Submitted by : Jatin Pherwani (B. Des, final year) Guide : Prof. Pradeep Yammiyavar (Head, CET IIT Guwahati)

Title : Dashboard design for management of smart electricity grids.

Acknowledgements

I express my sincere gratitude to the following people and authorities for their cooperation in my project’s field study and expert consultation.

• Assistant professor (Dr.) Praveen Kumar (Dept. of Electrical Engineering IIT Guwahati).

• The Assam State Electricity Board ASEB substation (IIT Gate).

• Engineers at State Load Dispatch Centre (SLDC), Assam. • Mr. H.C. Phukan, Chief General Manager(SLDC) Mr. Jatinder Baishya, Assistant General Manager(LDC)

Aim

The aim of this project is to allow efficient management of smart electricity grids in rural as well as urban areas primarily by catering the needs of engineers and technicians involved in monitoring and controlling the grid parameters for a huge and self sustaining electricity network.

Objectives

• To study the smart electricity grid phenomena holistically. • Perform a thorough need analysis at the management end

of the grid network.

• Visualize the data generated from the use of smart grid (by making comprehensible dynamic info graphs).

• Design a wholesome dashboard which can facilitate easy and quick decision making.

• Test the proposed concept with the users in their work environment.

• Explore new visualization mediums to depict the same information.

Methodology

The methodology that the project followed can broadly be grouped into three phases. The first being a basic background study and analysing expert inputs on the subject matter of smart electricity grids. The second phase is about following a user centred approach to design a solution that enables easy and quick decision making at the management end of the network. The third phase will comprise of various explorations in data visualization to set a different grammar in the visual domain of information representation.

1. Background Study and Secondary research 1.1 Literature Review 1.2 Subject Matter Expert (SME) interviews 2. User requirement analysis 2.1 Workstation observations 2.2 Contextual Interviews 2.3 Task analysis and Card sorting 2.4 User personas 2.5 Use case scenarios 3. Design 3.1 Data gathering / analysis 3.2 Ideate visualizations 3.3 Prototype concepts 3.4 Wireframe dashboard structure.

The literature review consists majorly of two parts, the first to acquaint myself with the important concepts of a smart electricity grid system and the second about various techniques used to visualize the grid parameters. What is a smart grid ? Smart grid is a modernized electrical grid that uses information and communications technology to gather and act on information, such as information about the behaviours of suppliers and consumers, in an automated fashion to improve the efficiency, reliability, economics, and sustainability of the production and distribution of electricity.[1] The term smart grid has been in use since at least 2003, when it appeared in the article "Reliability demands will drive automation investments" by Michael T. Burr[2]. A common element to most definitions is the application of digital processing and communications to the power grid, making data flow and information management central to the smart grid. Features of smart grid : 1.Reliability 2.Flexibility in network topology 3.Efficiency 4.Load adjustment 5.Peak curtailment/levelling and time of use pricing 6.Market-enabling 7.Demand Response

Literature Review

Visualizations of smart Grid parameters To determine how power moves through a transmission network from generators to loads, it is necessary to calculate the real and reactive power flow on each and every transmission line or transformer, along with associated bus voltages (in other words, the voltages at each node). With networks containing tens of thousands of buses and branches, such calculations yield a lot of numbers. Traditionally they were presented either in reams of tabular output showing the power flows at each bus or else as data in a static so-called one-line diagram. (One-line diagrams are so named because they represent the actual three conductors of the underlying three-phase electric system with a single equivalent line.)[3] The visualization challenge is to make these concepts intuitive. One simple yet effective technique to depict the flow of power in an electricity network is to use animated line flow. Here, the size, orientation, and speed of the arrows indicate the direction of power flow on the line, bringing the system almost literally to life. Dynamically sized pie charts are another visualization idea that has proven useful for quickly detecting overloads in a large network. On the one-line, the percentage fill in each pie chart indicates how close each transmission line is to its thermal limit. When thousands of lines must be considered, however, checking each and every value is not an option. Of course, tabular displays can be used to sort the values by loading percentage, but with a loss of geographical relevance.

Visualizations of Smart Grid parameters Because engineers and traders are mostly concerned with transmission lines near or above their limits, low-loaded lines can be eliminated by dynamically sizing the pie charts to become visible only when the loading is above a certain threshold. Contouring the grid Using pie charts to visualize these values is helpful, unless a whole host of them appear on the screen. Here, an entirely different visualization approach is useful--contouring. Contours are a familiar way of displaying continuous, spatially distributed data. The equal-temperature contours provided in a newspaper's weather forecast form a well-known example. The trouble with contouring power system data is that it is not spatially continuous. Bus voltage magnitudes exist only at buses, and power only as flows on the lines, yet the spaces between buses and lines appear in contour maps as continuous gradients, not as gaps. In practice the artificially blended spaces between nodes and lines do not matter much, as the main purpose of a contour is to show trends in data. [4] Values are exact only at the buses or on the lines. Colors can be used to represent a weighted average of nearby data-points. This color gradation brings out the spatial relationships in the data.

