Realistic μPMU Data Generation for Different Real-Time Events in an Unbalanced Distribution Network

Abstract

Monitoring, protection, and control processes are becoming more complex as distributed energy resources (DERs) penetrate distribution networks (DNs). This is due to the inherent nature of power DNs and the bi-directional flow of current from various sources to the loads. To improve the system’s situational awareness, the grid dynamics of the entire DER integration processes must be carefully monitored using synchronized high-resolution real-time measurement data from physical devices installed in the DN. μPMUs have been introduced into the DN to help with this. In comparison to traditional measurement devices, μPMUs can measure voltage, current, and their phasors, in addition to frequency and rate of frequency change (ROCOF). In this study, an approach to generating realistic event data for a real utility DN utilizing strategically installed μPMUs is proposed. The method employs an IEEE 34 test feeder with 12 μPMUs installed in strategic locations to generate real-time events-based realistic μPMU data for various situational awareness applications in an unbalanced DN. The node voltages and line currents were used to analyze the various no-fault and fault events. The author generated the data as part of his PhD research project, utilizing his real-time utility grid operation experience to be used for various situational awareness and fault location studies in a real unbalanced DN. The DN was modeled in DIgSILENT PowerFactory (DP) software. The generated realistic μPMU data can be utilized for developing data-driven algorithms for different event-detection, classification and section-identification research works.