
CIM/E Oriented Graph Database Model Architecture and Parallel Network Topology Processing
CIM/E is an easy and efficient electric power model exchange standard be...
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Importing Relationships into a Running Graph Database Using Parallel Processing
Importing relationships into a running graph database using multiple thr...
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Fast Grid Splitting Detection for N1 Contingency Analysis by Graph Computing
In this study, a graphcomputing based grid splitting detection algorith...
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Exploration of BiLevel PageRank Algorithm for Power Flow Analysis Using Graph Database
Compared with traditional relational database, graph database, GDB, is a...
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Exploration of Graph Computing in Power System State Estimation
With the increased complexity of power systems due to the integration of...
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APAN: Asynchronous Propagation Attention Network for Realtime Temporal Graph Embedding
Limited by the time complexity of querying khop neighbors in a graph da...
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Power Flow Analysis Using Graph based Combination of Iterative Methods and Vertex Contraction Approach
Compared with relational database (RDB), graph database (GDB) is a more ...
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Parallel Betweenness Computation in Graph Database for Contingency Selection
Parallel betweenness computation algorithms are proposed and implemented in a graph database for power system contingency selection. Principles of the graph database and graph computing are investigated for both node and edge betweenness computation. Experiments on the 118bus system and a real power system show that speedup can be achieved for both node and edge betweenness computation while the speeding effect on the latter is more remarkable due to the data retrieving advantages of the graph database on the power network data.
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