Narx Based Short Term Wind Power Forecasting Model
Abstract
This paper contributes a short-term wind power forecasting through Artificial Neural Network with nonlinear autoregressive exogenous inputs (NARX) model. The meteorological parameters like wind speed, temperature, pressure, and air density are considered as input parameters collected from KL University area and the calculated generated power as output parameters of neural network to predict the wind power generation. Based on hybrid forecasting technique a code is developed in MATLAB at different hidden layers and delay times.
Keywords
ANN, Hybrid method, Narx, Netc, Wind power forecasting
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PDFDOI: http://doi.org/10.11591/ijai.v4.i4.pp129-138
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IAES International Journal of Artificial Intelligence (IJ-AI)
ISSN/e-ISSN 2089-4872/2252-8938
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).