2018/03/15 by Zhangxin Zhou, Chen Yuan, Zhou, Zhangxin +14
Computer Science · Engineering · #Distributed #Distributed and Parallel Computing Systems #FOS: Computer and information sciences #Graph Theory and Algorithms #Parallel #Power Systems and Technologies #and Cluster Computing (cs.DC) #cs.DC
paper · pdf · doi:10.48550/arxiv.1803.05935
To be published (Accepted) in: Proceedings of the Power and Energy Society General Meeting (PESGM), Portland, OR, 2018
arxiv created 2018/03/15 · openalex publication_date 2018/03/15 · arxiv updated 2018/03/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
CIM/E is an easy and efficient electric power model exchange standard between different Energy Management System vendors. With the rapid growth of data size and system complexity, the traditional relational database is not the best option to store and process the data. In contrast, the graph database and graph computation show their potential advantages to handle the power system data and perform real-time data analytics and computation. The graph concept fits power grid data naturally because of the fundamental structure similarity. Vertex and edge in the graph database can act as both a parallel storage unit and a computation unit. In this paper, the CIM/E data is modeled into the graph database. Based on this model, the parallel network topology processing algorithm is established and conducted by applying graph computation. The modeling and parallel network topology processing have been demonstrated in the modified IEEE test cases and practical Sichuan power network. The processing efficiency is greatly improved using the proposed method.