The application research of multi-source heterogeneous energy big data analysis

Xuemin Han, Gaofeng Zheng, Peng Liu, Zhou Li, Junjie Ma, Xi Chen
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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.
多源异构能源大数据分析应用研究
随着能源工业的快速发展,对能源数据的处理提出了更高的要求。为了从多源异构数据中提取更多的价值,需要将各种来源和不同形式的数据结合起来构建数据分析流程。因此,数据处理技术与能源数据结构相结合;从数据聚合、数据处理、数据分析和数据服务四个方面对数据的分析与处理进行了描述。精准存储、算法库、对象分析、智能服务等也在大数据处理中得到创新应用。通过处理模型的建立和具体功能的实现,实现能源大数据的流通、聚合和共享。最后,通过平台的业务输出和用户的行为交互来体现数据价值。分析将推动能源生产和消费革命,推动能源产业升级转型。
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