Wind Speed & Power Forecasting using Artificial Neural Network (NARX) for New York Wind Energy Farm
Author(s):
Vijay Kumar , IMSEC Ghaziabad; Varun Kumar Singhal, IMSEC Ghaziabad; Atul Kushwaha, IMSEC Ghaziabad; Mayank Agarwal, IMSEC Ghaziabad; Abhishek Gupta, IMSEC GhaziabadKeywords:
Wind Power Forecasting, Artificial Neural Network, Nonlinear Autoregressive with Exogenous Inputs, Mean Absolute Percentage Error, Statistical Method and YAR ModelAbstract:
Continuous Depleting conventional fuel reserves and its impact as increasing global warming concerns have diverted world attention towards non-conventional energy sources. Out of different non-conventional energy sources wind energy can be consider as one of the cleanest source with minimum possible pollution or harmful emissions and has the potential to decrease the relying on conventional energy sources. Today Wind energy can play a vital role to meet our energy demands; however, it faces various issues such as intermittent nature and frequency instability. To reduce such issues the knowledge of futuristic weather conditions and wind speed trend are required. This work mainly describes the implementation of NARX Artificial neural network for wind speed & power forecasting with the help of historical data available from wind farms.
Other Details:
| Manuscript Id | : | J4RV3I9006 |
| Published in | : | Volume : 3, Issue : 9 |
| Publication Date | : | 01/12/2017 |
| Page(s) | : | 1-10 |
