IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i8p1427-d222587.html
   My bibliography  Save this article

Estimating Solar Irradiance on Tilted Surface with Arbitrary Orientations and Tilt Angles

Author

Listed:
  • Hsu-Yung Cheng

    (Department of Computer Science and Information Engineering, National Central University, 300 Zhongda Rd., Zhongli District, Taoyuan 32001, Taiwan)

  • Chih-Chang Yu

    (Department of Information and Computer Engineering, Chung Yuan Christian University, 200 Chung-Pei Rd., Zhongli District, Taoyuan 32023, Taiwan)

  • Kuo-Chang Hsu

    (Green Energy and Environment Research Laboratories, Industrial Technology Research Institute, 195 Sec.4, Chung-Hsing Rd., Chutung, Hsinchu 31057, Taiwan)

  • Chi-Chang Chan

    (Green Energy and Environment Research Laboratories, Industrial Technology Research Institute, 195 Sec.4, Chung-Hsing Rd., Chutung, Hsinchu 31057, Taiwan)

  • Mei-Hui Tseng

    (Green Energy and Environment Research Laboratories, Industrial Technology Research Institute, 195 Sec.4, Chung-Hsing Rd., Chutung, Hsinchu 31057, Taiwan)

  • Chih-Lung Lin

    (Department of Electronic Engineering, Hwa Hsia University of Technology, 111 Gon Jhuan Rd., Chung Ho dist., New Taipei City 23568, Taiwan)

Abstract

Photovoltaics modules are usually installed with a tilt angle to improve performance and to avoid water or dust accumulation. However, measured irradiance data on inclined surfaces are rarely available, since installing pyranometers with various tilt angles induces high costs. Estimating inclined irradiance of arbitrary orientations and tilt angles is important because the installation orientations and tilt angles might be different at different sites. The goal of this work is to propose a unified transfer model to obtain inclined solar irradiance of arbitrary tilt angles and orientations. Artificial neural networks (ANN) were utilized to construct the transfer model to estimate the differences between the horizontal irradiance and the inclined irradiance. Compared to ANNs that estimate the inclined irradiance directly, the experimental results have shown that the proposed ANNs with differential outputs can substantially improve the estimation accuracy. Moreover, the trained model can successfully estimate inclined irradiance with tilt angles and orientations not included in the training data.

