AMPS: Mathematical Foundations of Market Operations with Renewable Bidders

AMPS：可再生能源投标人市场运作的数学基础

• 批准号: 2229335
• 负责人: John Mitchell
• 金额: $ 30万
• 依托单位: Rensselaer Polytechnic Institute
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-15 至 2026-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2229335&HistoricalAwards=false
• 关键词: AMPS; Mathematical; Foundations; Market; Operations

This NSF AMPS project will develop mathematical foundations behind markets where renewable generators are allowed to bid their risk-adjusted cost curves into the market. While investments into renewable energy assets have been growing in recent years, renewable generators today typically act as "price takers" and are paid at market clearing prices that are determined from the cost curves submitted by the conventional generators. This market structure implies that even as renewable energy penetration increases over the next several decades, the market prices are going to be determined by a few conventional generators which can provide nearly risk-free energy commitments. To address this issue, in this project the research team will analyze the efficiency of a market where renewable energy suppliers can participate in electricity markets (just like conventional generators) by supplying cost curves associated with guaranteeing a certain amount of renewable supply. Development of risk-adjusted cost curves and their impact on the market operations will be investigated by a cross-disciplinary team of mathematical optimization and power systems researchers.Investigation of a market where renewables bid presents a paradigm shift from existing studies, and fundamental questions on market efficiency and risk-vs-cost trade-off remain to be explored in this context. This will be accomplished through three synergistic thrusts: 1) Analyzing the efficiency of markets under renewable bidders; 2) Deriving the risk-adjusted renewable supply cost curves; and 3) Analyzing the incentives for truthful bidding and convergence to equilibrium. Investigating these three research thrusts involves finding solutions to complex stochastic optimization and equilibrium problems that the research team will undertake in this project. The solutions with be evaluated in NY and TX market data using the EGRET power market simulation tool. The project will realize its broader impacts through cross-disciplinary training of graduate students, involvement of undergraduates in research, K-12 outreach, and collaboration with independent system operators and renewable generators to maximize the practical impact of the project. If successful, the project could lead to introduction of new market mechanisms that would improve the flexibility of renewable generators in managing their supply and associated storage, making renewable based power more economically viable.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这个NSF AMPS项目将开发市场背后的数学基础，允许可再生能源发电机将其风险调整后的成本曲线投入市场。虽然近年来对可再生能源资产的投资一直在增长，但今天的可再生能源发电机通常充当“价格接受者”，并按照根据传统发电机提交的成本曲线确定的市场清算价格支付。这种市场结构意味着，即使可再生能源的渗透率在未来几十年内增加，市场价格也将由几个可以提供几乎无风险能源承诺的传统发电机决定。为了解决这个问题，在本项目中，研究小组将分析可再生能源供应商可以通过提供与保证一定量的可再生能源供应相关的成本曲线来参与电力市场（就像传统发电机一样）的市场效率。由数学优化和电力系统研究人员组成的跨学科团队将研究风险调整成本曲线的发展及其对市场运营的影响。可再生能源竞标市场的调查是现有研究的范式转变，市场效率和风险与成本权衡的基本问题仍有待探索。这将通过三个协同推进来实现：1）分析可再生能源投标人下的市场效率; 2）推导出风险调整后的可再生能源供应成本曲线; 3）分析真实投标和收敛到均衡的激励。调查这三个研究重点涉及到寻找复杂的随机优化和平衡问题的解决方案，研究团队将在这个项目中进行。使用EGRET电力市场模拟工具，在纽约和德克萨斯州的市场数据中对解决方案进行评估。该项目将通过研究生的跨学科培训，本科生参与研究，K-12推广以及与独立系统运营商和可再生发电机合作来实现其更广泛的影响，以最大限度地发挥项目的实际影响。 如果成功的话，该项目可能会引入新的市场机制，提高可再生能源发电机在管理其供应和相关存储方面的灵活性，使可再生能源发电更具经济可行性。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。