheduling and dispatch (SSD)

algorithm that is capable of maintaining the grid stability in the presence of volatility in the power

generation. We then derive a closed-form bound to quantify the tradeoff between the storage capacity and

the outage probability. Under mild assumptions, we show that the outage probability decreases

exponentially with respect to the square of the storage capacity. This finding implies that energy storage is

an effective and economically viable solution to maintain the stability of a smart grid network, even in the

presence of many volatile and intermittent renewable energy sources. The impact of correlation in energy

generation on the stability of a smart grid network is also investigated .

ETPL

GC-028

Multilayer Consensus ECC-Based Password Authenticated Key-Exchange (MCEPAK)

Protocol for Smart Grid System

Abstract: This paper aims at providing a key agreement protocol for smart grid to cope with access control

of appliances/devices located inside a Home Area Network (HAN) by a set of controllers outside the HAN.

The commands/packets initiated by the controllers in crisis cases should be delivered fast and immune from

any interruption. The HAN controller, which acts as a gateway, should not cause any delay by decrypting

and re-encrypting the packets, nor should it has any chance to modify them. Considering the required level

of security and quality of service, we design our protocol with an Elliptic Curve Cryptography (ECC)

approach. We improve and implement the Password Authenticated Key Exchange (PAKE) protocol in two

steps. First, we propose an auxiliary mechanism that is an ECC version of PAKE, and then extend it to a

multilayer consensus model. We reduce the number of hash functions to one, and utilize a primitive

password shared between an appliance and HAN controller to construct four valid individual consensus and

authenticated symmetric keys between the appliance and upstream controllers by exchanging only 12

packets. Security analysis presents that our protocol is resilient to various attacks. Furthermore, performance

analysis shows that the delay caused by the security process is reduced by more than one half.

ETPL

GC-029 Relay-Aided Amplify-and-Forward Powerline Communications

Abstract: Powerline communications (PLC) is a favorable technique for many smart grid applications. By

transmitting information over the existing powerline infrastructure, PLC has the benefit of low deployment

cost. However, due to low transmit power, limited bandwidth, and harsh channel conditions, reliable long-

distance and high-capacity PLC is challenging. Relay-aided (RA-) PLC is promising in addressing these

issues. In this paper, we investigate the performance of the amplify-and-forward (AF) RA-PLC system from

an information-theoretic perspective. The capacity of AF-based RA-PLC is analyzed for frequency-selective

PLC channels. The capacity bounds are derived, and the optimal power allocation between the transmitting

nodes and the optimal power distribution over the signal frequency band are obtained. The capacity benefits



http://www.elysiumtechnologies.com, [email protected] and features of AF-based RA-PLC are evaluated with two prevalent powerline channel models. Based on the

signal attenuation model, the capacity of AF-based RA-PLC is compared with direct-link (DL-)PLC, and the

effect of relay location is revealed. In addition, based on the transmission line (TL) model, the effects of

branch density and load impedance on the capacity of AF-based RA-PLC are evaluated.

ETPL

GC-030 A Noninvasive Threat Analyzer for Advanced Metering Infrastructure in Smart Grid

Abstract: Advanced Metering Infrastructure (AMI) is the core component in a smart grid that exhibits a

highly complex network configuration. AMI comprises heterogeneous cyber-physical components, which

are interconnected through different communication media, protocols, and security measures. They are

operated using different data delivery modes and security policies. The inherent complexity and

heterogeneity in AMI significantly increases the potential of security threats due to misconfiguration or

absence of defense, which may cause devastating damage to AMI. Therefore, there is a need for creating a

formal model that can represent the global behavior of AMI configuration in order to verify the potential

threats. In this paper, we present SmartAnalyzer, a security analysis tool, which offers manifold

contributions: (i) formal modeling of AMI configuration that includes device configurations, topology,

communication properties, interactions among the devices, data flows, and security properties; (ii) formal

modeling of AMI invariants and user-driven constraints based on the interdependencies among AMI device

configurations, security properties, and security control guidelines; (iii) verifying the AMI configuration's

compliance with security constraints using a Satisfiability Modulo Theory (SMT) solver; (iv) reporting of

potential security threats based on constraint violations, (v) analyzing the impact of potential threats on the

system; and (vi) systematic diagnosing of SMT unsatisfiable traces and providing necessary remediation

plans. The accuracy and scalability of the tool are evaluated on an AMI testbed and various synthetic test

networks.

ETPL

GC-031

Taming Uncertainties in Real-Time Routing for Wireless Networked Sensing and

Control

Abstract: Real-time routing is a basic element of closed-loop, real-time sensing and control, but it is

challenging due to dynamic, uncertain link/path delays. The probabilistic nature of link/path delays makes

the basic problem of computing the probabilistic distribution of path delays NP-hard, yet quantifying

probabilistic path delays is a basic element of real-time routing and may well have to be executed by

resource-constrained devices in a distributed manner; the highly varying nature of link/path delays makes it

necessary to adapt to in-situ delay conditions in real-time routing, but it has been observed that delay-based

routing can lead to instability, estimation error, and low data delivery performance in general. To address

these challenges, we propose the Multi-Timescale Estimation (MTE) method; by accurately estimating the

mean and variance of per-packet transmission time and by adapting to fast-varying queueing in an accurate,

agile manner, MTE enables accurate, agile, and efficient estimation of probabilistic path delay bounds in a

distributed manner. Based on MTE, we propose the Multi-Timescale Adaptation (MTA) routing protocol;

MTA integrates the stability of an ETX-based directed-acyclic-graph (DAG) with the agility of

spatiotemporal data flow control within the DAG to ensure real-time data delivery in the presence of

dynamics and uncertainties. We also address the challenges of implementing MTE and MTA in resource-

constrained devices such as TelosB motes. We evaluate the performance of MTA using the NetEye and



http://www.elysiumtechnologies.com, [email protected] Indriya sensor network testbeds. We find that MTA significantly outperforms existing protocols, e.g.,

improving deadline success ratio by 89% and reducing transmission cost by a factor of 9.7 in the NetEye

testbed.

ETPL

GC-032 Sensing-Performance Tradeoff in Cognitive Radio Enabled Smart Grid

Abstract: Smart grid is widely considered to be the next generation of power grid, where power generation,

management, transmission, distribution, and utilization are fully upgraded to improve agility, reliability,

efficiency, security, economy, and environmental friendliness. Demand response management (DRM) is

recognized as a control unit of the smart grid, with the attempt to balance the real-time load as well as to

shift the peak-hour load. Communications are critical to the accuracy and optimality of DRM, and hence at

the core of the control performance of the smart grid. In this paper, we introduce cognitive radio into the

smart grid to improve the communication quality. By means of spectrum sensing and channel switching,

smart meters can decide to transmit data on either an original unlicensed channel or an additional licensed

channel, so as to reduce the communication outage. Considering the energy cost taxed by spectrum sensing

together with the control performance degradation incurred by imperfect communications, we formulate the

sensing-performance tradeoff problem between better control performance and lower communication cost,

paving the way towards a green smart grid. The impact of the communication outage on the control

performance of DRM is also analyzed, which reduces the profit of power provider and the social welfare of

the smart grid, although it may not always decrease the profit of power consumer. By employing the energy

detector, we prove that there exists a unique optimal sensing time which yields the maximum tradeoff

revenue, under the constraint that the licensed channel is sufficiently protected. Numerical results are

provided to validate our theoretical analysis.

ETPL

GC-033 Optimizing Electric Vehicle Charging With Energy Storage in the Electricity Market

The Information and Communication Technologies (ICT) that are currently under development for future

smart grid systems can enable load aggregators to have bidirectional communications with both the grid and

Electric Vehicles (EVs) to obtain real-time price and load information, and to adjust EV charging schedules

in real time. In addition, Energy Storage (ES) can be utilized by the aggregator to mitigate the impact of

uncertainty and inaccurate prediction. In this paper, we study a problem of scheduling EV charging with ES

from an electricity market perspective with joint consideration for the aggregator energy trading in the day-

ahead and real-time markets. We present a Mixed Integer Linear Programming (MILP) model to provide

optimal solutions as well as a simple polynomial-time heuristic algorithm based on LP rounding. In addition,

we present a communication protocol for interactions among the aggregator, the ES, the power grid, and

EVs, and demonstrate how to integrate the proposed scheduling approach in real-time charging operations.

Extensive simulation results based on real electricity price and load data have been presented to justify the

effectiveness of the proposed approach and to show how several key parameters affect its performance.

ETPL

GC-034

Stability Enhancement of Decentralized Inverter Control Through Wireless

Communications in Microgrids

Abstract: Decentralized inverter control is essential in distributed generation (DG) microgrids for low

deployment/operation cost and high reliability. However, decentralized inverter control suffers from a

limited system stability mainly because of the lack of communications among different inverters. In this



http://www.elysiumtechnologies.com, [email protected] paper, we investigate stability enhancement of the droop based decentralized inverter control in microgrids.

Specifically, we propose a power sharing based control strategy which incorporates the information of the

total real and reactive power generation of all DG units. The information is acquired by a wireless network

(such as a WiFi, ZigBee, and/or cellular communication network) in a decentralized manner. Based on the

desired power sharing of each DG unit and the acquired information of total generation, additional control

terms are added to the traditional droop controller. We evaluate the performance of the proposed control

strategy based on small-signal stability analysis. As timely communication may not be established for a

microgrid with low-cost wireless communication devices, two kinds of analytical models are developed with

respect to negligible and nonnegligible communication delays, respectively. Extensive numerical results are

presented to demonstrate the system stability under the proposed control strategy with respect to different.

ETPL

GC-035

Privacy-Aware Profiling and Statistical Data Extraction for Smart Sustainable Energy

Systems

Abstract: The growing population and global warming have been calling for more effective energy usage,

which have stimulated the emergence of smart sustainable energy technology. The distinct feature of this

newly emerging technology is the incorporation of advanced information and communication technologies

(ICT), which collects more detailed information on how energy is generated, distributed, and consumed.

Various smart metering technologies have also been proposed to support the optimization on sustainable

energy usage. Despite the obvious benefits of these technologies, people may still hesitate to adopt them

because of possible privacy breach. On the other hand, we observe that the major target information for

making the sustainable energy system smart is the aggregated statistics of energy usage, not the full detailed

usage profiles which would compromise customers' privacy. Thus, how to design schemes to collect

aggregated statistics while preserving customers' privacy becomes an important research problem. In this

paper, we propose two schemes to deal with this problem. The first one can support dynamic profiling,

which can extract aggregated statistical information without compromising individual privacy. The second

one aims to extract correlation information among various factors for the smart system design and can also

be used as an underlying tool for baseline inference and association rule mining.

ETPL

GC-036 Multi-Objective Optimal Energy Consumption Scheduling in Smart Grids

Abstract: A major source of inefficiency in power grids is the underutilization of generation capacity. This

is mainly because load demand during peak hours is much larger than that during off-peak hours. Moreover,

extra generation capacity is needed to maintain a security margin above peak load demand. As load demand

keeps increasing and two-way communications are enabled by smart meters (SMs), demand response (DR)

has been proposed as an alternative to installing new power plants in smart grids. DR makes use of real-time

schemes to allow users to modify their load demand patterns according to their energy consumption costs. In

particular, when load demand is high, energy consumption cost will be high and users may decide to

postpone certain amount of their consumption needs. This strategy may effectively reduce the peak load

demand and increases the off-peak demand, and hence could increase existing generation capacity utilization

and reduce the need to install extra generation plants. In this paper, we consider a third-party managing the

energy consumption of a group of users, and formulate the load scheduling problem as a constrained multi-

objective optimization problem (CMOP). The optimization objectives are to minimize energy consumption

cost and to maximize a certain utility, which can be conflicting and non-commensurable. We then develop



http://www.elysiumtechnologies.com, [email protected] two evolutionary algorithms (EAs) to obtain the Pareto-front solutions and the ε-Pareto front solutions to the

CMOP, respectively, which are validated by extensive simulation results.

