Journal of South China University of Technology(Natural Science Edition) ›› 2026, Vol. 54 ›› Issue (3): 21-30.doi: 10.12141/j.issn.1000-565X.250310

• Power & Electrical Engineering • Previous Articles     Next Articles

Plug-and-Play Control Strategy for Distributed Energy Storage Participation in Frequency Regulation

HUANG Xiangmin1  ZENG Jun1  WANG Pengxu1  WANG Tianlun1,2  LIU Junfeng3   

  1. 1. School of Electric Power, South China University of Technology, Guangzhou 510640, Guangdong, China;

    2. NR Electric Co., Ltd., Nanjing 211102, Jiangsu, China;

    3. School of Automation Science and Engineering, South China University of Technology, Guangzhou 510640, Guangdong, China

  • Online:2026-03-25 Published:2025-09-26

Abstract:

The frequency of the new electricity system is facing severe tests such as reduced rotational inertia, enhanced fault impact, and insufficient frequency regulation resources. Distributed resources, with distributed energy storage as a typical example, have become a new means and effective supplement for system frequency regulation. However, the contradiction between the autonomous demands of users and the deterministic requirements of the power grid restricts the application of distributed energy storage in the auxiliary frequency regulation scenario. To address this issue, first, the decision-making behavior psychology of distributed energy users is analyzed through prospect theory, and a more realistic distributed energy participation in frequency regulation simulation environment is constructed based on the user incentive response characteristic curve under non-rational decision-making. Secondly, a flexible control strategy for broadcasting dynamic incentive signals to distributed energy storage users is proposed. The nonlinear problem of frequency regulation is transformed into a system parameter estimation problem after dynamic linearization, and a model-free adaptive incentive control method is adopted to solve the uncertainty of user response and the difficulty of user cluster modeling. The cluster response model is dynamically linearized through real-time data of the cluster control system and the optimal real-time incentive signal is output. Finally, a case study of a single-area power system is conducted in MATLAB/Simulink. Under both step load fluctuation and continuous load fluctuation scenarios, the proposed method has good frequency tracking performance, with the maximum frequency deviation controlled below 0.0015 p.u., thereby verifying the adaptability and effectiveness of the proposed incentive control method.

Key words: distributed energy storage, frequency regulation, adaptive control, incentive response, user modeling