Decentralized Demand Response in Electricity Markets

Presenter: Andrew (Lu) Liu, Ph.D., associate professor, Purdue University

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), naïve 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.

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