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A genetic algorithm approach for clearing aggregator offers in a demand response exchange

机译:一种在需求响应交换中清除集合商报价的遗传算法

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In this paper, a pool-based market structure is implemented to trade demand response (DR) in a fully deregulated day-ahead electricity market. In this structure, the demand response aggregator provides load shifting/curtailment as DR offers to the demand response exchange (DRX) market competitively. The independent system operator (ISO) utilizes the DR service only during economic inefficiency. The DRX needs to clear the DR offers such that the overall system economic efficiency improves. Two search techniques have been implemented to clear the DRX market efficiently. One of the search methods is a local search where one DR offer is selected at a time; the other is the genetic algorithm (GA). We implement a rank-based GA in which the bus sensitivities were used for seeding the initial population to speed up convergence. These search techniques are implemented on IEEE RTS-96 system, and the DRX was cleared efficiently to improve the economic performance of the system.
机译:在本文中,在完全放松管制的日间电力市场中,实施了基于池的市场结构来进行贸易需求响应(DR)。在这种结构中,需求响应聚合器提供了负载转移/削减,这是因为DR竞争性地向需求响应交换(DRX)市场提供了服务。独立系统运营商(ISO)仅在经济效率低下时才使用DR服务。 DRX需要清除DR提供的内容,以提高整个系统的经济效率。已经实施了两种搜索技术来有效清除DRX市场。搜索方法之一是本地搜索,其中一次选择一个灾难恢复提议。另一个是遗传算法(GA)。我们实施了基于等级的遗传算法,其中将公交车的敏感性用于初始种群的播种,以加快收敛速度​​。这些搜索技术是在IEEE RTS-96系统上实现的,并且有效清除了DRX以提高系统的经济性能。

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