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Comparative Assessment of Performance for Home Energy Management Controller in Smart Grid

机译:智能电网中家庭能源管理控制器性能的比较评估

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This paper, provides comparative assessment of performance for home energy management (HEM) controller which categories the household appliances into three different categories 1) Fixed appliances 2) Interrupt able appliances and 3)Non-interrupt able appliances on the bases of their load profiles and user preference. It is designed on the bases of two bio-inspired algorithms, genetic algorithm (GA), bacterial for aging algorithm (BFA) and two nature-inspired algorithms binary particle swarm optimization algorithm (BPSO) and ant colony optimization algorithm (ACO). Demand side management system(DSM) is also inaugurate. Real time pricing (RTP) model is used for energy price calculation. The objectives of minimize electricity cost consumption and peak to average (PAR) ratio are achieve successfully, as simulations validates. Simulations perform foraforemention heuristic algorithms, ACO perform best amongall four algorithms. Average cost for schedule algorithms GA, BFA, BPSO and ACO are 95.58%, 81%, 90.4% and 76.48%respectively.
机译:本文提供了针对家庭能源管理(HEM)控制器的性能的比较评估,该控制器将家用电器分为以下三个不同的类别:1)固定设备2)可中断设备和3)不可中断设备(基于其负载曲线和用户偏好。它基于两种生物启发算法,遗传算法(GA),细菌老化算法(BFA)和两种自然启发算法二进制粒子群优化算法(BPSO)和蚁群优化算法(ACO)进行设计。需求方管理系统(DSM)也已启用。实时定价(RTP)模型用于能源价格计算。正如仿真所证实的那样,成功实现了将电力成本消耗最小化和峰均比(PAR)最小化的目标。仿真执行预先启发式算法,ACO在所有四种算法中表现最佳。调度算法GA,BFA,BPSO和ACO的平均成本分别为95.58%,81%,90.4%和76.48%。

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