{"title":"公用事业的分析和人工智能:解锁效率和可靠性","authors":"Amanda Mastrosimone, Andrew Biondi","doi":"10.1002/gas.22472","DOIUrl":null,"url":null,"abstract":"<p>The utility industry is facing challenges to increase operational efficiency, reduce costs, enhance reliability, and integrate renewable and distributed energy resources (DERs) onto the grid. Utilities are experimenting with approaches to intelligently use the vast amount of data they have using advanced analytics, artificial intelligence (AI), and machine learning (ML) techniques.</p>","PeriodicalId":100259,"journal":{"name":"Climate and Energy","volume":"42 1","pages":"1-9"},"PeriodicalIF":0.0000,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analytics and AI for Utilities: Unlocking Efficiency and Reliability\",\"authors\":\"Amanda Mastrosimone, Andrew Biondi\",\"doi\":\"10.1002/gas.22472\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The utility industry is facing challenges to increase operational efficiency, reduce costs, enhance reliability, and integrate renewable and distributed energy resources (DERs) onto the grid. Utilities are experimenting with approaches to intelligently use the vast amount of data they have using advanced analytics, artificial intelligence (AI), and machine learning (ML) techniques.</p>\",\"PeriodicalId\":100259,\"journal\":{\"name\":\"Climate and Energy\",\"volume\":\"42 1\",\"pages\":\"1-9\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-07-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Climate and Energy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/gas.22472\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Climate and Energy","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/gas.22472","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analytics and AI for Utilities: Unlocking Efficiency and Reliability
The utility industry is facing challenges to increase operational efficiency, reduce costs, enhance reliability, and integrate renewable and distributed energy resources (DERs) onto the grid. Utilities are experimenting with approaches to intelligently use the vast amount of data they have using advanced analytics, artificial intelligence (AI), and machine learning (ML) techniques.