摘要
禁忌搜索粒子群算法是针对粒子群算法局部搜索能力较弱和存在早熟收敛的问题,将禁忌搜索思想融入到粒子群算法中的混合算法,并将该算法应用到电力系统无功优化中。该方法在粒子群算法寻优过程的后期加入了禁忌表,扩大搜索空间,避免陷入局部最优。通过对IEEE 30节点测试系统和鸡西电网进行仿真计算,并与其他算法进行比较,结果表明该算法能取得更好的全局最优解,既加快了收敛速度,又提高了收敛精度。
To remedy defects existing in traditional particle swarm optimization algorithm （PSO） algorithm, such as it easy falls into local optima and its slower convergence in the later stage of search process, the PSO algorithm is integrated with tabu search to form tabu search-particle swarm optimization （TS-PSO） algorithm and applied to reactive power optimization of power system. In the later stage of search process a tabu list is added into the later stage of search process to enlarge search space and avoid falling into local optima. Simulation results of IEEE 30-bus system and a certain power network in Northeast China show that the proposed algorithm can attain a better global solution, accelerate convergence and improve accuracy of convergence.
出处
《电网技术》
EI
CSCD
北大核心
2011年第7期129-133,共5页
Power System Technology
关键词
粒子群优化算法
无功优化
禁忌搜索
网损
particle swarm optimization （PSO） algorithm
reactive power optimization
tabu search
network loss
