A Strategy Based On Community Detection For Parallel Topology Analysis In Power Networks
2017 13TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (ICNC-FSKD)(2017)
Abstract
Large-scale power grid will inevitably become a new trend in the development of power systems, thus the power grid structure will become increasingly complex. The traditional topology analysis method can not meet the requirements of real-time. Therefore a parallel topology analysis preconditioning strategy based on community discovery algorithm was proposed. This strategy effectively utilized the maximum edge betweenness to achieve the topological division of the power grid, which laid the foundation for the parallel topology formation mechanism between the multiple regions of the power grid. On the basis of topological division, the regional grid can be parallel and asynchronous to form the topology, thus according to certain communication and coordination rules, the construction of the global power grid topology can be completed through the distributed computing, which can significantly improve the efficiency of topology analysis.
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Key words
community detection, topology division, optimal partition, clustering
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