Electric Power ›› 2025, Vol. 58 ›› Issue (2): 103-110.DOI: 10.11930/j.issn.1004-9649.202409056

Previous Articles     Next Articles

Optimal Scheduling Strategy for Microgrid Considering the Support Capabilities of Grid Forming Energy Storage

Zhibin YAN1(), Li LI2(), Peng YANG3, Huihui SONG3(), bin CHE1, Panlong JIN1   

  1. 1. State Grid Ningxia Electric Power Co., Ltd., Yinchuan 750001, China
    2. School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150000, China
    3. School of New Energy, Harbin Institute of Technology (Weihai), Weihai 264200, China
  • Received:2024-09-12 Accepted:2024-12-11 Online:2025-02-23 Published:2025-02-28
  • Supported by:
    This work is supported by National Natural Science Foundation of China (No.52477085), Science and Technology Project of SGCC (No.1400-202435281A-1-1-ZN).

Abstract:

In order to coordinate the stability and operation efficiency of the microgrid, the inertial support characteristics and frequency support capability of the grid-forming storage are analyzed. Based on this, the optimization objectives of the microgrid are clarified, and the constraints such as power balance, equipment operation, system inertia, and reserve capacity are formed. Combined with the nonlinear optimization problem solver of the Optimization Toolbox, an optimization scheduling strategy considering the support capability of the grid-forming energy storage proposed. In order to test the effectiveness of the proposed strategy, the joint probability distribution function of wind and solar power generation is constructed by using the kernel density estimation method the Copula function, and the typical scenarios of new energy are formed based on the K-means clustering. The analysis is carried out under the typical scenarios, and results show that the proposed method can give full play to the support capability of the grid-forming energy storage and effectively improve the level of new energy consumption.

Key words: microgrid, grid forming energy storage, optimal scheduling, typical scenario, supporting characteristics