Short-term prediction of wind power based on grey wolf optimization Elman neural network algorithm

Abstract

The intermittence and fugitiveness of wind power is one of the significance ekements affecting the quality of wind power. Aiming at the random characteristics of wind power, the output power of short-term wind electricity is forecasted by collecting historical wind speed, power and other parameters of wind farm. A model of Elman network optimized by grey wolf arithmetic (GWO) is proposed to realize short period accurate forecast for wind power. The pattern is verified and analyzed on matlab. Compared with other prediction models, the prediction accuracy is higher, which shows the effectiveness and advancement of the model.