IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v147y2020ip1p515-528.html
   My bibliography  Save this article

Solar Irradiation Data Processing using estimator MatriceS (SIMS) validated for Portugal (southern Europe)

Author

Listed:
  • Silva, Hugo Gonçalves
  • Abreu, Edgar F.M.
  • Lopes, Francis M.
  • Cavaco, Afonso
  • Canhoto, Paulo
  • Neto, Jorge
  • Collares-Pereira, Manuel

Abstract

Accurate solar resource assessment is essential in all the different phases of solar energy systems design and implementation. On a local scale, the solar resource is best assessed from ground measurements and, if available, with the existence of complete time-series of hourly values for the long-term resource estimation. However, these usually suffer from the occurrence of data gaps that can be as large as several months for remote and/or less maintained stations. Such gaps hinder the correct assessment of solar availability and, for that matter, their filling is a crucial first step to perform an appropriate assessment. In this context, a method for Solar Irradiation Data Processing using estimator MatriceS (SIMS) has been developed and is presented here. The algorithm allows to determine long-term linear correlations between a network of spatially distributed stations and, with these, to identify possible outliers and to fill data gaps through the selection of the median value from the obtained estimations. The method is validated against global horizontal irradiation (GHI) data from a network that comprises 89 ground-measuring stations, being maintained by the Portuguese Meteorology Service (IPMA - Instituto Português do Mar e da Atmosfera), considering a period of 17 years (from 2001 to 2017). Two important assertions are made for coefficients between stations: (1) coefficients only decrease slightly with the distance between stations (with a median reduction of ∼0.0003 km−1), for the considered network; (2) asymptotic long-term coefficients are reached with only one year of data. Taking advantage of the SIMS method, GHI assessment is presented here in the form of availability maps over the Portuguese mainland, with the respective values being listed in a table for future reference. The present assessment confirms that Portugal is a suitable region for the implementation of solar energy systems, with GHI having availabilities up to 2028.4 kWh/m2/year ±3.4% in Sagres (southernmost part of Portugal).

Suggested Citation

  • Silva, Hugo Gonçalves & Abreu, Edgar F.M. & Lopes, Francis M. & Cavaco, Afonso & Canhoto, Paulo & Neto, Jorge & Collares-Pereira, Manuel, 2020. "Solar Irradiation Data Processing using estimator MatriceS (SIMS) validated for Portugal (southern Europe)," Renewable Energy, Elsevier, vol. 147(P1), pages 515-528.
  • Handle: RePEc:eee:renene:v:147:y:2020:i:p1:p:515-528
    DOI: 10.1016/j.renene.2019.09.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148119313394
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2019.09.009?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. Abreu, Edgar F.M. & Canhoto, Paulo & Prior, Victor & Melicio, R., 2018. "Solar resource assessment through long-term statistical analysis and typical data generation with different time resolutions using GHI measurements," Renewable Energy, Elsevier, vol. 127(C), pages 398-411.
    3. Escobar, Rodrigo A. & Cortés, Cristián & Pino, Alan & Pereira, Enio Bueno & Martins, Fernando Ramos & Cardemil, José Miguel, 2014. "Solar energy resource assessment in Chile: Satellite estimation and ground station measurements," Renewable Energy, Elsevier, vol. 71(C), pages 324-332.
    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. Prasad, Ramendra & Ali, Mumtaz & Xiang, Yong & Khan, Huma, 2020. "A double decomposition-based modelling approach to forecast weekly solar radiation," Renewable Energy, Elsevier, vol. 152(C), pages 9-22.
    2. Graça Gomes, João & Jiang, Juan & Chong, Cheng Tung & Telhada, João & Zhang, Xu & Sammarchi, Sergio & Wang, Shuyang & Lin, Yu & Li, Jialong, 2023. "Hybrid solar PV-wind-battery system bidding optimisation: A case study for the Iberian and Italian liberalised electricity markets," Energy, Elsevier, vol. 263(PD).
    3. Ailton M. Tavares & Ricardo Conceição & Francisco M. Lopes & Hugo G. Silva, 2022. "Development of a Simple Methodology Using Meteorological Data to Evaluate Concentrating Solar Power Production Capacity," Energies, MDPI, vol. 15(20), pages 1-27, October.

