Joint Chance-constrained Game for Coordinating Microgrids in Energy and Reserve Markets: A Bayesian Optimization Approach

Tuesday, May 23, 2023 - 4:00pm to 4:30pm

Event Calendar Category

LIDS & Stats Tea

Speaker Name

Yifu Ding

Affiliation

MITEI

Building and Room Number

LIDS Lounge

Abstract

Networked microgrids aggregate distributed energy resources and flexible loads to reach the minimum capacity for market participation and provide reserve services for the grid. However, due to uncertain renewable generations such as solar power, microgrids might under-deliver reserve services and breach the day-ahead contracts in the real-time market. If multiple microgrids fail to deliver services, this might cause a grid contingency. This talk presents a DRJCC market game simulating risk-aware bidding and system-wide reserve policy. Leveraging historical error samples, the reserve bidding strategy of each microgrid is formulated into a two-stage Wasserstein-metrics DRO model. A JCC regulates the under-delivered reserve capacities of all microgrids in a non-cooperative game. Considering the unknown correlation among players, a novel Bayesian optimization method approximates the optimal individual violation rates of microgrids and market equilibrium. The proposed game with the optimal rates is simulated with various numbers of players using California power market data. The proposed Bayesian method can effectively regulate the joint contract violation rate of the under-delivered reserve and secure the profit of microgrids in the reserve market.

Biography

Yifu joined the MIT Energy Initiative as a post-doctoral research associate in Jan 2023. She received her Ph.D. in Engineering Science from the University of Oxford. Her research focuses on probabilistic forecasts and advanced uncertainty-aware optimization in power system operations, particularly for extreme grid conditions such as disastrous blackouts or unscheduled load shedding. During her Ph.D., she visited Johns Hopkins University and the Alan Turing Institute in London, where she applied machine learning and game theory to research.