Load scheduling with Maximum Demand using Binary Particle Swarm Optimization

T. Remani, E. A. Jasmin, Imthias Ahamed T P
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引用次数: 16

Abstract

With continuously growing energy demand the importance of Demand Response(DR) programs is increasing in Smart Grid. Demand response relies on scheduling of loads under the constraints enforced by the utlity so as to reduce energy cost. Schedulable loads play an important role in such programs. The main aim of Demand Response programs is to minimize the energy cost considering the Maximum Demand (MD) limit and the operating constraints of the demand resources. Binary Particle Swarm Optimization(BPSO) is one of the soft computing methods suitable for addressing commitment problems. This paper suggests a method based on BPSO to solve the load scheduling problem with flexibe and non flexible loads and also having Maximum Demand constraint. The algorithm is validated for a number of loads having different characteristics.
基于二元粒子群优化的最大需求负荷调度
随着能源需求的不断增长,需求响应(DR)方案在智能电网中的重要性日益增加。需求响应依赖于在电力公司的约束下对负荷进行调度,从而降低能源成本。可调度负载在这类程序中起着重要作用。需求响应方案的主要目标是考虑最大需求(MD)限制和需求资源的运行约束,使能源成本最小化。二粒子群算法是一种适用于解决承诺问题的软计算方法。针对具有最大需求约束的柔性和非柔性负载调度问题,提出了一种基于BPSO的负载调度方法。该算法针对具有不同特征的负载进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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