Very-short term wind power forecasting through Adaptive Wavelet Neural Network

摘要

In recent days, accuracy enhancement of wind power forecasting is essential for integrating large amounts of wind power into the national electricity grid to mitigate its intermittency. This paper contributes evaluation of performance and accuracy enhancement of one step ahead with 10 minutes time series resolution of wind power forecasting through Adaptive Wavelet Neural Network (AWNN), using real time data of a wind farm with two wind power turbines. The effectiveness of this work is compared with Artificial Neural Networks (ANNs) and Adaptive Neuro-Fuzzy Inference System (ANFIS) standard approaches and the results established that the proposed model outperforms the standard approaches.