摘要
分布式发电系统中,精确的电网阻抗测量是实现并网逆变器在弱电网场合下高性能自适应控制的关键技术。传统主动测量法会对降低注入电网的电能质量,而被动测量方法中逐次迭代法估计精度不高。遗传算法全局搜索能力强、收敛速度快,在参数估计领域得到了广泛研究。为了准确估计并网逆变器电网阻抗,提出了一种基于遗传算法的电网阻抗估计方法。通过建立电网阻抗等效模型,将电网阻抗参数作为遗传算法的个体,在Simulink环境下搭建仿真模型,对比仿真分析了逐次迭代法与遗传算法进行阻抗估计的效果。仿真结果表明:遗传算法估计电网阻抗精度更高。
ABSTRACT：In distributed generation system, accurate grid impedance measurement is the key technology to realize the high performance adaptive control of the grid-connected inverter in the weak grid. The active measurement meth- ods can decrease the quality of the delivered power to the utility grid, and the accuracy of successive iteration method in passive measurement is not high. Genetic algorithm（GA） has been widely studied in parameter identification since it has strong global search capabilities and converges fast. In order to estimate the grid impedance of grid connected inverter accurately, a new method based on genetic algorithm was proposed. The impedance parameters were used as the individual of GA. Simulation and analysis of the grid impedance estimation using successive iteration method and GA were carried out. Simulation results show that mid impedance estimation usin~ GA has hizher accuracy.
出处
《计算机仿真》
北大核心
2018年第1期93-97,共5页
Computer Simulation
基金
国家自然科学基金(51407189
51477180)
关键词
分布式发电
电网阻抗估计
遗传算法
逐次迭代法
Distributed generation
Grid impedance estimation
Genetic algorithm
Successive iteration method
