2 citations · 3 across the 5 of their papers we have counts for
5 papers
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…
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…
Weather-Driven Flexibility Reserve Procurement: A NYISO Offshore Wind Power Case Study
Zhirui Liang, Robert Mieth, Yury Dvorkin +1
The growing penetration of variable renewable energy sources (VRES) requires additional flexibility reserve to ensure reliable power system operations. Current industry practice ty…
Operation-Adversarial Scenario Generation
Zhirui Liang, Robert Mieth, Yury Dvorkin
This paper proposes a modified conditional generative adversarial network (cGAN) model to generate net load scenarios for power systems that are statistically credible, conditioned…
Inertia Pricing in Stochastic Electricity Markets
Zhirui Liang, Robert Mieth, Yury Dvorkin
Maintaining the stability of renewable-dominant power systems requires the procurement of virtual inertia services from non-synchronous resources (e.g., batteries, wind turbines) i…