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Wind speed spatial estimation for energy planning in Sicily: A neural kriging application

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  1. Liu, Heping & Shi, Jing & Erdem, Ergin, 2010. "Prediction of wind speed time series using modified Taylor Kriging method," Energy, Elsevier, vol. 35(12), pages 4870-4879.
  2. Tar, Károly & Farkas, István & Rózsavölgyi, Kornél, 2011. "Climatic conditions for operation of wind turbines in Hungary," Renewable Energy, Elsevier, vol. 36(2), pages 510-518.
  3. Veronesi, F. & Grassi, S. & Raubal, M., 2016. "Statistical learning approach for wind resource assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 836-850.
  4. Morano, Pierluigi & Tajani, Francesco & Locurcio, Marco, 2017. "GIS application and econometric analysis for the verification of the financial feasibility of roof-top wind turbines in the city of Bari (Italy)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 999-1010.
  5. Beccali, M. & Cirrincione, G. & Marvuglia, A. & Serporta, C., 2010. "Estimation of wind velocity over a complex terrain using the Generalized Mapping Regressor," Applied Energy, Elsevier, vol. 87(3), pages 884-893, March.
  6. Petinrin, J.O. & Shaaban, Mohamed, 2015. "Renewable energy for continuous energy sustainability in Malaysia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 967-981.
  7. González-Longatt, Francisco & Medina, Humberto & Serrano González, Javier, 2015. "Spatial interpolation and orographic correction to estimate wind energy resource in Venezuela," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 1-16.
  8. Liang Pei & Chunhui Wang & Liying Sun & Lili Wang, 2022. "Temporal and Spatial Variation (2001–2020) Characteristics of Wind Speed in the Water Erosion Area of the Typical Black Soil Region, Northeast China," IJERPH, MDPI, vol. 19(17), pages 1-17, August.
  9. Wekesa, David Wafula & Wang, Cong & Wei, Yingjie & Kamau, Joseph N. & Danao, Louis Angelo M., 2015. "A numerical analysis of unsteady inflow wind for site specific vertical axis wind turbine: A case study for Marsabit and Garissa in Kenya," Renewable Energy, Elsevier, vol. 76(C), pages 648-661.
  10. Lagorse, Jeremy & Paire, Damien & Miraoui, Abdellatif, 2010. "A multi-agent system for energy management of distributed power sources," Renewable Energy, Elsevier, vol. 35(1), pages 174-182.
  11. Philippopoulos, Kostas & Deligiorgi, Despina, 2012. "Application of artificial neural networks for the spatial estimation of wind speed in a coastal region with complex topography," Renewable Energy, Elsevier, vol. 38(1), pages 75-82.
  12. Houndekindo, Freddy & Ouarda, Taha B.M.J., 2024. "Prediction of hourly wind speed time series at unsampled locations using machine learning," Energy, Elsevier, vol. 299(C).
  13. Jung, Sungmoon & Kwon, Soon-Duck, 2013. "Weighted error functions in artificial neural networks for improved wind energy potential estimation," Applied Energy, Elsevier, vol. 111(C), pages 778-790.
  14. Hur, J. & Baldick, R., 2016. "A new merit function to accommodate high wind power penetration of WGRs (wind generating resources)," Energy, Elsevier, vol. 108(C), pages 34-40.
  15. Maciej J. Nowak & Agnieszka Brelik & Anna Oleńczuk-Paszel & Monika Śpiewak-Szyjka & Justyna Przedańska, 2023. "Spatial Conflicts concerning Wind Power Plants—A Case Study of Spatial Plans in Poland," Energies, MDPI, vol. 16(2), pages 1-20, January.
  16. Marvuglia, Antonino & Messineo, Antonio, 2012. "Monitoring of wind farms’ power curves using machine learning techniques," Applied Energy, Elsevier, vol. 98(C), pages 574-583.
  17. Qiaomu Zhu & Jinfu Chen & Lin Zhu & Xianzhong Duan & Yilu Liu, 2018. "Wind Speed Prediction with Spatio–Temporal Correlation: A Deep Learning Approach," Energies, MDPI, vol. 11(4), pages 1-18, March.
  18. Ouammi, A. & Sacile, R. & Mimet, A., 2010. "Wind energy potential in Liguria region," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(1), pages 289-300, January.
  19. Christopher Jung, 2016. "High Spatial Resolution Simulation of Annual Wind Energy Yield Using Near-Surface Wind Speed Time Series," Energies, MDPI, vol. 9(5), pages 1-20, May.
  20. Sharifzadeh, Mahdi & Sikinioti-Lock, Alexandra & Shah, Nilay, 2019. "Machine-learning methods for integrated renewable power generation: A comparative study of artificial neural networks, support vector regression, and Gaussian Process Regression," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 513-538.
