Based on Improvement Immunity Algorithm Electrical Power System Optimal Power Flow Computation

This study presents an enhanced artificial immune algorithm specifically developed to address optimal power flow (OPF) problems in power systems. The algorithm is inspired by the immunological mechanisms of human and higher vertebrate immune systems, where the objective function and inequality constraints are conceptualized as antigens, while potential solutions within the search space are represented as antibodies. Solution evaluation and selection are performed based on affinity measures derived from antigen-antibody and antibody-antibody interactions. To maintain the comprehensive search capabilities of the foundational immune algorithm and ensure theoretical diversity, the concept of vector distance is incorporated into the algorithm's design. The effectiveness of the proposed method is validated through computational experiments conducted on the IEEE 30-bus test system, and a comparative analysis with conventional evolutionary algorithms, specifically genetic algorithms, indicates that the proposed algorithm exhibits superior global search capabilities and enhanced convergence properties.