AI-based Coordination and Optimal Power Sharing of Grid Forming Inverters

Mismatched line impedances between inverters in a power electronics dominated grid (PEDG) greatly impacts the power sharing between them. This uncontrolled power sharing may result in overloading of nearby grid forming inverters (GFMI)s, which in the long run may pose a threat to the reliability and resiliency of overall PEDG. This article proposes a control strategy to minimize the impact of mismatches in the line impedances to achieve optimum active power sharing in a cluster of inverter-based resources (IBRs). This is attained by determining the adjustments in GFMI’s primary control loop and indirectly adjusting the amplitude of its PCC voltage. The proposed regulated power controller (RPC) dynamically adjusts the GFMIs power output by changing their point of common coupling (PCC) voltage reference set point based on the calculated virtual impedance (VI) values. More specifically, the load changing node (LCN) detector monitors the system currents to determine the location of any inverter or load and RPC estimates the desired VI values required for attaining equal power sharing in real-time. Furthermore, this article proposes an artificial intelligence (AI)-driven approach for GFMIs to enable autonomous power set-points adjustments during load disruptions which is a significant advancement in energy management technology for a network comprising of $100 \%$ GFMI based sources. Multiple case studies are conducted to verify the practicality, effectiveness, and resilience of the suggested strategy.