    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. Armando Castillejo-Cuberos & José Miguel Cardemil & Rodrigo Escobar, 2021. "Analyzing Regional and Local Changes in Irradiance during the 2019 Total Solar Eclipse in Chile, Using Field Observations and Analytical Modeling," Energies, MDPI, vol. 14(17), pages 1-23, August.
    2. Paulescu, Marius & Badescu, Viorel & Budea, Sanda & Dumitrescu, Alexandru, 2022. "Empirical sunshine-based models vs online estimators for solar resources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    3. Choi, Kelvin, Tsz Hei & Brindley, Helen & Ekins-Daukes, N. & Escobar, Rodrigo, 2021. "Developing automated methods to estimate spectrally resolved direct normal irradiance for solar energy applications," Renewable Energy, Elsevier, vol. 173(C), pages 1070-1086.
    4. Gláucya Daú & Annibal Scavarda & Luiz Felipe Scavarda & Vivianne Julianelli Taveira Portugal, 2019. "The Healthcare Sustainable Supply Chain 4.0: The Circular Economy Transition Conceptual Framework with the Corporate Social Responsibility Mirror," Sustainability, MDPI, vol. 11(12), pages 1-19, June.
    5. Parrado, C. & Girard, A. & Simon, F. & Fuentealba, E., 2016. "2050 LCOE (Levelized Cost of Energy) projection for a hybrid PV (photovoltaic)-CSP (concentrated solar power) plant in the Atacama Desert, Chile," Energy, Elsevier, vol. 94(C), pages 422-430.
    6. Salazar, Germán & Checura Diaz, Miguel S. & Denegri, María J. & Tiba, Chigueru, 2015. "Identification of potential areas to achieve stable energy production using the SWERA database: A case study of northern Chile," Renewable Energy, Elsevier, vol. 77(C), pages 208-216.
    7. Antonanzas-Torres, F. & Sanz-Garcia, A. & Martínez-de-Pisón, F.J. & Antonanzas, J. & Perpiñán-Lamigueiro, O. & Polo, J., 2014. "Towards downscaling of aerosol gridded dataset for improving solar resource assessment, an application to Spain," Renewable Energy, Elsevier, vol. 71(C), pages 534-544.
    8. Starke, Allan R. & Cardemil, José M. & Escobar, Rodrigo & Colle, Sergio, 2018. "Multi-objective optimization of hybrid CSP+PV system using genetic algorithm," Energy, Elsevier, vol. 147(C), pages 490-503.
    9. Bessafi, Miloud & Oree, Vishwamitra & Khoodaruth, Abdel & Chabriat, Jean-Pierre, 2020. "Impact of decomposition and kriging models on the solar irradiance downscaling accuracy in regions with complex topography," Renewable Energy, Elsevier, vol. 162(C), pages 1992-2003.
    10. Habte, Aron & Sengupta, Manajit & Gueymard, Christian & Golnas, Anastasios & Xie, Yu, 2020. "Long-term spatial and temporal solar resource variability over America using the NSRDB version 3 (1998–2017)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    11. Antonanzas-Torres, F. & Sanz-Garcia, A. & Martínez-de-Pisón, F.J. & Perpiñán-Lamigueiro, O., 2013. "Evaluation and improvement of empirical models of global solar irradiation: Case study northern Spain," Renewable Energy, Elsevier, vol. 60(C), pages 604-614.
    12. Cornejo, Lorena & Martín-Pomares, Luis & Alarcon, Diego & Blanco, Julián & Polo, Jesús, 2017. "A through analysis of solar irradiation measurements in the region of Arica Parinacota, Chile," Renewable Energy, Elsevier, vol. 112(C), pages 197-208.
    13. David Abdul Konneh & Harun Or Rashid Howlader & Ryuto Shigenobu & Tomonobu Senjyu & Shantanu Chakraborty & Narayanan Krishna, 2019. "A Multi-Criteria Decision Maker for Grid-Connected Hybrid Renewable Energy Systems Selection Using Multi-Objective Particle Swarm Optimization," Sustainability, MDPI, vol. 11(4), pages 1-36, February.
    14. Marzo, Aitor & Ferrada, Pablo & Beiza, Felipe & Besson, Pierre & Alonso-Montesinos, Joaquín & Ballestrín, Jesús & Román, Roberto & Portillo, Carlos & Escobar, Rodrigo & Fuentealba, Edward, 2018. "Standard or local solar spectrum? Implications for solar technologies studies in the Atacama desert," Renewable Energy, Elsevier, vol. 127(C), pages 871-882.
    15. 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.
    16. 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.
    17. Gueymard, Christian A., 2014. "A review of validation methodologies and statistical performance indicators for modeled solar radiation data: Towards a better bankability of solar projects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 1024-1034.
    18. Song, Zhe & Liu, Jia & Yang, Hongxing, 2021. "Air pollution and soiling implications for solar photovoltaic power generation: A comprehensive review," Applied Energy, Elsevier, vol. 298(C).
    19. Jeffrey Walters & Jessica Kaminsky & Lawrence Gottschamer, 2018. "A Systems Analysis of Factors Influencing Household Solar PV Adoption in Santiago, Chile," Sustainability, MDPI, vol. 10(4), pages 1-17, April.
    20. Parrado, C. & Marzo, A. & Fuentealba, E. & Fernández, A.G., 2016. "2050 LCOE improvement using new molten salts for thermal energy storage in CSP plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 505-514.

    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:147:y:2020:i:p1:p:515-528. 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.