In the process of taking an expert’s take on the visualizations of Electricity Grids’ network and monitoring, two subject matter interviews were done. 1.Assistant professor (Dr.) Praveen Kumar at the Dept. of Electrical Engineering IIT Guwahati. The following observations were made, a few proved to be very insightful in the further design. • The basic parameters for management of any electrical

network can be done with the following 5 parameters : Voltage, Current, Frequency, Power Factor, Transformer temperature.

• In addition to these, each decentralized power generation site can be said to inject power into the smart grid along these five parameters only.

• Topological and geographical representations are of secondary importance.

• Once the pricing off power units gets to be volatile, it can be of use to show it in the dashboard.

• Power distribution policies vary with time too and once the smart devices and more renewable energy producing sites jump in, a visualization would of a lot more use.

Subject Matter Expert (SME) interviews

2. Mr. H.C. Phukan, Chief General Manager at the State Load Dispatch Center(SLDC), Kahilipara Assam. With the theoretical concepts of electricity transmission clear, visits were paid to the stat’s grid management center. The functions at the management end for a grid were thoroughly understood and reflected upon with discussions giving the following points. The major objectives of any grid management center shall comprise of the following:

• Demand Estimation for operational purpose.

• Scheduling for Merit Order Dispatch.

• Regulating Generation Load Balance.

• Schedule for Central Sector Drawl & Regulate it.

• Monitor bilateral power supply agreement.

• Maintaining system frequency in 49.0Hz to 50.5Hz.

• Restoration procedure planning and implementation.

• Load Shedding implementation.

• Coordination with RLDC and other constituents.

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Observations (Workstation)

The field visits covered observation sessions at the users actual workplace, in our case being the State Load Dispatch center, Kahilipara in Guwahati, Assam (Figure1). The center is one of the 18 present in the entire nation and is responsible for all electricity transmission, distribution and electric grid related regulations of the North-East Grid, one of the 5 major grids of the country. The office has about 25 employees with 5 main engineers, taking the important decisions at the management end of the system. On the first floor of the building takes place the monitoring and control of the electricity grids. With at least 8 CRT monitors and one huge LCD display (Figure3), the visualizations and all other grid related information are visible to the engineers and staff. Other than the conventional screens, which consisted of LCDs and CRTs, a digital display is included in the main room to show the grid’s frequency, which is a number close to 50, but of utmost importance to monitor any grid’s health (see Figure 2).

Figure 1 Figure 2

Figure 3

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Contextual Interviews

Mr. Jatinder Baishya is the Assistant General Manager at the Load Dispatch division in SLDC Assam. Other than holding a bachelors degree in electrical engineering, he has had a 3 month training for handling SCADA systems used in huge electrical networks. Most of his days at the office are busy, however he agreed to give us a couple of appointments to discuss the his role in the management of the electricity grids in the state. Mr. Baishya’s regular days involves decision making activities mostly done by looking at a SCADA system deployed to reflect the grid’s state. His job is to make sure that the objective set by the SLDC are met so that an efficient and ‘disciplined’ electricity network is established across the North East region of the country. The following three are primary objectives assigned to him : • Matching of forecasted & Actual Demand • Meticulous Planning for Day Ahead Schedule • Regulation of own generation according to frequency

profiles For all the above regulations to come to action, it must take Jatinder to follow a few protocols and take decisions at his own discretion but all mainly supported by the information he receives through visualizations of the SCADA’s man-machine interface(MMI) as they call it.

Figure 4

An evaluation of the current SCADA visualizations used by engineers was done at the SLDC Assam and otherwise as a part of desktop research. A few prominent screens appear to the picture at every stage of decision making for the Load distribution engineers. Line Diagrams : These are reduced versions of the electricity grid’s physical components like transmission lines, transformers, substations and power stations(see Figure 5). The screen visualizations are very heavy in terms of the information they depict, the segregation has been done by color and thickness of the lines, otherwise mostly textual information is presented to depict the name of places and corresponding elements. Looking at so much of coded information, taking a decision a quick glance is difficult for the engineers. The overlapping of lines and excess chart junk present in these diagrams, increase the cognitive workload of the users resulting in errors and taking more time to act on a situation. Import – Export Power Tables : The column charts depict the state of generation and supply of power to various end points(see figure 6). The information has three basic components, the power incoming the grid and the power leaving it for consumption. Also mentioned are the grid frequencies and Unscheduled Interchange (UI) rate of power at this time and frequency. Also represented are the name and KiloVoltage of the transmission lines carrying that load.

Figure 5

Figure 6

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Frequency Regulation : The grid at any point has a specific frequency at which the power is being generated and injected into it. This is the average of generating frequencies of all the power stations in the grid. Interestingly, this frequency is the most important parameter to be monitored at regular intervals by the engineers. It depicts the demand response activities and overall grid health. The frequency of power generation allotted in Indian scenario is 50.00 Hz. Any deviation from this number means some sort of deviation in the scheduled power distribution. It also affects the decision to buy electricity from other sources as the Availability Based Tariffs of electricity are a function of frequency of your grid. The grid frequency can judge the load shedding patterns of a region too. Since this number is of utter importance to the engineers, it is depicted in all the SCADA’s screen visualizations as a number value up to two or three decimal places. To keep more check, a digital display gives real time value of the grid frequency at an interval of one second (see Figure 7).

