Research On Reactive Power Optimization Of Power System With Doubly Fed Wind Farm

Energy is the basic driving force of a country's development,in the face of the growing shortage of fossil energy in today's society,declining air quality,present situation of increasingly serious haze problems,all countries will focus on the development of new energy.The new energy sources of grid connected power generation mainly include solar energy,wind energy,water power,nuclear energy,bio energy,etc.And wind energy has become the main force of the development of new energy because of its wide range of existence and high level of development and utilization.By the end of 2010,the cumulative installed capacity of China's wind power has leapt to the world's first.Wind power generation has shown a good development prospect and application prospect.With the continuous development of wind power research and development,wind power will provide more high-quality power for the national economic development.Double-fed induction generator is widely used in Chinese wind farms.so the dissertation selects the double fed induction wind generator representative as the research object,analyzes the basic types of doubly fed asynchronous wind generator and output characteristics,and using mathematical analysis method established mathematical model of doubly fed asynchronous wind generator and a dynamic mathematical model on the basis of this,the established trend of power system with doubly fed asynchronous wind generator mathematical model,expounds the active power of doubly fed asynchronous wind generator,the mathematical relationship between electric voltage and reactive power,thereby establishing the power system with doubly fed induction wind power flow calculation model.Secondly,the dissertation combines the advantages of particle swarm optimization algorithm and harmony search algorithm.The harmony search algorithm can effectively jump out of the local optimum and combine the characteristics of the particle swarm algorithm with the direction of convergence.The harmony of the elements in the library as the particles,each iteration,using particle swarm algorithm optimization of memory elements in the harmony memory of the harmony memory elements will then be optimized into improved harmony search algorithm.This dissertation selects four common multi-objective function convergence test to test the performance of optimization algorithm,and the convergence test of the intelligent common algorithm,results show that the improved algorithm has better convergence accuracy and convergence speed.Finally,the reactive power compensation problem of the wind farm connected to the power system with doubly fed induction generator(DFIG)is studied.A reactive power optimization model with minimum active power loss and minimum voltage deviation is proposed,using the above improved particle swarm optimization harmony search algorithm for power system including wind farms for research reactive power optimization.The improved particle swarm optimization and harmony search algorithm proposed in this dissertation is applied to the IEEE30 power system with wind farm to optimize the reactive power,and the particle swarm algorithm and non-dominated sorting genetic algorithm for reactive power optimization results of the algorithm are compared.The experimental results show that the improved particle swarm optimization and search algorithm has better convergence precision and fast convergence speed,after the use of the algorithm in power system reactive power optimization,the system of the node voltage has been improved to some extent,and further reduces the power loss value,ability to accept with the increasing of wind power system of power quality and power system of wind power,to promote the further development of wind power generation.