电网技术2017，Vol.41Issue(9)：2987-2995,9.DOI:10.13335/j.1000-3673.pst.2017.0011
基于灰狼优化算法的多机电力系统稳定器参数最优设计
Multi-Machine PSSParameter Optimal Tuning Basedon Grey Wolf Optimizer Algorithm
左剑 1张程稳 1肖逸 1李银红 1段献忠1
作者信息
- 1. 强电磁工程与新技术国家重点实验室(华中科技大学),湖北省 武汉市 430074
- 折叠
摘要
Abstract
A novel highly-efficientswarm intelligence optimization algorithm known asgreywolfoptimizer (GWO) can be applied to power system optimization.A parameter optimization designscheme is illustrated inthis paper for optimal tuningof powersystemstabilizer (PSS) parametersin a multi-machine power system. Traditional leading-lag type PSS parameter design is modeled as an optimization problem with objective ofoptimaleigenvalue-based quadratic performance. The optimization is to maximize damping ratio of electromechanical oscillation modes under different operating conditions by shifting electromechanicaleigenvalues toward left-half complex plane.GWO algorithm has characteristicsof insensitivity to initial solution values, higher optimization efficiency and global optimizationability.It is employed to iteratively search for optimum solution of PSS parameters. Simulation resultsof linear frequency-domaineigenvalue analysis and nonlinear time-domain dynamic simulationon IEEENew England 39 bus test systemare presented to demonstrate effectiveness and robustness of the proposed GWO-algorithm-based PSSindampingelectromechanical oscillationsofpower system under a wide range of operating conditions.Damping performance of the proposed PSS has obvious superiorityovertraditional phase-compensation-designed PSS. Further algorithm performance analysis shows that GWO algorithm is robustandnot sensitive to initial values.关键词
灰狼优化算法(GWO)/机电振荡/多机电力系统/参数优化/电力系统稳定器(PSS)Key words
grey wolf optimizer (GWO) algorithm/electromechanical oscillations/multi-machine power system/parameter optimization/power system stabilizer (PSS)分类
信息技术与安全科学引用本文复制引用
左剑,张程稳,肖逸,李银红,段献忠..基于灰狼优化算法的多机电力系统稳定器参数最优设计[J].电网技术,2017,41(9):2987-2995,9.
