Distribution Network Optimal Planning Based on Clouding Adaptive Ant Colony Algorithm

An improved ant algorithm based on cloud model is proposed, and it's applied to the power distribution planning. In view of the main disadvantage of being inclined to local convergence and being slow of the convergence rapidity of traditional ant algorithm, the pheromone decay coefficient and the pheromone intensity are qualitatively controlled and dynamic selected in this paper by making use of the uncertain qualitative association rule inference based on cloud model, in view of the advantage of uncertain converting qualitative concept to quantitative expression of cloud model. The algorithm overcomes the shortcoming of being inclined to local convergence and being slow of the convergence rapidity of traditional ant algorithm. Numerical simulation results of power distribution planning demonstrate the efficiency of the algorithm.