Study On Short-term Wind Speed Forecasting Method Of Wind Farm Based On Gauss Process Regression

As a pollution-free renewable energy,wind energy has attracted wide attention from all over the world.Wind power is one of the most important technologies to use wind energy nowadays,but the randomness of strong wind speed leads to intermittent wind power.Large-scale wind power access to the grid will have an adverse impact on the safety and stability of the power system.The accurate prediction of wind speed will help the power grid dispatching department to adjust the scheduling plan in time and improve the safety and stability of the power system.Therefore,it is of great significance to predict the wind speed of the wind farm.In this thesis,the short-term wind speed prediction method of wind farm is studied in depth.Aiming at the shortcomings of the traditional Gauss process regression model using conjugate gradient method to optimize the super parameters,an improved Gauss process regression model is proposed,that is,the quantum particle swarm algorithm instead of the conjugate gradient method is used to optimize the super parameters.The improved model is used to predict the short-term wind speed of the wind farm.The simulation results show that the prediction accuracy of the improved model is improved.In view of the non-stationary wind speed,a hybrid model prediction method based on variational mode decomposition and improved Gauss process regression is proposed.The method first decomposes the wind speed by the variational mode decomposition,and then sets up an improved Gauss process regression model for each component after decomposition and predicts the predicted values of each component to get the forecast value of wind speed.In order to better compare the merits and demerits of the model,a hybrid model based on empirical mode decomposition and improved Gauss process regression is established.The simulation results and the error analysis show that the hybrid model based on the variational mode decomposition and the improved Gauss process regression model can effectively improve the accuracy of wind speed prediction,which proves the feasibility of the prediction method and provides a new idea for improving the accuracy of wind speed prediction.