基于最小生成树编码的配电网恢复遗传算法

Distribution Network Restoration Based on the Genetic Algorithm with Minimum Spanning Tree Decoding

建立了大停电事故后配电网恢复的数学优化模型。通过改变目标函数参数,可以适应不同的系统恢复方案中各种可用电源容量的情况。遗传算法求解采用实数编码、最小生成树Prim算法解码,避免了不可行解的产生,大大提高了算法的计算效率。配电网潮流采用前推回代法计算,并利用Prim算法的中间结果直接得到各节点间的父子关系,减少了计算量。算例表明文中的算法稳定性好,收敛迅速。

A mathematical model for distribution network restoration after system blackout is developed. By changing the parameters of the goal function, the model can adapt to various cases of available power capacity in different restoration schemes. The genetic algorithm （GA） encodes with the ratio of branch and is decoded via the minimum spanning tree algorithm-Prim algorithm to bypass the generation of infeasible solutions, thus greatly improving the GA＇ s efficiency. The backward/forward sweep algorithm is then adopted to solve the distribution power flow, and the sequence of nodes for power flow calculation is directly determined by the intermediate results of the Prim algorithm. Computational results on two test systems demonstrate the satisfactory performance of the robustness and convergence of the algorithm proposed.