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Rapid construction of electric power systems leads to a large increase in quantities of network nodes and data, complicating network reconstruction issue significantly. However, the traditional serial algorithms can not reach a satisfactory computation speed; while some proposed parallel algorithms prior are only applicable to specialized cluster. In this paper, we propose a parallel algorithm of distribution network reconstruction conducted on cost-effective Hadoop cluster. Our algorithm complies with Map-Reduce distributed computing framework. It can process the data of each network node in parallel, thus accelerating power flow calculation. Moreover, our algorithm combines depth-first and breath-first principles together in branch traversals, which substantially improves the probability in finding the optimal solution. Feasibility and effectiveness of the proposed algorithm are verified on a Hadoop cluster.

A Cost-effective Parallel Algorithm of Distribution Network Reconfiguration on Hadoop Cluster