{"title":"电力中断给工业和商业用电消费者带来的成本","authors":"D. Michael, J., Sullivan, T. Vardell","doi":"10.1109/ICPS.1996.533934","DOIUrl":null,"url":null,"abstract":"This paper summarizes the results of a survey of 210 large commercial and industrial customers to obtain detailed descriptions of the components of interruption costs they would experience under varying outage conditions. In addition, the survey observed plant operating schedules, products and services, processes used machinery used in production, backup generation and equipment designed to ensure power quality. The paper describes a statistical approach for obtaining inexpensive outage cost estimates for individual customers by combining information from on-site interviews with less costly information obtained from utility representatives. Results from regression models estimated from the information obtained in the on-site survey are described in detail.","PeriodicalId":122944,"journal":{"name":"Proceedings of 1996 IAS Industrial and Commercial Power Systems Technical Conference","volume":"173 3","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"138","resultStr":"{\"title\":\"Power interruption costs to industrial and commercial consumers of electricity\",\"authors\":\"D. Michael, J., Sullivan, T. Vardell\",\"doi\":\"10.1109/ICPS.1996.533934\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper summarizes the results of a survey of 210 large commercial and industrial customers to obtain detailed descriptions of the components of interruption costs they would experience under varying outage conditions. In addition, the survey observed plant operating schedules, products and services, processes used machinery used in production, backup generation and equipment designed to ensure power quality. The paper describes a statistical approach for obtaining inexpensive outage cost estimates for individual customers by combining information from on-site interviews with less costly information obtained from utility representatives. Results from regression models estimated from the information obtained in the on-site survey are described in detail.\",\"PeriodicalId\":122944,\"journal\":{\"name\":\"Proceedings of 1996 IAS Industrial and Commercial Power Systems Technical Conference\",\"volume\":\"173 3\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-05-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"138\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 1996 IAS Industrial and Commercial Power Systems Technical Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPS.1996.533934\",\"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 1996 IAS Industrial and Commercial Power Systems Technical Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPS.1996.533934","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Power interruption costs to industrial and commercial consumers of electricity
This paper summarizes the results of a survey of 210 large commercial and industrial customers to obtain detailed descriptions of the components of interruption costs they would experience under varying outage conditions. In addition, the survey observed plant operating schedules, products and services, processes used machinery used in production, backup generation and equipment designed to ensure power quality. The paper describes a statistical approach for obtaining inexpensive outage cost estimates for individual customers by combining information from on-site interviews with less costly information obtained from utility representatives. Results from regression models estimated from the information obtained in the on-site survey are described in detail.