基于大数据平台的电网线损与窃电预警分析关键技术

提出了一种基于营配调贯通的海量数据分析技术，采用电力大数据平台关键技术构建电网线损与窃电预警分析系统，实现线损的一体化计算、分析与展示。在线损计算结果的基础上，综合利用电网企业现有海量数据，通过采用Hadoop离线分布式计算、Spark内存计算等大数据技术对线损率异常线路或台区进行深度挖掘，识别出可能存在的窃电行为，为供电企业反窃电稽查提供窃电预警和数据支持服务，进一步提升供电企业的经营效益。本系统的构建为大数据技术在电力行业的应用进行了验证和实践。

Key technologies of line loss and stealing electricity prediction analysis based on big data platform

Based on the adjustment of marketing and distribution massive data, this paper proposes a system for power grid line loss and stealing electricity prediction with the key technologies of electric power big data platform. The system provides the integration of calculation, analysis and visualization for line loss. According to the result of line loss calculation and the existing massive data of power grid enterprise, the system adopts the big data technology of Hadoop offline distributed computing and Spark memory computing algorithm to identify the potential acts of stealing electricity by big data mining for the abnormal line loss rate of line and supplying district. Therefore, it provides the stealing electricity prediction and data support services for power supply enterprise with anti-stealing inspection and improves the economic efficiency of enterprise. Through the construction of the system, the application of big data technologies in the electric power industry is verified and implemented. This work is supported by National Natural Science Foundation of China (No.61672276).