Forecasting, Optimization and Control of Distributed Flexible Resources

Presented by: Yan Pan, Senior Electric Power Engineer, GE Global Research Center and Reza Ghaemi, Senior Control Systems Engineer, General Electric Research Center

Thursday, October 19, 2017 | 1:00pm – 2:00pm ET

 

The availability of flexible resources is becoming increasingly important with increasing renewable generation. As part of the ARPA-E NODES project, a group of researchers are working on aggregating distributed flexible loads and DERs to provide grid services while maintaining customer quality-of-service. The presentation will cover the development of flexibility forecasts that use weather forecasts and other data to estimate the reserve potential of aggregate loads and DERs. An optimization framework that enables aggregation of a large numbers of flexible loads and DERs and determines the optimal day-ahead schedule for these resources will be discussed. Finally, a scalable control architecture for coordinating and controlling the resources in real-time with low latency will be presented.

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Yan Pan

Yan Pan is currently working with GE Global Research Center (GRC) as a Senior Electric Power Engineer. She received the B.S.E.E. and M.S.E.E. degree in Power Systems from Wuhan University, Wuhan, China in 2000 and 2003, respectively, and the Ph.D. degree in Electrical Engineering from the Center of Advanced Power Systems, Florida State University, Tallahassee, FL, in 2009. She worked with Beijing Sifang Automation Co., Ltd as a Protection Engineer in 2003-2005. In 2009, she joined GE GRC, leading and working on R&D projects in the areas of DMS/DERMS functions, Power System Protection, PMU applications, dynamic/static load modeling and so on. She is a senior member with IEEE PES.

 

Reza Ghaemi

Reza Ghaemi is a senior control systems engineer at General Electric Research Center (GRC). Prior to joining GRC, he was a post-doctoral researcher at Massachusetts Institute of Technology between 2010 and 2012. He was also a visiting scholar at the Automatic Control Laboratory at ETH Zurich in 2008. He received M.Sc. in Mathematics (stochastic and optimization) in 2009 and Ph.D. in Electrical Engineering, Systems in 2010 from the University of Michigan, Ann Arbor.

His research interests include optimal control, Model Predictive Control, system biology, supervisory control, aircraft flight path optimization, and decentralized power grid control.

 

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After the Webinar is Presented:

  • One (1) hour of Professional Development (PDH) will be available on the IEEE Smart Grid Resource Center for purchase within three (3) business days
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For any questions regarding this process, please contact Phyllis Caputo at p.caputo@ieee.org.




 

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