{"title":"The application research of multi-source heterogeneous energy big data analysis","authors":"Xuemin Han, Gaofeng Zheng, Peng Liu, Zhou Li, Junjie Ma, Xi Chen","doi":"10.1109/ISCID51228.2020.00044","DOIUrl":null,"url":null,"abstract":"With the rapid development of energy industry, more requirements are put forward for the processing of energy data. In order to extract more value from multi-source heterogeneous data, it is necessary to combine various sources and different forms of data to build a data analysis process. Therefore, data processing technology and energy data structure is combined; the analysis and processing of data are described from the perspectives of data aggregation, data processing, data analysis and data services. Precision storage, algorithm library, object analysis and intelligent services are also used in big data processing innovatively. Through the establishment of processing models and the realization of specific functions, the circulation, aggregation and sharing of energy big data can be achieved. Finally, the data value can be reflected through the business output of platform and behavior interaction of user. The energy production and consumption revolution will be promoted by analysis and the energy industry will upgrade and transform.","PeriodicalId":236797,"journal":{"name":"2020 13th International Symposium on Computational Intelligence and Design (ISCID)","volume":"164 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 13th International Symposium on Computational Intelligence and Design (ISCID)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCID51228.2020.00044","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
With the rapid development of energy industry, more requirements are put forward for the processing of energy data. In order to extract more value from multi-source heterogeneous data, it is necessary to combine various sources and different forms of data to build a data analysis process. Therefore, data processing technology and energy data structure is combined; the analysis and processing of data are described from the perspectives of data aggregation, data processing, data analysis and data services. Precision storage, algorithm library, object analysis and intelligent services are also used in big data processing innovatively. Through the establishment of processing models and the realization of specific functions, the circulation, aggregation and sharing of energy big data can be achieved. Finally, the data value can be reflected through the business output of platform and behavior interaction of user. The energy production and consumption revolution will be promoted by analysis and the energy industry will upgrade and transform.