Grey Wolf Optimization-Based Energy Management of BESS for Seamless Grid-Following Operation in PV-Integrated Microgrids

The large-scale adoption of Photo Voltaic (PV) generation in today’s microgrids poses substantial operational challenges, given the intermittent and uncertain nature of energy resources. These challenges result in power imbalances, voltage and frequency fluctuations, and degraded system resilience to grid disturbances. This paper proposes an intelligent energy management framework and control based on Grey Wolf Optimization for microgrids that incorporate battery energy storage systems. The proposed work effectively synchronizes the real-time PV generation, load demand, battery state of charge, and grid availability to attain adaptive power management in both grid-connected and island conditions. Differently from traditional control methods, this method allows seamless transition from Grid-Following (GFL) to Grid-Forming mode (GFM), and provides active and reactive power regulation, adaptive solar power curtailment, frequency stabilization, grid re-synchronization, and power imbalance compensation. This results in the effective control of the BESS, and thus, dynamic energy balancing, better utilization of renewable energy and voltage and frequency stability in transient operating conditions. The proposed control mechanism has been validated through extensive MATLAB simulations across various operational scenarios, which included changes in irradiance, fluctuations in load, renewable power containment, grid disconnection, island operation, and reconnection to the utility grid. Results from the simulations indicate that the GWO-based framework provides a quicker dynamic response, minimizes frequency deviations, increases renewable utilization, and exhibits a greater operational resilience when compared to conventional methods. The comparative simulation results demonstrate that the proposed GWO-based framework achieves a settling time, peak overshoot, solar-curtailment reduction, renewable energy utilization, and energy-harvest efficiency that outperforms the considered benchmark approaches under the investigated operating conditions. Additionally, the proposed strategy significantly improves the precision of energy sharing and ensures reliable operation of the microgrid (µ-grid) during more transitions and disturbances in the grid. These findings show that the GWO-based BESS energy management framework is an effective, robust, and scalable operation for improving the flexibility, stability, and reliability of next-generation PV-integrated microgrids characterized by high levels of renewable energy penetration.