What objective function should be used for optimal auctions in the ISO/RTO electricity market?

G. Stern, Joseph H. Yan, P. Luh, W.E. Blankson
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引用次数: 28

Abstract

In this paper, we provide mathematical formulations for the offer cost and MCP payment cost minimizations for optimal auctions in the ISO/RTO electricity market, and summarize the newly developed solution methodology using augmented Lagrangian relaxation and surrogate optimization for solving the optimal auction with the MCP payment objective function. Data has been used to test the method based on a simplified energy market, and for a given set of offers, the testing result demonstrates significant potential savings for electricity consumers if the MCP payment cost minimization is implemented in the ISO/RTO electricity markets. More importantly, this paper addresses economic implications of the objective function choice, including whether maximizing social welfare should be one of objectives of electricity industry deregulation. We conclude that an objective to maximize social welfare, even if it were determined to be desirable, is not achievable based on current bidding rules after moving from traditional vertically integrated utilities to a market approach, and is certainly not achieved by the offer cost minimization approach in use today. Other implications such as the inconsistency between the actual payment and the cost function minimized, and bidding behaviors are also discussed
ISO/RTO电力市场的最优拍卖应使用什么目标函数?
本文给出了ISO/RTO电力市场中最优竞价的报价成本和MCP支付成本最小化的数学公式,并总结了利用增广拉格朗日松弛法和代理优化法求解具有MCP支付目标函数的最优竞价问题的新方法。数据已用于基于简化能源市场的方法测试,对于给定的一组报价,测试结果表明,如果在ISO/RTO电力市场中实施MCP支付成本最小化,则电力消费者可能会节省大量潜在费用。更重要的是,本文讨论了目标函数选择的经济含义,包括社会福利最大化是否应该成为电力行业放松管制的目标之一。我们得出的结论是,在从传统的垂直整合公用事业转向市场方法后,基于当前的招标规则,社会福利最大化的目标即使被确定为可取的,也是无法实现的,而且今天使用的报价成本最小化方法当然也无法实现。本文还讨论了实际支付与成本函数最小化之间的不一致以及投标行为等问题
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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