随机模拟粒子群算法在风电场无功补偿中的应用

在风电机组机端装设无功补偿装置有利于改善风电对系统电压质量造成的负面影响。该文针对风电出力的随机性及负荷和系统电压的变化，提出了求最优无功补偿装置容量的机会约束规划模型，并利用随机模拟的粒子群算法求解。该模型以费用最小为目标函数，考虑了风速的概率分布、风电机组本身的有功和无功特性以及含风电场的潮流处理方法等。通过分析某配电网风电场无功、电压、功率因数的变化情况，利用该文方法进行无功补偿优化，结果表明模型与算法的有效性。

Application of Stochastic Simulation's Particle Swarm Algorithm in the Compensation of Reactive Power for Wind Farms

It is helpful to install reactive compensation equipment at wind turbine terminals to improve the bad influence of wind power on the voltage quality of power system. Because of the random feature of wind power and change variation of the load and system's voltage, a mathematical model based on chance constrained programming (CCP) is given. And an algorithm of stochastic simulation's particle swarm optimization is put forward to figure out the reactive power compensation capacity. The model's objective function is to minimize cost under consideration of probability distribution of wind speed, the characteristic of active and reactive power of wind turbines, the way of power flow calculation in wind power integrated system, and so on. By analyzing the variation of reactive power, voltage and power factor of wind farm and utilizing the given way to optimize reactive power compensation in a distribution network, the model and algorithm are proved effective.