• CSCD核心库收录期刊
  • 中文核心期刊
  • 中国科技核心期刊

Electric Power Construction ›› 2018, Vol. 39 ›› Issue (11): 60-68.doi: 10.3969/j.issn.1000-7229.2018.11.008

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Research on Collaborative Architecture for Edge Computing of  Residential Intelligent Usage of Electricity

LIU Sifang1, DENG Chunyu2, ZHANG Guobin2, QI Bing1,  LI Bin1, LI Dezhi2, SHI Kun2, YANG Bin3, XI Peifeng4   

  1. 1. School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China;2. China Electric Power Research Institute, Beijing 100192, China;3. State Grid Jiangsu Electric Power Company, Nanjing 210024, China;4. Shanghai Key Laboratory of Smart Grid Demand Response (Shanghai Electrical Apparatus Research Institute (Group) Co., Ltd.), Shanghai 200063, China
  • Online:2018-11-01
  • Supported by:
    This work is supported by Innovation Fund of China Electric Power Research Institute(No.5242001600HV).


With the acceleration of the development of power system and the popularization of intelligent home appliances, functions of intelligent terminals, extensive interconnection among terminals and intelligent collaboration are redefined. This paper proposes a collaborative architecture for edge computing of intelligent electricity usage for residential users, which can solve the overload problem when several high-power loads are working at the same time. Based on the edge computing reference architecture, the framework of collaborative strategy is analyzed. Then, according to the priority ranking of the home appliances, the cloud collaborative platform controls the switching of appliances, thus realizing the goal of avoiding the overload of power. This paper proposes a priority ranking method based on analytic hierarchy process (AHP), compares distributed and centralized collaborative architecture. Through edge computing on intelligent devices, the complex household appliance load data could be analyzed and processed, the operating mode of residential intelligent usage of electricity is optimized to ensure a smooth and highly efficient intelligent home appliance system.

Key words:  intelligent usage of electricity, edge computing, cloud collaboration, priority ranking of home appliances

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