Topology Modeling and Analysis of a Power Grid Network Using a Graph Database

Bowen Kan, Wendong Zhu, Guangyi Liu, Xi Chen, Di Shi, Weiqing Yu
<span title="">2017</span> <i title="Atlantis Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wjdkfhqywrdefeqoyzjz3os76i" style="color: black;">International Journal of Computational Intelligence Systems</a> </i> &nbsp;
We introduce a new method for storing, modeling, and analyzing power grid data. First, we present an architecture for building the network model for a power grid using the open source graph database Neo4j. Second, we design single-and multi-threading systems for initial energization analysis of the power grid network. We design the shortest path search function and conditional search function based on Neo4j. Finally, we compare the functionality and efficiency of our graph database with a
more &raquo; ... ional relational database in system initial energization analysis and the shortest path function problems on small to large data sets. The results demonstrate the efficiency and effectiveness of topology modeling and analysis using graph database for a power grid network.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.2991/ijcis.10.1.96">doi:10.2991/ijcis.10.1.96</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/de2juipzcfe2fj7ni4iz7qr25q">fatcat:de2juipzcfe2fj7ni4iz7qr25q</a> </span>
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