Name
Abstract | ||
|---|---|---|
Smart grid is an important platform for the exploitation of renewable energy resources and maintaining/improving the reliability of power grid. Challenges have been identified during the construction of smart grid, which calls for novel simulation, computation and data management technologies. For example, as the size of power systems continue to increase, new computational tools are needed to co-simulate the transmission and distribution networks, new data processing and analytical technologies are required to handle big data in power systems, new database technologies are required to manage huge amounts of equipment, etc. To handle these challenges, a graph computation based framework is proposed. Initial investigation of this framework shows that graph computation is a promising technology for solving many of the challenges that arise during the development of smart grid. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/BigDataCongress.2017.75 | 2017 IEEE International Congress on Big Data (BigData Congress) |
Keywords | Field | DocType |
Graph data model,Graph computation,Big data analytics,Power flow algorithm,Smart grid | Data mining,Data modeling,Data processing,Synchronization,Smart grid,Computer science,Electric power system,Big data,Data management,Distributed computing,Computation | Conference |
ISSN | ISBN | Citations |
2379-7703 | 978-1-5386-1997-1 | 0 |
PageRank | References | Authors |
0.34 | 3 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guangyi Liu | 1 | 223 | 36.37 |
| Kewen Liu | 2 | 0 | 0.68 |
| Di Shi | 3 | 0 | 0.34 |
| Wendong Zhu | 4 | 0 | 0.68 |
| Zhiwei Wang | 5 | 7 | 7.28 |
| Xi Chen | 6 | 15 | 5.39 |