Loading Events
  • This event has passed.

Special EECS Seminar, Mar 14

The California state legislature has set aggressive Green House Gas emissions reduction goals of 60% by 2030 and 80% by 2050. Achieving these goals requires combining strategies that significantly rethink how we plan and operate our power networks. In this talk I address how to rethink the dispatch of conventional generation, how to design and operate demand shaping strategies and the challenges to manage autonomous distribution system clusters in the presence of significant penetration of renewable generation. I present Risk Limiting Dispatch that significantly reduces integration cost of wind power compared to current operation procedures, without requiring ample redesign of markets. I then discuss demand shaping program targeting opportunities based on smart meter and appliance load data. I conclude the talk introducing two measurement and automation platforms for distribution side cluster management based on integrated power sensing.

Ram Rajagopal is an Assistant Professor of Civil and Environmental Engineering at Stanford University. He also directs the Stanford Sustainable Systems Laboratory. Prior to this, he was a DSP research engineer at National Instruments and a visiting researcher at IBM Research, where he worked on embedded control systems, machine learning and image processing. His current research interests include developing large scale sensing and market platforms, statistical models and stochastic control algorithms for integrating renewable energy into the grid, implementing new demand side management programs and coordinating ancillary services for power distribution networks. He holds a Ph.D. in Electrical Engineering and Computer Science and an M.A. in Statistics, both from the University of California Berkeley, and a Bachelor’s in Electrical Engineering from the Federal University of Rio de Janeiro. He is a recipient of the Powell Foundation Fellowship. He is the co-founder of Verivolt, LLC, a startup focused on creating cost effective and scalable sensing solutions for the smart grid. His work has resulted in various publications, 20 patents and several commercially adopted solutions.