A Systematic Review on Wind Energy Resources Forecasting by Neural Network

Abstract

The researchers have used various algorithms like Auto Regressive Integrated Moving Average (ARIMA), Nearest Neighbour Search, Wavelet Transform, Random Trees, Neural Network etc. to predict solar and wind forecasting. Though there are many algorithms for forecasting, Neural Network has gained special attention due its validity checking features. In these researches' the solar and wind data and pattern has been predicted by using Neural Network. Some researchers have combined neural network with another algorithm to form hybrid algorithm for prediction. Also, researches have been carried out combining two or three renewable energy resources like solar and wind etc. The review paper consists of Machine Learning techniques and wind energy resources, basic of wind resources parameters, wind energy resources prediction data using Neural Network, wind energy resources prediction data using Neural Network with its hybrid algorithm and wind and solar energy resources prediction using Neural Network with its hybrid algorithm. This paper complied scientometric with wind and solar energy resources forecasting with neural network in terms of distribution of documents, distribution of articles, citation of the documents, organization enhanced with research, organization enhanced with funding agencies and authors Contribution by year over the period 2010 -2020.