Reactive Power Optimization Based on CAPSO Algorithm

Reactive power optimization is a typical high-dimensional, nonlinear, discontinuous problem. Particle swarm optimization (PSO) algorithm has high convergence speed and is easy to implement, but it also exists precocious phenomenon, In the later stage of optimization, the improvement is not good and is easy to be trapped in local minima. To overcome this shortcoming, this article will introduce cloud model into adaptive particle swarm optimization (APSO), so, It is to divide the particles into two parts, close to or away from the best particle, the former particles weight of inertia will be adaptively adjusted by X-condition generator of cloud model. The article proposes the cloud adaptive particle swarm optimization (CAPSO) according to the theory. Considering minimum network loss as the objective function, make the simulation in standard IEEE14 node system. The results show that the improved CAPSO algorithm can achieve a better global optimal solution.