ETPL

GC-037 Advanced Power Distribution System Configuration for Smart Grid

Abstract: Power distribution systems should meet demands such as high reliability, efficiency, and

penetration of renewable energy generators (REGs) in a smart grid. In general, power distribution systems

are radial in nature. One-way power flow is the advantage of a radial system. However, the introduction of

REGs causes bidirectional power flow. Furthermore, there are limits to improvements in reliability and

efficiency in a radial system. Therefore, the upgrading of primary feeders from a radial to a loop

configuration has been considered in the Korea Smart Distribution Project. An advanced power distribution

system (APDS), in which primary feeders operate in a loop configuration, has been explored in this paper.

First, the design scheme of a conventional power distribution system configuration that adopts distribution

automation is introduced. Subsequently, an upgrading scheme of loop configuration using normally opened

tie switches and a tie switch selection algorithm for loss minimization are described. Finally, the advantages

of the upgraded configuration are reported through case studies. It is observed that the APDS configuration

can integrate more REGs from the viewpoint of voltage regulation. An advanced distribution system

allowing greater use of REGs will be a major contribution to smart grid implementation.

ETPL

GC-038 Smart Operation of HVDC Systems for Large Penetration of Wind Energy Resources

Abstract: The target for South Korea's domestic energy consumption is to increase the proportion of the total

energy consumption supplied by renewable energy to 11% by 2030. Increasing renewable energy generation

has become a natural trend, thereby making it an essential factor to be considered in research for the

development of a smart grid. The power system of Jeju Island is connected to the mainland (the Korean

Peninsula) through HVDC #1, with another line, HVDC #2, presently under construction. The purpose of

the first HVDC construction was essentially to supply a portion of the power supply to the Jeju area.

However, if the construction of HVDC #2 is completed, the role of the Jeju HVDC system in the Jeju power

system will be changed significantly. If flexibility through the operation of an HVDC system is increased,

more wind farms can be built on Jeju Island. In addition, depending on the operation of HVDC #1 and #2,

the stability of the Jeju power system will be changed greatly. In this paper, the operation of the HVDC lines

and its impacts are analyzed.

ETPL

GC-039

Operation Schemes of Smart Distribution Networks With Distributed Energy

Resources for Loss Reduction and Service Restoration

Abstract: The integration of Distributed Energy Resources (DERs) into the future Smart Distribution

Network (SDN) has challenging issues regarding the successful development of smart grids. The SDN offers

new opportunities in the improvement of the efficiency of power distribution networks. The DERs will be

distributed in the existing distribution networks, interconnected in customer areas and operated on its own

schedule without communication to the control center of the existing distribution system. The DER units

have both positive and negative effects regarding SDN operations. With the appropriate operation of the

DER units in the SDN, losses can be reduced during normal operations and they can support local loads

during abnormal conditions. Thus, the positive effects of the DER units need to be enabled in the SDN by

adopting advanced operation schemes. In this paper, the smart control functions for the DER units in the



http://www.elysiumtechnologies.com, [email protected] SDN are defined and classified. In addition, the integration schemes for the SDN with DER units are

introduced. The proposed operation strategies will be implemented into the Korean Smart Distribution

Management System (KSDMS) as operation schemes used for loss reduction and service restoration. A

sample case study shows the effectiveness of the proposed operation schemes to achieve smart operation

functions for the SDN with DER units.

ETPL

GC-040

Design of Smart Distribution Management System for Obtaining Real-Time Security

Analysis and Predictive Operation in Korea

Abstract: The Development of smart grids offers new opportunities to improve the efficiency of operating

and controlling distribution systems. It allows network operators to optimize the use of dispersed generation

resources and enables real-time communication between customers and utility service providers to allow

optimization and balancing of energy usage. Such an improvement in the flexibility and control of the

distribution network is only possible if the control center operator has more accurate knowledge of the real-

time situation of the network. The Korean Smart Distribution Management System (KSDMS) project was

started in 2009 to achieve advanced distribution operation for potential smart grid systems in Korea. In this

paper, we summarize two KSDMS design strategies for situational awareness in real-time distribution

operation. One is the preparation of standardized data acquisition networks. In the KSDMS, numerous data

related to the voltage, current, faults, power quality and load profiles of the network are gathered using a

standardized communication method based on IEC 61850. The other is a real-time security analysis tools for

smart distribution systems, designed to provide the distribution operator with accurate real-time situational

information and predictive operation. We present a database design which can be used commonly for all

security analysis programs in KSDMS.

ETPL

GC-041

Price Elasticity of Demand Modeling With Economic Effects on Electricity Markets

Using an Agent-Based Model

Abstract: Automated Metering Infrastructure (AMI) is a technology that would allow consumers to exhibit

price elasticity of demand under smart-grid environments. The market power of the generation and

transmission companies can be mitigated when consumers respond to price signals. Such responses by

consumers can also result in reductions in price spikes, consumer energy bills, and emissions of greenhouse

gases and other pollutants. In this paper, we use the Electricity Market Complex Adaptive System

(EMCAS), an agent-based model that simulates restructured electricity markets, to explore the impact of

consumers' price elasticity of demand on the performance of the electricity market. An 11-node test network

with eight generation companies and five aggregated consumers is simulated for a period of one month.

Results are provided and discussed for a case study based on the Korean power system.

ETPL

GC-042

Power Scheduling of Distributed Generators for Economic and Stable Operation of a

Microgrid

Abstract: This paper is concerned with the power dispatch problem of distributed generators (DGs) for

optimal operation of a microgrid. The objective is to minimize the fuel cost during the grid-connected

operation, while ensuring stable operation after islanding. To achieve this goal, the economic dispatch (ED)

problem and related constraints are formulated. The constraints considered in this study are: i) reserve for

variation in load demand, ii) reserve for variation in the power outputs of non-dispatchable DGs, iii) flow

limits between two adjacent areas, and iv) reserve for the stable islanded operation. The first three

constraints, which have been employed in ED problem for conventional power systems, are modified to



http://www.elysiumtechnologies.com, [email protected] apply to Microgrids. We also provide a detailed formulation of the constraint for stable islanded operation in

accordance with two power-sharing principles: i) fixed droop and ii) adjustable droop. The problem is

solved using a modified direct search method, and the effect of the constraints on the operational cost is

investigated via numerical simulations.

ETPL

GC-043 State Estimation for Supervisory Monitoring of Substations

Abstract: This paper introduces the application of state estimation to double bus double breaker distribution

substations, which are typically used in the Korean power system, to improve the reliability of substation

automation systems. In spite of the recent remarkable progress in the field of sensors and equipments, it is

hard to detect device malfunctions or degraded devices automatically in the supervisory monitoring system.

The object of the proposed system is not the state estimation itself, but its application to the supervisory

detection of the malfunction or degradation of the devices. The supervisory monitoring process consists of a

two step procedure-topology processing and normal state estimation. In a substation, the on-off states of the

circuit breakers determine the topology. This paper mainly presents the topology processing expert system

including the knowledge representation. The expert system is operated with a predefined period to identify

and correct topological errors in the distribution substations. The proposed system is now in the field test

stage in the Sanchung pilot substation and it will be applied to the next generation substation automation

system in Korea.

ETPL

GC-044

Study of the Effectiveness of a Korean Smart Transmission Grid Based on Synchro-

Phasor Data of K-WAMS

Abstract: ecent technological achievement in areas of distributed computing, networking, high speed

communications and digital control, as well as the availability of accurate GPS time source, are rapidly

becoming the enabling factors for the development of a new generation of real time power grid monitoring

tools. KDN (Korea electric power Date Network Co.) R&D department with KERI, Korea University and

LSIS has embarked on long term research and development work in the field of wide area systems

specifically applied to the power transmission grid in Korea. Primary focus will be on wide area

measurement and monitoring, analysis, assessment technique and tools aimed at preventing the propagation

of power grid instabilities. Of special interest are voltage stability and small signal stability. This project

aligns with KEPCO (the Korea Electric Power Company). In this paper, case studies performed with the use

of the developed system are presented.

ETPL

GC-045

Modified Dynamic Phasor Estimation Algorithm for the Transient Signals of

Distributed Generators

Abstract: In this paper, a modified dynamic phasor estimation method for protection relays is proposed to

calculate the dynamic phasor of a fundamental frequency component with time-variant amplitude. The fault

current is assumed to be the combination of a decaying dc offset, a decaying fundamental frequency

component and harmonics with constant amplitude. The exponential functions of the decaying dc offset and

fundament frequency component are replaced by Taylor series. Then, the LS (Least Square) technique is

used to estimate the magnitudes and the time constants of decaying components. The performance of the

algorithm is evaluated by using computer-simulated signals based on simple equations and fault current

signals collected from DFIG wind farm model in MATLAB Simulink. The test results indicate that the

proposed algorithm can accurately estimate the decaying amplitude and the time constant of the fundamental



http://www.elysiumtechnologies.com, [email protected] frequency component.

ETPL

GC-046

DSM Considered Probabilistic Reliability Evaluation and an Information System for

Power Systems Including Wind Turbine Generators

Abstract: This paper proposes a methodology for evaluating the probabilistic reliability, considering demand

side management (DSM) and Web based on a daily interval reliability information system for a grid

constrained composite power system including wind turbine generators(WTG). The proposed model can

consider capacity limitations and transmission line unavailabilities and the operation of WTG modeled by

multi-states. The importance of renewable energy sources is growing at a rapid rate due to environmental

concerns. A web based online daily time interval reliability integrated information system (WORRIS) is

applied using the methodology proposed in this paper. This paper describes the architecture of the WORRIS

Version 7.0 system.

ETPL

GC-047 A Quantitative Analysis on Future World Marketability of HTS Power Industry

Abstract: This study estimates total world market volumes of HTS power industry, one of the main smart

grid equipment in the future when the market penetration ratio reaches 100% in the future. The results of

this paper are based on the GOULDEN Report providing the total market volumes of conventional power

industry for the world market. This study determines the market penetration ratio using the judgment method

with market penetration S-curve induced from Delphi method and Product Life Cycle from 2011 (expected

to be a launching year, not the actual year) to 2050 (expected to be a final target year). For this purpose,

HTS market penetration ratio of each stage, so called innovation, early adapters, early/late majority and

laggard stage, is analyzed using S-curve and thus calculated the total future market volumes of HTS

equipment. In conclusion, this paper shows the quantitative analysis for HTS cable, FCL, transformer and

rotational machine in the world market.

ETPL

GC-048 An Information-Theoretic Approach to PMU Placement in Electric Power Systems

Abstract: This paper presents an information-theoretic approach to address the phasor measurement unit

(PMU) placement problem in electric power systems. Different from the conventional `topological

observability' based approaches, this paper advocates a much more refined, information-theoretic criterion,

namely the mutual information (MI) between PMU measurements and power system states. The proposed

MI criterion not only includes observability as a special case, but also rigorously models the uncertainty

reduction on power system states from PMU measurements. Thus, it can generate highly informative PMU

configurations. The MI criterion can also facilitate robust PMU placement by explicitly modeling

probabilistic PMU outages. We propose a greedy PMU placement algorithm, and show that it achieves an

approximation ratio of (1-1/e) for any PMU placement budget. We further show that the performance is the

best that one can achieve, in the sense that it is NP-hard to achieve any approximation ratio beyond (1-1/e) .

Such performance guarantee makes the greedy algorithm very attractive in the practical scenario of multi-

stage installations for utilities with limited budgets. Finally, simulation results demonstrate near-optimal

performance of the proposed PMU placement algorithm.

ETPL

GC-049

Analysis of Frequency Dynamics in Power Grid: A Bayesian Structure Learning

Approach



http://www.elysiumtechnologies.com, [email protected] Abstract: The oscillation of frequency in power grid is studied in this paper. The possibility association of

frequencies measured at different locations are modeled by a Bayesian network with the logical structure

learned using Bayesian structure learning and real measurements in the U.S. power grid. Frequency data

analysis and the detection of incorrect frequency measurements (caused by equipment error or malicious

attack) are performed over the logical Bayesian network structure. Such application of Bayesian network is a

powerful mathematical tool in computational intelligence. Without the physical power network topology

information, a two-branch search-and-score structure learning algorithm with L -1 regulation is proposed to

learn the logical structure, achieving around 97% correct prediction rate for future frequency and 92%

detection rate for false frequency data with 2% false alarm rate. The tool of epidemic propagation over this

logical network is also exploited to analyze the propagation of frequency changes. Using the Kolmogorov-

Smirnov test, such logical structure is demonstrated to be well approximated by the Small World network

model. And the propagation of frequency changes is demonstrated to be described by the Susceptible-

Infectious-Susceptible (SIS) model quite well. The Bayesian structure obtained from the real measurement is

statistically validated using a 5-fold training data and the Pearson system.

