IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v135y2019icp98-107.html
   My bibliography  Save this article

Analysis of satellite derived solar irradiance in islands with site adaptation techniques for improving the uncertainty

Author

Listed:
  • Mazorra Aguiar, L.
  • Polo, J.
  • Vindel, J.M.
  • Oliver, A.

Abstract

Electrical energy production using renewable energies is one of the most important challenges in recent years. Among renewable energies, it is worth highlighting photovoltaic and thermoelectric systems due to their adaptation to the Canary Islands. One of the most important issues to ensure the stability for solar power systems, mostly in insular grids as Canary Islands, is the precise knowledge of solar radiation. In this paper, we focus in Gridded Satellite data suitability for modelling Global Horizontal Irradiation (GHI) in islands with complicated orography, as Canary Islands. Solar radiation data retrieved from CM SAF and McClear model were analysed and compared with 22 ground measurement stations in Canary Islands. Moreover, this analysis presents the results of including a site-adaptation methodology for improving satellite suitability. We used different procedures to perform this site adaptation depending on the solar radiation conditions (clear sky or cloudy sky hours), the location of the measurement station (we establish two clusters according to the climate conditions) and the season. This study could provide information about satellite models suitability in islands and a better knowledge of solar radiation behavior. Furthermore, accurate satellite radiation data for wide spatial and temporal coverage could improve solar radiation modelling and forecasting.

Suggested Citation

  • Mazorra Aguiar, L. & Polo, J. & Vindel, J.M. & Oliver, A., 2019. "Analysis of satellite derived solar irradiance in islands with site adaptation techniques for improving the uncertainty," Renewable Energy, Elsevier, vol. 135(C), pages 98-107.
    • Handle: RePEc:eee:renene:v:135:y:2019:i:c:p:98-107
    DOI: 10.1016/j.renene.2018.11.099
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148118314186
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2018.11.099?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Antonanzas-Torres, F. & Cañizares, F. & Perpiñán, O., 2013. "Comparative assessment of global irradiation from a satellite estimate model (CM SAF) and on-ground measurements (SIAR): A Spanish case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 248-261.
    2. Global Energy Assessment Writing Team,, 2012. "Global Energy Assessment," Cambridge Books, Cambridge University Press, number 9781107005198, September.
    3. Polo, J. & Antonanzas-Torres, F. & Vindel, J.M. & Ramirez, L., 2014. "Sensitivity of satellite-based methods for deriving solar radiation to different choice of aerosol input and models," Renewable Energy, Elsevier, vol. 68(C), pages 785-792.
    4. Global Energy Assessment Writing Team,, 2012. "Global Energy Assessment," Cambridge Books, Cambridge University Press, number 9780521182935, September.
    5. Polo, J. & Martín, L. & Vindel, J.M., 2015. "Correcting satellite derived DNI with systematic and seasonal deviations: Application to India," Renewable Energy, Elsevier, vol. 80(C), pages 238-243.
    6. Reno, Matthew J. & Hansen, Clifford W., 2016. "Identification of periods of clear sky irradiance in time series of GHI measurements," Renewable Energy, Elsevier, vol. 90(C), pages 520-531.
    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. 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).
    2. Han, Jen-Yu & Vohnicky, Petr, 2022. "An optimized approach for mapping solar irradiance in a mid-low latitude region based on a site-adaptation technique using Himawari-8 satellite imageries," Renewable Energy, Elsevier, vol. 187(C), pages 603-617.
    3. Papadopoulos, Agis M., 2020. "Renewable energies and storage in small insular systems: Potential, perspectives and a case study," Renewable Energy, Elsevier, vol. 149(C), pages 103-114.
    4. Barbón, A. & Fortuny Ayuso, P. & Bayón, L. & Fernández-Rubiera, J.A., 2020. "Predicting beam and diffuse horizontal irradiance using Fourier expansions," Renewable Energy, Elsevier, vol. 154(C), pages 46-57.
    5. Salamalikis, Vasileios & Tzoumanikas, Panayiotis & Argiriou, Athanassios A. & Kazantzidis, Andreas, 2022. "Site adaptation of global horizontal irradiance from the Copernicus Atmospheric Monitoring Service for radiation using supervised machine learning techniques," Renewable Energy, Elsevier, vol. 195(C), pages 92-106.
    6. Narvaez, Gabriel & Giraldo, Luis Felipe & Bressan, Michael & Pantoja, Andres, 2021. "Machine learning for site-adaptation and solar radiation forecasting," Renewable Energy, Elsevier, vol. 167(C), pages 333-342.
    7. Paredes, Paula & Trigo, Isabel & de Bruin, Henk & Simões, Nuno & Pereira, Luis S., 2021. "Daily grass reference evapotranspiration with Meteosat Second Generation shortwave radiation and reference ET products," Agricultural Water Management, Elsevier, vol. 248(C).

