基于遗传算法的背靠背换流站控制系统参数优化

Parameter Optimization of Control System for Back to Back Converter Station based on Genetic Algorithm

背靠背换流站控制系统参数优化能够有效改善系统的运行性能.在研究背靠背换流站控制系统的工作原理后,推导出定电流、定电压、定熄弧角和定功率控制方式下系统的数学模型.把时间与绝对误差乘积的积分函数作为遗传算法的适应度函数,即控制系统参数优化的目标函数.给出了遗传算法用于参数优化的寻优过程及其参数的确定方法.最后,以灵宝背靠背换流站控制系统为例,给出了参数的优化结果,分析了换流站交流侧故障时直流系统的暂态过程.结果证明了遗传算法用于背靠背换流站控制系统参数优化的可行性和有效性.

Parameters optimization of control system for back to back converter station is a effective way to improve system operating performance. This paper researches the work theory of control system,derivates mathematical model of control system mode,such as constant current mode,constant extinction angle mode,constant voltage mode and constant power mode. Choosing ITAE performance index as genetic algorithm（ GA） adaptive function and the value of objective function for parameters optimization,also is the process of parameters optimization. Parameters determining method for GA is provided in this paper. Basing on this method,using Lingbao back to back converter station as an example,the results of final optimizating parameters ara given. Accodding to performance in transient process when AC side is in fault,genetic algorithm provided in parameters optimization for back tp back converter station is effective and feasible.