Electric Power ›› 2024, Vol. 57 ›› Issue (3): 34-42.DOI: 10.11930/j.issn.1004-9649.202312036

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Accurate Estimation Method of Customer Baseline Load for Continuous Participation of Industrial Users in Demand Response

Heng LIANG1(), Geng HUANG2, Bin HOU2, Xi YANG3, Xiaohu LUO3(), Da ZHANG1()   

  1. 1. Institute of Energy Environment and Economy, Tsinghua University, Beijing 100084, China
    2. School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
    3. Sichuan Energy Internet Research Institute, Tsinghua University, Chengdu 610000, China
  • Received:2023-12-11 Accepted:2024-03-10 Online:2024-03-23 Published:2024-03-28
  • Supported by:
    This work is supported by National Natural Science Foundation of China (No.71974109, No.72140005).

Abstract:

A computational method combining K-means cluster analysis with long- and short-term memory neural network algorithm is proposed, and transfer learning is carried out by industrial homogeneous group information to further optimize the estimation effect. Accurate estimation of industrial customer power baseline load under long-term continuous response is realized, and the accuracy of the demand response effect evaluation of industrial customers is improved. The effectiveness of the method is verified by the load data of industrial customers participating in demand response practice collected by the city-level virtual power plant platform.

Key words: demand response, customer baseline load estimation, cluster analysis