    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. Gueymard, Christian A. & Bright, Jamie M. & Lingfors, David & Habte, Aron & Sengupta, Manajit, 2019. "A posteriori clear-sky identification methods in solar irradiance time series: Review and preliminary validation using sky imagers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 412-427.
    2. Linares-Rodriguez, Alvaro & Quesada-Ruiz, Samuel & Pozo-Vazquez, David & Tovar-Pescador, Joaquin, 2015. "An evolutionary artificial neural network ensemble model for estimating hourly direct normal irradiances from meteosat imagery," Energy, Elsevier, vol. 91(C), pages 264-273.
    3. Tilmann Rave, 2013. "Innovationsindikatoren zum globalen Klimaschutz – FuE-Ausgaben und Patente," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 66(15), pages 34-41, August.
    4. Daniel Moran & Richard Wood, 2014. "Convergence Between The Eora, Wiod, Exiobase, And Openeu'S Consumption-Based Carbon Accounts," Economic Systems Research, Taylor & Francis Journals, vol. 26(3), pages 245-261, September.
    5. Lykke E. Andersen & Luis Carlos Jemio, 2016. "Decentralization and poverty reduction in Bolivia: Challenges and opportunities," Development Research Working Paper Series 01/2016, Institute for Advanced Development Studies.
    6. Inglesi-Lotz, Roula, 2017. "Social rate of return to R&D on various energy technologies: Where should we invest more? A study of G7 countries," Energy Policy, Elsevier, vol. 101(C), pages 521-525.
    7. Tom Mikunda & Tom Kober & Heleen de Coninck & Morgan Bazilian & Hilke R�sler & Bob van der Zwaan, 2014. "Designing policy for deployment of CCS in industry," Climate Policy, Taylor & Francis Journals, vol. 14(5), pages 665-676, September.
    8. Jun Nakatani & Tamon Maruyama & Kosuke Fukuchi & Yuichi Moriguchi, 2015. "A Practical Approach to Screening Potential Environmental Hotspots of Different Impact Categories in Supply Chains," Sustainability, MDPI, vol. 7(9), pages 1-15, August.
    9. Fichter, Tobias & Soria, Rafael & Szklo, Alexandre & Schaeffer, Roberto & Lucena, Andre F.P., 2017. "Assessing the potential role of concentrated solar power (CSP) for the northeast power system of Brazil using a detailed power system model," Energy, Elsevier, vol. 121(C), pages 695-715.
    10. Selosse, Sandrine & Ricci, Olivia & Maïzi, Nadia, 2013. "Fukushima's impact on the European power sector: The key role of CCS technologies," Energy Economics, Elsevier, vol. 39(C), pages 305-312.
    11. Kamjoo, Azadeh & Maheri, Alireza & Putrus, Ghanim A., 2014. "Chance constrained programming using non-Gaussian joint distribution function in design of standalone hybrid renewable energy systems," Energy, Elsevier, vol. 66(C), pages 677-688.
    12. Mokri, Alaeddine & Aal Ali, Mona & Emziane, Mahieddine, 2013. "Solar energy in the United Arab Emirates: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 340-375.
    13. Perrihan Al-Riffai & Julian Blohmke & Clemens Breisinger & Manfred Wiebelt, 2015. "Harnessing the Sun and Wind for Economic Development? An Economy-Wide Assessment for Egypt," Sustainability, MDPI, vol. 7(6), pages 1-27, June.
    14. Kim, Yeong Jae & Wilson, Charlie, 2019. "Analysing energy innovation portfolios from a systemic perspective," Energy Policy, Elsevier, vol. 134(C).
    15. Sofia Dahlgren & Jonas Ammenberg, 2021. "Sustainability Assessment of Public Transport, Part II—Applying a Multi-Criteria Assessment Method to Compare Different Bus Technologies," Sustainability, MDPI, vol. 13(3), pages 1-30, January.
    16. Jan K. Kazak & Joanna A. Kamińska & Rafał Madej & Marta Bochenkiewicz, 2020. "Where Renewable Energy Sources Funds are Invested? Spatial Analysis of Energy Production Potential and Public Support," Energies, MDPI, vol. 13(21), pages 1-26, October.
    17. David Bryngelsson & Fredrik Hedenus & Daniel J. A. Johansson & Christian Azar & Stefan Wirsenius, 2017. "How Do Dietary Choices Influence the Energy-System Cost of Stabilizing the Climate?," Energies, MDPI, vol. 10(2), pages 1-13, February.
    18. Jin-Young Kim & Hyun-Goo Kim & Yong-Heack Kang, 2017. "Offshore Wind Speed Forecasting: The Correlation between Satellite-Observed Monthly Sea Surface Temperature and Wind Speed over the Seas around the Korean Peninsula," Energies, MDPI, vol. 10(7), pages 1-15, July.
    19. Frame, Damien & Hannon, Matthew & Bell, Keith & McArthur, Stephen, 2018. "Innovation in regulated electricity distribution networks: A review of the effectiveness of Great Britain's Low Carbon Networks Fund," Energy Policy, Elsevier, vol. 118(C), pages 121-132.
    20. Silva Herran, Diego & Dai, Hancheng & Fujimori, Shinichiro & Masui, Toshihiko, 2016. "Global assessment of onshore wind power resources considering the distance to urban areas," Energy Policy, Elsevier, vol. 91(C), pages 75-86.

    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:eee:renene:v:135:y:2019:i:c:p:98-107. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    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.