Integration of photovoltaic (PV) systems into microgrids has gained significant attention due to its potential to enhance energy sustainability and resilience. However, PV microgrids face challenges such as islanding, posing safety risks and reliability concerns. This study proposes a comprehensive approach to address islanding in PV microgrids by employing advanced control strategies and optimization algorithms. The detection of islanding events is crucial for maintaining grid stability and ensuring the safety of utility workers. In this research, the Change of Frequency with respect to Change in Reactive Power (COF-CIQ) method is utilized for islanding detection due to its effectiveness in identifying islanding occurrences accurately and promptly. Furthermore, optimal control of PV microgrids is essential for maximizing energy efficiency and grid stability. This study explores the application of optimal controllers to regulate the operation of PV systems within microgrids. Specifically, the effectiveness of proportional-integral (PI) and fractional-proportional-integral (FOPI) controllers are tested in the performance of PV microgrid. To enhance the efficiency of the optimization process, three nature-inspired metaheuristic algorithms, namely Whale Optimization Algorithm (WOA), Grey Wolf Optimization (GWO), and Sine Cosine Algorithm (SCA), are employed for tuning the parameters of the controllers. These algorithms are known for their ability to find near-optimal solutions in complex optimization problem.