基于粒子群算法的低压配电网需求响应优化分配

Pragma Kar, Samiran Chattopadhyay, O. Ivanov, M. Gavrilas
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引用次数: 4

摘要

出于技术和经济原因,调峰是电力公司追求的主要目标。可再生资源的日益使用和对化石燃料发电的环境法规给高负荷电网的运行带来了新的挑战,特别是在高峰时段。解决这些问题的一种方法是使用需求响应(DR)等方法减少负载。DR项目在世界范围内主要针对工业客户,而针对住宅消费者的方法大多是理论上的,有一些试点项目正在进行中。本文提出了一种基于粒子群优化的中、低压变电站级需求响应算法,根据预设的舒适度和其他优化标准——受影响用户数、受影响舒适度、网络平衡和减损,在低压电网用户之间分配公用事业公司对变电站需求的DR水平。
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Optimal Demand Response Allocation in LV Distribution Networks Using the PSO Algorithm
Peak load shaving is a main objective sought by electricity utilities, for technical and economic reasons. The increasing use of renewable resources and the environmental regulations placed on fossil fuel electricity generation bring new challenges in the operation of highly loaded electricity networks, especially at peak hours. One way of addressing these problems is load reduction using methods such as Demand Response (DR). DR programs are in place worldwide mainly for industrial clients, while approaches for residential consumers are mostly theoretical, with a few pilot projects underway. This paper proposes a Particle Swarm Optimization-based algorithm for Demand Response at MV/LV substation level, where the DR level requested by the utility for a substation is distributed between the customers in the LV network according to preset comfort levels and other optimization criteria - affected number of users, affected comfort levels, network balancing and loss reduction.
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