降低风电场出力波动性有利于促进电网友好运行,而尾流优化控制是降低整场出力波动的重要措施.现有尾流优化控制大都基于稳态模型,却忽略尾流动态迟延特性.但尾流迟延在风速不确定性基础上会进一步增加风电场出力的波动性.为此,该文基于稳态尾流模型辅以迟延计算,构建风电场准稳态尾流模型以同时兼顾尾流干涉作用与动态迟延特性.在此基础上,提出一种考虑迟延的模型预测平稳控制方法(predictive control considering delay,MPC-D),以指令跟踪与功率波动最小为目标协调各机组出力.最后,在WFSim上构建含33台机组的风电场仿真模型,并基于此分析尾流迟延对风电机组以及整场运行性能影响.结果表明,所建准稳态尾流模型能同时模拟尾流速度损失、机组功率迟延和整场功率阶梯变化等特性.并且由MPC-D所得整场出力较基于稳态模型的控制方法平均相对误差、均方根误差以及滑动均方根误差均得到改善,同时能防止机组桨距角频繁动作.
Wake Control of Wind Farm Based on Model Predictive Control Considering Propagation Delay
Alleviating power fluctuation of wind farms is conducive to promoting the friendly operation of the grid,and wake control is one of the most effective measures to reduce the power fluctuation.Most existing studies are carried out based on steady wake model without considering the delay characteristics of wakes.However,wake delay can lead to the volatility of wind farm power in addition to wind uncertainty.Therefore,a quasi-steady wake model of wind farms is constructed to account for both wake interference and the delay characteristic by integrating the delay into the steady wake model.On this basis,a model predictive control considering delay(MPC-D)is proposed,and wind turbines are coordinated with the goal of command tracking and power fluctuation minimization.Finally,a medium-fidelity simulation model of a wind farm with 33 turbines is constructed on WFSim,and the impact of wake delay on the performance of wind turbines and the wind farm is analyzed.The results show that the proposed quasi-steady wake model can simulate the wake velocity loss,power delay of the turbines and power step change of the wind farm simultaneously.Moreover,the average relative error,root mean square error and sliding root mean square error of the wind farm power obtained by MPC-D are all smaller compared with those of the steady model based control.Meanwhile,MPC-D can further prevent frequent regulation of pitch angle of turbines.
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