Detecting Wind Power Ramp with Random Vector Functional Link (RVFL) Network

Abstract

Due to the intermittent nature of the wind, the wind speed is fluctuating. Fluctuating wind speed cause even more fluctuation in wind power generation. The sudden changes of the wind power injected into the power grid within a short time frame is known as power ramp, which can be harmful to the grid. This paper presents algorithms to detect the wind power ramps in a certain forecasting horizon. The importance and challenges of wind power ramp detection are addressed. Several different Wind power ramps are defined in this paper. A random vector functional link (RVFL) network is employed to predict the future occurrence of wind power ramp. The forecasting methods are evaluated with a real world wind power data set. The RVFL network has comparable performance as the benchmark methods: random forests (RF) and support vector machine (SVM) but it has better performance than the artificial neural network (ANN). The computation time of training and testing is also in favor of the RVFL network.