Research on user’s fine portrait method based on comprehensive electricity consumption index
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(1. Huaian Power Supply Company, Jiangsu Electric Power Co., Ltd., Huaian 223000, China; 2. CEC(Beijing)Technology Development Co., Ltd., Beijing 100055, China)

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This work is supported by Data Value-added Services Project of State Grid Jiangsu Electric Power Co., Ltd.(No.2019011)

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    Abstract:

    In the context of the construction of the energy internet, it is urgent to carry out a comprehensive analysis of the electricity consumption level and characteristics of enterprises, so as to optimize the energy consumption structure of enterprise users and improve the comprehensive service level of power enterprises. First of all, the comprehensive electricity consumption index is adopted to reflect the electricity consumption situation of enterprises. From the seven dimensions of reliable electricity consumption, economic electricity consumption, green electricity consumption, intelligent electricity consumption, interactive electricity consumption, macroeconomic prosperity and industrial prosperity, a multi-level and multi-dimensional comprehensive index system of comprehensive electricity consumption index is constructed. Secondly, based on the comprehensive electricity consumption index system, the comprehensive evaluation model of users’electricity consumption is built to accurately evaluate the electricity consumption level and efficiency of users, and realize the hierarchical, refined and multi-dimensional portrait of the electricity consumption of enterprise users. Based on the multi-dimensional portrait results, the electricity consumption of enterprise users is analyzed. Finally, four enterprises are selected for example analysis, and corresponding suggestions for electricity consumption optimization are put forward. This research method can effectively guide enterprises to use electricity scientifically and provide support for integrated energy service business of power enterprises.

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尤宏亮,郭平平,徐晓敏,杨迪,李瑛莉.基于综合用电指数的用户精细画像方法研究[J].电力需求侧管理英文版,2020,22(5):83-87.

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History
  • Received:June 19,2020
  • Revised:July 22,2020
  • Adopted:
  • Online: September 29,2020
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