{"title":"基于聚类方法的配水系统电能消耗估算","authors":"G. Grigoraș, M. Istrate, Florina Scarlatache","doi":"10.1109/ECAI.2013.6636174","DOIUrl":null,"url":null,"abstract":"The paper focuses on the development of a method based on representative load profiles of the hydrophore stations, in order to electrical energy consumption estimation in the water distribution system. The proposed method is based on two stages in which K-means clustering algorithm and a load simulation technique are exploited for estimating the electrical energy consumption. The method was tested on an urban water distribution system consists of 73 hydrophore stations. Results obtained demonstrate the ability of the proposed method to become the first step of an efficient management in the water distribution systems.","PeriodicalId":105698,"journal":{"name":"Proceedings of the International Conference on ELECTRONICS, COMPUTERS and ARTIFICIAL INTELLIGENCE - ECAI-2013","volume":"90 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Electrical energy consumption estimation in water distribution systems using a clustering based method\",\"authors\":\"G. Grigoraș, M. Istrate, Florina Scarlatache\",\"doi\":\"10.1109/ECAI.2013.6636174\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper focuses on the development of a method based on representative load profiles of the hydrophore stations, in order to electrical energy consumption estimation in the water distribution system. The proposed method is based on two stages in which K-means clustering algorithm and a load simulation technique are exploited for estimating the electrical energy consumption. The method was tested on an urban water distribution system consists of 73 hydrophore stations. Results obtained demonstrate the ability of the proposed method to become the first step of an efficient management in the water distribution systems.\",\"PeriodicalId\":105698,\"journal\":{\"name\":\"Proceedings of the International Conference on ELECTRONICS, COMPUTERS and ARTIFICIAL INTELLIGENCE - ECAI-2013\",\"volume\":\"90 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the International Conference on ELECTRONICS, COMPUTERS and ARTIFICIAL INTELLIGENCE - ECAI-2013\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ECAI.2013.6636174\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the International Conference on ELECTRONICS, COMPUTERS and ARTIFICIAL INTELLIGENCE - ECAI-2013","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECAI.2013.6636174","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Electrical energy consumption estimation in water distribution systems using a clustering based method
The paper focuses on the development of a method based on representative load profiles of the hydrophore stations, in order to electrical energy consumption estimation in the water distribution system. The proposed method is based on two stages in which K-means clustering algorithm and a load simulation technique are exploited for estimating the electrical energy consumption. The method was tested on an urban water distribution system consists of 73 hydrophore stations. Results obtained demonstrate the ability of the proposed method to become the first step of an efficient management in the water distribution systems.