Bio-Inspired Optimization for Frequency Stability in Microgrids with Electric Vehicle Support: Towards Sustainability of Renewable Energy Systems

The increasing integration of renewable energy sources (RES) such as solar and wind into modern microgrid systems has posed significant challenges for maintaining frequency stability, primarily due to their inherent variability and unpredictability. Conventional load frequency control (LFC) strategies, which depend on fixed system inertia and static tuning, often fail to cope with these highly dynamic conditions. In response, this study introduces an innovative hybrid control strategy that merges the Wave Search Algorithm (WSA) with the Balloon Effect (BE) model. This synergy is designed to support adaptive LFC in a multi-source microgrid comprising diesel generators, solar PV, and bi-directional electric vehicles (EVs). The WSA facilitates a balanced global and local search behavior, while the BE component enables structural adjustments in real-time by leveraging transfer function variations within the system. This integrated approach adaptively calibrates an integral controller to suppress frequency deviations and enhance overall system robustness. Through simulation of three realistic disturbance scenarios—namely, a sudden increase in load, an abrupt reduction in PV output, and a fluctuating load profile with EV contribution—the WSA+BE controller demonstrated clear superiority over classical techniques and alternative optimizers, including Jaya, SCO, GTO, and standalone WSA. Results show enhanced damping characteristics, quicker stabilization, and improved adaptability across all cases, confirming the proposed method's potential for reliable frequency control in RES-dominated microgrids.