ETPL

GC-050 Harmonic state estimation through optimal monitoring systems

Abstract: The present paper describes a methodology based on Evolutionary Algorithms (EAs) that defines

the configuration required for a monitoring system, in order to monitor voltage and current state variables

from a power network. The methodology defines not only the sites where the meters should be installed, but

also how their transducers (PTs and CTs) should be connected. The monitoring system's observability is

verified through three different rules based on Kirchhoff's laws. A branch-and-bound algorithm and a

modified Genetic Algorithm (GA) are used to solve the optimization problem. The objective is to reduce the

cost of the whole monitoring system. It is also shown why intelligent searching methods are required for

solving the optimization problem. Three different networks were used to assess the methodology's

performance: IEEE 14-bus system, IEEE 30-bus system and a real power distribution feeder. The results

were compared with the ones obtained through other methodologies that have already been published

before.

ETPL

GC-051

Fuzzy Control of Distributed PV Inverters/Energy Storage Systems/Electric Vehicles

for Frequency Regulation in a Large Power System

Abstract: Control is proposed from the view point of the frequency fluctuation problem produced by the

large penetration of PV power and sudden load variation. The fuzzy based frequency control has three

inputs: average insolation, change of insolation and frequency deviation. Following these three inputs, a

frequency control system for the distributed PV inverters is proposed. For the case of different insolations in

the different areas of the power system, a coordinated control method of the distributed PV inverters, energy

storage systems (ESSs) and EVs is presented. The proposed method is simulated by considering dual power

and information flows between supply and demand sides in a large power system and is found satisfactory to

provide frequency control and to reduce tie-line power fluctuations.

ETPL

GC-052

Reinforcement Learning Based Real-Time Wide-Area Stabilizing Control Agents to

Enhance Power System Stability

Abstract: In this paper, the design of a network of real-time close-loop wide-area decentralized power

system stabilizers (WD-PSSs) is investigated. In this approach, real-time wide-area measurement data are



http://www.elysiumtechnologies.com, [email protected] processed and utilized to design a set of stability agents based on a Reinforcement Learning (RL) method.

Recent technological breakthroughs in wide-area measurement system (WAMS) make the use of the

system-wide signals possible in designing power system controllers. The main design objectives of these

controllers are to stabilize the system after severe disturbances and mitigate the oscillations afterward. The

proposed stability agents are decentralized and autonomous. The proposed method extends the stability

boundary of the system and achieves the above goals without losing any generator or load area and without

any knowledge of the disturbances causing the response. This paper describes the developed framework and

addresses different challenges in designing such a network. A case study is provided to illustrate and verify

the performance and robustness of the proposed approach.

ETPL

GC-053

Intelligent Local Area Signals Based Damping of Power System Oscillations Using

Virtual Generators and Approximate Dynamic Programming

Abstract: his paper illustrates the development of an intelligent local area signals based controller for

damping low-frequency oscillations in power systems. The controller is trained offline to perform well

under a wide variety of power system operating points, allowing it to handle the complex, stochastic, and

time-varying nature of power systems. Neural network based system identification eliminates the need to

develop accurate models from first principles for control design, resulting in a methodology that is

completely data driven. The virtual generator concept is used to generate simplified representations of the

power system online using time-synchronized signals from phasor measurement units at generating stations

within an area of the system. These representations improve scalability by reducing the complexity of the

system “seen” by the controller and by allowing it to treat a group of several synchronous machines at

distant locations from each other as a single unit for damping control purposes. A reinforcement learning

mechanism for approximate dynamic programming allows the controller to approach optimality as it gains

experience through interactions with simulations of the system. Results obtained on the 68-bus New

England/New York benchmark system demonstrate the effectiveness of the method in damping low-

frequency inter-area oscillations without additional control effort.

ETPL

GC-054

Optimized Control of DFIG-Based Wind Generation Using Sensitivity Analysis and

Particle Swarm Optimization

Abstract: Optimal control of large-scale wind farm has become a critical issue for the development of

renewable energy systems and their integration into the power grid to provide reliable, secure, and efficient

electricity. Among many enabling technologies, the latest research results from both the power and energy

community and computational intelligence (CI) community have demonstrated that CI research could

provide key technical innovations into this challenging problem. In this paper, we propose a sensitivity

analysis approach based on both trajectory and frequency domain information integrated with evolutionary

algorithm to achieve the optimal control of doubly-fed induction generators (DFIG) based wind generation.

Instead of optimizing all the control parameters, our key idea is to use the sensitivity analysis to first identify

the critical parameters, the unified dominate control parameters (UDCP), to reduce the optimization

complexity. Based on such selected parameters, we then use particle swarm optimization (PSO) to find the

optimal values to achieve the control objective. Simulation analysis and comparative studies demonstrate the

effectiveness of our approach.

ETPL

GC-055

A Multi-Timescale Scheduling Approach for Stochastic Reliability in Smart Grids

With Wind Generation and Opportunistic Demand



http://www.elysiumtechnologies.com, [email protected] Abstract: In this study, we focus on the stochastic reliability of smart grids with two classes of energy users-

traditional energy users and opportunistic energy users (e.g., smart appliances or electric vehicles), and

investigate the procurement of energy supply from both conventional generation (base-load and fast-start)

and wind generation via multi-timescale scheduling. Specifically, in day-ahead scheduling, with the

distributional information of wind generation and demand, we characterize the optimal procurement of the

energy supply from base-load generation and the day-ahead price; in real-time scheduling, with the

realizations of wind generation and the demand of traditional energy users, we optimize real-time price to

manage opportunistic demand so as to achieve system-wise reliability and efficiency. More specifically, we

consider two different models for opportunistic energy users: non-persistent and persistent, and characterize

the optimal scheduling and pricing decisions for both models by exploiting various computational and

optimization tools. Numerical results demonstrate that the proposed scheduling and pricing schemes can

effectively manage opportunistic demand and enhance system reliability, thus have the potential to improve

the penetration of wind generation.

ETPL

GC-056

Hybrid Approach for Power System Operational Planning With Smart Grid and

Small-Signal Stability Enhancement Considerations

Abstract: Operational planning of power systems, especially in terms of overall reliability and security, is a

key issue in the smart grid development. Hence, it is necessary to develop new strategies to cope with

increasing uncertainties arising from the fast changing ways power systems are being operated. This paper

presents a comprehensive approach to determine an optimal transmission network expansion plan

considering the enhancement of small-signal stability through wide-scale deployment of the existing and

planned transmission system assets. The dynamic model of the transmission network operational planning

(TNOP) is solved based on a combination of the Mean-Variance Mapping Optimization (MVMO), and the

classic dynamic programming method embedded with a heuristic procedure. Besides, a probabilistic

eigenanalysis-based recursive method is proposed to determine the optimal control strategies that are highly

relevant to the enhancement of the system small-signal stability performance throughout the planning

horizon. Numerical results demonstrate the viewpoint and the effectiveness of the proposed approach in

providing optimal strategies of minimum cost while avoiding the instability risk associated to poorly

damped low-frequency electromechanical oscillations.

ETPL

GC-057

Contingency-Based Nodal Market Operation Using Intelligent Economic Alarm

Processor

Abstract: This paper focuses on system monitoring and alarm processing and the use of those alarms for

economic decision in the nodal electricity market. The task of an Intelligent Economic Alarm Processor

(IEAP) is to analyze thousands of alarm messages and extract useful information that explains cause-effect

sequences associated with the unexpected contingencies. A graphical Fuzzy Reasoning Petri-nets (FRPN)

model that uses fuzzy logic parameters to effectively tackle the uncertainties is built. The economic alarm

processor module then processes the fault event signal, analyzes the impact on the market operation

activities and different participants, and gives recommendations to optimize the total economic impact under

fault scenarios. A contingency-based strategic bidding model concept is proposed to help the market

participants take advantages of the latest system operation information and maximize their benefits over the

competitors.




ETPL

GC-058

Energy Load Forecasting Using Empirical Mode Decomposition and Support Vector

Regression

Abstract: In this paper we focus our attention on the long-term load forecasting problem, that is the

prediction of energy consumption for several months ahead (up to one or more years), useful in order to ease

the proper scheduling of operative conditions (such as the planning of fuel supply). While several effective

techniques are available in the short-term framework, no reliable methods have been proposed for long-term

predictions. For this purpose, we describe in this work a new procedure, which exploits the Empirical Mode

Decomposition method to disaggregate a time series into two sets of components, respectively describing

the trend and the local oscillations of the energy consumption values. These sets are then used for training

Support Vector Regression models. The experimental results, obtained both on a public-domain and on an

office building dataset, allow to validate the effectiveness of the proposed method.

ETPL

GC-059 A Noninvasive Threat Analyzer for Advanced Metering Infrastructure in Smart Grid

Abstract: Advanced Metering Infrastructure (AMI) is the core component in a smart grid that exhibits a

highly complex network configuration. AMI comprises heterogeneous cyber-physical components, which

are interconnected through different communication media, protocols, and security measures. They are

operated using different data delivery modes and security policies. The inherent complexity and

heterogeneity in AMI significantly increases the potential of security threats due to misconfiguration or

absence of defense, which may cause devastating damage to AMI. Therefore, there is a need for creating a

formal model that can represent the global behavior of AMI configuration in order to verify the potential

threats. In this paper, we present SmartAnalyzer, a security analysis tool, which offers manifold

contributions: (i) formal modeling of AMI configuration that includes device configurations, topology,

communication properties, interactions among the devices, data flows, and security properties; (ii) formal

modeling of AMI invariants and user-driven constraints based on the interdependencies among AMI device

configurations, security properties, and security control guidelines; (iii) verifying the AMI configuration's

compliance with security constraints using a Satisfiability Modulo Theory (SMT) solver; (iv) reporting of

potential security threats based on constraint violations, (v) analyzing the impact of potential threats on the

system; and (vi) systematic diagnosing of SMT unsatisfiable traces and providing necessary remediation

plans. The accuracy and scalability of the tool are evaluated on an AMI testbed and various synthetic test

networks.

ETPL GC-

060

A Game Theory Strategy to Integrate Distributed Agent-Based Functions in Smart

Grids

Abstract: The increasing incorporation of renewable energy sources and the emergence of new forms and

patterns of electricity consumption are contributing to the upsurge in the complexity of power grids. A

bottom-up-agent-based approach is able to handle the new environment, such that the system reliability can

be maintained and costs reduced. However, this approach leads to possible conflicting interests between

maintaining secure grid operation and the market requirements. This paper proposes a strategy to solve the

conflicting interests in order to achieve overall optimal performance in the electricity supply system. The

method is based on a cooperative game theory to optimally allocate resources from all (local) actors, i.e.,



http://www.elysiumtechnologies.com, [email protected] network operators, active producers, and consumers. Via this approach, agent-based functions, for

facilitating both network services and energy markets, can be integrated and coordinated. Simulations are

performed to verify the proposed concept on a medium voltage 30-bus test network. Results show the

effectiveness of the approach in optimally harmonizing functions of power routing and matching.

ETPL

GC-061

A SAX-Based Advanced Computational Tool for Assessment of Clustered Rooftop

Solar PV Impacts on LV and MV Networks in Smart Grid

Future distribution networks with increasing level of solar PV penetration will be managed using smart grid

technologies capable of producing appropriate and timely response during normal and abnormal operational

events. Distribution feeder loads vary throughout the day according to the trend of consumption of the

customers. Solar PV outputs fluctuate in proportion to irradiance level of sun. Simultaneous occurrence of

both of these variations would result in various operating conditions that may lead to unexpected events, and

would require a large amount of network data to be processed and analyzed for decision making. It is

envisaged that such data will be available in the future grids with the availability of smart technologies and

advanced communication in residential dwellings, commercial buildings and industrial complexes. In this

paper, an advanced intelligent computational tool is developed to characterize and analyze the large amount

of data associated with wide variations in network behavior using SAX (Symbolic Aggregate

Approximation) and pattern recognition. The proposed tool is capable of dealing with network asymmetry,

load unbalance, single-phase solar PV integration and their impacts on upstream networks and will assist in

making right and timely decision to mitigate adverse impacts of solar PV. The proposed tool has been tested

with a practical three-phase distribution system in Australia and can provide an extensive assessment with

less computational efforts and time.

