Enhancing Auto Recloser Insights with PMU Data
Raja Shekar Nalluri, Bhanu Ganesh Garita, Pradeep Kumar Yemula, Shiva Kumar Muta, Chandra Sekhar Marazoni, Natarai Pathri · 2024
Phasor Measurement Unit (PMU) data have revolutionized system operations significantly with improvement in the decision-making process during power restoration by reducing dependency on traditional field communications, which often led to delays. Even with a limited number of PMUs, real-time event detection has become possible. The paper presents a data-driven analytical methodology which serves as a First Information Report (FIR) by generating a report within one minute of the occurrence of fault. This is in-house developed analytics at SLDC of Telangana State, which provides fault signature analysis for the system operator. Additionally, the FIR supplements the sequence of events(SoE) and disturbance recorder(DR) reports which are prepared later. Four real-time case studies are prepared to focus on Auto-Recloser(AR) operations during single line-to-ground (SLG) faults. The primary objective is to demonstrate the effectiveness of the data driven analytics in both near real-time and offline reporting, offering timely insights well ahead of traditional DR and SoE systems.