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Research Article

Wind energy assessment and mapping using terrain nonlinear autoregressive neural network (TNARX) and wind station data

ORCID Icon & | (Reviewing Editor)
Article: 1452594 | Received 28 Dec 2017, Accepted 12 Mar 2018, Published online: 26 Mar 2018

References

  • Abbes, M. , & Belhadj, J. (2014). Development of a methodology for wind energy estimation and wind park design. Journal of Renewable and Sustainable Energy , 6 , 053103.10.1063/1.4895919
  • Ahmad, A. , & Anderson, T . (2014). Global solar radiation prediction using artificial neural network models for New Zealand. Paper presented at proceedings of the 52nd Annual Australian Solar Council Scientific Conference, Melbourne, May 2014.
  • Ak, R. , Li, Y. , Vitelli, V. , & Zio, E. (2012). Estimation of wind speed prediction intervals by multi-objective genetic algorithms and neural networks. In Acts of the XLVI Scientific Meeting of the Italian Statistical Society . Rome: Italy.
  • Akdağ, S. A. , & Dinler, A. (2009). A new method to estimate Weibull parameters for wind energy applications. Energy Conversion and Management , 50 , 1761–1766.10.1016/j.enconman.2009.03.020
  • Akinci, T. (2011). Short term wind speed forecasting with ANN in Batman, Turkey. Electronics & Electrical Engineering , 1 , 41–45.
  • Akpinar, E. K. , & Akpinar, S. (2005). An assessment on seasonal analysis of wind energy characteristics and wind turbine characteristics. Energy Conversion and Management , 46 , 1848–1867.10.1016/j.enconman.2004.08.012
  • Albani, A. , & Ibrahim, M. (2014). An assessment of wind energy potential for selected sites in malaysia using feed-in tariff criteria. Wind Engineering , 38 , 249–259.10.1260/0309-524X.38.3.249
  • Albani, A. , Ibrahim, M. , & Yong, K. (2009). Investigation on wind energy potential at Sabah State of Malaysia. In 10th UMT International Annual Symposium on Empowering Science Technology and Innovation Towards a Better Tomorrow (pp. 11–13).
  • Alkhatib, A. , Heire, S. , & Kurt, M. (2012). Detailed analysis for Implementing a short term wind speed prediction tool using artificial neural networks. International Journal on Advances in Networks and Services , 5 , 149-158.
  • Al-Nassar, W. , Alhajraf, S. , Al-Enizi, A. , & Al-Awadhi, L. (2005). Potential wind power generation in the State of Kuwait. Renewable Energy , 30 , 2149–2161.10.1016/j.renene.2005.01.002
  • Anand, A. P. , Saravanan, R. , & Muthaiah, R. (2013). Threshold prediction of a cyclostationary feature detection process using an artificial neural network. International Journal of Engineering & Technology (0975–4024) , 5 , 164–176.
  • Anwari, M. , Rashid, M. , Muhyiddin, H. , & Ali, A. (2012). An evaluation of hybrid wind/diesel energy potential in Pemanggil Island Malaysia. In Power Engineering and Renewable Energy (ICPERE) International Conference on (pp. 1–5).
