Parallel Betweenness Computation in Graph Database for Contingency Selection

TL;DR

This paper presents parallel algorithms for betweenness computation implemented in a graph database, significantly improving speed for power system contingency analysis by leveraging graph data retrieval efficiencies.

Contribution

It introduces parallel betweenness algorithms tailored for graph databases, enhancing computational efficiency in power system contingency selection.

Findings

Speed-up achieved for node and edge betweenness calculations

Greater speed improvement for edge betweenness due to graph database data retrieval

Validated on 118-bus and real power systems

Abstract

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 118-bus system and a real power system show that speed-up 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.