A Dynamic Self-Healing System for Harmonic and Unbalanced Smart Microgrids Considering Renewable Energy Intermittency

This paper presents a dynamic, self-healing system for smart microgrids that addresses the harmonic distortion, voltage imbalance, and Renewable Energy Source (RES) intermittency using an Improved Whale Optimization Algorithm (IWOA). The IWOA simultaneously optimizes four equally weighted objectives — active power losses, voltage deviation, Total Harmonic Distortion (THD), and Phase Voltage Unbalance Rate (PVUR) — thereby overcoming the limitations of the conventional methods. An enhanced IWOA movement mechanism prevents the premature convergence in complex, unbalanced harmonic scenarios. When validated on a modified IEEE 33-bus system under diverse fault, load, and generation conditions, with realistic RES and harmonic modeling, the IWOA was found to significantly improve THD and PVUR compared to the conventional approaches. Furthermore, the IWOA outperforms the standard Whale Optimization Algorithm (WOA) by converging faster and providing a superior final solution, thus demonstrating its effectiveness in enhancing the microgrid resilience and power quality.