{"title":"探讨楼宇用电智能化管理方法的案例研究","authors":"C. Quintero M., J. Jiménez Mares","doi":"10.1109/CLEI.2012.6427182","DOIUrl":null,"url":null,"abstract":"The power consumption in buildings represent a 30–40% of the final energy usage, which is caused by: HVAC (Heating, ventilation and air conditioning), lighting and appliances with any connection to the power grid. The major challenge is to minimize the power consumption by optimizing the operation of several loads without impact in the customer's comfort. For this purpose, the design of an Energy-Efficiency Management Model using Intelligent Systems is presented in this paper. Furthermore a comparative analysis is carried out to evaluate the power consumption performance of some Demand Side Management (DSM) techniques. In this case Direct Load Control, Load Priority and Scheduled Programming techniques using Fuzzy Logic and Artificial Neural Networks (ANN) are compared with the proposed approach. Experimental testing is performed with the consumption data base. The testing results show that energy savings can be achieved through control of the states of various loads.","PeriodicalId":263586,"journal":{"name":"Latin American Computing Conference / Conferencia Latinoamericana En Informatica","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Towards an intelligent management approach for power consumption in buildings case study\",\"authors\":\"C. Quintero M., J. Jiménez Mares\",\"doi\":\"10.1109/CLEI.2012.6427182\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The power consumption in buildings represent a 30–40% of the final energy usage, which is caused by: HVAC (Heating, ventilation and air conditioning), lighting and appliances with any connection to the power grid. The major challenge is to minimize the power consumption by optimizing the operation of several loads without impact in the customer's comfort. For this purpose, the design of an Energy-Efficiency Management Model using Intelligent Systems is presented in this paper. Furthermore a comparative analysis is carried out to evaluate the power consumption performance of some Demand Side Management (DSM) techniques. In this case Direct Load Control, Load Priority and Scheduled Programming techniques using Fuzzy Logic and Artificial Neural Networks (ANN) are compared with the proposed approach. Experimental testing is performed with the consumption data base. The testing results show that energy savings can be achieved through control of the states of various loads.\",\"PeriodicalId\":263586,\"journal\":{\"name\":\"Latin American Computing Conference / Conferencia Latinoamericana En Informatica\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Latin American Computing Conference / Conferencia Latinoamericana En Informatica\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CLEI.2012.6427182\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Latin American Computing Conference / Conferencia Latinoamericana En Informatica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CLEI.2012.6427182","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Towards an intelligent management approach for power consumption in buildings case study
The power consumption in buildings represent a 30–40% of the final energy usage, which is caused by: HVAC (Heating, ventilation and air conditioning), lighting and appliances with any connection to the power grid. The major challenge is to minimize the power consumption by optimizing the operation of several loads without impact in the customer's comfort. For this purpose, the design of an Energy-Efficiency Management Model using Intelligent Systems is presented in this paper. Furthermore a comparative analysis is carried out to evaluate the power consumption performance of some Demand Side Management (DSM) techniques. In this case Direct Load Control, Load Priority and Scheduled Programming techniques using Fuzzy Logic and Artificial Neural Networks (ANN) are compared with the proposed approach. Experimental testing is performed with the consumption data base. The testing results show that energy savings can be achieved through control of the states of various loads.