Optimizing the power outputs to all the thermal generators in the power system while solving the Generation Fuel Cost Optimization problem using Weighted Average Algorithm

This study presents the application of the recently proposed meta-heuristic algorithm, the Weighted Average Algorithm (WAA), to optimize the allocation of power output for a 20-thermal-generator power system, considering power losses in solving the Generation Fuel Cost Optimization (GFCO) problem. The optimization of the power output of all thermal generators aims to minimize the total generation fuel cost. A 100MW solar power plant and a 100MW wind power plant are integrated into the given system to support optimization, reducing the generation burden on all existing generators and lowering emissions. The performance of WAA is evaluated by comparing all results obtained by the algorithm with those of the Golf optimization algorithm (GOA) across different criteria. The comparison results show that for each hour of operation, WAA can save 22.955 $ on the lowest total generation fuel cost (LGFC), 46.851 $ on the average total generation fuel cost (AGFC), and 75.760 $ on the maximum total generation fuel cost (MGFC). Moreover, WAA offers greater stability and faster convergence than GOA throughout the optimization process. All these results and superiority indicate that WAA is a highly effective search methods and the algorithm is highly considered utilizing to solve such the