Electric Power ›› 2022, Vol. 55 ›› Issue (10): 32-44.DOI: 10.11930/j.issn.1004-9649.202205074

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Bi-level Optimization Model of Demand Response Considering Regulation Potential of Load Aggregator

TAN Mingcong1, WANG Lingling1, JIANG Chuanwen1, LIU Hanghang2, WU Liersha3, TANG Jiong3   

  1. 1. Key Laboratory of Control of Power Transmission and Conversion(Shanghai Jiao Tong University), Ministry of Education, Shanghai 200240, China;
    2. Dongying Power Supply Company of State Grid Shandong Electric Power Company, Dongying 257000, China;
    3. Powerchina Hydropower Development Group Co., Ltd., Chengdu 610000, China
  • Received:2022-05-25 Revised:2022-08-04 Online:2022-10-28 Published:2022-10-20
  • Supported by:
    This work is supported by National Key Research & Development Program of China (No.2018YFB0905200) and Science & Technology Project of SGCC (Research and Application of Coordination and Interaction Technology of Source Grid Load and Storage under Electric Power Spot Market, No.52061620009M).

Abstract: The participation of demand response in power system regulation is an effective supplement to generation side regulation. In order to fully tap the potential of demand side resource regulation, a bi-level optimization model of distribution system is designed considering the interaction and transaction mode among the power grid, distribution system operator (DSO) and load aggregator (LA), and the role of each player and the transaction object in the demand response are clarified. The upper level considers the coordination and interaction between the player of source, load and storage inside DSO and the LA, and optimizes the dispatching of the distribution system with the goal of maximizing the profit of DSO. The lower level aims to maximize the LA’s profit of aggregating inverter air conditioners and electric vehicles. Based on the actual operating characteristics of inverter air conditioners and electric vehicles, a demand response model is constructed to fully tap its regulation potential and formulate load regulation strategies. For model solving, the bi-level optimization problem is transformed into an easier linear programming problem through the Karush-Kuhn-Tucker condition and big M method. The case study results show that the proposed bi-level model can fully tap the regulation potential of LA, reduce the electricity purchase from the main network, and improve the income of DSO and LA.

Key words: distribution system operator, load aggregator, demand response, bi-level optimization