基于遗传算法的配电网扩展规划方法研究

Research on power distribution network extension planning method based on genetic algorithm

现有配电网扩展规划方法的节点电压标么值较低,该算法易陷入局部最优而无法得到全局最优解,因此,文章提出基于遗传算法的配电网扩展规划方法。建立目标函数并设定节点功率平衡约束以减少误合。设定惩罚函数并通过潮流计算以得到分布式电源的处理方法。建立分布式电源的配电网扩展模型,并将模型中的约束条件及惩罚系数计入目标函数中。对需求解的变量进行编码,形成遗传算法的染色体,通过变异概率和交叉概率值与个体平均适应度的比较,将优秀值保留进入下一代,劣值淘汰后加快算法收敛,完成配电网的规划优化。实验结果表明,在接入分布式电源后,小组3节点电压值的提升增加了用户用电的稳定性和可靠性;收敛次数与计算次数保持一致,该方法具有较好的收敛性能,实现了良好的应用。

The node voltage standard value of the existing distribution network expansion planning method is low,and the algorithm is easy to fall into local optimization and cannot obtain the global optimal solution.Therefore,this paper proposes a distribution network expansion planning method based on genetic algo.Establish the objective function and set the node power balance constraints to reduce false connection.Set the penalty function and calculate the power flow to get the processing method of distributed power generation.Establish the distribution network expansion model of distributed power,and include the constraints and penalty coefficients in the model into the objective function.The variables of the demand solution are encoded to form the chromosome of the genetic algo.By comparing the probability of variation and the cross probability value with the average fitness of the individual,the excellent value is reserved for the next generation.After the inferior value is eliminated,the algorithm convergence is accelerated to complete the planning and optimization of the distribution network.The experimental results show that after the distributed power supply is connected,the increase of the voltage value of the three nodes in the group increases the stability and reliability of the user's electricity consumption,the number of convergences is consistent with the number of calculations,and the method has good convergence performance and realizes good application.