ETPL

GC-062 On Improving Distortion Power Quality Index in Distributed Power Grids

Abstract: This paper presents the Euclidean norm based new power quality index (PQI), which is directly

related to the distortion power generated from nonlinear loads, to apply for a practical distribution power

network by improving the performance of the previous PQI proposed by the authors. The proposed PQI is

formed as a combination of two factors, which are the electrical load composition rate (LCR) and the

Euclidean norm of total harmonic distortions (THDs) in measured voltage and current waveforms. The

reduced multivariate polynomial (RMP) model with the one-shot training property is applied to estimate the

LCR. Based on the proposed PQI, the harmonic pollution ranking, which indicates how much negative

effect each nonlinear load has on the point of common coupling (PCC) with respect to distortion power, is

determined. Its effectiveness and validity are verified by the experimental results from its prototype's

implementation in a laboratory with a single-phase 3 kW photovoltaic (PV) grid-connected inverter, which

contributes to a small distortion in voltage at the PCC, and practical nonlinear loads. Then, the harmonic

current injection model based time-domain simulations are carried out to prove the effectiveness of the

proposed PQI under the other conditions with different nonlinear loads.

ETPL

GC-063 Smart Grid Communication: Its Challenges and Opportunities

The necessity to promote smart grid (SG) has been recognized with a strong consensus. The SG integrates

electrical grids and communication infrastructures and forms an intelligent electricity network working with

all connected components to deliver sustainable electricity supplies. Many advanced communication



http://www.elysiumtechnologies.com, [email protected] technologies have been identified for SG applications with a potential to significantly enhance the overall

efficiency of power grids. In this paper, the challenges and applications of communication technologies in

SG are discussed. In particular, we identify three major challenges to implement SG communication

systems, including standards interoperability, cognitive access to unlicensed radio spectra, and cyber

security. The issues to implement SG communications on an evolutional path and its future trends are also

addressed. The aim of this paper is to offer a comprehensive review of state-of-the-art researches on SG

communications.

ETPL

GC-064 Day-Ahead Resource Scheduling Including Demand Response for Electric Vehicles

Abstract: The energy resource scheduling is becoming increasingly important, as the use of distributed

resources is intensified and massive gridable vehicle (V2G) use is envisaged. This paper presents a

methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of

distributed generation and V2G. The main focus is the comparison of different EV management approaches

in the day-ahead energy resources management, namely uncontrolled charging, smart charging, V2G and

Demand Response (DR) programs in the V2G approach. Three different DR programs are designed and

tested (trip reduce, shifting reduce and reduce+shifting). Other important contribution of the paper is the

comparison between deterministic and computational intelligence techniques to reduce the execution time.

The proposed scheduling is solved with a modified particle swarm optimization. Mixed integer non-linear

programming is also used for comparison purposes. Full ac power flow calculation is included to allow

taking into account the network constraints. A case study with a 33-bus distribution network and 2000 V2G

resources is used to illustrate the performance of the proposed method.

ETPL

GC-065

Modified Particle Swarm Optimization Applied to Integrated Demand Response and

DG Resources Scheduling

Abstract: The elastic behavior of the demand consumption jointly used with other available resources such

as distributed generation (DG) can play a crucial role for the success of smart grids. The intensive use of

Distributed Energy Resources (DER) and the technical and contractual constraints result in large-scale non

linear optimization problems that require computational intelligence methods to be solved. This paper

proposes a Particle Swarm Optimization (PSO) based methodology to support the minimization of the

operation costs of a virtual power player that manages the resources in a distribution network and the

network itself. Resources include the DER available in the considered time period and the energy that can be

bought from external energy suppliers. Network constraints are considered. The proposed approach uses

Gaussian mutation of the strategic parameters and contextual self-parameterization of the maximum and

minimum particle velocities. The case study considers a real 937 bus distribution network, with 20310

consumers and 548 distributed generators. The obtained solutions are compared with a deterministic

approach and with PSO without mutation and Evolutionary PSO, both using self-parameterization.

ETPL

GC-066

Comprehensive Real-Time Microgrid Power Management and Control With

Distributed Agents

Abstract: Advances in smart grid technology have yet to coalesce into a comprehensive solution integrating

the landscape of future power systems. The microgrid concept may offer a solution for combining advanced

components and enabling technologies within an infrastructure that must expand to meet emerging demands.

As autonomous power system entities, microgrids require robust real-time power management and control to



http://www.elysiumtechnologies.com, [email protected] simultaneously operate jointly with the utility, provide reliable service, and help achieve customer-driven

objectives utilizing local power system assets. In this paper, a decentralized control architecture for

microgrids is presented, along with a simulation environment appropriate for on-going investigations into

real-time, agent-based decision-making. Challenges faced by operating self-organizing multi-agent system

(MAS) are presented, as well as results for a representative power management scenario for a multi-asset

microgrid capable of operating in grid-interconnected or islanded mode. The system and formulations

presented demonstrate the viability and capability of decentralized agent-based control for microgrids and

illustrate their potential towards achieving smart grid goals.

ETPL

GC-067

Biogeography Based Optimal State Feedback Controller for Frequency Regulation of a

Smart Microgrid

Abstract: Development of “Q” and “R” matrices for designing a Linear Quadratic Regulator (LQR) is still a

research challenge. The theory says they should belong to the group of positive definite matrices, so we need

to find out the most suitable amongst them in order to obtain the desired response. In this paper

biogeography based optimization (BBO) technique has been applied to come up with the best “Q” and “R”

matrices such that the frequency excursion following a disturbance in a microgrid is minimized. As all the

states in a practical system may not be measurable hence, we have used Kalman estimator to estimate them.

These estimated states along with other measured states are used by the LQR to produce the desired control

signal. The microgrid is made smarter by using the agent based scheme integrated with a master controller

and a proper communication protocol. The simulation results show that the proposed approach improves the

microgrid frequency response and also gives a new alternative method for frequency control of a smart

microgrid.

ETPL

GC-068

Economic Analysis and Power Management of a Small Autonomous Hybrid Power

System (SAHPS) Using Biogeography Based Optimization (BBO) Algorithm

Abstract: In this study, Biogeography Based Optimization (BBO) algorithm is developed for the prediction

of the optimal sizing coefficient of Small Autonomous Hybrid Power System (SAHPS) in remote areas.

BBO algorithm is used to evaluate optimal component sizing and operational strategy by minimizing the

total cost of SAHPS, while guaranteeing the availability of energy. Due to the complexity of the SAHPS

design with nonlinear integral planning, BBO algorithm is used to solve the problem. The developed BBO

Algorithm has been applied to design the wind/PV/hydro hybrid energy systems to supply a colony located

in the area of Jaipur, Rajasthan (India) during the period of January, 2010 to January 2011. It is clear from

the results that the proposed BBO method has excellent convergence property, requires less computational

time and can avoid the shortcoming of premature convergence of other optimization techniques to obtain a

better solution

ETPL

GC-069

Advanced Metering for Phase Identification, Transformer Identification, and

Secondary Modeling

Abstract: Advanced metering infrastructure (AMI) offers utilities new ways to model and analyze

distribution circuits. Results from two circuits introduce a new method to identify phasing of transformers

and single-phase taps using voltage and kilowatt-hour measurements from AMI. In addition to phase

identification, we show how to use the same approach to create or check meter-to-transformer mappings.

These algorithms are based on linear regression and basic voltage drop relationships. With this approach,

secondary connectivity and impedance models can be auto generated. In addition, detection of unmetered



http://www.elysiumtechnologies.com, [email protected] load appears possible. Also demonstrated is use of AMI to estimate primary-side voltage profiles.

ETPL

GC-070

A Multiagent Modeling and Investigation of Smart Homes With Power Generation,

Storage, and Trading Features

Abstract: Smart homes, as active participants in a smart grid, may no longer be modeled by passive load

curves; because their interactive communication and bidirectional power flow within the smart grid affects

demand, generation, and electricity rates. To consider such dynamic environmental properties, we use a

multiagent-system-based approach in which individual homes are autonomous agents making rational

decisions to buy, sell, or store electricity based on their present and expected future amount of load,

generation, and storage, accounting for the benefits each decision can offer. In the proposed scheme, home

agents prioritize their decisions based on the expected utilities they provide. Smart homes' intention to

minimize their electricity bills is in line with the grid's aim to flatten the total demand curve. With a set of

case studies and sensitivity analyses, we show how the overall performance of the home agents converges-as

an emergent behavior-to an equilibrium benefiting both the entities in different operational conditions and

determines the situations in which conventional homes would benefit from purchasing their own local

generation-storage systems.

ETPL

GC-071

Smart Personal Sensor Network Control for Energy Saving in DC Grid Powered LED

Lighting System

Abstract: Emerging smart grid technologies aim to renovate traditional power grid by integrating intelligent

devices and their communications for monitoring and automation of the power grid to enable efficient

demand-side energy management. In this paper, energy management in smart dc building grid powered dc

electrical appliances like lighting is investigated, in particular energy savings from proposed personal

lighting management strategy. Unlike conventional fluorescent lamps powered mainly by ac grid, LED

luminaires are dc in nature, thus results in significant power conversion losses, if operate on traditional ac

powered system, are analyzed with proposed dc distribution building grid for LED lighting. This paper

continues to explore the use of smart wireless sensors for personal control of the dc grid powered networked

LED lighting. Experimental results show that the proposed smart LED lighting system with an energy

saving mechanism incorporated is able to achieve similar lighting performance as the conventional lighting

condition, while at the same time, able to attain about 44% energy saving as compared to the original ac

fluorescent system. For a low voltage dc grid being implemented, the maximum power loss and voltage drop

of the developed dc distribution building grid are 2.25% and 3% respectively.

ETPL

GC-072

The Impact of Load Characterization on the Average Properties of Statistical Models

for Powerline Channels

Abstract: In this paper the impact of load characterization on the statistical modeling of indoor powerline

channels is investigated in the bandwidth 100 kHz-50 MHz. Our analysis refers to the mean properties of

such channels (so that their time-varying features are ignored) and is based on: a) the use of the statistical

channel simulator, which has been validated through experimental measurements, described in ; b) the

availability of a set of experimental results about the impedance of various appliances. Our numerical and

experimental results evidence that, on the one hand, for frequencies beyond 20 MHz the influence of load

characterization on the accuracy of statistical channel modelling is marginal; however, on the other hand, for

frequencies in the order of 0-20 MHz the properties of the loads connected to a power network can



http://www.elysiumtechnologies.com, [email protected] appreciably affect the properties of the channel model.

ETPL

GC-073 An Intelligent Home Energy Management System to Improve Demand Response

Abstract: Demand Response (DR) and Time-of-Use (TOU) pricing refer to programs which offer incentives

to customers who curtail their energy use during times of peak demand. In this paper, we propose an

integrated solution to predict and re-engineer the electricity demand (e.g., peak load reduction and shift) in a

locality at a given day/time. The system presented in this paper expands DR to residential loads by

dynamically scheduling and controlling appliances in each dwelling unit. A decision-support system is

developed to forecast electricity demand in the home and enable the user to save energy by recommending

optimal run time schedules for appliances, given user constraints and TOU pricing from the utility company.

The schedule is communicated to the smart appliances over a self-organizing home energy network and

executed by the appliance control interfaces developed in this study. A predictor is developed to predict,

based on the user's life style and other social/environmental factors, the potential schedules for appliance run

times. An aggregator is used to accumulate predicted demand from residential customers.

