基于布谷鸟搜索优化算法的国内可移动负荷调度

R. Çakmak, I. Altas
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引用次数: 19

摘要

电力系统已经发展到更先进的结构,称为“智能电网”。其中,需求侧管理(DSM)是智能电网的重要手段之一。DSM技术提高了电网的效率,并通过使用财政激励的需求响应(DR)计划来调整消费者的电力需求。本研究采用布谷鸟搜索算法(Cuckoo search algorithm, CSA)调度可移动的国内负荷,在考虑消费者偏好的同时,尽可能保证负荷曲线的均衡。本文的主要动机是利用最近发展的元启发式CSA方法对小区内可移动家电的使用时间进行调度。本文提出了在考虑用户经济效益需求的前提下,通过调度和运行可移动的国内负荷来提高电网效率和寿命的方法。将提出的基于CSA的调度机制与遗传算法的调度机制进行了比较。结果表明,CSA在调度和性能方面优于遗传算法。
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Scheduling of domestic shiftable loads via Cuckoo search optimization algorithm
Electrical power systems have been developed to more advanced structures called as “smart grids”. Among many other issues, demand side management (DSM) is one of the important instruments of the smart grids. DSM techniques increase the efficiency of the grid, and modify consumer’s electrical demand via demand response (DR) programs using financial incentives. In this study, shiftable domestic loads scheduled by Cuckoo search algorithm (CSA) to ensure balanced load curve as much as possible while considering the consumers’ preferences. The main motivation of this paper is scheduling the usage hours of the shiftable household appliances in a neighborhood by applying the recently developed metaheuristic CSA. This paper proposes an approach to increase the efficiency and lifetime of utility network by scheduling and operating shiftable domestic loads while considering consumer’s demand in terms of financial benefits. Proposed CSA based scheduling mechanism is compared with that of Genetic algorithm (GA). The results reveal positive effects of the scheduling and the performance of the CSA over GA.
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