摘要
粒子群算法(PSO)具有简单易实现,可调参数少的优点。将其用于最优潮流的求解,结合混合罚函数来限制最优潮流的约束条件,使粒子群算法的寻优速度加快,迭代次数减少。通过在IEEE9节点和IEEE30节点上的仿真计算表明,该算法在加快迭代速度和收敛精度上都取得了较好的效果。
A brief introduction of Particle Swarm Optimization （PSO）, one of the new evolutionary optimization algorithms, is given in this paper. It is used in the solution of the optimal power flow along with the Multi-- Sequential Unconstrained Minimization Technique, which is composed of interior point penalty function and exterior point penalty function. PSO can be implemented easily with few parameters need to be identified. The hybrid algorithms are applied to the calculation of IEEE9 bus and IEEE30 bus systems respectively. The results prove that the application of the PSO and Multi-Sequential Unconstrained Minimization Technique can improve the speed of iteration and the precision of convergence.
出处
《中国农村水利水电》
北大核心
2007年第2期90-92,共3页
China Rural Water and Hydropower
