Improved Whale Optimization Algorithm for Dynamic Optimal Power Flow with Renewable Energy Penetration

This paper proposes the Improved Whale Optimization Algorithm (IWOA) method to solve the Dynamic Optimal Power Flow (DOPF) problem in Renewable Energy Systems (RES), taking into account the influence of Energy Storage (ES). The convergence performance of the Whale Optimization Algorithm (WOA) algorithm is enhanced by incorporating Fuzzy Logic Control (FLC) in the exploration phase. The FLC assists the IWOA agents in finding the optimal weight values more quickly. The weights generated by the IWOA method are dynamic, continuously adjusting based on the deviation or error in the agents' movement during each iteration, which is essential for locating the global optimum. This paper primarily uses FLC to determine the weights, accelerating the IWOA optimization process. The effectiveness of this method is tested on the IEEE 30-bus system with the integration of PV and ES. The findings of this study demonstrate the superiority of the IWOA method over the WOA algorithm, resulting in a lower generation cost of $25/day and a faster convergence time.