Adaptive memory-polarization for improved performance of mho relay in presence of Grid-Following PV

Abstract

This paper addresses the challenges posed by high Grid-Following (GFL) Photovoltaic (PV) penetration on the dynamic performance of memory-polarized mho relays, crucial for close-in fault protection in power systems. Traditional memory-polarized mho relays, designed for synchronous generator-dominated systems, utilize a scalar weight to dynamically expand their mho characteristics based on memory voltage, enhancing resistive reach. However, the unique transient behavior of Inverter-Based Resources (IBRs) like GFL PV during faults can disrupt this mechanism, compromising relay reliability. To overcome this limitation, this research introduces a novel algorithm that employs a complex weight parameter in the memory polarization process, replacing the conventional scalar approach. This complex weight allows for more precise and adaptable control of the mho characteristic’s dynamic expansion, enabling the relay to better respond to the complex voltage and current transients introduced by GFL PV. The study investigates the dynamic expansion of the mho element’s maximum diameter (dmax) and memory vector angle (θm) under various fault scenarios (three-phase, single-line-to-ground, and line-to-line) to evaluate the algorithm’s effectiveness. The proposed complex weight algorithm is validated across diverse fault types, varying complex weight factors, and different fault resistances, considering GFL PV generators with reactive power priority and IEEE Standard 2800–2022 compliant Low/High Voltage Ride-Through capabilities. The results demonstrate significantly enhanced reliability and stability of memory-polarized mho relays in systems with high GFL PV penetration, showcasing the superior performance of the complex weight approach.