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Effect of Solar Irradiation Inter-Annual Variability on PV and CSP Power Plants Production Capacity: Portugal Case-Study

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  • Ailton M. Tavares

    (Cátedra Energias Renováveis, IIFA, Universidade de Évora, Edifício Ário Lobo de Azevedo, Nossa Senhora da Tourega, 7000-083 Évora, Portugal
    Instituto de Ciências da Terra (ICT), IIFA, Universidade de Évora, Rua Romão Ramalho 59, 7002-554 Évora, Portugal
    Laboratório Associado de Energia, Transporte e Aeronáutica (LAETA), Universidade de Évora, Rua Romão Ramalho 59, 7002-554 Évora, Portugal)

  • Ricardo Conceição

    (High Temperature Processes Unit, IMDEA Energy, Avda. Ramón de La Sagra 3, 28935 Móstoles, Madrid, Spain)

  • Francisco M. Lopes

    (Instituto Dom Luiz (IDL), Faculdade de Ciências, Universidade de Lisboa, Campo Grande, 1749-016 Lisboa, Portugal
    Instituto Português do Mar e da Atmosfera (IPMA), Rua C ao Aeroporto, 1749-077 Lisboa, Portugal)

  • Hugo G. Silva

    (Laboratório Associado de Energia, Transporte e Aeronáutica (LAETA), Universidade de Évora, Rua Romão Ramalho 59, 7002-554 Évora, Portugal
    Departamento de Física, ECT, Universidade de Évora, Rua Romão Ramalho 59, 7002-554 Évora, Portugal
    INEGI Alentejo, Universidade de Évora, Largo dos Colegiais 2, 7000-803 Évora, Portugal)

Abstract

The sizing of solar energy power plants is usually made using typical meteorological years, which disregards the inter-annual variability of the solar resource. Nevertheless, such variability is crucial for the bankability of these projects because it impacts on the production goals set at the time of the supply agreement. For that reason, this study aims to fill the gap in the existing literature and analyse the impact that solar resource variability has on solar power plant production as applied to the case of Portugal (southern Europe). To that end, 17 years (2003–2019) of meteorological data from a network of 90 ground stations hosted by the Portuguese Meteorological Service is examined. Annual capacity factor regarding photovoltaic (PV) and concentrating solar power (CSP) plants is computed using the System Advisor Model, used here for solar power performance simulations. In terms of results, while a long-term trend for increase in annual irradiation is found for Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI), 0.4148 and 3.2711 kWh/m 2 /year, respectively, consistent with a solar brightening period, no corresponding trend is found for PV or CSP production. The latter is attributed to the long-term upward trend of 0.0231 °C/year in annual average ambient temperature, which contributes to PV and CSP efficiency reduction. Spatial analysis of inter-annual relative variability for GHI and DNI shows a reduction in variability from the north to the south of the country, as well as for the respective power plant productions. Particularly, for PV, inter-annual variability ranges between 2.45% and 12.07% in Faro and Santarém, respectively, while higher values are generally found for CSP, 3.71% in Faro and 16.04% in São Pedro de Moel. These results are a contribution to future instalments of PV and CSP systems in southern Portugal, a region with very favourable conditions for solar energy harvesting, due to the combination of high production capacity and low inter-annual variability.

Suggested Citation

  • Ailton M. Tavares & Ricardo Conceição & Francisco M. Lopes & Hugo G. Silva, 2024. "Effect of Solar Irradiation Inter-Annual Variability on PV and CSP Power Plants Production Capacity: Portugal Case-Study," Energies, MDPI, vol. 17(21), pages 1-20, November.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:21:p:5490-:d:1512902
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    References listed on IDEAS

    as
    1. Lopes, Francis M. & Conceição, Ricardo & Fasquelle, Thomas & Silva, Hugo G. & Salgado, Rui & Canhoto, Paulo & Collares-Pereira, Manuel, 2020. "Predicted direct solar radiation (ECMWF) for optimized operational strategies of linear focus parabolic-trough systems," Renewable Energy, Elsevier, vol. 151(C), pages 378-391.
    2. Martin Wild, 2016. "Decadal changes in radiative fluxes at land and ocean surfaces and their relevance for global warming," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 7(1), pages 91-107, January.
    3. Kariuki, Boniface Wainaina & Sato, Tomonori, 2018. "Interannual and spatial variability of solar radiation energy potential in Kenya using Meteosat satellite," Renewable Energy, Elsevier, vol. 116(PA), pages 88-96.
    4. Cavaco, Afonso & Canhoto, Paulo & Collares Pereira, Manuel, 2021. "Procedures for solar radiation data gathering and processing and their application to DNI assessment in southern Portugal," Renewable Energy, Elsevier, vol. 163(C), pages 2208-2219.
    5. 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.
    6. Polo, J. & Téllez, F.M. & Tapia, C., 2016. "Comparative analysis of long-term solar resource and CSP production for bankability," Renewable Energy, Elsevier, vol. 90(C), pages 38-45.
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