Demand Side Management in Smart Home using Grey Wolf Optimization

M. Danish, I. Ashraf, Sheraz Kirmani
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Abstract

In highly developed Smart Homes, Home Energy Management Systems (HEMS) are considered to deal with the use of energy. In order to balance the supply and the demand, an Optimal Home Energy Management (OHEM) system is proposed in this paper to manage time slot for the use of electric appliance with the economic benefits in electricity tariffs including the customer satisfaction. For Demand Response (DR), Real Time Pricing (RTP) is considered on hourly basis in the electricity tariff plan. First, the constrained optimization problem is formulated into a mathematical function and the objective function is established. In this an objective function is defined by utility function that maximizes the customer satisfaction and reduces the electricity tariff. Minimization of Objective function is performed by the Grey Wolf Optimisation (GWO) Algorithm which gives the optimal solution. The simulation result shows that by using the GWO algorithm in an OHEM system, electrical appliances can be managed in appropriate time slots to improve electricity rates with reasonable compromise on consumer satisfaction. In addition, electricity cost and consumer satisfaction can be adjusted by varying weighting parameter in an objective function.
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基于灰狼优化的智能家居需求侧管理
在高度发达的智能家居中,家庭能源管理系统(HEMS)被认为是处理能源使用的系统。为了实现家庭用电供需平衡,本文提出了一种最优家庭能源管理(OHEM)系统,在兼顾用户满意度和电价经济效益的前提下,对家庭用电时段进行管理。对于需求响应(DR),实时定价(RTP)在电价计划中是按小时计算的。首先将约束优化问题转化为数学函数,建立目标函数;在此,目标函数被定义为效用函数,以最大化客户满意度和降低电价。采用灰狼优化算法对目标函数进行最小化,得到最优解。仿真结果表明,将GWO算法应用到OHEM系统中,可以在合理降低用户满意度的前提下,对电器进行合理的时隙管理,从而提高电价。此外,电力成本和消费者满意度可以通过改变目标函数中的权重参数来调整。
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