ETPL

GC-074

Adaptive Negotiation Agent for Facilitating Bi-Directional Energy Trading Between

Smart Building and Utility Grid,

Abstract: Smart and green buildings have attracted much attention in recent years. Development of an

effective negotiation model for facilitating the bi-directional energy trading between the utility grid and the

building is important for enhancing the building intelligence. In this paper, a negotiation agent based on

adaptive attitude bidding strategy (AABS) is proposed. A comprehensive set of factors for the integrated

smart building and utility grid system is taken into account in developing the negotiation model. The AABS

based negotiation agent turns out to be able to dynamically adjust its behavior in response to varying

attitudes in the negotiation process. In addition, an improved particle swarm optimization-adaptive attitude

bidding strategy (PSO-AABS) based negotiation agent is developed for adaptively adjusting the trader's

decisions according to the opponent's behaviors. It turns out to be capable of making rational deals in bi-

directional energy trading by maximizing the trader's payoffs with reduced negotiation time. The feasibility

of the proposed negotiation agents is evaluated by the simulation results.

ETPL

GC-075

Optimal Planning and Routing in Medium Voltage PowerLine Communications

Networks

Abstract: This paper deals with the problem of deploying a PowerLine Communication (PLC) network over

a medium voltage (MV) power grid. The PLC network is used to connect the end nodes (ENs) of the MV

grid to the service provider by means of PLC network nodes enabled as access points. In particular, a

network planning problem is faced wherein we require to define the PLC network topology by deciding

which MV network nodes are to be enabled as access points. An optimization problem is then formulated,

which minimizes the cost of enabling the access points and maximizes the reliability of PLC network paths

in a multi-objective optimization fashion. This work also considers resiliency (i.e., it guarantees the PLC

network connectivity even in case of link faults) and capacity constraints (i.e., it checks that there are

enough resources to transmit the estimated amount of traffic over the PLC network paths). As a byproduct,

the optimization algorithm also returns the optimal routing. Simulations based on realistic MV network

topologies validate the proposed approach




ETPL

GC-076

A Scalable Three-Step Approach for Demand Side Management of Plug-in Hybrid

Vehicles

Abstract: In this paper, we present a scalable approach for DSM (demand side management) of PHEVs

(plug-in hybrid electric vehicles). Essentially, our approach consists of three steps: aggregation,

optimization, and control. In the aggregation step, individual PHEV charging constraints are aggregated

upwards in a tree structure. In the optimization step, the aggregated constraints are used for scalable

computation of a collective charging plan, which minimizes costs for electricity supply. In the real-time

control step, this charging plan is used to create an incentive signal for all PHEVs, determined by a market-

based priority scheme. These three steps are executed iteratively to cope with uncertainty and dynamism. In

simulation experiments, the proposed three-step approach is benchmarked against classic, fully centralized

approaches. Results show that our approach is able to charge PHEVs with comparable quality to optimal,

centrally computed charging plans, while significantly improving scalability.

ETPL

GC-077

Using ICT-Controlled Plug-in Electric Vehicles to Supply Grid Regulation in

California at Different Renewable Integration Levels

Abstract: The purpose of this paper is to quantify the potential for plug-in electric vehicles (PEVs) to meet

operating reserve requirements associated with increased deployment of wind and solar generation. The

paper advances prior PEV estimates in three key ways. First, we employ easily implementable scheduling

strategies with very low centralized computing requirements. Second, we estimate PEV availability based on

data sampled from the National Household Travel Survey (NHTS). Third, we predict regulation demand on

a per minute basis using published models from the California ISO for 20% and 33% renewable electricity

supply. Our key results are as follows: First, the amount of regulation up and regulation down energy

delivered by PEVs can be balanced by using a hybrid of two scheduling strategies. Second, the percentage

of regulation energy that can be delivered with PEVs is always significantly higher than the percentage of

conventional regulation power capacity that is deferred by PEVs. Third, regulation up is harder to satisfy

with PEVs than regulation down. Fourth, the scheduling strategies we employ here have a limited impact on

load following requirements. Our results indicate that 3 million PEVs could satisfy a significant portion-but

not all-of the regulation energy and capacity requirements that are anticipated in California in 2020.

ETPL

GC-078

Efficient Computation of Sensitivity Coefficients of Node Voltages and Line Currents

in Unbalanced Radial Electrical Distribution Networks

Abstract: The problem of optimal control of power distribution systems is becoming increasingly

compelling due to the progressive penetration of distributed energy resources in this specific layer of the

electrical infrastructure. Distribution systems are, indeed, experiencing significant changes in terms of

operation philosophies that are often based on optimal control strategies relying on the computation of

linearized dependencies between controlled (e.g., voltages, frequency in case of islanding operation) and

control variables (e.g., power injections, transformers tap positions). As the implementation of these

strategies in real-time controllers imposes stringent time constraints, the derivation of analytical dependency

between controlled and control variables becomes a non-trivial task to be solved. With reference to optimal

voltage and power flow controls, this paper aims at providing an analytical derivation of node voltages and

line currents as a function of the nodal power injections and transformers tap-changers positions. Compared

to other approaches presented in the literature, the one proposed here is based on the use of the [Y]

compound matrix of a generic multi-phase radial unbalanced network. In order to estimate the



http://www.elysiumtechnologies.com, [email protected] computational benefits of the proposed approach, the relevant improvements are also quantified versus

traditional methods. The validation of the proposed method is carried out by using both IEEE 13 and 34

nodes test feeders. The paper finally shows the use of the proposed method for the problem of optimal

voltage control applied to the IEEE 34 node test feeder

ETPL

GC-079

Power Flow Optimization for Smart Microgrids by SDP Relaxation on Linear

Networks

Abstract: In a smart microgrid currents injected by distributed energy resources (DERs) and by the point of

common coupling can be adapted to minimize the energy cost. Design and quality constraints usually make

the problem grow fast with the number of nodes in the network. In this paper we provide a solution to the

optimization problem having a significantly reduced complexity with respect to existing techniques. The

efficiency of the proposed solution stems by modeling the smart microgrid as a linear network where loads

are approximated as impedances. This simplification allows avoiding explicit use of power flow equations,

and having a number of equation proportional to the number of DERs rather than to the total number of

nodes (loads and DERs). The optimal power flow problem is then solved by a semidefinite programming

(SDP) relaxation, which provides the initial point for the search of a feasible solution by a sequential convex

programming procedure based on a local linear approximation of non-convex constraints. Numerical results

show the merits of the proposed approach for typical smart microgrid scenarios.

ETPL

GC-080

Simulative Comparison of Multiprotocol Label Switching and OpenFlow Network

Technologies for Transmission Operations

Abstract: Utility companies are integrating multiprotocol label switching (MPLS) technologies into existing

backbone networks, including networks between substations and control centers. MPLS has mechanisms for

efficient overlay technologies as well as mechanisms to enhance security: features essential to the

functioning of the smart grid. However, with MPLS routing and other switching technologies innovation is

restricted to the features enclosed “in the box.” More specifically, there is no practical way for utility

operators or researchers to test new ideas such as alternatives to IP or MPLS on a realistic scale to obtain the

experience and confidence necessary for real world deployments. As a result, novel ideas go untested.

Conversely, the OpenFlow framework has enabled significant advancements in network research. OpenFlow

provides utility operators and researchers the programmability and flexibility necessary to enable innovation

in next-generation communication architectures for the smart grid. This level of flexibility allows OpenFlow

to provide all features of MPLS and also allows OpenFlow devices to co-exist with existing MPLS devices.

The simulation results in this paper demonstrate that OpenFlow performs as well as MPLS, and may

therefore be considered an alternative to MPLS for smart grid applications.

ETPL

GC-081 Multi-Agent Based Hierarchical Hybrid Control for Smart Microgrid

Abstract: This paper studies the smart control issue for an autonomous microgrid in order to maintain the

secure voltages as well as maximize economic and environmental benefits. A control scheme called as

multi-agent based hierarchical hybrid control is proposed versus the hierarchical control requirements and

hybrid dynamic behaviors of the microgrid. The control scheme is composed of an upper level energy

management agent, several middle level coordinated control agents and many lower level unit control

agents. The goals of smart control are achieved by designed control strategies. The simulations are given to

demonstrate the effectiveness of proposed smart control for an autonomous microgrid.




ETPL

GC-082

Electric Vehicle Mobility in Transmission-Constrained Hourly Power Generation

Scheduling

Abstract: The proposed approach evaluates the effect of integrating a large number of electric vehicles

(EVs) on power grid operation and control. The EV fleets could serve as electricity load when drawing

energy from the grid and as energy storage (vehicle-to-grid) when delivering energy to the grid. The paper

considers two operating modes for EV fleets which are consumer-controlled and grid-controlled. The power

grid generation mix represents a multitude of units including thermal, hydro, and wind. The paper considers

the impact of EV battery utilization on offsetting the hourly variability of wind generation units in

transmission-constrained power grids. The paper considers charging/discharging schedule of EV batteries

and consumer driving requirements on the optimal hourly transmission-constrained commitment and

dispatch of generation units in the day-ahead scheduling. The hourly solution of the proposed method will

minimize the cost of supplying the hourly load while satisfying the temporal constraints of individual

components in power grids.

ETPL

GC-083 Optimal Control of End-User Energy Storage

Abstract: An increasing number of retail energy markets show price fluctuations, providing users with the

opportunity to buy energy at lower than average prices. We propose to temporarily store this inexpensive

energy in a battery, and use it to satisfy demand when energy prices are high, thus allowing users to exploit

the price variations without having to shift their demand to the low-price periods. We study the battery

control policy that yields the best performance, i.e., minimizes the total discounted costs. The optimal policy

is shown to have a threshold structure, and we derive these thresholds in a few special cases. The cost

savings obtained from energy storage are demonstrated through extensive numerical experiments, and we

offer various directions for future research

ETPL

GC-084

Distribution Power Flow Management Utilizing an Online Constraint Programming

Method

Abstract: This paper presents a novel active power flow management (PFM) method for managing multiple

distributed generator (DG) units connected to medium voltage distribution networks. The method uses the

artificial intelligence technique of constraint programming to autonomously manage DG real power outputs

and offers flexible and network agnostic characteristics. The method is assessed using multiple scenarios on

two real case study networks to examine simulated closed-loop control actions under certain thermal

excursions. The test cases are explored with algorithms implemented, in software, on commercially

available substation computing hardware to identify computation timescales and investigate algorithm

robustness when presented with measurement error. The archival value of this paper is in the specification

and evaluation of a novel application of the constraint programming technique for online control of DG in

thermally constrained distribution networks.

ETPL

GC-085 Fully Distributed Coordination of Multiple DFIGs in a Microgrid for Load Sharing

Abstract: When wind power penetration is high, the available generation may be more than needed,

especially for wind-powered microgrids working autonomously. Because the maximum peak power tracking

algorithm may result in a supply-demand imbalance, an alternative algorithm is needed for load sharing. In

this paper, a fully distributed control scheme is presented to coordinate the operations of multiple doubly-fed



http://www.elysiumtechnologies.com, [email protected] induction generators (DFIGs) in a microgrid. According to the proposed control strategy, each bus in a

microgrid has an associated bus agent that may have two function modules. The global information

discovery module discovers the total available wind generation and total demand. The load sharing control

module calculates the generation reference of a DFIG. The consensus-based algorithm can guarantee

convergence for microgrids of arbitrary topologies under various operating conditions. By controlling the

utilization levels of DFIGs to a common value, the supply-demand balance can be maintained. In addition,

the detrimental impact of inaccurate and outdated predictions of maximum wind power can be alleviated.

The generated control references are tracked by coordinating converter controls and pitch angle control.

Simulation results with a 5-DFIG microgrid demonstrate the effectiveness of the proposed control scheme.

ETPL

GC-086

Residential Distribution System Harmonic Compensation Using PV Interfacing

Inverter

Abstract: The increased non-linear loads in today's typical home are a growing concern for utility

companies. This situation might be worsened by the harmonic resonance introduced by the installation of

capacitor banks in the distribution network. To mitigate the harmonic distortions, passive or active filters are

typically used. However, with the increasing implementation of distributed generation (DG) in residential

areas, using DG systems to improve the power quality is becoming a promising idea, particularly because

many DG systems, such as photovoltaic (PV), wind and fuel cells, have DG-grid interfacing converters. In

this paper, the potential for using photovoltaic (PV) interfacing inverters to compensate the residential

system harmonics is explored. A system model including the residential load and DG is first developed. An

in-depth analysis and comparison of different compensation schemes based on the virtual harmonic damping

impedance concept are then carried out. The effects of the capacitor banks in the system are also studied.

The effectiveness of the harmonic compensation strategies under different conditions is verified through

analysis and simulations.

