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首页> 外文期刊>Turkish Journal of Electrical Engineering and Computer Sciences >Competitive unit maintenance scheduling in a deregulated environment based on preventing market power
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Competitive unit maintenance scheduling in a deregulated environment based on preventing market power

机译:在规避环境中基于防止市场支配力的竞争性设备维护计划

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With the advent of electricity markets, the traditional approach to unit maintenance scheduling (UMS) needs to undergo major changes in order to be compatible with competitive environment structures. The transition from a vertical power system to a competitive structure makes many challenges for policymakers and market designers. In this paper, a new approach to UMS in competitive electricity markets is presented. The main part of this study involves both how to treat generating companies (GENCOs) fairly and how to guarantee power system security during the maintenance scheduling. This paper advances the UMS in the electricity market so that one can determine which maintenance plans are to be selected while guaranteeing power system security and ensuring fair competition among GENCOs. The main contribution of this study is the constructing of a new kind of UMS to prevent market power and economic withholding. In order to guarantee power system security, a probabilistic approach of reliability analysis is presented. This probabilistic methodology is designed based on the health levelization and well-being analysis technique. The optimal strategy profile is defined by a genetic algorithm, so it can strike the right balance between profit and security with fair competition. In the end, maintenance scheduling as numerical results for 9 GENCOs of a large-scale IEEE reliability test system is applied to show the applicability of the proposed framework.
机译:随着电力市场的到来,传统的单元维护计划(UMS)方法需要进行重大更改,以与竞争环境结构兼容。从垂直动力系统到竞争结构的转变对政策制定者和市场设计者提出了许多挑战。本文提出了在竞争性电力市场中UMS的新方法。本研究的主要内容涉及如何公平对待发电公司(GENCO)以及如何在维护计划中保证电力系统的安全性。本文提出了UMS在电力市场上的发展,以便人们能够确定要选择的维护计划,同时保证电力系统的安全性并确保GENCO之间的公平竞争。这项研究的主要贡献是构建一种新型的UMS,以防止市场支配力和经济隐瞒。为了保证电力系统的安全性,提出了一种可靠性分析的概率方法。这种概率方法是根据健康水平和幸福感分析技术设计的。最佳策略配置文件是由遗传算法定义的,因此它可以在公平竞争的情况下在利润和安全性之间取得适当的平衡。最后,以大型IEEE可靠性测试系统的9个GENCO的维护结果作为数值结果,证明了该框架的适用性。

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