Extraction of Geospatial Topology and Graphics for Distribution Automation Framework

Abstract

Maintaining the integrity of an electrical distribution network for the supervisory control and data acquisition (SCADA) database is a challenging task due to the increasingly changing network topology. Despite the labor-intensive database maintenance that is prone to human error, the use of inaccurate data can lead to erroneous computational results. This paper proposes an automated framework to extract geospatial datasets for SCADA of distribution systems using two standardized exchange formats: (1) Common information model (CIM/XML) which describes the topology, and (2) CIM graphics in scalable vector graphics (SVG) format from the World Wide Web consortium (W3C), which illustrates the dynamic and static geographical schematics. A comparator which determines the changes between different datasets is proposed to avoid importing all data. The proposed framework is evaluated using case studies consisting of thousands of CIM-based elements.