ETPL

GC-087 Distributed Control of the Power Supply-Demand Balance

Abstract: This paper aims to achieve a balance of power in a group of prosumers, based on a price

mechanism, i.e., to steer the difference between the total production and consumption of power to zero. We

first set the information network topology such that the prosumers exchange price (power) information with

their neighbors according to a chosen information network topology. Based on the exchanged information

and the prosumers own measured power demand, each prosumer uses a local control strategy to turn on and

off its power generator to cooperatively achieve the global balance. More specifically, the local control

strategy results from a distributed model predictive control method based on dual decomposition and sub-

gradient iterations. The method achieves a unique dynamic price signal for each prosumer. Simulation

results with realistic data validate the method.

ETPL

GC-088

Cyber-Physical Security Testbeds: Architecture, Application, and Evaluation for

Smart Grid

Abstract: The development of a smarter electric grid will depend on increased deployments of information

and communication technology (ICT) to support novel communication and control functions. Unfortunately,

this additional dependency also expands the risk from cyber attacks. Designing systems with adequate cyber

security depends heavily on the availability of representative environments, such as testbeds, where current

issues and future ideas can be evaluated. This paper provides an overview of a smart grid security testbed,



http://www.elysiumtechnologies.com, [email protected] including the set of control, communication, and physical system components required to provide an

accurate cyber-physical environment. It then identifies various testbed research applications and also

identifies how various components support these applications. The PowerCyber testbed at Iowa State

University is then introduced, including the architecture, applications, and novel capabilities, such as

virtualization, Real Time Digital Simulators (RTDS), and ISEAGE WAN emulation. Finally, several attack

scenarios are evaluated using the testbed to explore cyber-physical impacts. In particular, availability and

integrity attacks are demonstrated with both isolated and coordinated approaches, these attacks are then

evaluated based on the physical system's voltage and rotor angle stability.

ETPL

GC-089 On the Exact Solution to a Smart Grid Cyber-Security Analysis Problem

Abstract: This paper considers a smart grid cyber-security problem analyzing the vulnerabilities of electric

power networks to false data attacks. The analysis problem is related to a constrained cardinality

minimization problem. The main result shows that an relaxation technique provides an exact optimal

solution to this cardinality minimization problem. The proposed result is based on a polyhedral

combinatorics argument. It is different from well-known results based on mutual coherence and restricted

isometry property. The results are illustrated on benchmarks including the IEEE 118-bus, IEEE 300-bus, and

the Polish 2383-bus and 2736-bus systems..

ETPL

GC-090

Demand-Side Management via Distributed Energy Generation and Storage

Optimization

Abstract: Demand-side management, together with the integration of distributed energy generation and

storage, are considered increasingly essential elements for implementing the smart grid concept and

balancing massive energy production from renewable sources. We focus on a smart grid in which the

demand-side comprises traditional users as well as users owning some kind of distributed energy sources

and/or energy storage devices. By means of a day-ahead optimization process regulated by an independent

central unit, the latter users intend to reduce their monetary energy expense by producing or storing energy

rather than just purchasing their energy needs from the grid. In this paper, we formulate the resulting grid

optimization problem as a noncooperative game and analyze the existence of optimal strategies.

Furthermore, we present a distributed algorithm to be run on the users' smart meters, which provides the

optimal production and/or storage strategies, while preserving the privacy of the users and minimizing the

required signaling with the central unit. Finally, the proposed day-ahead optimization is tested in a realistic

situation.

ETPL

GC-091 Automatic Distributed Voltage Control Algorithm in Smart Grids Applications

Abstract: The widespread use of distributed generation (DG), which is installed in medium-voltage

distribution networks, impacts the future development of modern electrical systems that must evolve

towards smart grids. A fundamental topic for smart grids is automatic distributed voltage control (ADVC).

The voltage is now regulated at the MV busbar acting on the on-load tap changer of the HV/MV

transformer. This method does not guarantee the correct voltage value in the network nodes when the

distributed generators deliver their power. In contrast, the ADVC allows control of the voltage acting on a



http://www.elysiumtechnologies.com, [email protected] single generator; therefore, a better voltage profile can be obtained. In this paper, an approach based on

sensitivity theory is shown to control the node voltages regulating the reactive power injected by the

generators. After the theoretical analysis, a numerical example is presented to validate the theory. The

proposed voltage regulation method has been developed in collaboration with Enel Distribuzione S.p.A. (the

major Italian DSO), and it will be applied in the Smart Grids POI-P3 pilot project, which is financed by the

Italian Economic Development Ministry. Before the real field application in the pilot project, a real-time

digital simulation has been used to validate the algorithm presented. Moving in this direction, Enel

Distribuzione S.p.A. built a new test center in Milan equipped with a real-time digital simulator (from RTDS

Technologies).

ETPL GC-

092

IGDT Based Robust Decision Making Tool for DNOs in Load Procurement Under

Severe Uncertainty

This paper presents the application of information gap decision theory (IGDT) to help the distribution

network operators (DNOs) in choosing the supplying resources for meeting the demand of their customers.

The three main energy resources are pool market, distributed generations (DGs), and the bilateral contracts.

In deregulated environment, the DNO is faced with many uncertainties associated to the mentioned

resources which may not have enough information about their nature and behaviors. In such cases, the

classical methods like probabilistic methods or fuzzy methods are not applicable for uncertainty modeling

because they need some information about the uncertainty behaviors like probability distribution function

(PDF) or their membership functions. In this paper, a decision making framework is proposed based on

IGDT model to solve this problem. The uncertain parameters considered here, are as follows: price of

electricity in pool market and demand of each bus. The robust strategy of DNO is determined to hedge him

against the risk of increasing the total cost beyond what it is willing to pay. The effectiveness of the

proposed tool is assessed and demonstrated by applying it on a large distribution network.

ETPL

GC-093 Energy Imbalance Management Using a Robust Pricing Scheme

Abstract: This paper focuses on the problem of energy imbalance management in a microgrid. The problem

is investigated from the power market perspective. Unlike the traditional power grid, a microgrid can obtain

extra energy from a renewable energy source (RES) such as a solar panel or a wind turbine. However, the

stochastic input from the RES brings difficulty in balancing the energy supply and demand. In this study, a

novel pricing scheme is proposed that provides robustness against such intermittent power input. The

proposed scheme considers possible uncertainty in the marginal benefit and the marginal cost of the power

market. It uses all available information on the power supply, power demand, and imbalanced energy. The

parameters of the scheme are evaluated using an performance index. It is shown that the parameters can be

obtained by solving a linear matrix inequality problem, which is efficiently solvable due to its convexity.

Simulation examples are given to show the favorable performance of the proposed scheme in comparison

with existing area control error pricing schemes.linear matrix inequality problem,area control error pricing

schemes.

ETPL

GC-094

Estimating the Impact of Electric Vehicle Smart Charging on Distribution

Transformer Aging

Abstract: This paper describes a method for estimating the impact of plug-in electric vehicle (PEV)

charging on overhead distribution transformers, based on detailed travel demand data and under several



http://www.elysiumtechnologies.com, [email protected] different schemes for mitigating overloads by shifting PEV charging times (smart charging). The paper also

presents a new smart charging algorithm that manages PEV charging based on estimated transformer

temperatures. We simulated the varied behavior of drivers from the 2009 National Household Transportation

Survey, and transformer temperatures based an IEEE standard dynamic thermal model. Results are shown

for Monte Carlo simulation of a 25 kVA overhead distribution transformer, with ambient temperature data

from hot and cold climate locations, for uncontrolled and several smart-charging scenarios. These results

illustrate the substantial impact of ambient temperatures on distribution transformer aging, and indicate that

temperature-based smart charging can dramatically reduce both the mean and variance in transformer aging

without substantially reducing the frequency with which PEVs obtain a full charge. Finally, the results

indicate that simple smart charging schemes, such as delaying charging until after midnight can actually

increase, rather than decrease, transformer aging.

ETPL

GC-095

Design Considerations of a Centralized Load Controller Using Thermostatically

Controlled Appliances for Continuous Regulation Reserves

Abstract: This paper presents design considerations for a centralized load controller to control

thermostatically controlled appliances (TCAs) for continuous regulation reserves (CRRs). The controller

logics for setting up the baseline load, generating priority lists, issuing dispatch commands, and tuning the

simplified forecaster model using measurement data are described. To study the impacts of different control

parameter settings on control performance and device lifetimes, a system consisting of 1000 heating,

ventilating, and air-conditioning (HVAC) units in their heating modes is modeled to provide a CRR 24

hours a day. Four cases are modeled to evaluate the impact of forecasting errors, minimum HVAC turn-off

times, response delays, and consumer overrides. The results demonstrate that a centralized TCA load

controller can provide robust, good quality CRRs with reduced communication needs for the two-way

communication network and inexpensive load control devices. Most importantly, because the controller

precisely controls the aggregated HVAC load shapes while maintaining load diversity, the controllable and

measurable load services that it provides can be used for many other demand response applications, such as

peak shaving, load shifting, and arbitrage.

ETPL

GC-096

Applications and Trends of High Performance Computing for Electric Power Systems:

Focusing on Smart Grid

Abstract: Over the last 15 years, significant changes have occurred in the areas of electric power systems

and high performance computing (HPC). HPC has seen the maturation of cluster computing, the advent of

multi-core computing, the creation of grid and cloud computing, and the sudden rise of the graphics

processing unit (GPU) for general purpose computing. These changes have also been coupled with the slow

ending of Moore's law. Electric power systems have also undergone many changes including the

introduction of the advanced metering infrastructure and other advanced technologies for data collection, the

inclusion of renewable/distributed power generation, and the addition of electric vehicles as stochastic loads.

Clear goals have also been set for the development of the smart grid-a unique cyber-physical system (CPS)

that requires the interaction of the electric power system and HPC. As such, this work explores the many

ways in which HPC will be used in the smart grid and its CPS in the future including real-time and off-line

analysis, data mining/storage, intelligent coordination, security, simulation, and visualization.

ETPL

GC-097

Uncertainty-Aware Household Appliance Scheduling Considering Dynamic Electricity

Pricing in Smart Home



http://www.elysiumtechnologies.com, [email protected] Abstract: High quality demand side management has become indispensable in the smart grid infrastructure

for enhanced energy reduction and system control. In this paper, a new demand side management technique,

namely, a new energy efficient scheduling algorithm, is proposed to arrange the household appliances for

operation such that the monetary expense of a customer is minimized based on the time-varying pricing

model. The proposed algorithm takes into account the uncertainties in household appliance operation time

and intermittent renewable generation. Moreover, it considers the variable frequency drive and capacity-

limited energy storage. Our technique first uses the linear programming to efficiently compute a

deterministic scheduling solution without considering uncertainties. To handle the uncertainties in household

appliance operation time and energy consumption, a stochastic scheduling technique, which involves an

energy consumption adaptation variable , is used to model the stochastic energy consumption patterns for

various household appliances. To handle the intermittent behavior of the energy generated from the

renewable resources, the offline static operation schedule is adapted to the runtime dynamic scheduling

considering variations in renewable energy. The simulation results demonstrate the effectiveness of our

approach. Compared to a traditional scheduling scheme which models typical household appliance

operations in the traditional home scenario, the proposed deterministic linear programming based scheduling

scheme achieves up to 45% monetary expense reduction, and the proposed stochastic design scheme

achieves up to 41% monetary expense reduction. Compared to a worst case design where an appliance is

assumed to consume the maximum amount of energy, the proposed stochastic design which considers the

stochastic energy consumption patterns achieves up to 24% monetary expense reduction without violating

the target trip rate of 0.5%. Furthermore, the proposed ener- y consumption scheduling algorithm can always

generate the scheduling solution within 10 seconds, which is fast enough for household appliance

applications.