  • Anyi, M. , Kirke, B. , & Ali, S. (2010). Remote community electrification in Sarawak, Malaysia. Renewable Energy , 35 , 1609–1613.10.1016/j.renene.2010.01.005
  • Azad, A. K. , Rasul, M. G. , & Yusaf, T. (2014). Statistical diagnosis of the best weibull methods for wind power assessment for agricultural applications. Energies , 7 , 3056–3085.10.3390/en7053056
  • Bagiorgas, H. , Assimakopoulos, M. , Theoharopoulos, D. , Matthopoulos, D. , & Mihalakakou, G. (2007). Electricity generation using wind energy conversion systems in the area of Western Greece. Energy Conversion and Management , 48 , 1640–1655.10.1016/j.enconman.2006.11.009
  • Ball, R. A. , Purcell, L. C. , & Carey, S. K. (2004). Evaluation of solar radiation prediction models in North America. Agronomy Journal , 96 , 391–397.10.2134/agronj2004.3910
  • Bekele, G. , & Palm, B. (2009). Wind energy potential assessment at four typical locations in Ethiopia. Applied Energy , 86 , 388–396.10.1016/j.apenergy.2008.05.012
  • Bilgili, M. , Sahin, B. , & Yasar, A. (2007). Application of artificial neural networks for the wind speed prediction of target station using reference stations data. Renewable Energy , 32 , 2350–2360.10.1016/j.renene.2006.12.001
  • Burton, T. , Jenkins, N. , Sharpe, D. , & Bossanyi, E. (2011). Wind energy handbook . Hoboken, NJ: John Wiley & Sons.10.1002/9781119992714
  • Burton, T. , Jenkins, N. , Sharpe, D. , & Bossanyi, E. (2012). Wind energy handbook . Hoboken: John Wiley & Sons.
  • Carolin Mabel, M. , & Fernandez, E. (2008). Analysis of wind power generation and prediction using ANN: A case study. Renewable Energy , 33 , 986–992.10.1016/j.renene.2007.06.013
  • Celik, A. (2003). Assessing the suitability of wind speed probabilty distribution functions based on wind power density. Renewable Energy , 28 , 1563–1574.10.1016/S0960-1481(03)00018-1
  • Chang, T. P. (2011). Estimation of wind energy potential using different probability density functions. Applied Energy , 88 , 1848–1856.10.1016/j.apenergy.2010.11.010
  • Coville, A. , Siddiqui, A. , & Vogstad, K.-O. (2011). The effect of missing data on wind resource estimation. Energy , 36 , 4505–4517.10.1016/j.energy.2011.03.067
  • Daut, I. , Razliana, A. , Irwan, Y. , & Farhana, Z. (2012). A study on the wind as renewable energy in perlis, Northern Malaysia. Energy Procedia , 18 , 1428–1433.10.1016/j.egypro.2012.05.159
  • Dike, V. N. , Chineke, C. T. , Nwofor, O. K. , & Okoro, U. K. (2011). Wind energy potential in some coastal cities of Niger-Delta region of Nigeria. The Pacific Journal ODF Science and Technology , 12 , 598-604.
  • Fripp, M. , & Wiser, R. H. (2008). Effects of temporal wind patterns on the value of wind-generated electricity in California and the Northwest. IEEE Transactions on Power Systems , 23 , 477–485.10.1109/TPWRS.2008.919427
  • Gomes, P. , & Castro, R. (2012). Wind Speed and wind power forecasting using statistical models: AutoRegressive moving average (ARMA) and artificial neural networks (ANN). International Journal of Sustainable Energy , 1 , 36–45.
  • Gualtieri, G. , & Secci, S. (2014). Extrapolating wind speed time series vs. Weibull distribution to assess wind resource to the turbine hub height: A case study on coastal location in Southern Italy. Renewable Energy , 62 , 164–176.10.1016/j.renene.2013.07.003
  • GWEC . (2013). Global wind report 2016. Retrieved March 20, 2018, from http://gwec.net/publications/global-wind-report-2/global-wind-report-2016/
  • Islam, M. , Rahim, N. , Solangi, K. , & Saidur, R. (2012). Assessing wind energy potentiality for selected sites in Malaysia. Energy Education Science and Technology Part A-Energy Science and Research , 29 , 611–626.
  • Islam, M. , Saidur, R. , & Rahim, N. (2011). Assessment of wind energy potentiality at Kudat and Labuan, Malaysia using Weibull distribution function. Energy , 36 , 985–992.10.1016/j.energy.2010.12.011
  • Jakhrani, A. , Othman, A. , Rigit, A. , & Samo, S. (2013). Assessment of solar and wind energy resources at five typical locations in Sarawak. Journal of Energy and Environment , 4 , 234–239.
