The application discloses a kind of wind farm multi-objective
yaw control methods considering
power load comprehensive benefits, belong to
wind power generation technical field.The wind farm whole
tail flow modeling of
yaw state is considered by analyzing
tail flow model, the inflow data of each wind
turbine in wind farm is determined, and the total power and average life of wind farm are quickly and accurately predicted by combining wind
turbine power,
thrust coefficient curve and S-N curve of transition section
pipe node.Single wind
turbine power optimization and wind turbine fatigue life optimization with power constraint are integrated to establish a two-stage multi-objective control
optimization system, and by building a Bayesian
machine learning network, the optimal
yaw combination of each stage is located quickly by using efficient and accurate power and life prediction data.The application can accurately and efficiently provide the optimal yaw strategy considering
power load comprehensive benefits according to real-time
wind speed data, while meeting the power generation demand of wind farm, the load is maximized to extend the service life of wind turbine.