ETPL

GC-098

Optimized Thermal and Electrical Scheduling of a Large Scale Virtual Power Plant in

the Presence of Energy Storages

Abstract: Smart grids are often analyzed using a top-down approach, i.e., starting from communication and

control technologies evolution, to then focus on their effects on active and passive users, in terms of new

services, higher efficiency and quality of supply. However, with their bottom-up approach, virtual power

plants (VPP) are very promising instruments for promoting an effective integration of distributed generation

(DG) and energy storage devices as well as valid means for enabling consumers to respond to load

management signals, when operated under the supervision of a scheduling coordinator. These aggregation

factors can be very profitable for the distributed energy resources (DERs) economy and for the energy

network itself. This paper presents a new algorithm to optimize the day-ahead thermal and electrical

scheduling of a large scale VPP (LSVPP) which contains: a) many small-scale producers and consumers

(“prosumers”) distributed over a large territory and b) energy storage and cogeneration processes. The

algorithm also takes into account the actual location of each DER in the public network and their specific

capability. Thermal and electrical generator models, load and storage devices are very detailed and flexible,

as are the rates and incentives framework. Several novelties, with respect to the previous literature, are

proposed. Case study results are also described and discussed.

ETPL

GC-099

Optimal Design of Grid-Connected PEV Charging Systems With Integrated

Distributed Resources



http://www.elysiumtechnologies.com, [email protected] Abstract: The penetration of plug-in electric vehicles and renewable distributed generation is expected to

increase over the next few decades. Large scale unregulated deployment of either technology can have a

detrimental impact on the electric grid. However, appropriate pairing of these technologies along with some

storage could mitigate their individual negative impacts. This paper presents a framework and an

optimization methodology for designing grid-connected systems that integrate plug-in electric vehicle

chargers, distributed generation and storage. To demonstrate its usefulness, this methodology is applied to

the design of optimal architectures for a residential charging case. It is shown that, given current costs,

maximizing grid power usage minimizes system lifecycle cost. However, depending upon the location's

solar irradiance patterns, architectures with solar photovoltaic generation can be more cost effective than

architectures without. Additionally, Li-ion storage technology and micro wind turbines are not yet cost

effective when compared to alternative solutions.

ETPL GC-

100

Achieving Optimality and Fairness in Autonomous Demand Response: Benchmarks

and Billing Mechanisms

Abstract: Autonomous demand response (DR) programs are scalable and result in a minimal control

overhead on utilities. The idea is to equip each user with an energy consumption scheduling (ECS) device to

automatically control the user's flexible load to minimize his energy expenditure, based on the updated

electricity pricing information. While most prior works on autonomous DR have focused on coordinating

the operation of ECS devices in order to achieve various system-wide goals, such as minimizing the total

cost of generation or minimizing the peak-to-average ratio in the load demand, they fall short addressing the

important issue of fairness. That is, while they usually guarantee optimality, they do not assure that the

participating users are rewarded according to their contributions in achieving the overall system's design

objectives. Similarly, they do not address the important problem of co-existence when only a sub-set of

users participate in a deployed autonomous DR program. In this paper, we seek to tackle these shortcomings

and design new autonomous DR systems that can achieve both optimality and fairness. In this regard, we

first develop a centralized DR system to serve as a benchmark. Then, we develop a smart electricity billing

mechanism that can enforce both optimality and fairness in autonomous DR systems in a decentralized

fashion.

ETPL

GC-101 A Market Based Scheme to Integrate Distributed Wind Energy

Abstract: Efficiently integrating wind energy into the smart grid is gaining momentum under renewable

portfolio standard (RPS) with deep wind penetration. Due to the randomness of wind energy production,

ancillary service (AS) is needed in large amount to regulate wind power for system stability and reliability.

As a result, the cost of wind power depends on the AS market and may be, quite higher than that of

conventional power. Therefore, it is challenging to economically integrate wind energy with current power

system to satisfy RPS. With the communication, sensing and advanced control features incorporated into the

smart grid, the interactions among the grid components will facilitate solving this problem. In this paper, we

consider the wind energy integration of small-scale utilities installed with wind turbines and acted as

distributed energy resources (DERs). Since wind energy can be integrated to serve customer load or enter a

separate green energy market, we propose a theoretical framework to dynamically determine the role of

wind energy and provide long-term RPS guarantee. This approach results in a simple dynamic threshold

control policy which maximizes the expectation of the profit for a green utility and is easily implemented



http://www.elysiumtechnologies.com, [email protected] online.

ETPL

GC-102 Optimal Integration of Distributed Energy Storage Devices in Smart Grids

Abstract: Energy storage is traditionally well established in the form of large scale pumped-hydro systems,

but nowadays is finding increased attraction in medium and smaller scale systems. Such expansion is

entirely complementary to the forecasted wider integration of intermittent renewable resources in future

electrical distribution systems (Smart Grids). This paper is intended to offer a useful tool for analyzing

potential advantages of distributed energy storages in Smart Grids with reference to both different possible

conceivable regulatory schemes and services to be provided. The Smart Grid Operator is assumed to have

the ownership and operation of the energy storage systems, and a new cost-based optimization strategy for

their optimal placement, sizing and control is proposed. The need to quantify benefits of both the Smart Grid

where the energy storage devices are included and the external interconnected grid is explored. Numerical

applications to a Medium Voltage test Smart Grid show the advantages of using storage systems related to

different options in terms of incentives and services to be provided.

ETPL

GC-103 A Microgrid Energy Management System Based on the Rolling Horizon Strategy

Abstract: A novel energy management system (EMS) based on a rolling horizon (RH) strategy for a

renewable-based microgrid is proposed. For each decision step, a mixed integer optimization problem based

on forecasting models is solved. The EMS provides online set points for each generation unit and signals for

consumers based on a demand-side management (DSM) mechanism. The proposed EMS is implemented for

a microgrid composed of photovoltaic panels, two wind turbines, a diesel generator and an energy storage

system. A coherent forecast information scheme and an economic comparison framework between the RH

and the standard unit commitment (UC) are proposed. Solar and wind energy forecasting are based on

phenomenological models with updated data. A neural network for two-day-ahead electric consumption

forecasting is also designed. The system is tested using real data sets from an existent microgrid in Chile

(ESUSCON). The results based on different operation conditions show the economic sense of the proposal.

A full practical implementation of the system for ESUSCON is envisioned.

ETPL

GC-104

Tackling the Load Uncertainty Challenges for Energy Consumption Scheduling in

Smart Grid

Abstract: In this paper, we propose a novel optimization-based real-time residential load management

algorithm that takes into account load uncertainty in order to minimize the energy payment for each user.

Unlike most existing demand side management algorithms that assume perfect knowledge of users' energy

needs, our design only requires knowing some statistical estimates of the future load demand. Moreover, we

consider real-time pricing combined with inclining block rate tariffs. In our problem formulation, we take

into account different types of constraints on the operation of different appliances such as must-run

appliances, controllable appliances that are interruptible, and controllable appliances that are not

interruptible. Our design is multi-stage. As the demand information of the appliances is gradually revealed

over time, the operation schedule of controllable appliances is updated accordingly. Simulation results

confirm that the proposed energy consumption scheduling algorithm can benefit both users, by reducing

their energy expenses, and utility companies, by improving the peak-to-average ratio of the aggregate load



http://www.elysiumtechnologies.com, [email protected] demand.

ETPL

GC-105

Energy and Performance Management of Green Data Centers: A Profit Maximization

Approach

Abstract: While a large body of work has recently focused on reducing data center's energy expenses, there

exists no prior work on investigating the trade-off between minimizing data center's energy expenditure and

maximizing their revenue for various Internet and cloud computing services that they may offer. In this

paper, we seek to tackle this shortcoming by proposing a systematic approach to maximize green data

center's profit, i.e., revenue minus cost. In this regard, we explicitly take into account practical service-level

agreements (SLAs) that currently exist between data centers and their customers. Our model also

incorporates various other factors such as availability of local renewable power generation at data centers

and the stochastic nature of data centers' workload. Furthermore, we propose a novel optimization-based

profit maximization strategy for data centers for two different cases, without and with behind-the-meter

renewable generators. We show that the formulated optimization problems in both cases are convex

programs; therefore, they are tractable and appropriate for practical implementation. Using various

experimental data and via computer simulations, we assess the performance of the proposed optimization-

based profit maximization strategy and show that it significantly outperforms two comparable energy and

performance management algorithms that are recently proposed in the literature.

ETPL

GC-106

A Multi Charging Station for Electric Vehicles and Its Utilization for Load

Management and the Grid Support

Abstract: This paper discusses the modeling of a multi charging station for Electric Vehicles (EVs) and its

utilisation for grid support. Allowing the EVs to charge and discharge without any control may lead to

voltage variations in the grid. However, if the charging/discharging of the EVs is done in an intelligent

fashion, they can act as distributed energy sources and can smoothen the load profile of the distribution

network by providing peak shaving and valley filling. The presented work mainly focuses on the control

architecture for using the EVs' batteries as distributed energy storage systems. This enables in maintaining

the node voltage within the prescribed limit by valley filling and peak shaving. The control architecture is

based on fuzzy control techniques. The proposed architecture is implemented on the distribution network of

Guwahati city. Dynamic load profile is used to check the effectiveness of the proposed architecture for

flattening the load profile.

ETPL

GC-107

Multi-Objective Optimization for the Operation of an Electric Distribution System

With a Large Number of Single Phase Solar Generators

Abstract: The extensive connection of single phase solar generators which are also called microFITs (micro

feed-in tariff), to distribution systems may lead to a phase unbalance condition, a problem further

complicated due to the widespread use of single phase loads. Energy losses also change significantly when

microFITs are implemented. This paper addresses these problems with respect to the connection of a large

number of microFITs and single phase loads to three phase distribution systems. In this research, a

probabilistic model has been utilized for estimating hourly solar irradiance, and a genetic algorithm has been

employed as a means of generating a non-dominated Pareto front for minimizing the current unbalance and

energy loss in the distribution system. A decision-making process has been developed in order to determine

a single optimum solution from the Pareto front generated. Operational controls, such as voltage drop,



http://www.elysiumtechnologies.com, [email protected] transmission limits, and voltage unbalance limits, are taken into consideration in this analysis. In the context

of smart grids, the proposed algorithm will facilitate the deployment of small-sized solar generators. The

proposed method has been applied on an IEEE 123 bus distribution system in order to demonstrate the

validity of the proposed algorithm.

ETPL

GC-108

A Versatile Clustering Method for Electricity Consumption Pattern Analysis in

Households

Abstract: Analysis and modeling of electric energy demand is indispensable for power planning, operation,

facility investment, and urban planning. Because of recent development of renewable energy generation

systems oriented for households, there is also a great demand for analysing the electricity usage and

optimizing the way to install electricity generation systems for each household. In this study, employing

statistical techniques, a method to model daily consumption patterns in households and a method to extract a

small number of their typical patterns are presented. The electricity consumption patterns in a household is

modeled by a mixture of Gaussian distributions. Then, using the symmetrized generalized Kullback-Leibler

divergence as a distance measure of the distributions, typical patterns of the consumption are extracted by

means of hierarchical clustering. The statistical modeling of daily consumption patterns allows us to capture

essential similarities of the patterns. By experiments using a large-scale dataset including about 500 houses'

consumption records in a suburban area in Japan, it is shown that the proposed method is able to extract

typical consumption patterns.

ETPL

GC-109 Aggregation Model-Based Optimization for Electric Vehicle Charging Strategy

Abstract: This paper presents an aggregation charging model for large numbers of electric vehicles (EVs). A

genetic algorithm (GA) is employed to obtain the stochastic feature parameters of the aggregation model,

and a charging strategy based on the aggregation model is developed to reduce the power fluctuation level

caused by EV charging. In addition, an updatable optimization method is proposed to track the variation of

the EV charging characteristics. The proposed charging strategy and optimization method are validated by

the simulation results.

ETPL

GC-110

Detecting and Locating Faulty Nodes in Smart Grids Based on High Frequency Signal

Injection

Abstract: An on-line method for detecting and locating a faulty node in the utility grid is proposed for smart

grids. The method is based on injection of high frequency (A-Band) current signal into the grid that would

impose voltages (less than 1V according to EN50065-1 standard) on the nodes to determine changes in the

impedance characteristics. This detection is accomplished on-line without interrupting the power flow in the

network. The developed algorithm has been implemented within an electrical power system model. This low

voltage network model has been tested with different fault scenarios. The proposed procedure is able to

detect the faulty nodes with high accuracy.

