Friday, March 18, 2022 - 11:00am to 12:00pm
Event Calendar Category
Other LIDS Events
Speaker Name
Yury Dvorkin
Affiliation
New York University
Zoom meeting id
974 6030 4229
Join Zoom meeting
https://mit.zoom.us/j/97460304229
Abstract
Integration of volatile and uncertain renewable energy resources and synergistic energy storage and demand response technologies motivates the pursuit of stochastic electricity market designs to accommodate these resources and technologies efficiently and reliably. However, until recently the primary means of achieving these goals rested on the use of traditional optimization techniques and, in particular, on stochastic optimization and its proxies. However, recent developments make it possible to “re-invent” stochastic electricity markets borrowing results from data science, machine learning and financial engineering. This presentation will first describe how stressing of load and renewable time series can be achieved using principal component analysis and generative adversarial networks, and then how these stressed time series could be integrated into a stochastic electricity market design. Building on this result, we will describe a machine learning approach to stochastic-market clearing that affords both market- and operation-feasible solutions and reduces computational requirements.
Biography
Yury Dvorkin (he/him/his) is an Assistant Professor and Goddard Junior Faculty Fellow in the Department of Electrical and Computer Engineering at New York University’s Tandon School of Engineering with an affiliated appointment at NYU’s Center for Urban Science and Progress. Before joining NYU, he was a Ph.D. student (class of 2016) at the University of Washington, under the supervision of Prof. Daniel S. Kirschen, and a graduate student researcher (2014) at the Center for Nonlinear Studies, Los Alamos National Laboratory. For his dissertation work, entitled “Operations and Planning in Sustainable Power Systems“, Yury was awarded the inaugural 2016 Scientific Achievement Award by Clean Energy Institute (University of Washington). In 2019, Yury received the NSF CAREER Award to investigate small-scale electricity trading. Later this year, Yury received the Goddard Junior Faculty Fellowship. Also, Yury is a dedicated reviewer, who was awarded with the Best Reviewer Award from IEEE Transactions on Power Systems (2014, 2015, 2016, 2017, 2018), IEEE Transactions on Sustainable Energy (2014, 2015, 2016), and IEEE Transactions on Smart Grids (2016). Since 2019, Yury has been an Associate Editor of the IEEE Transactions on Smart Grid. Yury’s research focuses on developing modeling and algorithmic solutions to assist society in accommodating emerging smart grid technologies (e.g., intermittent generation, demand response, storage, smart appliances, cyber infrastructure) using multi-disciplinary methods in engineering, operations research, economics, and policy analysis. His current research is funded by the National Science Foundation, US Department of Energy, US Department of Transportation, Advanced Research Projects-Energy, Electric Power Research Institute, New York State Energy Research and Development Authority, and Alfred P. Sloan Foundation.