中文摘要：

大规模、高集中度风电接入系统,增大了风电爬坡风险。文中分析了风电爬坡特性,以及风机本身的功率控制对爬坡特性的影响。在现有风机平滑控制的基础上,提出一种风机爬坡功率的有限度控制策略。该策略引入预测控制理论,通过预测、在线优化、反馈控制3个模块的配合,优化风机参考功率,使风机有效跟踪参考功率。预测模块采用动态神经网络超短期预测模型得到风功率预测曲线,在线优化模块根据建立的爬坡率和弃风量最小优化模型,通过二次规划算法快速获得优化出力曲线,反馈控制模块产生变速变桨距协调控制规律。仿真结果表明,该控制策略实现了平滑风机出力、增大风机发电量及改善转速特性的目标。

英文摘要：

Integrated wind power of large scale and high concentration will increase the risk of wind ramping.This paper analyzes the wind ramping characteristics and the effect of wind turbine power control on wind ramping.Based on the existing wind turbine smooth control,a finite control strategy for wind turbine ramping power is proposed.By coordination between the prediction module,online optimization module and feedback control module,it is enabled to optimize the reference power, improve the ability of tracking the reference power and smooth the output power of wind turbines.Based on the ultra-short-term wind speed forecasting model,the dynamic neural network is used to get the forecasting wind power curve.In the optimization module,the optimization model of minimum ramping rate and minimum abandoned power is used to get the optimal output power curve quickly by the quadratic programming algorithm.The specific variable-speed variable-pitch coordinated control law is generated in the feedback control module.The simulation results show that the proposed strategy can realize the targets of smoothing the output power, increasing the generating capacity and improving the rotor speed characteristics of wind turbines.