Intelligent Algorithm for Optimal Load Management in Smart Home Appliance Scheduling in Distribution System

H. Swalehe, B. Marungsri
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引用次数: 14

Abstract

One of the essential factor for the better operation of an electrical power system is load demand. Normally, higher load demand leads to instability and insufficient power supply. To make an electrical power system stable and sufficient, a good correlation between demand and supply should exist. A survey conducted during 2011 indicated that residential sector is consuming 18% of total energy. Also, the demand was seen to increase rapidly close to and sometimes beyond the supply. Hence, this paper focuses on appliance scheduling for cost reduction and peak load reduction by increasing demand-side response in the smart home. A load management algorithm is developed in MATLAB which reduces both cost and peak load consumption by managing the operation according to utility controls and consumer preferences. The optimization problem was solved by using Genetic Algorithm (GA) technique. The simulation results depicted that GA can be adopted for appliance scheduling in the household, reduction of electrc bill as well as cutback of peak demand from the demand side.
配电系统智能家电调度中最优负荷管理的智能算法
负荷需求是电力系统良好运行的重要因素之一。通常情况下,较高的负荷需求会导致不稳定和电力供应不足。为了使电力系统稳定和充足,需求和供应之间应该存在良好的相关性。2011年进行的一项调查表明,住宅部门消耗了总能源的18%。此外,需求增长迅速,接近供应,有时甚至超过供应。因此,本文将重点研究智能家居中通过增加需求侧响应来降低成本和降低峰值负荷的设备调度。在MATLAB中开发了一种负荷管理算法,该算法通过根据公用事业控制和消费者偏好管理运行来降低成本和峰值负荷消耗。采用遗传算法对优化问题进行求解。仿真结果表明,遗传算法可用于家庭电器调度,降低电费,从需求侧削减高峰需求。
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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