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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:本文为家庭能源管理(下摆)控制器的表现提供了比较评估,该公司的家用电器分为三种不同类别1)固定电器2)中断软件和3)非中断能够在其负载型材的基础上的设备用户偏好。它是在两个生物启发算法的基础上,遗传算法(GA),用于老化算法(BFA)的细菌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)。需求侧管理系统(DSM)也在揭开。实时定价(RTP)模型用于能源价格计算。随着仿真验证,成功地实现了最大限度地减少了电力成本消耗和峰值(PAR)比率的目标。仿真执行开发的启发式算法,ACO在四个算法中表现最佳。安排算法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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