Hadoop架构下基于分布式粒子群算法的骨架网络重构方法

A Novel Skeleton Network Reconfiguration Method Based on Distributed PSO Algorithm and Hadoop Architecture

大停电后网络重构阶段的主要目的是通过黑启动电源给失电厂站送电并建立一个稳定的网架,为下一阶段负荷的全面恢复奠定基础。针对确定网络重构阶段的最优目标网架问题,提出一种骨架网络重构方法。该方法首先综合考虑节点、支路在网络中的影响力,具体指以节点重要度、支路重要度分别表征网络中电源与负荷节点的重要程度、网络中各支路对与之相连节点的支撑作用及其在网络中的影响力;同时,为降低重构过程中出现故障的风险和加快后期负荷的全面恢复,提出节点聚集度指标,以表征重构网架的覆盖均匀程度;其次,考虑到大规模骨架网络重构问题属于高维优化的范畴,单机版算法求解高维优化问题时计算效率低,为此提出一种基于Hadoop平台的分布式粒子群算法,该算法利用集群的计算和存储能力求解高维问题时能够显著提高计算效率;最后,以IEEE 30、57和300节点标准系统为例验证所提网络重构方法的有效性。

Main purpose of network reconfiguration stage is to supply power to outage power stations through black start power and to build a stable network,laying foundation for full recovery of loads in the next stage.A network reconfiguration method is proposed to determine optimal target network in network reconfiguration stage.Firstly,the method considers influence of nodes and lines in the network.It means to measure essentiality of power nodes and load nodes by means of a specific importance degree of node,support of branch to node connected with the branch,and branch influence by means of a specific importance degree of branch.Node aggregation degree measuring coverage uniformity of reconstructed network is proposed to reduce failure risk in reconfiguration process and accelerate full recovery of loads in the next stage.Secondly,computational efficiency is lower when single version algorithm is used to solve high dimensional optimization problems,and large scale network reconfiguration is a high dimension optimization problem.Therefore,a distributed particle swarm optimization algorithm based on Hadoop platform is proposed to get optimum solution of the target network taking advantage of cluster computing and storage capacity.Finally,the proposed method is verified on IEEE 30,57 and 300 systems to demonstrate its efficiency.