ETPL

GC-111 Wireless Network Design for Transmission Line Monitoring in Smart Grid

Abstract: In this paper, we develop a real-time situational awareness framework for the electrical

transmission power grid using Wireless Sensor Network (WSN). While WSNs are capable of cost efficient

monitoring over vast geographical areas, several technical challenges exist. The low power, low data rate

devices cause bandwidth and latency bottlenecks. In this paper, our objective is to design a wireless network



http://www.elysiumtechnologies.com, [email protected] capable of real-time delivery of physical measurements for ideal preventive or corrective control action. For

network design, we formulate an optimization problem with the objective of minimizing the installation and

operational costs while satisfying the end-to-end latency and bandwidth constraints of the data flows. We

study a hybrid hierarchical network architecture composed of a combination of wired, wireless and cellular

technologies that can guarantee low cost real-time data monitoring. We formulate a placement problem to

find the optimal location of cellular enabled transmission towers. Further, we present evaluation results of

the optimization solution for diverse scenarios. Our formulation is generic and addresses real world

scenarios with asymmetric sensor data generation, unreliable wireless link behavior, non-uniform cellular

coverage, etc. Our analysis shows that a transmission line monitoring framework using WSN is indeed

feasible using available technologies. Our results show that wireless link bandwidth can be a limiting factor

for cost optimization

ETPL

GC-112 Reliability Modeling and Evaluation of Power Systems With Smart Monitoring

Abstract: Smart grid technologies leveraging advancements in sensors, communications, and computing

offer new avenues for reliability enhancements of complex power grids by increasing the up-times and

reducing the down times. This paper discusses various aspects of smart grid monitoring and proposes a

mathematical model to assess its impact on power grid reliability. Based on a multiple-state Markov chain

model, the failure and repair rates of power components with and without monitoring provisions are

determined and compared. The proposed formulation incorporates the failure rates of the monitoring

systems themselves and the impact on system/component reliability.

ETPL

GC-113

A Novel Hierarchical Section Protection Based on the Solid State Transformer for the

Future Renewable Electric Energy Delivery and Management (FREEDM) System

Abstract: The effectiveness of a protection scheme in any power grid is essential to the reliability of the

supply. One of the main goals of the FREEDM systems is to increase supply reliability to end users.

However, traditional protection methods, including over current, sequential components, and wide

differential area protection, are not suitable for this system for several reasons that will be explained in the

paper. A new protection strategy is presented in this paper. This protection scheme takes advantage not only

of the system configuration but mostly of the solid state transformer capability and design to minimize any

circuit and communication that are needed for a successful protection strategy. A real time digital simulator

(RTDS) is used to model a sample FREEDM system in order to verify the proposed protection scheme.

Hardware-in-the-loop (HIL) testing was performed to verify the proposed protection scheme.

ETPL

GC-114 An Initial Investigation for Locating Self-Clearing Faults in Distribution Systems

Abstract: An approach of inverse time-domain transient analysis is devised as a possible method of locating

self-clearing, sub-cycle incipient faults in distribution systems. Simplified modeling and formulation of a

fault distance calculation from a substation for ground faults in circuits is made using only the discrete

voltage and current samples obtained at the substation. The formula in principle seeks to find the value of a

line inductance to the fault from the substation by analyzing the transient waveform of phase voltage and

current. In particular, in the equivalent circuit of the faulted system, the method applies voltage injection and

superposition principle, obtains net fault voltage and current, and calculates the line inductance to the fault

as fault distance. The steps for implementing the formula from substation sampled data are detailed and



http://www.elysiumtechnologies.com, [email protected] illustrated, followed by validation test results with eleven actual transient faults.

ETPL

GC-115

Optimal Integration of Phasor Measurement Units in Power Systems Considering

Conventional Measurements

Abstract: This paper presents an integer linear programming (ILP) framework for the optimal placement of

phasor measurement units (PMUs), in the presence of conventional measurements. Furthermore, by the

proposed method, the power system remains completely observable during all possible single contingencies

for lines and measurement devices. In doing so, the potential of circuit equations associated with both PMUs

and conventional measurements as well as the network topology are fully utilized by a system of equations

to reach the minimum possible numbers of required PMUs. The limitation of communication channels is

also taken into account in the proposed ILP-based framework. The method is implemented on several IEEE

test systems which have already been equipped with conventional measurements. The comparison between

obtained results of the proposed method and those of other methods reveals its superiority in the modeling of

robust PMU placement problem (OPP) in the presence of conventional measurements. As such, a smooth

transition from the SCADA-based monitoring system to the PMU-dominated WAMS is ensured. Moreover,

this method is successfully applied on three large-scale test systems, which demonstrates it can effectively

be employed for robust OPP in realistic power systems.

ETPL

GC-116

Identification of Critical Components for Voltage Stability Assessment Using Channel

Components Transform

Abstract: Channel Components Transform (CCT) is a recently developed technique to decouple

interconnected power networks. This paper aims to further explore the CCT and extend its applications.

Methods and algorithms are proposed to extend its application in identifying the critical generators and

branches of a network from the voltage stability perspective. The proposed methods are verified by case

studies conducted on multiple test systems. This paper also demonstrates the capability of the CCT to work

properly when a limited number of phasor measurement units are available. For this purpose, a strategy is

proposed to determine the number and location of PMU installations that are sufficient to track the modes of

voltage collapse and associated critical components. The proposed allocation strategy is examined through

case studies of an actual power system.

ETPL

GC-117

Application of Dynamic State and Parameter Estimation Techniques on Real-World

Data

Abstract: The objective of this paper is to apply two dynamic state and parameter estimation techniques to

real-world data. Dynamic state and parameter estimation can estimate equivalent generator internal voltages

and rotor angles (dynamic states) during electromechanical dynamics. In addition, parameters such as the

transient reactances and inertia can be estimated. A set of real world data recorded by Eastern

Interconnection Phasor Measurement Units (PMU) regarding a generator trip event is analyzed in this paper.

An estimation algorithm developed by Chow was applied to estimate the states and parameters of a transfer

path. An alternative estimation method based on the classic generator model and swing equation is presented

in this paper and applied to the real world PMU data with the aid of digital filtering technology. Challenges

in real-world data applications are identified in this paper.

ETPL

GC-118

Primary Frequency Response From Electric Vehicles in the Great Britain Power

System




Abstract: With the increasing use of renewable energy in the Great Britain (GB) power system, the role of

electric vehicles (EVs) contributes to primary frequency response was investigated. A tool was developed to

estimate the EV charging load based on statistical analysis of EV type, battery capacity, maximum travel

range and battery state of charge. A simplified GB power system model was used to investigate the

contribution of EVs to primary frequency response. Two control modes were considered: disconnection of

charging load (case I) and discharge of stored battery energy (case II). For case II, the characteristic of the

EV charger was also considered. A case study shows results for the year 2020. Three EV charging

strategies: “dumb” charging, “off-peak” charging, and “smart” charging, were compared. Simulation results

show that utilizing EVs to stabilize the grid frequency in the GB system can significantly reduce frequency

deviations. However the requirement to schedule frequency response from conventional generators is

dynamic throughout the day.

ETPL

GC-119

Evaluation of Semiconductor Based Methods for Fault Isolation on High Voltage DC

Grids

Abstract: This paper investigates methods for dc fault current fast interruption in high-power dc networks. A

four terminal 1.2 GW dc transmission grid is used as a test system. The study compares four semiconductor-

based devices for dc fault isolation: series hybrid dc breaker, half bridge and full bridge dc chopper, and

LCL thyristor converter. The study considers performance of devices, costs and losses, and also application

with larger dc grids. A hybrid dc CB has lowest losses, but the component sizing crucially depends on the

speed of fault detection. It is demonstrated that fast communication between various devices in the dc grid is

mandatory but might be very challenging. On the other hand, dc choppers and LCL converter component

sizing is not dependent on the speed of protection, and there is no need for communication across dc grids.

Additionally, they offer the capability of voltage stepping and dc cable power regulation. The LCL converter

provides inherent fault current interruption and needs no overrating for dc faults. It also ives better

efficiency compared to dc choppers. The performance of these dc breakers is demonstrated using detailed

transient PSCAD simulation for dc faults.

ETPL

GC-120

The Impact of Solid State Fault Current Limiter on Power Network With Wind-

Turbine Power Generation

In this paper, it is aimed to investigate the impact of the various solid-state fault current limiters (SSFCLs)

on several electric power networks with the wind-turbine power generation (WTPG). Distributed

generations (DGs) are predicted to perform an increasing role in the future electrical power system. Expose

of the DG, can change the fault current during a grid disturbance and disturb the existing distribution system

protection. Fault current limiters (FCLs) can be sorted into L-types (inductive) and R-types (resistive) by the

fault current limiting impedance. In this paper, a new SSFCL has been proposed. SSFCLs can provide the

fast system protection during a rigorous fault. The act of dynamic damping enhancement via the SSFCL is

appraised in the presence of the wind-turbine power generation. Hence, its efficiency as a protective device

for the wind-turbine system is confirmed via some case studies by time-domain simulation based on the

PSCAD/EMTDC.

ETPL

GC-121

The Study of a Regional Decentralized Peer-to-Peer Negotiation-Based Wide-Area

Backup Protection Multi-Agent System



http://www.elysiumtechnologies.com, [email protected] Abstract: Conventional protection relays, which use local signals to locate faults, are a poor fit to modern

power grids when compared to communication-based alternatives. This article presents a novel Wide-Area

Backup Protection (WABP) algorithm that uses information shared across wide-area communication

networks. The WABP algorithm fuses and integrates information in a regional decentralized peer-to-peer

negotiation architecture for enhanced effectiveness. Line decision-making agents (LDAs), focused on line-

fault detection, collect distance and directional protection information on both sides of a line. If LDAs

cannot detect a fault locally, wide-area information that includes directional protection and line-fault states

from neighboring lines is collected to locate the fault. The LDA considers the possible presence of relay

misoperations, protection failures, and/or communication failures. Regional decision-making agents (RDAs)

that reside in a regional decision-making device (RDD) in the monitoring layer of a substation can negotiate

in a peer-to-peer manner without a control center. The RDA serves as the manager, coordinator, and

message transponder for the LDAs. The design of the WABP is described including its architecture,

workflow, and its agents' functions. Simulation scenarios illustrate the correctness of the WABP multi-agent

system and the higher fault-tolerance of its response to misoperations, protection failures, and

communication failures.

ETPL

GC-122 Wide-Area Traveling Wave Fault Location System Based on IEC61850

Existing traveling wave fault location systems employ the double-end method and do not make use of data

from neighboring substations. If one of the data acquisition equipments at either end of a line fails to capture

the fault transient, no fault location result can be obtained. A wide-area traveling wave fault location (WA-

TWFL) system, which makes use of traveling wave data from various substations across the monitored

network, is introduced. The WA-TWFL algorithm first identifies the area of the monitored network in which

the source of the disturbance originated by analyzing the traveling wave propagation times using the

extended double end method. Then, the faulty line, and the distance to fault, are determined using selected

records from the identified area of the disturbance. This approach provides fault location reliability than the

traditional TWFL algorithm. Traveling wave data models based on IEC61850, which supports open

communication and interoperability between data acquisition equipment and the master station of the WA-

TWFL, are also presented in this paper. The feasibility of the proposed algorithm is proved using traveling

wave data from an actual fault on a power grid in China.

ETPL

GC-123

Using a Distributed Agent-Based Communication Enabled Special Protection System

to Enhance Smart Grid Security

Abstract: Future smart grid capabilities promise to leverage network technologies to revolutionize the

production, transmission, distribution, and consumption of electrical power. This smart grid revolution is

more than just smart meters. Improvements in situational awareness are also likely to enhance security and

reliability in power transmission systems. However, reliance on Internet-like communication networks also

exposes vulnerabilities to increased risk from cyber-attack and other forms of Byzantine (i.e., anomalous)

behavior. This article advocates the use of an agent-based decentralized protection system using peer-to-peer

communications, reputation-based trust and a data retransmission scheme to combat malicious attacks and

other Byzantine failures. The research presented used the electric power and communication synchronizing

simulator (EPOCHS) federated simulation platform to demonstrate the added robustness provided to a

special protection system in the face of an adversary by successfully defending against malicious attacks.




Education

Final Year IEEE Project 2013-2014 - Grid Computing Project Title and Abstract