{"title":"将抄表网络扩展到阿莫莱尤的农村地区","authors":"M.J. Koyna, R.M. Wiesehan","doi":"10.1109/REPCON.1999.768695","DOIUrl":null,"url":null,"abstract":"Utilities throughout the world are considering network meter reading (NMR) to help them better understand and serve their customers, establish operational excellence, and quickly react to changing regulatory requirements. While most companies are considering NMR for strategic reasons, they must also prove the cost effectiveness of such a system. In 1995, AmerenUE (then Union Electric) made a decision to install the CellNet Data Systems NMR network in its metropolitan service territory. This decision was predicated on the perceived benefits of NMR and the company's desire to position itself for successful operation in the competitive world. Since that decision was made, over 800000 automated meters (including supporting infrastructure and information handling systems) have been installed and operated. The company's experience with NMR during over three years has substantiated the originally perceived benefits of system deployment. After a comprehensive review of NMR performance and a detailed evaluation of relevant economic factors, AmerenUE made the decision to extend automated meter reading into its rural service territories starting in 1998. This paper presents the bases for that decision. Economic benefits and technical considerations of implementing the system in a low customer-density setting are addressed. Extended applications, including outage detection, transformer load management and current diversion detection are also discussed.","PeriodicalId":364482,"journal":{"name":"1999 Rural Electric Power Conference (Cat. No. 99CH36302)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Extension of network meter reading into rural districts at AmerenUE\",\"authors\":\"M.J. Koyna, R.M. Wiesehan\",\"doi\":\"10.1109/REPCON.1999.768695\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Utilities throughout the world are considering network meter reading (NMR) to help them better understand and serve their customers, establish operational excellence, and quickly react to changing regulatory requirements. While most companies are considering NMR for strategic reasons, they must also prove the cost effectiveness of such a system. In 1995, AmerenUE (then Union Electric) made a decision to install the CellNet Data Systems NMR network in its metropolitan service territory. This decision was predicated on the perceived benefits of NMR and the company's desire to position itself for successful operation in the competitive world. Since that decision was made, over 800000 automated meters (including supporting infrastructure and information handling systems) have been installed and operated. The company's experience with NMR during over three years has substantiated the originally perceived benefits of system deployment. After a comprehensive review of NMR performance and a detailed evaluation of relevant economic factors, AmerenUE made the decision to extend automated meter reading into its rural service territories starting in 1998. This paper presents the bases for that decision. Economic benefits and technical considerations of implementing the system in a low customer-density setting are addressed. Extended applications, including outage detection, transformer load management and current diversion detection are also discussed.\",\"PeriodicalId\":364482,\"journal\":{\"name\":\"1999 Rural Electric Power Conference (Cat. No. 99CH36302)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1999 Rural Electric Power Conference (Cat. No. 99CH36302)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/REPCON.1999.768695\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1999 Rural Electric Power Conference (Cat. No. 99CH36302)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/REPCON.1999.768695","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Extension of network meter reading into rural districts at AmerenUE
Utilities throughout the world are considering network meter reading (NMR) to help them better understand and serve their customers, establish operational excellence, and quickly react to changing regulatory requirements. While most companies are considering NMR for strategic reasons, they must also prove the cost effectiveness of such a system. In 1995, AmerenUE (then Union Electric) made a decision to install the CellNet Data Systems NMR network in its metropolitan service territory. This decision was predicated on the perceived benefits of NMR and the company's desire to position itself for successful operation in the competitive world. Since that decision was made, over 800000 automated meters (including supporting infrastructure and information handling systems) have been installed and operated. The company's experience with NMR during over three years has substantiated the originally perceived benefits of system deployment. After a comprehensive review of NMR performance and a detailed evaluation of relevant economic factors, AmerenUE made the decision to extend automated meter reading into its rural service territories starting in 1998. This paper presents the bases for that decision. Economic benefits and technical considerations of implementing the system in a low customer-density setting are addressed. Extended applications, including outage detection, transformer load management and current diversion detection are also discussed.