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Appliances Scheduling Using Hybrid Scheme of Genetic Algorithm and Elephant Herd Optimization for Residential Demand Response

机译:遗传和大象群优化混合算法的居民需求响应调度

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The invention of Smart Grid (SG) have revolutionized the traditional electricity consumption pattern as well as distribution. The technology of communication and information have been involved in almost every domain so for Smart Grids. Production of electricity is not cheap, hence with the help of information and technology, Smart Meters (SM) play vital role to control, manage and perform optimization to utilize the electric power efficiently on consumer side and called Demand Side Management (DSM). In the proposed research paper, a Home Energy Management System (HEMS) have been proposed to optimize the home appliances to reduce the maximum cost. Elephant Herd Optimization (EHO) algorithm have been implemented along with our own hybrid of EHO algorithm. This EHO is hybrid of Genetic Algorithm (GA) and called Genetic Elephant Herd Optimization (GEHO). Results of simulation shows that GEHO scheduled the appliance more efficiently to reduce maximum cost when comparing with regular EHO and unscheduled schemes. Peak to Average Ration (PAR) also have been observed. GEHO and unscheduled have equal PAR due to scheduling of maximum appliances on either sides but EHO have small PAR. For further understanding of cost optimization different Operation Time Interval (OTI) have been applied. Trends of load and cost with all of three schemes have been discussed in detail.
机译:智能电网(SG)的发明彻底改变了传统的用电方式和配电方式。通信和信息技术已经涉及到几乎每个领域,因此对于智能电网也是如此。电力生产并不便宜,因此在信息和技术的帮助下,智能电表(SM)在控制,管理和执行优化以在用户方有效利用电力方面起着至关重要的作用,被称为需求方管理(DSM)。在提出的研究论文中,提出了一种家庭能源管理系统(HEMS),以优化家用电器以降低最大成本。象群优化(EHO)算法已与我们自己的EHO混合算法一起实现。此EHO是遗传算法(GA)的混合,称为遗传象群优化(GEHO)。仿真结果表明,与常规EHO和非计划方案相比,GEHO更有效地计划了设备,以降低最大成本。还观察到峰均比(PAR)。由于双方调度的最大设备数,GEHO和未调度的PAR相等,但是EHO的PAR较小。为了进一步了解成本优化,已应用了不同的操作时间间隔(OTI)。已经详细讨论了这三种方案的负载和成本趋势。

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