Figure 7

Data Charts and Archives : The power distribution authorities have a set of protocols, which every grid managing organization must follow. These mainly include the order of grid recovery, the archiving of all abnormal grid states and load shedding instructions. Huge amount of data is stored in big hard drives of terabyte capacities and mediated with the cloud.

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Ideation (Crude Concepts)

The visits to the SLDC office and coming across the various parameters important in grid management allowed many insights to trigger in the visualization paradigm. As the next step in project I chose to give a first attempt at the novel visualization methods that might prove to be more useful and less cumbersome for engineers. As the ‘smartness’ of the grid increases, more parameters might join in the picture to be monitored at an authority. Here in this report, the first iterations of the three chosen platforms is presented.

Figure 8

Line Diagram Abstraction : The line diagram as we had seen was a very heavy and dense info graphic to absorb. As an attempt to simplify it and add the geographical position of the stations and lines, the proposed diagram is presented. The basic approach in reducing this visualization was centered around the idea of reducing the cognitive workload on the viewers’ minds. Inspired from the London Tube’s map, the visualization uses lines only at ninety and forty –five degrees, reducing the excess computation for the brain. Overlapping has been tried to be kept at a minimum however the data cannot be challenged. A different and supposedly simpler grammar is introduced to reduce the chart junk due to the earlier used symbols. A much simpler version of transformer symbol and power stations is used. Geography is the main addition to this line diagram, which makes it comprehendible for a layman, however it is a distorted map and the places and boundaries are not accurate.

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Ideation (Crude Concepts)

Figure 9

Input and Output power : The power input-output screen has been converted for a table with just textual information, to a radial spider visualization. The 17 end points are taken as the vertices of the polygon, and radial lines outward are the transmission line carrying that load. The red area peak gives the demand in that region. Where as the blue region shows the amount of electricity allotted if the schedule was to be followed. Unlike the earlier table, this visualization additionally shows the shortage and load shedding possibilities in the region. The actual values are also depicted so there is hardly any trade off in terms of the figurative display of information.

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Ideation (Crude Concepts)

Figure 10

Frequency Regulation: A discussed before, the frequency monitoring is of prime importance to ant grid managing authority. The regional grid frequency, cumulatively makes up the grid’s total frequency. The different power stations across a region experience a change in frequency due to the load patterns of that area. The individual ‘area’ in the grid ends up having the same frequency, as it spreads to the nearest power station. Hence making the regional information of power generation frequency of interest to the engineers. The frequency of entire grid is represented over a gradation scale with it’s mid point being 50.00 Hz. Any fluctuation is evident in the map as the color of the region is altered accordingly. The mid value is chosen to be green and going off it shall produce noticeable changes in the color values. To depict drastic changes in frequency, which can be fatal for the grid (and cause blackouts) highly contrasting red color is used, this should invite immediate attention of the engineers and allow them to act accordingly. Another idea being to display callouts with regions frequencies but only higher than normal values. The entire area is again an abstracted version of the actual map.

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Discussion

The project aims at visualizing electricity grid parameters important at the management end, and making them comprehensively into a dashboard. While the semester long work mostly included field research and user requirement analysis, the generated concepts are of potential to cater the existing problems pertaining to data visualization. All the concepts are prototyped in Flash CS5 software for inclusion in the dashboard's design. More interactive visualizations shall join the existing ones as an explorations, given the scenarios of an implemented smart grid. A few interesting domains left to be explored are the visualization of price management in a smart grid and three-dimensional info graphics of the smart grid parameter. Visualization software packs a large amount of information into a single computer-generated image, enabling viewers to interpret the data more rapidly and more accurately than ever before. This kind of software will become still more useful, even indispensable, as electricity grids are integrated over ever-larger areas, as transmission and generation become competitive markets, and as transactions grow in number and complexity. Thus, In the new world of competition, power traders, grid managers, public service boards, and the public itself all need to take in what’s happening at a glance.

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References

[1] U.S. Department of Energy. "Smart Grid / Department of Energy". Retrieved August 20, 2013. [2]Jump up "Smart Grids European Technology Platform | www.smartgrids.eu". smartgrids.eu. 2011 [last update]≤. Retrieved August 11, 2013. [3] Visualizing the Electric Grid BY THOMAS J . OVERBYE University of Illinois at Urbana-Champaign & JAMES D. WEBER PowerWorld Corp. Smart Grid Analytics Aaron DeYonker VP of Products @ eMeter, a Siemens Business LiveData SmartGrid Manager report

Exploring the imperative of revitalizing America’s electric infrastructure. (prepared for the U.S. Department of Energy by Litos Strategic Communication under contract No. DE-AC26-04NT41817, Subtask 560.01.04)

Visualizing Energy Resources Dynamically on Earth Arjun Shankar1, PhD John Stovall2, Steve Fernandez1, Rangan Sukumar1, Alex Sorokine1, and Femi Omitaomu1 1Computational Sciences; 2Energy Sciences Oak Ridge National Laboratory