Z. Fan, Qipeng Chen, G. Kalogridis, S. Tan, D. Kaleshi
{"title":"The power of data: Data analytics for M2M and smart grid","authors":"Z. Fan, Qipeng Chen, G. Kalogridis, S. Tan, D. Kaleshi","doi":"10.1109/ISGTEurope.2012.6465630","DOIUrl":null,"url":null,"abstract":"Machine to machine (M2M) communication has been gaining momentum in recent years as a key enabling technology for a wide range of applications including smart grid, e-health, home/industrial automation, and smart cities. However, with the current communication systems mainly optimized for human to human communications, there are important capabilities that need to be developed in M2M systems in order to fully realize the new smart services enabled by M2M. In this paper, we provide an overview of M2M and its applications to smart grid. In particular, we discuss technical areas where data mining and machine learning can play an important role in realizing various smart functionalities in the future power grid. As a case study, we also present a novel phase identification technique in smart grid based on smart meter data. Preliminary results have demonstrated the effectiveness of the proposed algorithm.","PeriodicalId":244881,"journal":{"name":"2012 3rd IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"30","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 3rd IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISGTEurope.2012.6465630","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 30
Abstract
Machine to machine (M2M) communication has been gaining momentum in recent years as a key enabling technology for a wide range of applications including smart grid, e-health, home/industrial automation, and smart cities. However, with the current communication systems mainly optimized for human to human communications, there are important capabilities that need to be developed in M2M systems in order to fully realize the new smart services enabled by M2M. In this paper, we provide an overview of M2M and its applications to smart grid. In particular, we discuss technical areas where data mining and machine learning can play an important role in realizing various smart functionalities in the future power grid. As a case study, we also present a novel phase identification technique in smart grid based on smart meter data. Preliminary results have demonstrated the effectiveness of the proposed algorithm.