A Novel Horse Herd Optimization Algorithm for Optimal Economic Dispatch in Sulbagsel Electricity System

This study investigates the optimization of generation costs for thermal power plants in the South Sulawesi (Sulbagsel) electricity system in Indonesia. The novel swarm intelligence method, the horse herding optimization algorithm (HHOA), is inspired by the social behavior of horses within herds across different age groups. HHOA is a new metaheuristic algorithm recognized for its high efficiency in exploration and exploitation. The primary objective of the HHOA method is to minimize generation costs. To evaluate the effectiveness of the proposed method, similar swarm intelligence techniques, namely particle swarm optimization (PSO) and whale optimization algorithm (WOA), are also employed. Statistical analysis demonstrates that HHOA offers superior exploration and exploitation capabilities, along with strong consistency and accuracy. The optimization results for thermal generation costs during mid-day peak loads indicate that the PSO method reduces costs by 23.78%, the WOA method by 23.02%, while the HHOA-based method achieves a reduction of 24.23%.