A novel hybrid renewable energy microgrid optimization algorithm supported with wind, solar, and backup diesel generators is suggested in this research work. The proposed Dual Predator Optimization (DPO) algorithm combines the Whale Optimization Algorithm (WOA), and Grey Wolf Optimizer (GWO). This algorithm integrates with a hybrid microgrid to optimize the use of renewable resources, reduce reliance on fossil fuel, and increase the cost-effectiveness by adjusting these parameters over time. The DPO is flexible and more suitable for hybrid energy management taking into consideration the exploration (exploitation) of system-level energy behaviors simultaneously in large-scale problems. The results show that the DPO is efficient in handling hybrid systems by significantly reducing electricity costs and decreasing probabilities of non-supply. It was determined that in comparison to the current GWO and WOA, the Cost of Energy (COE) of the proposed DPO algorithm is decreased to an average of 20%, while Loss of Power Supply Probability (LPSP) increases to an average of 7.5%.