Analysis And Prediction Of Wind Speed And Power In Large Wind Farms

We are faced with the depletion of fossil fuels and the impact on human life.people are increasingly aware of the importance of accelerating the development and utilization of new energy sources.New energy sources include wind,solar,nuclear,biomass,tidal,geothermal and other energy sources.Wind energy,as one of the most promising natural gas and no renewable energy sources,plays an important role in today’s energy shortages and in times of pollution.Based on the premise of wind energy,this paper analyzes the fluctuation characteristics,wind data and power forecast of wind power.The fluctuation characteristics of wind power are analyzed.A definition of the fluctuation characteristic-the fluctuation coefficient is proposed based on the ratio of the rate of change and the ratio of the first order differential sequence to the total installed capacity.Studies have shown that with the increase in the number of grid units.Volatility weakened.Then,through the analysis of the pair and the analysis,the total output of the wind field is more similar to that of the regional convergence,and the difference is less and less.The same degree of output of the wind field and the convergence of the regional convergence did not change with the increase of the time scale,but the overall form was consistent.The wind data in wind power wind power curve modeling are analyzed.According to the measured wind power data of the wind farm,the corresponding scatter plot is drawn.Around the standard wind speed power curve up and down,put forward a portable viscous interval.The scatter in this interval is the valid data;the continuous scatter outside this interval is the anomaly data.Use this sticky interval to effectively remove the wind data.A wind power forecasting method based on Kalman filter and support vector machine is proposed.By analyzing the wind power series,the ARIMA model is used as the equation of Kalman filter.Then the SVM prediction is used to predict the equation,and the Kalman filter is used to realize the fusion multi-step prediction.Finally,a concrete example is given,and the evaluation accuracy is evaluated by the evaluation index of the National Energy Bureau.It can be seen from the prediction results that the prediction error can be canceled in the fusion prediction algorithm,which reduces the error accumulation and improves the prediction accuracy.Finally,the platform of ultra short-term power forecasting system of wind farm is introduced.The platform can achieve data management,wind power prediction,error analysis.