Title :
Parametrical needs for wind speed prediction using ANN
Author :
Agrawal, Alok ; Sandhu, K.S.
Author_Institution :
Dept. of Electr. Eng., NIT Kurukshetra, Kurukshetra, India
Abstract :
In last few decades there has been a upward trend towards sustainable energy generation and consumption. Effect is a direct result of depleting fossil fuel reserves as well as increasing global concerns regarding the ill-effects of ongoing power generation techniques. In this sector wind power generation tends to play a vital role. However, the arbitrary nature of wind resource is a major hindrance in its application. Wind speed forecasting enables us to know the future wind reserve at any target site, as well as helps us to handle power issues that could result as an inadvertent effect of wind power integration into the system. In this paper focus was on finding out the most influential parameters for wind speed prediction purposes. These parameters when incorporated into any Numerical Weather Prediction (NWP) model would lead to best prediction results. Results have been verified over a time horizon of 6 and 12 hours ahead using 1 and 2 year models, respectively. Data from VABB airport, Mumbai was used for modelling and prediction purposes.
Keywords :
energy consumption; neural nets; sustainable development; weather forecasting; wind power; ANN; energy consumption; fossil fuel reserves; numerical weather prediction model; sustainable energy generation; wind power generation; wind speed forecasting; wind speed prediction; Artificial neural networks; Data models; Forecasting; Mathematical model; Predictive models; Wind forecasting; Wind speed; Artificial Neural Network Based Yearly Auto-regressive (ANN-AR) Model; Feed Forward Artificial Neural Network (FFANN); Numerical Weather Prediction; Parametrical Combination; Performance Evaluation Parameter; Time Horizon;
Conference_Titel :
Computing, Communication & Automation (ICCCA), 2015 International Conference on
Conference_Location :
Noida
Print_ISBN :
978-1-4799-8889-1
DOI :
10.1109/CCAA.2015.7148372