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Spatio-temporal characterization of long-term solar resource using spatial functional data analysis: Understanding the variability and complementarity of global horizontal irradiance in Ecuador

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  • Tapia, Mariela
  • Heinemann, Detlev
  • Ballari, Daniela
  • Zondervan, Edwin

Abstract

Understanding the spatio-temporal variability of the solar resource is crucial to effectively support solar power utilization. Unfortunately, long-term and high-resolved measurements of solar irradiance are generally scarce, challenging the characterization for larger areas. In this paper, we propose a methodology to characterize the spatio-temporal variability of global horizontal irradiance (GHI) at a regional scale using long-term satellite-derived data. Spatial functional data analysis (sFDA) is used to identify areas with similar intra-annual variability patterns. The methodology is applied to a 21-year period data on Ecuador retrieved from the National Solar Radiation Database. Being the first time that sFDA is used for this purpose, the results indicate that it provides an appropriate basis for the interannual variability and complementarity analyses. In Ecuador's mainland, twenty-two subregions with four seasonal patterns are identified. The highest GHI potential (5.4 kWhm−2d−1) with the lowest variability (3.4%) is found in the Inter-Andean valleys. Further, seasonal complementarities between the coast and western Andes are identified. In Galapagos, high values are found over all islands (≥4.8 kWhm−2d−1), characterized by three subregions with one seasonal pattern. Our findings provide the first comprehensive spatio-temporal characterization of GHI in Ecuador, which aims at supporting a sustainable energy transition in the country.

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  • Tapia, Mariela & Heinemann, Detlev & Ballari, Daniela & Zondervan, Edwin, 2022. "Spatio-temporal characterization of long-term solar resource using spatial functional data analysis: Understanding the variability and complementarity of global horizontal irradiance in Ecuador," Renewable Energy, Elsevier, vol. 189(C), pages 1176-1193.
  • Handle: RePEc:eee:renene:v:189:y:2022:i:c:p:1176-1193
    DOI: 10.1016/j.renene.2022.03.049
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    1. Elvira Romano & Jorge Mateu & Ramon Giraldo, 2015. "On the performance of two clustering methods for spatial functional data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(4), pages 467-492, October.
    2. Laguarda, A. & Alonso-Suárez, R. & Terra, R., 2020. "Solar irradiation regionalization in Uruguay: Understanding the interannual variability and its relation to El Niño climatic phenomena," Renewable Energy, Elsevier, vol. 158(C), pages 444-452.
    3. Sun, Xixi & Bright, Jamie M. & Gueymard, Christian A. & Acord, Brendan & Wang, Peng & Engerer, Nicholas A., 2019. "Worldwide performance assessment of 75 global clear-sky irradiance models using Principal Component Analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 111(C), pages 550-570.
    4. Sengupta, Manajit & Xie, Yu & Lopez, Anthony & Habte, Aron & Maclaurin, Galen & Shelby, James, 2018. "The National Solar Radiation Data Base (NSRDB)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 51-60.
    5. Julien Jacques & Cristian Preda, 2014. "Functional data clustering: a survey," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 8(3), pages 231-255, September.
    6. R. Giraldo & P. Delicado & J. Mateu, 2012. "Hierarchical clustering of spatially correlated functional data," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 66(4), pages 403-421, November.
    7. Henao, Felipe & Viteri, Juan P. & Rodríguez, Yeny & Gómez, Juan & Dyner, Isaac, 2020. "Annual and interannual complementarities of renewable energy sources in Colombia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    8. 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).
    9. Cevallos-Sierra, Jaime & Ramos-Martin, Jesús, 2018. "Spatial assessment of the potential of renewable energy: The case of Ecuador," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1154-1165.
    10. Giraldo, Ramón & Dabo-Niang, Sophie & Martínez, Sergio, 2018. "Statistical modeling of spatial big data: An approach from a functional data analysis perspective," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 126-129.
    11. Cantão, Mauricio P. & Bessa, Marcelo R. & Bettega, Renê & Detzel, Daniel H.M. & Lima, João M., 2017. "Evaluation of hydro-wind complementarity in the Brazilian territory by means of correlation maps," Renewable Energy, Elsevier, vol. 101(C), pages 1215-1225.
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