{"title":"基于灰狼优化(Gwo)算法的家庭能源管理系统中家电的最优调度","authors":"A. R. Jordehi","doi":"10.1109/PTC.2019.8810406","DOIUrl":null,"url":null,"abstract":"In smart homes, under price-based or incentivebased demand response programs, home energy management system (HEMS) aims to determine optimal schedule of appliances in order to minimise electricity bill of the home. This scheduling problem is commonly formulated as a constrained optimisation problem with integer decision variables. Metaheuristics are the most popular algorithms for solving engineering optimisation problems. Grey wolf optimisation (GWO) is a swarm-based metaheuristic optimisation algorithm, inspired from the performance of wolves and has shown promising performance in solving some engineering optimisation problems. In this paper, GWO is used for solving the problem of optimal scheduling of appliances in HEM systems. The problem is solved for two different homes with different set of appliances. For each home, the problem is solved for two cases with different DR programs. The performance of GWO is compared with the well-established particle swarm optimisation (PSO) algorithm. The results indicate the outperformance of the proposed GWO with respect to PSO.","PeriodicalId":187144,"journal":{"name":"2019 IEEE Milan PowerTech","volume":" 11","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Optimal Scheduling of Home Appliances in Home Energy Management Systems Using Grey Wolf Optimisation (Gwo) Algorithm\",\"authors\":\"A. R. Jordehi\",\"doi\":\"10.1109/PTC.2019.8810406\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In smart homes, under price-based or incentivebased demand response programs, home energy management system (HEMS) aims to determine optimal schedule of appliances in order to minimise electricity bill of the home. This scheduling problem is commonly formulated as a constrained optimisation problem with integer decision variables. Metaheuristics are the most popular algorithms for solving engineering optimisation problems. Grey wolf optimisation (GWO) is a swarm-based metaheuristic optimisation algorithm, inspired from the performance of wolves and has shown promising performance in solving some engineering optimisation problems. In this paper, GWO is used for solving the problem of optimal scheduling of appliances in HEM systems. The problem is solved for two different homes with different set of appliances. For each home, the problem is solved for two cases with different DR programs. The performance of GWO is compared with the well-established particle swarm optimisation (PSO) algorithm. The results indicate the outperformance of the proposed GWO with respect to PSO.\",\"PeriodicalId\":187144,\"journal\":{\"name\":\"2019 IEEE Milan PowerTech\",\"volume\":\" 11\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE Milan PowerTech\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PTC.2019.8810406\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Milan PowerTech","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PTC.2019.8810406","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal Scheduling of Home Appliances in Home Energy Management Systems Using Grey Wolf Optimisation (Gwo) Algorithm
In smart homes, under price-based or incentivebased demand response programs, home energy management system (HEMS) aims to determine optimal schedule of appliances in order to minimise electricity bill of the home. This scheduling problem is commonly formulated as a constrained optimisation problem with integer decision variables. Metaheuristics are the most popular algorithms for solving engineering optimisation problems. Grey wolf optimisation (GWO) is a swarm-based metaheuristic optimisation algorithm, inspired from the performance of wolves and has shown promising performance in solving some engineering optimisation problems. In this paper, GWO is used for solving the problem of optimal scheduling of appliances in HEM systems. The problem is solved for two different homes with different set of appliances. For each home, the problem is solved for two cases with different DR programs. The performance of GWO is compared with the well-established particle swarm optimisation (PSO) algorithm. The results indicate the outperformance of the proposed GWO with respect to PSO.