EPNES: Foreward Contracts, Multisettlement Equilibrium and Risk Management in Competitive Electricity Markets

远期合同和金融风险管理工具是竞争性电力市场的基本要素。它们通过市场机制缓解市场力量，抑制价格波动，并确保系统可靠性。在电力背景下设计和研究这种机制需要一种跨学科的方法，利用经济学、运筹学和金融工程的发展，同时调整和扩展这些领域的现有知识，以适应电力系统的实际情况。该研究项目将通过汇集一支在电力经济、优化和金融数学方面具有专业知识的研究团队来开发这样一种跨学科的方法。该项目包括三个主要技术部分：通过直流电网的序贯纳什均衡模型分析两个结算电力市场；发展计算方法，将现实的两个结算均衡模型作为具有均衡约束的同时优化问题来计算；以及发展随机价格变动下特定远期合约和期权的定价方法。这项研究将有助于解决电力行业重组带来的技术和政策问题，并将培训参与研究的研究生，以应对该行业面临的多学科挑战。在该项目下开发的计算技术将在加州市场的现实商业模型上进行测试。这个项目产生的新知识将通过教学模块整合到为工业工程和电气工程专业学生提供的广泛的研究生和本科课程中。

Forward contracts arid financial risk management instruments are essential elements of competitive electricity markets. They mitigate market power, suppress price volatility and ensure system reliability through market mechanisms. The design and study of such mechanisms in the context of electricity requires an interdisciplinary approach that capitalizes on developments in economics, operations research, and financial engineering while adapting and extending the existing knowledge in these areas to match the physical realities of electricity systems. This research project will develop such an interdisciplinary approach by bringing together a research team with expertise in power economics, optimization and financial mathematics. The project consist of three main technical components: Analysis of two settlement electricity markets through sequential Nash equilibrium models on DC power networks; Development of computational methods for calculating realistic two settlement equilibrium models as simultaneous optimization problems subject to equilibrium constraints; and Development of pricing methodologies for specific forward contracts and options under stochastic price movements. This research will help address technical and policy issues prompted by the restructuring of the electricity industry and will train graduate students participating in the research to cope with the multidisciplinary challenges facing that industry. The computational techniques developed under this project will be tested on realistic commercial models of the California market. New knowledge resulting from this project will be integrated through teaching modules into a broad spectrum of graduate and undergraduate courses offered to industrial engineering and to electrical engineering students.