Name
Title | ||
|---|---|---|
Exploration of Bi-Level PageRank Algorithm for Power Flow Analysis Using Graph Database |
Abstract | ||
|---|---|---|
Compared with traditional relational database, graph database (GDB) is a natural expression of most real-world systems. Each node in the GDB is not only a storage unit, but also a logic operation unit to implement local computation in parallel. This paper firstly explores the feasibility of power system modeling using GDB. Then a brief introduction of the PageRank algorithm and the feasibility analysis of its application in GDB are presented. Then the proposed GDB based bi-level PageRank algorithm is developed from PageRank algorithm and Gauss-Seidel methodology realize high performance parallel computation. MP 10790 case, and its extensions, MP 10790*10 and MP 10790*100, are tested to verify the proposed method and investigate its parallelism in GDB. Besides, a provincial system, FJ case which include 1425 buses and 1922 branches, is also included in the case study to further prove the proposed algorithm's effectiveness in real world. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/BigDataCongress.2018.00026 | 2018 IEEE International Congress on Big Data (BigData Congress) |
Keywords | DocType | Volume |
Graph database,high-performance computing,PageRank,parallel computing,power flow analysis | Journal | abs/1809.01415 |
ISSN | ISBN | Citations |
2379-7703 | 978-1-5386-7233-4 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chen Yuan | 1 | 27 | 12.30 |
| Yi Lu | 2 | 0 | 2.03 |
| Kewen Liu | 3 | 0 | 0.68 |
| Guangyi Liu | 4 | 223 | 36.37 |
| Renchang Dai | 5 | 0 | 2.03 |
| Zhiwei Wang | 6 | 1 | 1.79 |