IDEAS home Printed from https://ideas.repec.org/a/gam/jforec/v7y2025i1p13-d1609971.html
   My bibliography  Save this article

Forecasting Wind Speed Using Climate Variables

Author

Listed:
  • Rafael Araujo Couto

    (Department of Industrial Engineering, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rio de Janeiro 22541-041, Brazil)

  • Paula Medina Maçaira Louro

    (Department of Industrial Engineering, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rio de Janeiro 22541-041, Brazil)

  • Fernando Luiz Cyrino Oliveira

    (Department of Industrial Engineering, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rio de Janeiro 22541-041, Brazil)

Abstract

Wind energy in Brazil has been steadily growing, influenced significantly by climate change. To enhance wind energy generation, it is essential to incorporate external climatic variables into wind speed modeling to reduce uncertainties. Periodic Autoregressive Models with Exogenous Variables (PARX), which include the exogenous variable ENSO, are effective for this purpose. This study modeled wind speed series in Rio Grande do Norte, Paraíba, Pernambuco, Alagoas, Sergipe, Rio Grande do Sul, and Santa Catarina, considering the spatial correlation between these states through PARX-Cov modeling. Additionally, the correlation with ENSO indicators was used for out-of-sample prediction of climatic variables, aiding in wind speed scenario simulation. The proposed PARX and PARX-Cov models outperformed the current model used in the Brazilian electric sector for simulating future wind speed series. Specifically, the PARX-Cov model with the Cumulative ONI index is most suitable for Pernambuco, Rio Grande do Sul, and Santa Catarina, while the PARX-Cov with the SOI index is more appropriate for Rio Grande do Norte. For Alagoas and Sergipe, the PARX with the Cumulative ONI index is the best fit, and the PARX with the Cumulative Niño 4 index is most suitable for Paraíba.

Suggested Citation

  • Rafael Araujo Couto & Paula Medina Maçaira Louro & Fernando Luiz Cyrino Oliveira, 2025. "Forecasting Wind Speed Using Climate Variables," Forecasting, MDPI, vol. 7(1), pages 1-23, March.
  • Handle: RePEc:gam:jforec:v:7:y:2025:i:1:p:13-:d:1609971
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2571-9394/7/1/13/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2571-9394/7/1/13/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Anderson Mitterhofer Iung & Fernando Luiz Cyrino Oliveira & André Luís Marques Marcato, 2023. "A Review on Modeling Variable Renewable Energy: Complementarity and Spatial–Temporal Dependence," Energies, MDPI, vol. 16(3), pages 1-24, January.
    2. Efstathios Paparoditis & Dimitris N. Politis, 2018. "The asymptotic size and power of the augmented Dickey–Fuller test for a unit root," Econometric Reviews, Taylor & Francis Journals, vol. 37(9), pages 955-973, October.
    3. A. I. McLeod, 1995. "Diagnostic Checking Of Periodic Autoregression Models With Application," Journal of Time Series Analysis, Wiley Blackwell, vol. 16(6), pages 647-648, November.
    4. Perini de Souza, Noele Bissoli & Sperandio Nascimento, Erick Giovani & Bandeira Santos, Alex Alisson & Moreira, Davidson Martins, 2022. "Wind mapping using the mesoscale WRF model in a tropical region of Brazil," Energy, Elsevier, vol. 240(C).
    5. de Aquino Ferreira, Saulo Custodio & Cyrino Oliveira, Fernando Luiz & Maçaira, Paula Medina, 2022. "Validation of the representativeness of wind speed time series obtained from reanalysis data for Brazilian territory," Energy, Elsevier, vol. 258(C).
    6. Ferreira, Pedro Guilherme Costa & Oliveira, Fernando Luiz Cyrino & Souza, Reinaldo Castro, 2015. "The stochastic effects on the Brazilian Electrical Sector," Energy Economics, Elsevier, vol. 49(C), pages 328-335.
    7. Staffell, Iain & Pfenninger, Stefan, 2016. "Using bias-corrected reanalysis to simulate current and future wind power output," Energy, Elsevier, vol. 114(C), pages 1224-1239.
    8. Gruber, Katharina & Klöckl, Claude & Regner, Peter & Baumgartner, Johann & Schmidt, Johannes, 2019. "Assessing the Global Wind Atlas and local measurements for bias correction of wind power generation simulated from MERRA-2 in Brazil," Energy, Elsevier, vol. 189(C).
    9. Cardoso de Mendonça, Mário Jorge & Moreira Pessanha, José Francisco & Andrade de Almeida, Victor & Toscano Medrano, Luiz Alberto & Hunt, Julian David & Pereira Junior, Amaro Olímpio & Nogueira, Erika , 2024. "Synthetic wind speed time series generation by dynamic factor model," Renewable Energy, Elsevier, vol. 228(C).
    10. Escobari, Diego & Garcia, Sergio & Mellado, Cristhian, 2017. "Identifying bubbles in Latin American equity markets: Phillips-Perron-based tests and linkages," Emerging Markets Review, Elsevier, vol. 33(C), pages 90-101.
    11. Huang, Xu & Maçaira, Paula Medina & Hassani, Hossein & Cyrino Oliveira, Fernando Luiz & Dhesi, Gurjeet, 2019. "Hydrological natural inflow and climate variables: Time and frequency causality analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 480-495.
    12. Pfenninger, Stefan & Staffell, Iain, 2016. "Long-term patterns of European PV output using 30 years of validated hourly reanalysis and satellite data," Energy, Elsevier, vol. 114(C), pages 1251-1265.
    13. Anup Suryawanshi & Debraj Ghosh, 2015. "Wind speed prediction using spatio-temporal covariance," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 75(2), pages 1435-1449, January.
    14. Olauson, Jon & Bergkvist, Mikael, 2015. "Modelling the Swedish wind power production using MERRA reanalysis data," Renewable Energy, Elsevier, vol. 76(C), pages 717-725.
    Full references (including those not matched with items on IDEAS)

