Optimal Unit Scheduling using Modified Ant Lion Optimization Algorithm for Secure Operation

This article presents the solution for the OPF problem using Modified Ant Lion Optimization (MALO) based on a chaotic map to enhance its initial random walk, leading to better solutions. The MALO algorithm minimizes cost by computing the generators' real output power and finding the best OPF solution. This analysis uses a standard 24-hour data of IEEE 14 bus test system for OPF solution. Further, the results obtained from the proposed MALO algorithm have been compared with particle swarm optimization and teaching learning-based optimization algorithm. Results show that the proposed MALO algorithm is flexible, more accurate, and applicable for the standard IEEE 14 bus test system.