[Iefac.list] IISE Energy Systems Division Fall Webinar - Decentralized Demand Response in Electricity Markets

[Fan, Lei]

Dear All:

The IISE energy systems division would like to invite you to attend our Fall webinar on OCT/24, 2 p.m. eastern time.  If interested, please register by https://www.iise.org/details.aspx?id=49549.

Title: Decentralized Demand Response in Electricity Markets

Presenter: Dr. Andrew Liu, Associate Professor Purdue University


Abstract. There has been a rapid growth of distributed energy resources (DERs) at the distribution level of power systems, which, if managed properly, can help improve the entire power grid's efficiency and reliability, offset electricity price volatility, and promote renewable energy. However, due to the large number of DERs and the fact that they are owned by autonomous consumers, direct control by centralized authorities, such as system operators (e.g. ISOs) or utilities, is impossible. While real-time electricity pricing (RTP) is an approach to entice the distributed resources to act properly, since all DERs would receive the same price signals (such as day-ahead (DA) wholesale prices), naive response would cause significant price volatility and system instability in real time. To avoid such a "herding" effect, we propose a multiarmed bandit (MAB) game framework in which each consumer plays an MAB problem to minimize the cumulative regret, as opposed to naively responding to day-ahead prices. Numerical results show very fast convergence to a steady-state of the MAB game with much reduced-price volatility and lower transmission congestion costs than the naïve-response case.





Bio. Andrew (Lu) Liu, is an associate professor with the School of Industrial Engineering at Purdue University, where he joined in 2009. He received his Ph.D. in Applied Mathematics and Statistics from The Johns Hopkins University in 2009 and a B.S. in Applied Mathematics from Beijing Institute of Technology. Dr. Liu's main research lies in the interactions of optimization and game theory, with applications to model and analyze energy markets, environmental policies, and smart grid. He has received two best publication awards from the Institute for Operations Research and Management Science (INFORMS) and is the Purdue Discovery Park Research Fellow in 2014 - 2015. His work has been funded by multiple agencies, including NSF, DOE, U.S. Air Force, and California Energy Commission. Before joining Purdue, Dr. Liu worked at the management consulting company, ICF International, in Fairfax Virginia, responsible for developing large-scale optimization models for energy market and environmental policy analysis.



Lei Fan
Assistant Professor
Technology Building 2, Engineering Technology Department,
College of Technology,University of Houston

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