COMPARATIVE ANALYSIS BETWEEN SATELLITE-DERIVED SPECTRAL ALBEDO AND FIELD ALBEDO MEASUREMENTS
A CASE STUDY FOR PORTABLE ALBEDO BENCH VALIDATION
DOI:
https://doi.org/10.59627/cbens.2022.1135Keywords:
Albedo, Remote Sensing, Albedo Measurement BenchAbstract
Perusing to increase the specific production (MWh/MWp), a large part of the new photovoltaic projects is adopting bifacial photovoltaic modules, capable of performing the energy conversion on both sides of the module, taking advantage of reflected solar radiation (albedo) by the ground cover. Therefore, when selecting a site to receive a new photovoltaic plant, it is of extreme importance to be in a place with a ground cover that already offers a high albedo value. Using remote sensing to find the albedo of a site has the advantage of having a relatively low cost to filter places of interest, in addition to allowing the imaging of large areas that are difficult to reach or lacking in information. However, installing fixed stations to confirm these measurements are relatively expensive due to the requirement of advanced equipment. This work proposes to use a portable albedo measurement bench as an intermediate between these two steps, measuring by remote sensing and validation with fixed stations. With a portable bench, it would be possible to validate several previously identified points of interest and limit the installation of fixed stations for a high temporal resolution campaign only to the places of high potential albedo previously measured in the field with the portable bench.
Downloads
References
Alvarez, C. A.; Stape, J. L.; Sentelhas, P. C.; Gonçalves, J. L. M.; Sparovek, G. 2013. Köppen’s climate classification map for Brazil, Meteorologische Zeitschrift, vol. 22, n. 6. pp. 711-728.
ASTM E1918-16. Standard Test Method for Measuring Solar Reflectance of Horizontal and Low-Sloped Surfaces in the Field. ASTM International, [s. l.], v. i, n. Reapproved 2015, 2016.
Barreto, A. M. F.; Suguio, K.; Bezerra, F. H. R.; Tatumi, S. H.; Yee, M.; Giannini, P, C. F. 2004. Geologia e geomorfologia do quaternário costeiro do estado do Rio Grande do Norte, Revista do Instituto de Geociências, vol. 4, n. 2, pp. 1-12.
Bayless, D. 2005. Statistical Rejection of “Bad” Data–Chauvenet’s Criterion. Disponível em: https:// chetaero.files.wordpress.com/2016/11/chauvenet.pdf. Acesso em Dez. 2021.
Bezerra, F. H. R.; Amaro, V. E. Sensoriamento remoto aplicado à neotectônica da faixa litorânea oriental do estado do Rio Grande do Norte, IX SBSR – IX Simpósio Brasileiro de Sensoriamento Remoto, Santos.
Callegare, A. O.; Lopes, C. R.; Souza, L. J.; Brizolla, M. C.; Honorata, V. 2011. Estudo sobre o albedo em diferentes tipos de superfície, 10p. Disponível em: http:// meteorologia.florianopolis.ifsc.edu.br/formularioPI/arquivos_de_usuario/201022B.pdf. Acesso em Dez. 2021.
Chavez, J. P. S. 1989. An improved dark-object subtration technique for atmospheric scattering correction of multispectral data, Remoste Sensing of Environmet, v. 62, n. 3, pp. 451 – 479.
Chen, S. C.; Herz, R. 1996. Estudos quantitativos e calibração radiométrica de dados digitais do Landsat-5, VIII SBSR – VIII Simpósio Brasileiro de Sensoriamento Remoto, Salvador.
Congedo, L. 2021. Semi-Automatic Classification Plugin: A Python tool for the download and processing of remote sensing images in QGI, The Journal of Open Source Software, vol. 6, n. 64, pp. 3172.
EPE. Relatório Síntese Balanço Energético Nacional 2021. Balanço nacional de energia, [s. l.], 2021. Disponível em: https://www.epe.gov.br/pt/publicacoes-dados-abertos/publicacoes/balanco-energetico-nacional-2021. Acesso em Dez. 2021.
IEA. Renewables – Global Energy Review 2021 – Analysis. Global Energy Review 2021, [s. l.], 2021. Disponível em: https://www.iea.org/reports/global-energy-review-2021. Acesso em Dez. 2021.
