Single-Objective Optimal Power Flow Using Artificial Hummingbird Algorithm

This study introduces a novel artificial hummingbird algorithm (AHA) for addressing the optimal power flow (OPF) problem. The objectives of this OPF challenge are to minimize total generation costs, emissions, and active power losses. A penalty-based constraint handling method is used to address various restrictions of the OPF problem. The suggested algorithm has undergone testing on the standard IEEE 30-bus test system. The results obtained with the artificial hummingbird algorithm (AHA) are contrasted with those from the grey wolf optimisation (GWO) method. The comparison demonstrates the superiority of the artificial hummingbird algorithm (AHA) relative to the GWO algorithm.