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A Method for Evaluating Demand Response Potential of Industrial Loads Based on Fuzzy Control

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Listed:
  • Yan Li

    (Energy Development Research Institute of China Southern Power Grid, Guangzhou 510663, China)

  • Zhiwen Liu

    (Energy Development Research Institute of China Southern Power Grid, Guangzhou 510663, China)

  • Chong Shao

    (Energy Development Research Institute of China Southern Power Grid, Guangzhou 510663, China)

  • Bingjun Lin

    (Beihai Power Supply Bureau Guangxi Power Grid Co., Ltd., Beihai 536000, China)

  • Jiayu Rong

    (Energy Development Research Institute of China Southern Power Grid, Guangzhou 510663, China)

  • Nan Dong

    (Energy Development Research Institute of China Southern Power Grid, Guangzhou 510663, China)

  • Buyun Su

    (Energy Development Research Institute of China Southern Power Grid, Guangzhou 510663, China)

  • Yuejia Hong

    (Energy Development Research Institute of China Southern Power Grid, Guangzhou 510663, China)

Abstract

Demand response (DR) can ensure electricity supply security by shifting or shedding loads, which plays an important role in a power system with a high proportion of renewable energy sources. Industrial loads are vital participants in DR, but it is difficult to assess DR potential because of many complex factors. In this paper, a new method based on fuzzy control is given to assess the DR potential of industrial loads. A complete assessment framework including four steps is presented. Firstly, the industrial load data are preprocessed to mitigate the influence of noisy and transmission losses, and then the K-means algorithm considering the optimal cluster number is used to calculate baseline load of industrial load. Subsequently, an open-loop fuzzy controller is designed to predict the response factor of different industrial loads. Three strongly correlated indicators, namely peak load rate, electricity intensity, and load flexibility, are selected as the input of fuzzy control, which represents response willingness. Finally, the baseline load of diverse clustering scenarios and the response factor are used to calculate the DR potential of different industrial loads. The proposed method takes into account both economic and technical factors comprehensively, and thus, the results better represent the available DR potential in real-world situations. To demonstrate the effectiveness of the proposed method, the case of a medium-sized city in China is studied. The simulation focuses on the top eight industrial types, and the results show they can contribute about 189 MW available DR potential.

Suggested Citation

  • Yan Li & Zhiwen Liu & Chong Shao & Bingjun Lin & Jiayu Rong & Nan Dong & Buyun Su & Yuejia Hong, 2024. "A Method for Evaluating Demand Response Potential of Industrial Loads Based on Fuzzy Control," Energies, MDPI, vol. 17(20), pages 1-14, October.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:20:p:5146-:d:1499860
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    References listed on IDEAS

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