Greener. Estudo Estratégico Grandes Usinas Solares 2021. [S. l.: s. n.], 2021. Disponível em: https://www.greener.com.br/estudo/estudo-estrategico-grandes-usinas-solares-2021/. Acesso em Dec. 2021.
Instituto Nacional de Meteorologia. 2021. Dados das séries temporais climáticas da Rede do INMET. Disponível em: http://www.inmet.gov.br. Acesso em Set 2021.
Lindsay, A.; Chiodetti, M.; Dupeyrat, P.; Binesti, D.; Lutun, E.; Radouane K. Key elements in the design of bifacial PV power plants. 31st EU PVSEC, [s. l.], p. 1764–1769, 2015.
Luque, A.; Cuevas, A.; Ruiz, J. M. DOUBLE-SIDED n+ -p-n+ SOLAR CELL FOR BIFACIAL CONCENTRATION. Solar Cells: Their Science, Technology, Applications and Economics, [s. l.], v. 2, n. 2, p. 151–166, 1980.
Matthew, M. W.; Adler-Golden, S.M.; Berk, A. S. C.; Richtsmeier, R. Y.; Levine, L. S.; Bernstein, P. K.; Acharya, G. P.; Anderson, G. W.; Felde, M. P.; Hoke, A.; Ratkowski, H. H.; Burke, R. D.; Miller, D. P. 2000. Status of Atmospheric Correction Using a MODTRAN4-based Algorithm. SPIE Proceedings, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery, vol. 6, n. 4049, pp. 199-207.
Otterman, J. 1977. Anthropogenic impact on the albedo of the earth, Climate Change, vol 1, pp. 137-155.
PV Lighthouse, c2021. Solar Path Calculator - Version 1.1, 20-August-2013. Disponível em: https://www.pvlighthouse.com.au/calculator-map. Acesso em Dec. 2021.
Rocha, A. V.; Oliveira, C. C. A.; Lima, J. A. R.; Paula, J. C. O.; Souza, S. S. 2012, VII CONNEPI – VII Congresso Norte Nordeste de Pesquisa e Inovação, Palmas.
Rosenberg, N. J.; Blad, B. L.; Verma, S. B. 1983. Microclimate: the biological environment. 2ª ed. Wiley-Interscience, New York.
Sanches, I. D.; Andrade, R. G.; Quartaroli, C. F.; Rodrigues, C. A. G. 2011. Análise comparativa de três métodos de correção atmosférica de imagens Landsata 5 - TM para obtenção de reflectância de superfície e NDVI, XV SBSR – XV Simpósio Brasileiro de Sensoriamento Remoto, Curitiba.
Sousa Júnior, J. G. A.; Demattê, J. A. M.; Genú, A. M. 2008. Comportamento espectral dos solos na paisagem a partir de dados coletados por sensores terrestre e orbital, Revista Brasileira de Ciência do Solo, vol. 32, pp. 727-738.
Silva, B. B.; Braga, A. C.; Braga, C. C.; Oliveira, L. M. M.; Montenegro, S. M. G. L.; Barbosa Júnior, B. 2018. Procedures for calculation of the albedo with OLI-Landsat 8 images: application to the Brazilian semi-arid, Revista Brasileira de Engenharia Agrícola e Ambiental, vol. 20, n. 1, pp. 3 – 8.
VDMA. International Technology Roadmap for Photovoltaic - 2020 Results. VDMA, [s. l.], v. 12th Ed., n. March 2021, 2021. Disponível em: https://itrpv.vdma.org. Acesso em Dez. 2021.
Wang, T.; Shushi, P.; Krinner, G.; Ryder, J.; Li, Y.; Nédélec, S. D.; Ottlé, C. 2015. Impacts of satellite-based snow albedo assimilation on Offline and Coupled Land Surface Model Simulations, Plos One, 0137275, pp. 1 – 9.
Wang, Z.; Erb, A. M.; Schaaf, C. B.; Sun, Q.; Liu, Y.; Yang, Y.; Shuai, Y.; Casey, K. A.; Román, M. O. 2016. Early spring post-fire snow albedo dynamics in high latitude boreal forest using Landsat-8 OLI data, Remote Sensing of Environment, vol. 185, pp. 71-83.
