A Multi-Objective Genetic Algorithm Approach for Synergetic Source-Storage-Load Dispatch in a Residential Microgrid

Subho Paul, N. Padhy
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引用次数: 3

Abstract

The current work presented in this article proposes a day ahead multi-objective optimization portfolio for a residential microgrid or a home consisting of different domestic appliances and rooftop solar panels associated with storage device. The proposed framework aims to determine synergetic source-storage-load dispatch schedule by simultaneously minimizing the electricity cost, ocular discomfort and thermal discomfort experienced by the home occupants for the following day while controlling switching of the discrete loads (like washing machine, dryer etc.) and consumption of the continuous loads (like air-conditioner, lights etc.). The entire optimization framework takes the form of a mixed integer non-linear programming and the solution technique is proposed using Genetic Algorithm. The simulation is carried out on practical data set of a residential unit to prove effectiveness of the designed method.
住宅微电网源蓄负荷协同调度的多目标遗传算法
本文中介绍的当前工作为住宅微电网或由不同家用电器和与存储设备相关的屋顶太阳能电池板组成的家庭提出了提前一天的多目标优化组合。所提出的框架旨在通过同时控制离散负载(如洗衣机、烘干机等)的开关和连续负载(如空调、灯等)的消耗,最大限度地减少家庭居住者在第二天所经历的电力成本、视觉不适和热不适,来确定协同的源-存储-负载调度计划。整个优化框架采用混合整数非线性规划的形式,并采用遗传算法求解。在一个住宅单元的实际数据集上进行了仿真,验证了所设计方法的有效性。
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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