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针对虚拟同步发电机控制的光储构网型逆变器在复杂多变扰动下暂态和稳态调节能力不足的问题，提出一种考虑精细区间划分的虚拟惯量与虚拟阻尼协同自适应的功频稳定控制策略。首先，设计基于非线性函数的虚拟惯量自适应调节机制，通过将角速度变化率及其变化量映射至虚拟惯量系数的调节过程，并划分精细化的调节区间，从而优化系统在功频动态调节过程中的稳定性；其次，考虑系统在频率扰动下的稳定性，在阻尼控制环节引入一阶超前滞后环节，实现暂态阻尼和稳态阻尼的动态自适应切换，从而降低网侧频率扰动下的系统稳态输出功率误差；最后，通过验证试验的结果及分析表明，所提出的参数协同自适应控制策略在有功功率扰动下与传统控制策略、传统自适应控制策略、RBF神经网络自适应控制策略功率响应的最大超调量分别为3.2%、6%、5.3%、3.5%,本文提出的控制策略在电网频率扰动、电网电压扰动以及弱电网下具有良好的适应性。
Abstract：Aiming at the insufficient transient and steady-state regulation capability of grid-forming photovoltaic-storage inverters based on virtual synchronous generator control under complex and variable disturbances, this paper proposed a coordinated adaptive power-frequency stability control strategy for virtual inertia and virtual damping with fine interval division. Firstly, a nonlinear function-based virtual inertia adaptive regulation mechanism was designed, which maps the angular velocity change rate and its variation to the adjustment of the virtual inertia coefficient and divides fine regulation intervals to optimize the system stability during dynamic power-frequency regulation. Secondly, considering system stability under frequency disturbances, a first-order lead-lag link was introduced into the damping control loop to realize dynamic adaptive switching between transient damping and steady-state damping, thereby reducing the steady-state output power error under grid-side frequency disturbances. Finally, verification results show that under active power disturbance, the maximum power response overshoot of the proposed coordinated adaptive parameter control strategy, the traditional control strategy, the traditional adaptive control strategy, and the RBF neural network adaptive control strategy are 3.2%, 6%, 5.3%, and 3.5%, respectively, the proposed control strategy has favorable adaptability under grid frequency disturbances, grid voltage disturbances, and weak grid conditions.
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基本信息:
DOI：10.13880/j.cnki.65-1174/n.2026.21.006
中图分类号:TM464;TM712
引用信息:
[1]姜三涛,黎劲松,龚立娇,等.基于参数协同自适应的光储构网型逆变器功频稳定控制策略[J].石河子大学学报(自然科学版),2026,44(02):172-183.DOI:10.13880/j.cnki.65-1174/n.2026.21.006.
基金信息:
新疆生产建设兵团科技计划项目(2024AA004)
2025-10-21
2025
2026-03-04
2026-04-21
2026
1
2026-04-21
2026-04-21
2026-04-21