Suggested Citation

  • Hsu-Yung Cheng & Chih-Chang Yu & Kuo-Chang Hsu & Chi-Chang Chan & Mei-Hui Tseng & Chih-Lung Lin, 2019. "Estimating Solar Irradiance on Tilted Surface with Arbitrary Orientations and Tilt Angles," Energies, MDPI, vol. 12(8), pages 1-14, April.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:8:p:1427-:d:222587
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/8/1427/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/8/1427/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Robledo, Luis & soler, Alfonso, 1998. "Modelling irradiance on inclined planes with an anisotropic model," Energy, Elsevier, vol. 23(3), pages 193-201.
    2. Lund, Henrik, 2007. "Renewable energy strategies for sustainable development," Energy, Elsevier, vol. 32(6), pages 912-919.
    3. Angelis-Dimakis, Athanasios & Biberacher, Markus & Dominguez, Javier & Fiorese, Giulia & Gadocha, Sabine & Gnansounou, Edgard & Guariso, Giorgio & Kartalidis, Avraam & Panichelli, Luis & Pinedo, Irene, 2011. "Methods and tools to evaluate the availability of renewable energy sources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(2), pages 1182-1200, February.
    4. Notton, Gilles & Paoli, Christophe & Ivanova, Liliana & Vasileva, Siyana & Nivet, Marie Laure, 2013. "Neural network approach to estimate 10-min solar global irradiation values on tilted planes," Renewable Energy, Elsevier, vol. 50(C), pages 576-584.
    5. David, Mathieu & Lauret, Philippe & Boland, John, 2013. "Evaluating tilted plane models for solar radiation using comprehensive testing procedures, at a southern hemisphere location," Renewable Energy, Elsevier, vol. 51(C), pages 124-131.
    6. Dahmani, Kahina & Dizene, Rabah & Notton, Gilles & Paoli, Christophe & Voyant, Cyril & Nivet, Marie Laure, 2014. "Estimation of 5-min time-step data of tilted solar global irradiation using ANN (Artificial Neural Network) model," Energy, Elsevier, vol. 70(C), pages 374-381.
    7. Seyed Abbas Mousavi Maleki & H. Hizam & Chandima Gomes, 2017. "Estimation of Hourly, Daily and Monthly Global Solar Radiation on Inclined Surfaces: Models Re-Visited," Energies, MDPI, vol. 10(1), pages 1-28, January.
    8. Singh, G.K., 2013. "Solar power generation by PV (photovoltaic) technology: A review," Energy, Elsevier, vol. 53(C), pages 1-13.
    9. Ellabban, Omar & Abu-Rub, Haitham & Blaabjerg, Frede, 2014. "Renewable energy resources: Current status, future prospects and their enabling technology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 748-764.
    10. Demain, Colienne & Journée, Michel & Bertrand, Cédric, 2013. "Evaluation of different models to estimate the global solar radiation on inclined surfaces," Renewable Energy, Elsevier, vol. 50(C), pages 710-721.
    11. El-Sebaii, A.A. & Al-Hazmi, F.S. & Al-Ghamdi, A.A. & Yaghmour, S.J., 2010. "Global, direct and diffuse solar radiation on horizontal and tilted surfaces in Jeddah, Saudi Arabia," Applied Energy, Elsevier, vol. 87(2), pages 568-576, February.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Miguel López Santos & Xela García-Santiago & Fernando Echevarría Camarero & Gonzalo Blázquez Gil & Pablo Carrasco Ortega, 2022. "Application of Temporal Fusion Transformer for Day-Ahead PV Power Forecasting," Energies, MDPI, vol. 15(14), pages 1-22, July.
    2. Arumugham, Dinesh Rajan & Rajendran, Parvathy, 2021. "Modelling global solar irradiance for any location on earth through regression analysis using high-resolution data," Renewable Energy, Elsevier, vol. 180(C), pages 1114-1123.
    3. Tong Liu & Li Liu & Yufang He & Mengfei Sun & Jian Liu & Guochang Xu, 2021. "A Theoretical Optimum Tilt Angle Model for Solar Collectors from Keplerian Orbit," Energies, MDPI, vol. 14(15), pages 1-17, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Yadav, Amit Kumar & Chandel, S.S., 2013. "Tilt angle optimization to maximize incident solar radiation: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 503-513.
    3. Ahmed, R. & Sreeram, V. & Mishra, Y. & Arif, M.D., 2020. "A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    4. Zafar, Muhammad Wasif & Shahbaz, Muhammad & Hou, Fujun & Sinha, Avik, 2018. "¬¬¬¬¬¬From Nonrenewable to Renewable Energy and Its Impact on Economic Growth: Silver Line of Research & Development Expenditures in APEC Countries," MPRA Paper 90611, University Library of Munich, Germany, revised 10 Dec 2018.
    5. Hu, ZhiWen & Wang, HanYi, 2024. "Feasibility study of energy storage using hydraulic fracturing in shale formations," Applied Energy, Elsevier, vol. 354(PB).
    6. Gulin, Marko & Pavlović, Tomislav & Vašak, Mario, 2016. "Photovoltaic panel and array static models for power production prediction: Integration of manufacturers’ and on-line data," Renewable Energy, Elsevier, vol. 97(C), pages 399-413.
    7. Turgut Karahüseyin & Serkan Abbasoğlu, 2022. "Performance Loss Rates of a 1 MWp PV Plant with Various Tilt Angle, Orientation and Installed Environment in the Capital of Cyprus," Sustainability, MDPI, vol. 14(15), pages 1-23, July.
    8. Sharma, Vikrant & Chandel, S.S., 2013. "Performance and degradation analysis for long term reliability of solar photovoltaic systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 753-767.
    9. Cheng, Hsu-Yung, 2017. "Cloud tracking using clusters of feature points for accurate solar irradiance nowcasting," Renewable Energy, Elsevier, vol. 104(C), pages 281-289.
    10. Huang, Zishuo & Yu, Hang & Peng, Zhenwei & Zhao, Mei, 2015. "Methods and tools for community energy planning: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 1335-1348.
    11. Kaddoura, Tarek O. & Ramli, Makbul A.M. & Al-Turki, Yusuf A., 2016. "On the estimation of the optimum tilt angle of PV panel in Saudi Arabia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 626-634.
    12. Teke, Ahmet & Yıldırım, H. Başak & Çelik, Özgür, 2015. "Evaluation and performance comparison of different models for the estimation of solar radiation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 1097-1107.
    13. Eitan, Avri & Herman, Lior & Fischhendler, Itay & Rosen, Gillad, 2019. "Community–private sector partnerships in renewable energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 95-104.
    14. Fang, Debin & Zhao, Chaoyang & Kleit, Andrew N., 2019. "The impact of the under enforcement of RPS in China: An evolutionary approach," Energy Policy, Elsevier, vol. 135(C).
    15. Buffat, René & Grassi, Stefano & Raubal, Martin, 2018. "A scalable method for estimating rooftop solar irradiation potential over large regions," Applied Energy, Elsevier, vol. 216(C), pages 389-401.
    16. Seyed Abbas Mousavi Maleki & H. Hizam & Chandima Gomes, 2017. "Estimation of Hourly, Daily and Monthly Global Solar Radiation on Inclined Surfaces: Models Re-Visited," Energies, MDPI, vol. 10(1), pages 1-28, January.
    17. Cheng, Hsu-Yung & Yu, Chih-Chang & Lin, Chih-Lung, 2021. "Day-ahead to week-ahead solar irradiance prediction using convolutional long short-term memory networks," Renewable Energy, Elsevier, vol. 179(C), pages 2300-2308.
    18. Ceballos-Fuentealba, Irlanda & Álvarez-Miranda, Eduardo & Torres-Fuchslocher, Carlos & del Campo-Hitschfeld, María Luisa & Díaz-Guerrero, John, 2019. "A simulation and optimisation methodology for choosing energy efficiency measures in non-residential buildings," Applied Energy, Elsevier, vol. 256(C).
    19. Dahmani, Kahina & Notton, Gilles & Voyant, Cyril & Dizene, Rabah & Nivet, Marie Laure & Paoli, Christophe & Tamas, Wani, 2016. "Multilayer Perceptron approach for estimating 5-min and hourly horizontal global irradiation from exogenous meteorological data in locations without solar measurements," Renewable Energy, Elsevier, vol. 90(C), pages 267-282.
    20. Qyyum, Muhammad Abdul & Dickson, Rofice & Ali Shah, Syed Fahad & Niaz, Haider & Khan, Amin & Liu, J. Jay & Lee, Moonyong, 2021. "Availability, versatility, and viability of feedstocks for hydrogen production: Product space perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:12:y:2019:i:8:p:1427-:d:222587. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.