CIM/E Oriented Graph Database Model Architecture and Parallel Network Topology Processing

TL;DR

This paper models CIM/E power system data into a graph database and develops a parallel processing algorithm, significantly improving efficiency in network topology analysis for power systems.

Contribution

It introduces a novel graph database model for CIM/E data and a parallel network topology processing method leveraging graph computation.

Findings

Processing efficiency is greatly improved.

Modeling CIM/E data as a graph enhances analysis.

Validated on IEEE and Sichuan power network cases.

Abstract

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.