Pricing Under Uncertainty in Multi-Interval Real-Time Markets

• 成果类型: Article
• 署名作者: Cho, Jehum; Papavasiliou, Anthony
• 刊物名称: OPERATIONS RESEARCH
• ISSN/ISSBN: 0030-364X
• DOI: 10.1287/opre.2022.2314
• 发表日期: 2023
• 关键词: stochastic-approximation; formulation

摘要

Recent research has demonstrated that real-time auctions can generate the need for side payments, even if the market clearing models are convex, because of the rolling nature of real-time market clearing. This observation has inspired proposals for modifying the real-time market-clearing model in order to account for binding past decisions. We extend this analysis in order to account for uncertainty by proposing a real-time market clearing model with look-ahead and an endogenous representation of uncertainty. We define two different types of expected lost opportunity cost as performance metrics. Our market-clearing model provides the price signal minimizing one of these metrics using the Stochastic Gradient Descent algorithm. We present results from a case study of the ISO New England system under a scenario of significant renewable energy penetration while accounting for ramp rates, storage, and transmission constraints.