CLOUD-BASED SOFTWARE PLATFORM FOR BIG DATA ANALYTICS IN SMART GRIDS

University of Southern California, Los Angeles, USA

ABSTRACT

Smart Grid

information integration pipeline secure repositoryscalable machine-learning models

demand forecasting portal

KEYWORDS:

1. THE SMART GRID CYBER-PHYSICAL SYSTEM

reliableefficient

Renewables

Phasor Measurement Units Smart meters

Building and Home Area Networks

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This article has been accepted for publication in Computing in Science and Engineering but has not yet been fully edited.Some content may change prior to final publication.

Cyber-Physical System (CPS) physicalcomputational

. In the absence of computational and analytics support for automated decisions, the human grid operators are ill equipped to examine and utilize millions of data and control points for managing the dynamism in energy usage patterns.

smart

“Big Data” challenge

multi-disciplinary

Cloud-based software platformLos

Angeles Smart Grid Projectdynamic demand-

response optimization (D2R) challenge application

semantic information integration pipeline secure repository

Generation

TransmissionDistribution

MicrogridsResidentialUtility Commercial

Control Center

Rooms

Buildings

HVAC & Lighting

Solar Co-generation

Electric Vehicles

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This article has been accepted for publication in Computing in Science and Engineering but has not yet been fully edited.Some content may change prior to final publication.

scalable machine-learning models web portal and mobile app

Cloud technologies

2. D2R IN THE USC CAMPUS MICROGRID Los Angeles Smart Grid Project

intermittent sources

Demand response optimization (DR)

dynamic demand response optimization (D2R)

intelligent decision making when, by how much, whom to target

USC campus microgrid

instrumented

direct controls

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living laboratory

real-world environment

3. D2R SOFTWARE PLATFORM ON CLOUDS demand forecasting

strategy selection

hybrid Cloud and cluster infrastructure

Floeprivate Cloud infrastructure on-demand

resource elasticity

observe, orient, decide & act (OODA)

Customers, Facilities

Forecast Demand

Ingest Data

Store & Share Data

Visuali-zation

Decide D2R

Strategy

Generation Capacity Data

Equipment, Sensors

Environment, Events

Engineers

Analysts

Researchers

Customers

Monitor

Curtailment Notification – Voluntary and Direct Load Control

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public Cloud storage platforms manageable reliableco-location

Cryptonite

Data-driven forecasting models

OpenPlanetMapReduce platform scale private Cloud infrastructure

learn actSmart Grid

portal Android mobile app

4. DYNAMIC INFORMATION INTEGRATION PIPELINE

in silico

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application dynamism

Floe

pellets

coordinatorresource manager

scale-out scale-inscale-up

scale-down

ForkJoinPool

automatic

data transport data parsingsemantic annotation data storage

Floe

Sensor Transport

Event Parser

File Transport

Web Transport

DocumentParser

Semantic Annotate

Data Store Insert

Data Store Update

Cloud Infrastructure Provider

Allocate

Launch

Acquire/Release

Initiate

Compose

IniFloe Framework

Semantic Info Integration Pipeline

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sensor transport pellet document parsing pelletsemantic annotation pellet

SPARQL3 insert pellet

D55Watts sensor KAP building Civil Engineering department

5. SCALABLE DEMAND FORECASTING

www.w3.org/RDF www.w3.org/TR/rdf-sparql-query

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Regression Tree

Outside TemperatureBuilding Net Area Day of the Week

0

2

4

6

8

10

Ener

gy C

onsu

mpt

ion

(KW

h)

Day & Time Intervals (Hours)

ObservedARIMA (–6 hours)Reg. Tree (–48 hours)

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OpenPlanet

FutureGrid

6. DISCUSSION & CONCLUSIONS

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IEEE International Scalable Computing Challenge (SCALE) award for 2012

ACKNOWLEDGMENTS

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This article has been accepted for publication in Computing in Science and Engineering but has not yet been fully edited.Some content may change prior to final publication.

REFERENCES U.S. Energy Information Administration (EIA) IEEE Industrial Electronics

Magazine

Communications of the ACM

ACEEE Summer Study on Energy Efficiency in Buildings

Los Angeles Department of Water and Power

International Conference on Information Technology : New Generations

IEEE International Cloud Computing Conference

International Workshop on MapReduce and its Applications (MAPREDUCE)

Future Generation Computer Systems

The Fourth Paradigm: Data-Intensive Scientific Discovery,

International Workshop on Domain Driven Data Mining

BIOGRAPHIES

Yogesh Simmhan

Saima Aman

Alok Kumbhare

Digital Object Indentifier 10.1109/MCSE.2013.39 1070-9924/$26.00 2013 IEEE

This article has been accepted for publication in Computing in Science and Engineering but has not yet been fully edited.Some content may change prior to final publication.

Rongyang Liu

Sam Stevens

Qunzhi Zhou

Viktor Prasanna

Digital Object Indentifier 10.1109/MCSE.2013.39 1070-9924/$26.00 2013 IEEE

This article has been accepted for publication in Computing in Science and Engineering but has not yet been fully edited.Some content may change prior to final publication.