Optimization of Economic Distribution in Electric Power Systems Utilizing an Adaptive Immune Cloning Approach

In order to establish a balanced distribution of power and minimize generation costs within the power system, we propose an adaptive immune clone algorithm grounded in a mathematical model for economic load allocation. This algorithm incorporates concepts such as scaling transformation, elite clone mutation, heuristic clone crossover, and clone selection, which theoretically improve solution diversity. Simulations conducted on a power system consisting of three machines and six buses produced results that validate the algorithm’s effectiveness. When compared to genetic algorithms, the enhanced algorithm demonstrates superior global search capabilities, a diminished likelihood of converging on local optima, and a quicker convergence rate.