摘要
针对某1000 MW超超临界机组,建立了具有较高精度和良好动态性能、考虑机组回热循环特性的机组负荷及主汽压力神经网络预测模型.在此基础上,提出了一种协调系统综合智能预测优化控制方法.该方法利用负荷及主汽压力预测模型在机组变负荷过程中分别对除氧器水位调门开度、汽轮机调门开度及燃料量指令进行实时优化,改善协调控制效果.借助1 000 MW超超临界机组仿真机,进行了详细的协调优化控制仿真试验.结果表明:该方法可有效提高机组动态过程负荷的响应速度和调节精度,大大减小变负荷过程中主汽压力的控制偏差,具有较好的工程实用性.
To study the flow mechanism of a wind farm based on yawed wind turbine using wake deflection control strategy by multi-scale simulation,two full-scale 5MW wind turbines laid in line were simulated in the atmospheric boundary layer environment through unsteady CFD method.Results show that the total power generation of wind farm can be increased by intentionally yawing the upstream wind turbine.According to the analysis of velocity field,the wake of upstream wind turbine would deform when the turbine is placed yawingly,and according to the analysis of vorticity field,a counter-rotating vortex pair would be observed as the yawed wake propagates,which would lead to the macroscopic wake deflection.However,the wake deviation effect is significant just at the hub height.The distorted wake still spreads its low speed regions to other areas.
出处
《动力工程学报》
CAS
CSCD
北大核心
2017年第8期640-648,共9页
Journal of Chinese Society of Power Engineering
基金
国家自然科学基金资助项目(61174111)
