Short-term Wind Power Prediction And Its Impact On Load Forecasting

Short-term wind power forecasting is very important to the operation of grid-connected wind power generation systems. This paper proposed a method based on the characteristic of wind speed series. At first, the trends and oscillation cycle components was extracted from wind speed series by singular spectrum analysis. Based on singular spectrum analysis method the sample series are reconstructed using the quasi-periodic signal components. Secondly, considering the impact of temperature and atmospheric pressure on wind speed, a short-term wind speed forecasting model based on least squares support vector machine was presented by using principal component analysis to determine the principal components of the original high-dimensional data matrix as input variables. And then, an output power forecasting model of wind farm was built by considering wake effect. At last, an example of short-term wind power prediction was provided. Matlab 7.0 was also used to demonstrate the validity of this method. And the influence of wind power on load forecasting was discussed based on citing the conception of"equivalent load".