Journal of Shanghai Jiao Tong University ›› 2025, Vol. 59 ›› Issue (6): 845-856.doi: 10.16183/j.cnki.jsjtu.2023.353

• New Type Power System and the Integrated Energy • Previous Articles     Next Articles

Reactive Power-Voltage Droop Gain Online Tuning Method of Photovoltaic Inverters for Improvement of Stable Output Power Capability in Weak Grids

WANG Yuyang1,2, ZHANG Chen1,2(), ZHANG Yu1,2, WANG Yiming3, XU Po3, CAI Xu1,2   

  1. 1. School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
    2. Key Laboratory of Control of Power Transmission and Conversion of the Ministry of Education, Shanghai Jiao Tong University, Shanghai 200240, China
    3. Ginlong Technologies Co., Ltd., Ningbo 315712, Zhejiang, China
  • Received:2023-07-28 Accepted:2023-09-07 Online:2025-06-28 Published:2025-07-04
  • Contact: ZHANG Chen E-mail:nealbc@sjtu.edu.cn

Abstract:

The active power output capability and small signal stability in weak grids are key factors that limit stable photovoltaic (PV) power generation. To improve stably generating PV power in weak grids, an adaptive control method for PV inverters based on online tuning of the reactive power-voltage (Q-V) droop gain is proposed. First, to ensure active power output capability in weak grids, a “first optimization” method for the Q-V droop gain is proposed, considering voltage and current constraints. Then, to address stability constraints in weak grids, impedance modeling and stability analysis of the PV inverter system are conducted. A mapping relationship between the “parameter-weakest pole” is established with the weakest pole of the closed-loop system as a stability constraint based on the artificial neural network. A “second adjustment” method for the Q-V droop gain is developed at stably generating active power. Combined with the extended Kalman-filter-based grid impedance estimation, the proposed Q-V droop gain adaptive tuning method is realized. The effectiveness of the proposed adaptive control method is validated on the Modeling Tech real-time simulation platform.

Key words: adaptive control, converter, stability, photovoltaic (PV) power generation, voltage droop control, weak grid, artificial intelligence

CLC Number: