Frequency regulation is critical for maintaining balance between supply and demand in interconnected power systems, ensuring grid stability and preventing disruptions. This becomes increasingly important with the integration of renewable energy sources, such as photovoltaic (PV) units, which introduce variability and complexity into power systems. In this regards, this study presents a novel approach to frequency regulation in a two-area interconnected power system comprising thermal and PV units. A Proportional-Integral (PI) controller is designed, and its parameters are optimally tuned using the flood algorithm (FLA). The innovative use of the FLA ensures robust performance and efficient frequency stabilization under varying operational conditions. The implementation details of the FLA-tuned PI controller are provided, and its performance is rigorously compared with PI controllers tuned using several state-of-the-art optimization techniques. These include sea horse optimization, salp swarm algorithm, whale optimization algorithm, shuffled frog-leaping algorithm, and firefly algorithm. The comparative analysis is based on numerical results of performance metrics, demonstrating the robustness and effectiveness of each tuning method. Performance indices, including maximum overshoot, settling time and steady-state error are used to evaluate the robustness of the designed PI controllers. The frequency variations for the two-area thermal and PV power system are analyzed post-optimization, highlighting the superiority of the FLA-based PI controller in maintaining system stability under various operational conditions. The proposed FLA-based PI controller achieved a reduction in maximum overshoot by 28.3 %, a decrease in settling time by 23.4 %, and an improvement in steady-state error by 15.7 % compared to the next best-performing optimization method. These results demonstrate the significant advantages of the FLA in optimizing frequency regulation.