Evaluation of Abandoned Wind Power by Neural Network Method

Wind farm operation is characterized by large scale, fast and disorderly, the construction of grid structure is not complete, the fast adjustment of power supply in the power grid does not match to others, the objective laws of electric power system and uncontrollable and intermittent of wind power, and adjustable power supply capacity constraints in power grid, all of them cause the consumptive ability of wind power grid, which leads to more and more abandoned wind. This paper studies the tower neural network method, according to different height wind speed and wind direction data of historical wind tower measuring, combining with the fan power of historical observation data of wind farm, and building the neural network model, then the sample data will be input to the neural network model which has built to get theoretical power fan and abandoned wind power. By comparing the wind tower method, neural network method, model machine method with area integral method calculate abandoned wind power data, evaluate the effect that based on abandoned wind power tower evaluation model of neural network method in low wind speed has a good reference value, relatively close to the measured wind speed.