The invention relates to a distribution network reconstruction method employing a parallel genetic algorithm based on an undirected spanning tree. The method comprises the following steps: obtaining parameters; performing Monte Carlo simulation sampling; randomly generating an initial population with feasible topology, and setting an initial value of iteration frequency n as 1; performing load flow calculation; calculating a target function value, determining whether constraint conditions are satisfied, if not, returning to the step for re-generating the initial population, and if yes, dividing an existing population into multiple sub populations for performing parallel genetic operation; generating one random permutation P from 1 to Nsub, and establishing a mapping relation between a target sub population i and a source sub population pi, wherein P=[p1, p2,..., pNsub]; replacing the worst individual of each target sub population with an optimal individual of one corresponding source sub population; and determining whether the iteration frequency n reaches requirements, if not, adding one to the iteration frequency and returning to the step of load flow calculation, and if yes, outputting a distribution network reconstruction scheme. Compared to the prior art, the method has the advantages of high calculation efficiency, high integration, close connection with reality and the like.