References
[1]. Ahmed, W. U., Zahed, M. J. H., Rahman, M. A., &
Mamun, M. (2014, September). Numerical study of two
nd and three bladed savonius wind turbine. In 2 International
Conference on Green Energy and Technology (pp. 36-40).
IEEE.
[2]. Alberto, P.,Fausto, P., Garcia, M.,Perez, J. M. P., & Diego,
R. (2018). A survey of artificial neural network in wind energy
system. Applied Energy, 228, 1822-1836.
[3]. Ali, S. A., Nawaz, M. F., Bilal, M., Ahmad, F., & Hayat, U. Y.
(2015, June). Modeling of wind power plant using MATLAB.
In 2015, Power Generation System and Renewable Energy
Technologies (PGSRET) (pp. 1-5). IEEE.
[4]. Alshehri, J., Alzahrani, A., & Khalid, M. (2019, May). Wind
energy conversion systems and artificial neural networks: Role
and applications. In 2019, IEEE Innovative Smart Grid
Technologies - Asia (ISGT Asia) (pp. 1777-1782). IEEE.
[5]. Amrutha, J., & Ajai, R. A. S. (2018). Performance analysis
of Back propagation algorithm of artificial neural networks
in verilog. In 3rd IEEE International Conference on Recent
Trends in Electronics, Information & Communication
Technology (RTEICT), 1547-1550.
[6]. Anirudh, S., & Shekhawat. (2014). Wind power
forecasting using artificial neural network. International
Journal of Engineering Research & Technology (IJERT), 3(4),
993-998.
[7]. Bilal, B., Ndongo, M., Adjallah, K. H., Sava, A., Kébé, C.
M., Ndiaye, P. A., & Sambou, V. (2018, February). Wind
turbine power output prediction model design based on
artificial neural networks and climatic spatiotemporal data.
In 2018, IEEE International Conference on Industrial Technology
(ICIT) (pp. 1085-1092). IEEE.
[8]. Chainok, B., Tunyasrirut, S., Wangnipparnto, S., &
Permpoonsinsup, W. (2017, March). Artificial neural network
model for wind energy on urban building in Bangkok. In
2017, International Electrical Engineering Congress
(iEECON) (pp. 1-4). IEEE.
[9]. Environmental Science. (n. d.). Renewable Energy: All
you need to know. Retrieved from https://www.environme
ntalscience.org/renewable-energy.
[10]. Jitendra, K., Rajarshi, D., &Tarun, S. (2015). Modeling
of thermal power plant using neural network and regression
technique. Journal of Scientific Research and Advance.
166-174.
[11]. Lee, K. Y., Heo, J. S., Hoffman, J. A., Kim, S. H., & Jung,
W. H. (2007, June). Neural network-based modeling for a
large-scale power plant. In 2007, IEEE Power Engineering
Society General Meeting (pp. 1-8). IEEE.
[12]. Liu, Z., Gao, W., Wan, Y. H., & Muljadi, E. (2012,
September). Wind power plant prediction by using neural
networks. In 2012, IEEE Energy Conversion Congress and
Exposition (ECCE) (pp. 3154-3160). IEEE.
[13]. Luna, J., Gros, S., Geisler, J., Falkenberg, O., Noga, R.,
& Schild, A. (2018, October). Super-short term wind speed
prediction based on artificial neural networks for wind
turbine control applications. In IECON 2018 – 44th Annual
Conference of the IEEE Industrial Electronics Society (pp. 1952-1957). IEEE.
[14]. MathWorks. (n.d.). Deep learning. Retrieved from
https://www.mathworks.com/help/deeplearning/ref/nn
start.html
[15]. Mishra, A. K., & Ramesh, L. (2009, April). Application of
neural networks in wind power (generation) prediction. In
2009, International Conference on Sustainable Power
Generation and Supply (pp. 1-5). IEEE.
[16]. Mishra, M., & Srivastava, M. (2014). A view of artificial
neural network. In International Conference on Advances
in Engineering & Technology Research (ICAETR - 2014), 1-3.
[17]. Mohammad, M., Peeyush, T., & Shahjahan. (2011).
Applications of artificial neural networks in electric power
industry: A review. International Journal of Electrical
Engineering, 4(2), 161-171.
[18]. Musyafa, A., & Noriyati, R. D. (2012). Implementation
of pitch angle wind turbine position for maximum power.
Academic Research International, 3(1), 510-518.
[19]. Nithya, M., Nagarajan, S., & Navaseelan, P. (2017,
April). Fault detection of wind turbine system using neural
networks. In 2017, IEEE Technological Innovations in ICT for
Agriculture and Rural Development (TIAR) (pp. 103-108). IEEE.
[20]. Răzuşi, P. C., & Eremia, M. (2011, September).
Prediction of wind power by artificial intelligence
th techniques. In 2011, 16 International Conference on
Intelligent System Applications to Power Systems (pp. 1-6).
IEEE.
[21]. Ritchie, H., & Roser, M. (2015). Energy. Our World in
Data. Retrieved from https://ourworldindata.org/energy
[22]. Shahat, A., Haddad, R. J., Kalaani, Y. (2015). An
artificial neural network model for wind energy estimation.
In Proceedings of the IEEE Southeast Conference. Fort
Lauderdale, Florida: IEEE.
[23]. Shivnandam, S. N., & Deepa, S. N. (2006). Introduction
to neural networks using MATLAB 6.0. Tata McGraw-Hill
Education.
[24]. WES 80. (n.d.). Wind energy solutions. Retrieved from
https://windenergysolutions.nl/turbines/windturbine-wes-80/
