IDEAS home Printed from https://ideas.repec.org/r/eee/rensus/v56y2016icp246-260.html
   My bibliography  Save this item

Evaluation of empirical models for predicting monthly mean horizontal diffuse solar radiation

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Chen, Wei-Hsin & Aniza, Ria & Arpia, Arjay A. & Lo, Hsiu-Ju & Hoang, Anh Tuan & Goodarzi, Vahabodin & Gao, Jianbing, 2022. "A comparative analysis of biomass torrefaction severity index prediction from machine learning," Applied Energy, Elsevier, vol. 324(C).
  2. Limouni, Tariq & Yaagoubi, Reda & Bouziane, Khalid & Guissi, Khalid & Baali, El Houssain, 2023. "Accurate one step and multistep forecasting of very short-term PV power using LSTM-TCN model," Renewable Energy, Elsevier, vol. 205(C), pages 1010-1024.
  3. Kieu Anh Nguyen & Walter Chen & Bor-Shiun Lin & Uma Seeboonruang, 2020. "Using Machine Learning-Based Algorithms to Analyze Erosion Rates of a Watershed in Northern Taiwan," Sustainability, MDPI, vol. 12(5), pages 1-16, March.
  4. Ramadhan, Raden A.A. & Heatubun, Yosca R.J. & Tan, Sek F. & Lee, Hyun-Jin, 2021. "Comparison of physical and machine learning models for estimating solar irradiance and photovoltaic power," Renewable Energy, Elsevier, vol. 178(C), pages 1006-1019.
  5. Moreno, Sinvaldo Rodrigues & Mariani, Viviana Cocco & Coelho, Leandro dos Santos, 2021. "Hybrid multi-stage decomposition with parametric model applied to wind speed forecasting in Brazilian Northeast," Renewable Energy, Elsevier, vol. 164(C), pages 1508-1526.
  6. Jawed Mustafa & Shahid Husain & Saeed Alqaed & Uzair Ali Khan & Basharat Jamil, 2022. "Performance of Two Variable Machine Learning Models to Forecast Monthly Mean Diffuse Solar Radiation across India under Various Climate Zones," Energies, MDPI, vol. 15(21), pages 1-32, October.
  7. Renno, C. & Perone, A., 2021. "Experimental modeling of the optical and energy performances of a point-focus CPV system applied to a residential user," Energy, Elsevier, vol. 215(PA).
  8. Jamil, Basharat & Akhtar, Naiem, 2017. "Comparison of empirical models to estimate monthly mean diffuse solar radiation from measured data: Case study for humid-subtropical climatic region of India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 1326-1342.
  9. Mohammadi, Kasra & Shamshirband, Shahaboddin & Kamsin, Amirrudin & Lai, P.C. & Mansor, Zulkefli, 2016. "Identifying the most significant input parameters for predicting global solar radiation using an ANFIS selection procedure," Renewable and Sustainable Energy Reviews, Elsevier, vol. 63(C), pages 423-434.
  10. Yang, Liu & Cao, Qimeng & Yu, Ying & Liu, Yan, 2020. "Comparison of daily diffuse radiation models in regions of China without solar radiation measurement," Energy, Elsevier, vol. 191(C).
  11. Hassan, Gasser E. & Youssef, M. Elsayed & Mohamed, Zahraa E. & Ali, Mohamed A. & Hanafy, Ahmed A., 2016. "New Temperature-based Models for Predicting Global Solar Radiation," Applied Energy, Elsevier, vol. 179(C), pages 437-450.
  12. Froguel, Lucas Belasque & de Lima Prado, Thiago & Corso, Gilberto & dos Santos Lima, Gustavo Zampier & Lopes, Sergio Roberto, 2022. "Efficient computation of recurrence quantification analysis via microstates," Applied Mathematics and Computation, Elsevier, vol. 428(C).
  13. Wiktor Olchowik & Jędrzej Gajek & Andrzej Michalski, 2023. "The Use of Evolutionary Algorithms in the Modelling of Diffuse Radiation in Terms of Simulating the Energy Efficiency of Photovoltaic Systems," Energies, MDPI, vol. 16(6), pages 1-32, March.
  14. Laila Ouazzani Chahidi & Marco Fossa & Antonella Priarone & Abdellah Mechaqrane, 2021. "Evaluation of Supervised Learning Models in Predicting Greenhouse Energy Demand and Production for Intelligent and Sustainable Operations," Energies, MDPI, vol. 14(19), pages 1-15, October.
  15. Năstase, Gabriel & Șerban, Alexandru & Dragomir, George & Brezeanu, Alin Ionuț & Bucur, Irina, 2018. "Photovoltaic development in Romania. Reviewing what has been done," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 523-535.
  16. Nunez Munoz, Maria & Ballantyne, Erica E.F. & Stone, David A., 2022. "Development and evaluation of empirical models for the estimation of hourly horizontal diffuse solar irradiance in the United Kingdom," Energy, Elsevier, vol. 241(C).
  17. Jamil, Basharat & Akhtar, Naiem, 2017. "Estimation of diffuse solar radiation in humid-subtropical climatic region of India: Comparison of diffuse fraction and diffusion coefficient models," Energy, Elsevier, vol. 131(C), pages 149-164.
  18. Fan, Junliang & Wu, Lifeng & Zhang, Fucang & Cai, Huanjie & Ma, Xin & Bai, Hua, 2019. "Evaluation and development of empirical models for estimating daily and monthly mean daily diffuse horizontal solar radiation for different climatic regions of China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 168-186.
