上海交通大学学报 ›› 2025, Vol. 59 ›› Issue (6): 845-856.doi: 10.16183/j.cnki.jsjtu.2023.353

• 新型电力系统与综合能源 • 上一篇    下一篇

提升弱网有功稳定输出能力的光伏逆变器Q-V下垂系数在线调整方法

王语阳1,2, 张琛1,2(), 张宇1,2, 王一鸣3, 许颇3, 蔡旭1,2   

  1. 1.上海交通大学 电子信息与电气工程学院,上海 200240
    2.上海交通大学 电力传输与功率变换控制教育部重点实验室,上海 200240
    3.锦浪科技股份有限公司,浙江 宁波 315712
  • 收稿日期:2023-07-28 接受日期:2023-09-07 出版日期:2025-06-28 发布日期:2025-07-04
  • 通讯作者: 张琛 E-mail:nealbc@sjtu.edu.cn
  • 作者简介:王语阳(1999—),硕士生,从事光伏并网稳定性与自适应控制研究.
  • 基金资助:
    锦浪科技股份有限公司科技项目(22H010300150);国家自然科学基金重点项目(51837007)

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

摘要:

弱电网下静态有功输出与小扰动稳定能力是制约光伏可靠并网发电的关键因素.为提升弱电网下光伏发电系统有功稳定输出能力,提出一种基于无功功率-电压(Q-V)下垂系数自适应在线调整方法的光伏逆变器稳定控制方法.首先,为保障弱电网下的静态有功输出能力,提出计及电压、电流限制约束的Q-V下垂系数“一次优化”方法.然后,为进一步满足弱电网稳定性约束,开展光伏逆变器并网系统阻抗建模与稳定性分析,基于人工智能神经网络实现以闭环系统最弱极点为稳定性约束条件的“参数-最弱模式”映射关系和以有功稳定输出为目标的Q-V下垂系数“二次调整”方法;结合卡尔曼滤波器辨识的电网阻抗信息,最终实现所提Q-V下垂系数自适应在线调整方法.最后,利用远宽实时仿真平台对所提控制方法的有效性进行了分析与验证.

关键词: 自适应控制, 变换器, 稳定性, 光伏发电, 下垂控制, 弱电网, 人工智能

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

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