Economic Reliability of Deregulated Power Markets: A Machine Learning Model for Design and Assessment

放松管制的电力市场的经济可靠性：用于设计和评估的机器学习模型

• 批准号: 0400268
• 负责人: Tapas Das
• 金额: $ 21万
• 依托单位: University of South Florida
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-05-01 至 2008-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0400268&HistoricalAwards=false
• 关键词: Economic; Reliability; Deregulated; Power; Markets

One of the main reasons behind power market design flaws is the lack of comprehensive quantitative models that take into account important market features. This deficiency coupled with an absence of computationally viable methods for solving stochastic games (e.g., obtaining Nash Equilibrium) that can be used to model market behavior has resulted in lower economic reliability for power markets. The objectives of this research are: 1) to develop a stochastic game theoretic modeling framework consisting of features like energy bidding and price settlement policies, FTR auction, demand elasticity and other evolving market rules, 2) to formulate a reinforcement learning (RL) based solution methodology and develop its convergence analysis, 3) to conduct testing and benchmarking with power market industry data, and 4) to develop plans to train students and also offer continuing education for power market professionals. The proposed model and its solution methodology would allow us to identify the equilibrium state of a market, which is characterized by steady state bidding strategies of the market participants and the resulting energy prices. Thus the economic reliability of alternative market designs can be assessed before implementation. The RL based solution methodology can also be extended to problems in other sectors of economy. The broader impacts would include 1) enhanced economic reliability of power markets through dissemination of knowledge gained from the research, 2) increased competition due to better market design resulting in process innovation and price reduction, and 3) development of a diverse group of professionals capable of designing and analyze deregulated power markets.

电力市场设计缺陷背后的主要原因之一是缺乏考虑重要市场特征的全面定量模型。这种缺陷加上无法用于解决随机游戏的计算可行方法（例如，获得可用于模拟市场行为的NASH平衡）的方法，导致对电力市场的经济可靠性降低。这项研究的目标是：1）制定一个随机游戏理论建模框架，包括能源竞标和价格和解政策，FTR拍卖，需求弹性和其他不断发展的市场规则，2）制定基于强化的市场规则（RL）的解决方案方法，以提供基于解决方案的方法，并开发其融合和培训的融合和培训数据，并培训学生的动力，并在4）进行培训，并在4）进行培训，并在4）进行了培训，并培训了Power Markets，4）4）市场专业人士。拟议的模型及其解决方案方法将使我们能够确定市场的均衡状态，该市场的特征是市场参与者的稳态招标策略和由此产生的能源价格。因此，可以在实施之前评估替代市场设计的经济可靠性。基于RL的解决方案方法也可以扩展到其他经济领域的问题。更广泛的影响包括1）通过传播从研究中获得的知识来提高电力市场的经济可靠性，2）由于更好的市场设计而增加竞争，从而导致过程创新和价格降低，以及3）开发能够设计和分析导管电力市场的各种专业人士的发展。