Research On Reactive Power Optimization In Power Grid Containing Wind Farm In Baotou

In recent years, wind energy as a clean and renewable energy, due to its superior characteristics, getting more and more attention and application. Wind farm power systems will change the original structure and flow distribution system, and have influence on the system loss and voltage stability to some extent. Therefore, if the reliability of Wind farm grid and stable operation is needed, reactive power optimization of the wind power system is necessary.Firstly, development of wind power technology and the research status of wind power; summary discusses the impact on aspects of system operation and planning of the wind farms into the electric power system. Then study the asynchronous model and operating characteristics of wind turbines, wind farms come to the equivalent model. Power system containing wind farms load flow calculation chart is made, and Batou power system containing Bayin wind farms flow calculation.Then, improved particle swarm optimization algorithm is introduced. PSO algorithm generation, the basic principles and calculation process is introduced; then gives an improved particle swarm optimization method and calculation processes; a numerical example to verify the dynamic collaborative learning factor inertia weight particle swarm algorithm is superior in performance.Finally the principle of reactive power optimization algorithm, the performance of several common reactive compensation devices are introduced; active power loss to a minimum of the objective function, including wind farm reactive power optimization model. Batou power system containing Bayin wind farms, the use of dynamic collaborative learning factor inertia weight particle swarm optimization algorithm to calculate reactive power. In the case of the final volume and location of reactive power compensation device uncertain, get the optimal reactive power compensation scheme.