Application of Machine Learning to Power Grid Analysis Mike Zhou (State Grid EPRI, China) JianFeng Yan, DongYu Shi (China EPRI, China) Donghao Feng (KeDong Electric Power Control Sys Com., China) 1 IEEE PES Technical Webinar Sponsored by IEEE PES Big Data Subcommittee Contact Info : [email protected]
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ApplicationofMachineLearningtoPowerGrid Analysis
MikeZhou(StateGridEPRI,China)JianFeng Yan,DongYu Shi (ChinaEPRI,China)
• Introduction• Open Platform for Applying Machine Learning (ML)• Power Grid Model Service• Research on Applying ML to Online DSA• ML Research Roadmap of CEPRI
• Introduction• Open Platform for Applying Machine Learning• Power Grid Model Service• Research on Applying ML to Online DSA• ML Research Roadmap of CEPRI
• Load bus P,Q adjusted by a random factor [0~200%], load Q is further adjusted by random factor [+/-20%]
• The load changes are randomly distributed to the generator buses
Gen Area
Load Area
Training Case
IEEE-14 Bus case as the basecase. Power is flowing from the Gen Area to the Load Area. When the operation condition changes, predict• Bus voltage, P, Q• Interface flow• N-1 CA max branch power flow
Average 0.00028pu 0.00055rad 0.00225pu 0.00171pudV(msg,ang): Bus voltage predicted is compared with the accurate AC Power Flow results dP/Qmax: Bus voltage predicted is used to compute the network max bus power mismatch
[2] “The InterPSS Community Site”, www.interpss.org
Agenda14
• Introduction• Open Platform for Applying Machine Learning• Power Grid Model Service• Research on Applying ML to Online DSA• ML Research Roadmap of CEPRI
[3] M. Zhou, “Solving Power System Analysis Problems Using Modern Software Approach,“ US Gov FERC Increasing Market and Planning Efficiency through Improved Software Meeting, DC June 2010.
[3]
InterPSSSoftwareArchitecture17
Application Suite
Traditional ApproachLittle could be extended
and customized
InterPSS Core Engine
InterPSS ApproachApplication created by
extension, integration and customization
Extensions
Desktop Edition
Cloud Edition
Integration with other systems
ü
[4] M. Zhou, Q.H. Huang, “InterPSS: A New Generation Power System Simulation Engine," submitted to PSCC 2018
[4]
PowerNetworkObjectModel18
[5] E. Zhou, "Object-oriented Programming C++ and Power System Simulation," IEEE Trans. on Power Systems, Vol. 11, No. 1 Feb. 1996.
• Introduction• Open Platform for Applying Machine Learning• Power Grid Model Service• Research on Applying ML to Online DSA• ML Research Roadmap of CEPRI F
• Introduction• Open Platform for Applying Machine Learning• Power Grid Model Service• Research on Applying ML to Online DSA• ML Research Roadmap of CEPRI F