基于多时间尺度降阶的光伏发电控制参数优化

提出了一种基于多时间尺度降阶的光伏发电系统参数优化方法。首先综合考虑主电路及控制策略建立了其小信号模型,利用特征值分析和参与因子分析初步确定了影响系统振荡的主要因素。其次对小信号模型进行多时间尺度降阶,并基于降阶模型分析控制器参数对振荡模式的影响,确定了需优化的主要控制器参数及其取值范围。最后分别以原模型和降阶模型为研究对象进行参数寻优,并在MATLAB中仿真对比了优化前后系统的小干扰稳定性。研究结果表明,降阶模型能够不同程度地反映光伏发电系统的振荡模式,为控制器参数优化提供建议;基于降阶模型和原模型的优化结果均能使系统在小扰动下更快地恢复到稳态,且前者计算速度更快,验证了所提方法的正确性和有效性。

Parameter Optimization of Photovoltaic Power Generation System Based on Multi-time Scale Reduction

The controller parameters of photovoltaic power generation system are very important for its stable operation.Therefore,a parameter optimization method of photovoltaic power generation system based on multi-time scale reduction is proposed.Firstly,it established a small signal model considering the main circuit and control strategy and determined the main factors affecting the system oscillation by eigenvalue analysis and participation factor analysis.Secondly,it reduced the small signal model in multi-time scale,analyzed the influence of the controller parameters on oscillation mode based on the reduced-order model,and determined the main controller parameters and their ranges to be optimized.Finally,it optimized the parameters by the original model and the reduced-order model,simulated the small-interference stability of the system before and after optimization and compared them in MATLAB.The results show that the reduced-order model can reflect the oscillation mode of photovoltaic power generation system to varying degrees and provide suggestions for the optimization of controller parameters.The optimization results based on the reduced-order model and the original model can recover to stable operation faster under small disturbances,and the former calculates faster,which verifies the correctness and effectiveness of the proposed method.