Research On Reactive Power Optimization Based On Hybrid Intelligent Algorithm And Its Application

The optimization and adjustment of power system can promote economic and smooth development of the electric power system,the reactive power optimization can guarantee the safety of power system effectively,It plays a very important role in the process of improving power quality and increasing economic benefits.Reactive power optimization of power system should be able to reduce the active power loss,and improve the voltage quality and increase stability of power system.Great victory has been achieved with the particle swarm algorithm in solving power system optimization problems.However,the particle swarm algorithm is easy to fall into the local optima.which limits its practical effect.A new optimization algorithm of power system is proposed,namely the filled function of particle swarm algorithm,and the particle swarm algorithm combined with the filling function can overcome the shortcoming of particle swarm algorithm effectively.It is easy to achieve the purpose of global optimization,and the optimization problem is solved more effectively.Firstly,the background of reactive power optimization is introduced,and the present situation of domestic and international researches on algorithms involved in reactive power optimization are summarized in this thesis,Then,the mathematical model of the objective function of reactive power optimization are given based on the penalty function,and the particle swarm algorithm and the filled function method in the hybrid algorithm are introduced.Next,the reactive power optimization is simulated and calculated with using the MATLAB tool in the research.With IEEE14 node system as an example to verify the effectiveness,thestandard particle swarm optimization algorithm for the optimization results has been analyzed.Compared with filled function of particle swarm algorithm,the simulation results show that the hybrid method of filled function of particle swarm algorithm has good ability of optimization to control the node voltage and reduce the net loss.In view of the defects of the filled function particle swarm optimization algorithm,it is improved to enhance the global searching capability of particle swarm optimization algorithm and the computation speed is obviously increased.Taking the IEEE30 node system as an example,the reactive power optimization simulation is carried out.At the same time,the power system with wind farm is simulated to verify the extensive application of the algorithm.The simulation results show that the hybrid algorithm proposed is reliable and effective.