{"title":"配电系统智能家电调度中最优负荷管理的智能算法","authors":"H. Swalehe, B. Marungsri","doi":"10.1109/IEECON.2018.8712166","DOIUrl":null,"url":null,"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.","PeriodicalId":6628,"journal":{"name":"2018 International Electrical Engineering Congress (iEECON)","volume":"58 1","pages":"1-4"},"PeriodicalIF":0.0000,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Intelligent Algorithm for Optimal Load Management in Smart Home Appliance Scheduling in Distribution System\",\"authors\":\"H. Swalehe, B. Marungsri\",\"doi\":\"10.1109/IEECON.2018.8712166\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":6628,\"journal\":{\"name\":\"2018 International Electrical Engineering Congress (iEECON)\",\"volume\":\"58 1\",\"pages\":\"1-4\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Electrical Engineering Congress (iEECON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEECON.2018.8712166\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Electrical Engineering Congress (iEECON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEECON.2018.8712166","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Intelligent Algorithm for Optimal Load Management in Smart Home Appliance Scheduling in Distribution System
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.