1 citations · 1 across the 3 of their papers we have counts for
3 papers
eess.SY2024
Learning with Adaptive Conservativeness for Distributionally Robust Optimization: Incentive Design for Voltage Regulation
Zhirui Liang, Qi Li, Joshua Comden +2
Information asymmetry between the Distribution System Operator (DSO) and Distributed Energy Resource Aggregators (DERAs) obstructs designing effective incentives for voltage regula…
cs.LG2023★ 1 cited
A Physics-Informed Machine Learning for Electricity Markets: A NYISO Case Study
Robert Ferrando, Laurent Pagnier, Robert Mieth +4
This paper addresses the challenge of efficiently solving the optimal power flow problem in real-time electricity markets. The proposed solution, named Physics-Informed Market-Awar…
math.OC2023
Data-Driven Inverse Optimization for Marginal Offer Price Recovery in Electricity Markets
Zhirui Liang, Yury Dvorkin
This paper presents a data-driven inverse optimization (IO) approach to recover the marginal offer prices of generators in a wholesale energy market. By leveraging underlying marke…