  21. Fadare, D.A., 2010. "The application of artificial neural networks to mapping of wind speed profile for energy application in Nigeria," Applied Energy, Elsevier, vol. 87(3), pages 934-942, March.
  22. Collados-Lara, Antonio-Juan & Baena-Ruiz, Leticia & Pulido-Velazquez, David & Pardo-Igúzquiza, Eulogio, 2022. "Data-driven mapping of hourly wind speed and its potential energy resources: A sensitivity analysis," Renewable Energy, Elsevier, vol. 199(C), pages 87-102.
  23. Cellura, Maurizio & Guarino, Francesco & Longo, Sonia & Mistretta, Marina, 2015. "Different energy balances for the redesign of nearly net zero energy buildings: An Italian case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 100-112.
  24. El Alimi, Souheil & Maatallah, Taher & Dahmouni, Anouar Wajdi & Ben Nasrallah, Sassi, 2012. "Modeling and investigation of the wind resource in the gulf of Tunis, Tunisia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(8), pages 5466-5478.
  25. Vladimir Simankov & Pavel Buchatskiy & Semen Teploukhov & Stefan Onishchenko & Anatoliy Kazak & Petr Chetyrbok, 2023. "Review of Estimating and Predicting Models of the Wind Energy Amount," Energies, MDPI, vol. 16(16), pages 1-24, August.
  26. Ouammi, Ahmed & Zejli, Driss & Dagdougui, Hanane & Benchrifa, Rachid, 2012. "Artificial neural network analysis of Moroccan solar potential," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 4876-4889.
  27. Hanslian, David & Hošek, Jiří, 2015. "Combining the VAS 3D interpolation method and Wind Atlas methodology to produce a high-resolution wind resource map for the Czech Republic," Renewable Energy, Elsevier, vol. 77(C), pages 291-299.
  28. Soulis, Konstantinos X. & Manolakos, Dimitris & Ntavou, Erika & Kosmadakis, George, 2022. "A geospatial analysis approach for the operational assessment of solar ORC systems. Case study: Performance evaluation of a two-stage solar ORC engine in Greece," Renewable Energy, Elsevier, vol. 181(C), pages 116-128.
  29. Ouammi, Ahmed & Sacile, Roberto & Zejli, Driss & Mimet, Abdelaziz & Benchrifa, Rachid, 2010. "Sustainability of a wind power plant: Application to different Moroccan sites," Energy, Elsevier, vol. 35(10), pages 4226-4236.
  30. Fateh Mehazzem & Maina André & Rudy Calif, 2022. "Efficient Output Photovoltaic Power Prediction Based on MPPT Fuzzy Logic Technique and Solar Spatio-Temporal Forecasting Approach in a Tropical Insular Region," Energies, MDPI, vol. 15(22), pages 1-21, November.
  31. Carta, J.A. & Ramírez, P. & Velázquez, S., 2009. "A review of wind speed probability distributions used in wind energy analysis: Case studies in the Canary Islands," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(5), pages 933-955, June.
  32. Youngmin Seo & Sungwon Kim & Vijay Singh, 2015. "Estimating Spatial Precipitation Using Regression Kriging and Artificial Neural Network Residual Kriging (RKNNRK) Hybrid Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(7), pages 2189-2204, May.
  33. Leer, Donald & Chang, Byungik & Chen, Gerald & Carr, David & Starcher, Kenneth & Issa, Roy, 2013. "Windtane contour map of the state of Texas," Renewable Energy, Elsevier, vol. 58(C), pages 140-150.
  34. Rubin, Ofir David, 2010. "Equilibrium pricing in electricity markets with wind power," ISU General Staff Papers 201001010800002361, Iowa State University, Department of Economics.
  35. Calif, Rudy & Emilion, Richard & Soubdhan, Ted, 2011. "Classification of wind speed distributions using a mixture of Dirichlet distributions," Renewable Energy, Elsevier, vol. 36(11), pages 3091-3097.
  36. de la Rosa, Juan José González & Pérez, Agustín Agüera & Palomares Salas, José Carlos & Ramiro Leo, José Gabriel & Muñoz, Antonio Moreno, 2011. "A novel inference method for local wind conditions using genetic fuzzy systems," Renewable Energy, Elsevier, vol. 36(6), pages 1747-1753.
  37. Foley, Aoife M. & Leahy, Paul G. & Marvuglia, Antonino & McKeogh, Eamon J., 2012. "Current methods and advances in forecasting of wind power generation," Renewable Energy, Elsevier, vol. 37(1), pages 1-8.
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