AMPS: Mathematical Foundations of Market Operations with Renewable Bidders

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组将其风险调整后的成本曲线投标进入市场。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企业通常扮演着“价格接受者”的角色，并按照由传统发电企业提交的成本曲线决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有所提高，市场价格仍将由少数能够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，在这个项目中，研究小组将通过提供与保证一定数量的可再生能源供应相关的成本曲线，分析可再生能源供应商可以参与电力市场（就像传统发电机一样）的市场效率。一个由数学优化和电力系统研究人员组成的跨学科小组将研究风险调整成本曲线的发展及其对市场运作的影响。对可再生能源竞标市场的调查呈现出与现有研究的范式转变，在这种背景下，关于市场效率和风险与成本权衡的基本问题仍有待探讨。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)推导经风险调整后的可再生能源供应成本曲线；3)分析真实竞价和趋同均衡的激励机制。研究这三个研究重点包括寻找复杂随机优化和平衡问题的解决方案，研究小组将在这个项目中承担这些问题。利用EGRET电力市场仿真工具对纽约和得克萨斯州的市场数据进行了评估。该项目将通过对研究生的跨学科培训、本科生参与研究、K-12外展以及与独立系统运营商和可再生能源发电机的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，该项目可能导致引入新的市场机制，从而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，使基于可再生能源的电力在经济上更加可行。该奖项反映了美国国家科学基金会的法定使命，并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，被认为值得支持。

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.