基于遗传算法的故障限流器全局优化配置

Optimize the Allocation of Global Fault Current Limiter Based on Genetic Algorithms

为了更好地解决新型故障限流器的全局优化配置问题,该文提出了一种基于改进遗传算法的多目标优化配置方法,并运用PSASP和MATLAB软件进行了联合仿真。该方法以安装故障限流器的投资成本、网络损耗和短路容量裕度三方面为优化目标,提出了一种考虑短路水平和系统自阻抗的综合灵敏度筛选方法。综合考虑经济性和网络紧密性,建立了限流器优化配置的数学模型,并在传统的遗传算法上构造哈希表。最后通过PSASP和MATLAB软件对39节点算例进行联合仿真,得到了最优限流方案,并证明了该方法的有效性。

To better address the new fault current limiter global optimization configuration problem,we propose a multi-objective optimization configuration method based on improved genetic algorithm,and cosimulating by MATLAB and PSASP software.The investment cost of the process to install a fault current limiter,network losses and short-circuit capacity margin for the three optimization objectives,proposed a short-circuit level and system integration considering the sensitivity of the screening method of self-impedance.Considering the economy and the tightness of the network,the establishment of a mathematical model of the flow restrictor optimization configuration,and in the traditional genetic algorithms constructs a hash table.Finally a 39 nodes network through PSASP and MATLAB software co-simulation study to obtain the optimal limiting programs,and prove the effectiveness of this method.