In the electricity market, it is quite common that the market participants make "selfish" strategies to harvest the maximum profits for themselves, which may cause the social benefit loss and impair the sustainability of the society in the long term. Regarding this issue, in this work, we will discuss how the social profit can be improved through strategic demand response (DR) management. Specifically, we explore two interaction mechanisms in the market: Nash equilibrium (NE) and Stackelberg equilibrium (SE) among utility companies (UCs) and user-UC interactions, respectively. At the user side, each user determines the optimal energy-purchasing strategy to maximize its own profit. At the UC side, a governmental UC (g-UC) is considered, who aims to optimize the social profit of the market. Meanwhile, normal UCs play games to maximize their own profits. As a result, a basic leader-following problem among the UCs is formulated under the coordination of the independent system operator (ISO). Moreover, by using our proposed demand function amelioration (DFA) strategy, a multi-timescale leader-following problem is formulated. In this case, the maximal market efficiency can be achieved without changing the "selfish instinct" of normal UCs. In addition, by considering the local constraints for the UCs, two projection-based pricing algorithms are proposed for UCs, which can provide approximate optimal solutions for the resulting non-convex social profit optimization problems. The feasibility of the proposed algorithms is verified by using the concept of price of anarchy (PoA) in a multi-UC multi-user market model in the simulation.
翻译:在电力市场中,市场参与者制定“自私”战略为自己获取最大利润,这很常见,因为市场参与者制定“自私”战略为自己获取最大利润,这可能会造成社会福利损失,并损害社会的长期可持续性。关于这一问题,我们将在这项工作中讨论如何通过战略需求反应管理来提高社会利润。具体地说,我们探讨市场中的两个互动机制:电力公司(UCs)之间的纳什平衡(Nash sal)和斯塔克勒贝格平衡(Se),以及用户-UC的互动。在用户方面,每个用户都决定最佳能源购买战略,以最大限度地增加其自身利润。在UCs方面,政府采用旨在优化市场社会利润概念的UCUC(G-U),同时,正常的UC会玩游戏,以尽量扩大自己的利润。因此,在独立系统操作者(ISO)的协调下,正在设计一个基本的领导者应对UCs之间的问题。此外,通过使用我们提出的需求调整(DFA)战略,一个多时间级领导人跟踪问题。在UC方面,通过不使用正常的市场成本预测,因此,最高成本效率可以实现。