基于Sobol序列的量子粒子群求解电力经济调度

Quantum-Behaved Particle Swarm Optimization Based on Sobol Sequence Solving Economic Power Dispatch

Sobol序列是准随机序列的一种,它与均匀分布的区别在于采样更均匀,为了增加种群多样性,提出了基于Sobol随机序列的量子粒子群,并对边界粒子进行变异,用于求解电力系统经济调度问题.通过对13个机组的数值仿真表明,该算法在收敛精度和迭代速度上有较好的效果.

Sobol sequence is a quasi-random sequence, and the difference between Sobol sequence and the u-niform distribution is that Sobol sequence has more uniform sampling. In order to increase the diversity of particles, we introduce a quantum-behaved particle swarm optimization with a bounded mutation operator based on random Sobol sequence. Then we apply this algorithm to a 13-unit system, and the experimental results indicate that the algorithm is characterized by high speed, high accuracy and good convergence.