基于改进多目标万有引力算法的UPFC选址定容

Site Selection and Determination of Capacity for UPFC Based on Improved Multi-objective Gravitational Search Algorithm

综合考虑系统可用输电能力、静态电压稳定裕度以及投资费用,建立了用于统一潮流控制器UPFC的选址及定容的多目标优化模型,而且考虑了多个约束条件。将动态权重和粒子群优化算法引入到万有引力搜索算法中,并通过改进的多目标万有引力搜索算法对UPFC的安装地点与补偿容量进行寻优,得到包含可用输电能力、静态电压稳定裕度、投资费用信息3种指标的Pareto前沿解集。最后通过对IEEE-14节点进行验证,并与多目标万有引力搜索算法优化结果进行对比,结论表明所采用的算法能得到更优的解,更适用于UPFC的选址与定容。

With the consideration of available transfer capability(ATC),static voltage stability margin,and investment cost of power system,a multi-objective optimization model of site selection and determination of capacity is established for a unified power flow controller(UPFC)under multiple constraints.Dynamic weight and particle swarm optimization algorithm are introduced to gravitational search algorithm(GSA),and by using the improved multi-objective GSA(IMOGSA),the site selection and determination of capacity for UPFC are optimized to obtain the Pareto solution set,in which ATC,static voltage stability margin,and investment cost are included.Finally,the proposed method is validated on an IEEE 14-node system.Compared with the optimization results of multi-objective GSA(MOGSA),it is concluded that the proposed algorithm can get a better solution,which is more suitable for the site selection and determination of capacity of UPFC.