摘要
随着电力网络规模的扩大,电力系统优化问题日益复杂,故提出了一种采用遗传禁忌GATS混合优化策略对电力系统稳定器PSS和静止无功补偿器SVC附加线性稳定控制器进行参数协调优化的设计方法。该方法结合遗传算法GA和禁忌搜索算法TS各自的优点,将禁忌搜索引入到遗传算法的变异操作,改进了遗传算法的变异算子,具有比常规遗传算法更强的局部搜索能力。在10机新英格兰电力系统上对该优化方法进行了测试。特征值分析表明,该设计方法能有效地将多种不同运行方式下系统的特征根移到复平面目标函数限定的区域内,保证了小扰动稳定性控制的鲁棒。同时还对不同优化方法的收敛性及计算时间进行了比对,结果表明遗传禁忌混合策略的性能优于常规遗传算法以及遗传模拟退火混合优化策略。
In this paper,a hybrid optimization approach based on genetic algorithm and tabu search is presented for the coordination design of parameters of PSS and SVC damping controller. The approach, adopting TS as GA mutation operator,possesses advantages of both TS and GA and has stronger local search ability than conventional genetic algorithm. By considering several representative operating conditions in the objective function,the robustness of the damping controllers is ensured. Simulation is performed on the 10- machine New England test power system. Result of eigenvalue analysis verifies that the proposed method can displace eigenvalues into the specified area on the complex plan, and thus the PSS and SVC damping controllers can provide sufficient damping for low frequency oscillations in different operating conditions. Compared with genetic algorithm and genetic simulated annealing hybrid algorithm, the result shows that GATS hybrid algorithm has better performance on convergence and time cost.
出处
《电力系统及其自动化学报》
CSCD
北大核心
2006年第1期43-47,70,共6页
Proceedings of the CSU-EPSA
关键词
遗传算法
禁忌搜索算法
电力系统稳定器
静止无功补偿器
低频振荡
genetic algorithm（GA）
tabu search （TS）
power system stabilizer（PSS）
static var compensator （SVC）
low frequency oscillation