  19. Saioa Etxebarria Berrizbeitia & Eulalia Jadraque Gago & Tariq Muneer, 2020. "Empirical Models for the Estimation of Solar Sky-Diffuse Radiation. A Review and Experimental Analysis," Energies, MDPI, vol. 13(3), pages 1-23, February.
  20. Yingbo Pang & Iftikhar Azim & Momina Rauf & Muhammad Farjad Iqbal & Xinguang Ge & Muhammad Ashraf & Muhammad Atiq Ur Rahman Tariq & Anne W. M. Ng, 2022. "Prediction of Bidirectional Shear Strength of Rectangular RC Columns Subjected to Multidirectional Earthquake Actions for Collapse Prevention," Sustainability, MDPI, vol. 14(11), pages 1-25, June.
  21. Mahmood Ahmad & Badr T. Alsulami & Ramez A. Al-Mansob & Saerahany Legori Ibrahim & Suraparb Keawsawasvong & Ali Majdi & Feezan Ahmad, 2022. "Predicting Subgrade Resistance Value of Hydrated Lime-Activated Rice Husk Ash-Treated Expansive Soil: A Comparison between M5P, Support Vector Machine, and Gaussian Process Regression Algorithms," Mathematics, MDPI, vol. 10(19), pages 1-19, September.
  22. Kim, Jangkyum & Oh, Hyeontaek & Choi, Jun Kyun, 2022. "Learning based cost optimal energy management model for campus microgrid systems," Applied Energy, Elsevier, vol. 311(C).
  23. Qin, Wenmin & Wang, Lunche & Lin, Aiwen & Zhang, Ming & Xia, Xiangao & Hu, Bo & Niu, Zigeng, 2018. "Comparison of deterministic and data-driven models for solar radiation estimation in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 579-594.
  24. Martín-Pomares, Luis & Martínez, Diego & Polo, Jesús & Perez-Astudillo, Daniel & Bachour, Dunia & Sanfilippo, Antonio, 2017. "Analysis of the long-term solar potential for electricity generation in Qatar," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 1231-1246.
  25. Feng, Lan & Lin, Aiwen & Wang, Lunche & Qin, Wenmin & Gong, Wei, 2018. "Evaluation of sunshine-based models for predicting diffuse solar radiation in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 168-182.
  26. Luo, Laipeng & Zhang, Zhiyi & Li, Chong & Nishu, & He, Fang & Zhang, Xingguang & Cai, Junmeng, 2021. "Insight into master plots method for kinetic analysis of lignocellulosic biomass pyrolysis," Energy, Elsevier, vol. 233(C).
  27. Jamil, Basharat & Akhtar, Naiem, 2017. "Comparative analysis of diffuse solar radiation models based on sky-clearness index and sunshine period for humid-subtropical climatic region of India: A case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 329-355.
  28. Wang, Lunche & Lu, Yunbo & Zou, Ling & Feng, Lan & Wei, Jing & Qin, Wenmin & Niu, Zigeng, 2019. "Prediction of diffuse solar radiation based on multiple variables in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 151-216.
  29. Lin, Chun-Tin & Chang, Keh-Chin & Chung, Kung-Ming, 2023. "Re-modeling the solar diffuse fraction in Taiwan on basis of a typical-meteorological-year data," Renewable Energy, Elsevier, vol. 204(C), pages 823-835.
  30. Wang, Lunche & Kisi, Ozgur & Zounemat-Kermani, Mohammad & Salazar, Germán Ariel & Zhu, Zhongmin & Gong, Wei, 2016. "Solar radiation prediction using different techniques: model evaluation and comparison," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 384-397.
  31. Moretón, R. & Lorenzo, E. & Pinto, A. & Muñoz, J. & Narvarte, L., 2017. "From broadband horizontal to effective in-plane irradiation: A review of modelling and derived uncertainty for PV yield prediction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 886-903.
  32. Zhiyong Tian & Bengt Perers & Simon Furbo & Jianhua Fan & Jie Deng & Janne Dragsted, 2018. "A Comprehensive Approach for Modelling Horizontal Diffuse Radiation, Direct Normal Irradiance and Total Tilted Solar Radiation Based on Global Radiation under Danish Climate Conditions," Energies, MDPI, vol. 11(5), pages 1-19, May.
  33. Abunima, Hamza & Park, Woan-Ho & Glick, Mark B. & Kim, Yun-Su, 2022. "Two-Stage stochastic optimization for operating a Renewable-Based Microgrid," Applied Energy, Elsevier, vol. 325(C).
  34. Mohammad Rezaie-Balf & Niloofar Maleki & Sungwon Kim & Ali Ashrafian & Fatemeh Babaie-Miri & Nam Won Kim & Il-Moon Chung & Sina Alaghmand, 2019. "Forecasting Daily Solar Radiation Using CEEMDAN Decomposition-Based MARS Model Trained by Crow Search Algorithm," Energies, MDPI, vol. 12(8), pages 1-23, April.
  35. Wu, Wei & Tang, Xiaoping & Lv, Jiake & Yang, Chao & Liu, Hongbin, 2021. "Potential of Bayesian additive regression trees for predicting daily global and diffuse solar radiation in arid and humid areas," Renewable Energy, Elsevier, vol. 177(C), pages 148-163.
  36. Chhawchharia, Saransch & Sahoo, Sarat Kumar & Balamurugan, M. & Sukchai, Sukruedee & Yanine, Fernando, 2018. "Investigation of wireless power transfer applications with a focus on renewable energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 888-902.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.