  • Kalogirou, S. A. (2000). Applications of artificial neural-networks for energy systems. Applied Energy , 67 , 17–35.10.1016/S0306-2619(00)00005-2
  • Karim, Z. B. A. F. H. A. (2012). Wind energy potential at Kudat. Renewable Energy , 6 , 12-19.
  • Keyhani, A. , Ghasemi-Varnamkhasti, M. , Khanali, M. , & Abbaszadeh, R. (2010). An assessment of wind energy potential as a power generation source in the capital of Iran, Tehran. Energy , 35 , 188–201.10.1016/j.energy.2009.09.009
  • Mohammadi, K. , Mostafaeipour, A. , Dinpashoh, Y. , & Pouya, N. (2014). Electricity generation and energy cost estimation of large-scale wind turbines in Jarandagh, Iran. Journal of Energy , 2014 , 8.
  • Mostafaeipour, A. , Sedaghat, A. , Dehghan-Niri, A. , & Kalantar, V. (2011). Wind energy feasibility study for city of Shahrbabak in Iran. Renewable and Sustainable Energy Reviews , 15 , 2545–2556.10.1016/j.rser.2011.02.030
  • Moussavi, S. Z. , & Kashkooli, F. R. (2013). Small signal stability assessment of power systems with large-scale wind farms. Arabian Journal for Science and Engineering , 38 , 2493–2502.10.1007/s13369-013-0562-9
  • Muhammad, S. L. , Abidin, W. A. W. Z. , Chai, W. Y. , Baharun, A. , & Masri, T. (2014). Development of wind mapping based on artificial neural network (ANN) for energy exploration in Sarawak. International Journal of Renewable Energy Research (IJRER) , 4 , 618–627.
  • Olaofe, Z. O. , & Folly, K. A. (2012). Statistical analysis of wind resources at darling for energy production. International Journal of Renewable Energy Research (IJRER) , 2 , 250–261.
  • Oyedepo, S. O. , Adaramola, M. S. , & Paul, S. S. (2012). Analysis of wind speed data and wind energy potential in three selected locations in south-east Nigeria. International Journal of Energy and Environmental Engineering , 3 , 1–11.
  • Palma, J. , Castro, F. , Ribeiro, L. , Rodrigues, A. , & Pinto, A. (2008). Linear and nonlinear models in wind resource assessment and wind turbine micro-siting in complex terrain. Journal of Wind Engineering and Industrial Aerodynamics , 96 , 2308–2326.10.1016/j.jweia.2008.03.012
  • Philippopoulos, K. , & Deligiorgi, D. (2009). Statistical simulation of wind speed in Athens, Greece based on Weibull and ARMA models. International Journal of Energy and Environment , 3 , 151–158.
  • Philippopoulos, K. , & Deligiorgi, D. (2012). Application of artificial neural networks for the spatial estimation of wind speed in a coastal region with complex topography. Renewable Energy , 38 , 75–82.10.1016/j.renene.2011.07.007
  • Philippopoulos, K. , Deligiorgi, D. , & Kouroupetroglou, G. (2015). Artificial neural network modeling of relative humidity and air temperature spatial and temporal distributions over complex terrains. In Pattern Recognition Applications and Methods (pp. 171-187). Berlin: Springer.
  • Portal, S. G. (2007). Demography, geography and economy [Online]. Retrieved from http://www.Sarawak.gov.my/en/about
  • Ray, M. , Rogers, A. , & McGowan, J. (2006). Analysis of wind shear models and trends in different terrains . Lakewood: University of Massachusetts, Department of Mechanical and Industrial Engineering, Renewable Energy Research Laboratory.
  • Sen, H.a. T. E. (2012)Wind velocity vertical extrapolation by extended power law. Advances Metrology , 4, 16.
  • Wahab, A. A . (2004, December). Establishing the wind map for Sabah and Sarawak, Malaysia, eprints.utm.my/2688/.
  • WEA . (2012). Wind in power. 2016. Retrieved from www.ewea.org/fileadmin/files/library/publications/statistics/EWEA-Annual-Statistics-2015