关于新能源并网供电无功性能优化设计研究

Research on Optimized Design of Reactive Power Performance of New Energy Grid Connected Power Supply Simplified Particle Swarm Optimization

由于新能源发电易受风力、光照等自然条件的影响,且接入配电网会改变潮流走向,增加系统无功优化的难度。鉴此,提出了一种基于判断因子的自适应粒子群算法,利用基于平均熵初始化的策略,增加种群的多样性;通过使用判断因子对粒子适应度值的收敛性进行动态跟踪的方法,实现惯性权重的的自适应调节,解决了后期粒子易陷入局部最优的问题,增加了算法全局寻优的能力;然后配合正弦变化的学习因子调整策略,提高了算法的收敛速度;最后对较好适应度值粒子的位置进行Logistic混沌映射进一步提高搜索精度。通过对含新能源接入的IEEE-30节点配电系统进行建模仿真且与其它两种算法相比较,验证了提出的算法寻优性和收敛性更好。

An adaptive particle swarm algorithm based on judgment factor is proposed. The algorithm uses the strategy based on the average entropy to increase the diversity of the population. By using the method of determining the convergence of the particle fitness value by the judgment factor,the adaptive adjustment of the inertia weight is realized,which solves the problem that the later particles are easy to fall into the local optimal value,which increases the global optimization ability of the algorithm. And then the learning strategy with the sine-changing learning factor is adjusted to improve the convergence rate of the algorithm. Finally,Logistic chaotic mapping of the position of the better fitness value is used to further improve the search precision. With the IEEE-33 node distribution system as an example,the simulation shows that the proposed algorithm has better convergence and better performance than the optimization results of the other two algorithms,which has better performance in solving the problem of reactive power optimization of new energy distribution network.