Graph Computing Based Power Network Analysis Applications

被引：0
|
作者：
Liu G. [1 ,2 ]
Dai R. [1 ]
Lu Y. [3 ]
Liu K. [2 ]
Wang Z. [1 ]
Yuan C. [1 ]
Fan H. [1 ]
Dai J. [1 ]
机构：
[1] Global Energy Interconnection Research Institute North America, San Jose, 95134, CA
[2] Global Energy Interconnection Research Institute, Beijing
[3] State Grid Sichuan Electric Power Company, Chengdu
来源：
Diangong Jishu Xuebao/Transactions of China Electrotechnical Society | 2020年 / 35卷 / 11期
关键词：
Contingency analysis; Energy management system; Graph computing; Graph database; Power flow; State estimation; Topology analysis;
D O I：
10.19595/j.cnki.1000-6753.tces.190901
中图分类号：
学科分类号：
摘要：
This paper discussed the bottlenecks of current energy management system (EMS) for grid modernization and smart grid. To meet the requirements for the next generation EMS, a graph-based power system online parallel computing approach is proposed in this paper. In this approach, the power system is modeled as a graph and the power system analysis and computing are performed on the graph all in memory. To improve the computation efficiency, a suite of parallel computing algorithm based on graph is developed to solve power flow and state estimation equations. Taking the graph computing advantages on nodal and hierarchical parallelism, the graph-based state estimation, power flow, and contingency analysis applications are implemented and integrated in a developed EMS prototype. The case study on a real provincial system verified the advantages of graph computing and its computation efficiency is outperformed than commercial EMS. The potential applications on EMS using graph computing are presented at the end of the paper. © 2020, Electrical Technology Press Co. Ltd. All right reserved.
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页码：2339 / 2348
页数：9
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