【摘要】 随着大型风电场的快速发展,减小尾流效应造成的风电场能量损失成为研究热点之一。针对风电场实际运行中的风速变化以及尾流延时问题,基于尾流延时模型,建立考虑时间变量的风电场功率预测模型。以风电场输出功率最大化为目标,设计了非线性预测控制器,该控制器采用非线性预测模型,并采用PSO算法对预测时域内的性能指标进行优化,得到各台风机的控制值。基于Sim Wind Farm软件对该控制策略进行验证,并与传统风电场控制策略进行仿真比较,结果表明,这种新控制策略可以有效提升风电场的总体功率。更多还原

【Abstract】 As the fast develepment of large wind farms, reducing the power loss caused by wake effects has become one of the hottest topic today. To deal with the wind variation and wake delay,a wind farm power prediction model which includes the time variables is built based on wake delay model. A nonlinear model predictive controller is designed to boost the capture power of the wind farm. This controller adopts nonlinear predictive model and particle swarm optimization(PSO)algorithm to optimize the control variables in a predition horizon and obtain the control settings of each wind turbine. This paper uses Sim Wind Farm platform to test the proposed strategy and the traditional wind farm control strategies. Simulation results show that the proposed strategy can improved the total wind farm power effectively.更多还原