    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. de Aquino Ferreira, Saulo Custodio & Cyrino Oliveira, Fernando Luiz & Maçaira, Paula Medina, 2022. "Validation of the representativeness of wind speed time series obtained from reanalysis data for Brazilian territory," Energy, Elsevier, vol. 258(C).
    2. Gruber, Katharina & Regner, Peter & Wehrle, Sebastian & Zeyringer, Marianne & Schmidt, Johannes, 2022. "Towards global validation of wind power simulations: A multi-country assessment of wind power simulation from MERRA-2 and ERA-5 reanalyses bias-corrected with the global wind atlas," Energy, Elsevier, vol. 238(PA).
    3. Melo, Gustavo de Andrade & Cyrino Oliveira, Fernando Luiz & Maçaira, Paula Medina & Meira, Erick, 2025. "Exploring complementary effects of solar and wind power generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 209(C).
    4. Grothe, Oliver & Kächele, Fabian & Wälde, Mira, 2025. "High-resolution working layouts and time series for renewable energy generation in Europe," Renewable Energy, Elsevier, vol. 239(C).
    5. Johann Baumgartner & Katharina Gruber & Sofia G. Simoes & Yves-Marie Saint-Drenan & Johannes Schmidt, 2020. "Less Information, Similar Performance: Comparing Machine Learning-Based Time Series of Wind Power Generation to Renewables.ninja," Energies, MDPI, vol. 13(9), pages 1-23, May.
    6. Moraes, L. & Bussar, C. & Stoecker, P. & Jacqué, Kevin & Chang, Mokhi & Sauer, D.U., 2018. "Comparison of long-term wind and photovoltaic power capacity factor datasets with open-license," Applied Energy, Elsevier, vol. 225(C), pages 209-220.
    7. Hayes, Liam & Stocks, Matthew & Blakers, Andrew, 2021. "Accurate long-term power generation model for offshore wind farms in Europe using ERA5 reanalysis," Energy, Elsevier, vol. 229(C).
    8. Madeleine McPherson & Theofilos Sotiropoulos-Michalakakos & LD Danny Harvey & Bryan Karney, 2017. "An Open-Access Web-Based Tool to Access Global, Hourly Wind and Solar PV Generation Time-Series Derived from the MERRA Reanalysis Dataset," Energies, MDPI, vol. 10(7), pages 1-14, July.
    9. Marko Hočevar & Lovrenc Novak & Primož Drešar & Gašper Rak, 2022. "The Status Quo and Future of Hydropower in Slovenia," Energies, MDPI, vol. 15(19), pages 1-13, September.
    10. Lukas Kriechbaum & Philipp Gradl & Romeo Reichenhauser & Thomas Kienberger, 2020. "Modelling Grid Constraints in a Multi-Energy Municipal Energy System Using Cumulative Exergy Consumption Minimisation," Energies, MDPI, vol. 13(15), pages 1-23, July.
    11. Steinegger, Josef & Hammer, Andreas & Wallner, Stefan & Kienberger, Thomas, 2024. "Revolutionizing heat distribution: A method for harnessing industrial waste heat with supra-regional district heating networks," Applied Energy, Elsevier, vol. 372(C).
    12. Behrang Shirizadeh, Quentin Perrier, and Philippe Quirion, 2022. "How Sensitive are Optimal Fully Renewable Power Systems to Technology Cost Uncertainty?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    13. Omoyele, Olalekan & Hoffmann, Maximilian & Koivisto, Matti & Larrañeta, Miguel & Weinand, Jann Michael & Linßen, Jochen & Stolten, Detlef, 2024. "Increasing the resolution of solar and wind time series for energy system modeling: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    14. Liu, Hailiang & Andresen, Gorm Bruun & Greiner, Martin, 2018. "Cost-optimal design of a simplified highly renewable Chinese electricity network," Energy, Elsevier, vol. 147(C), pages 534-546.
    15. Géremi Gilson Dranka & Paula Ferreira, 2020. "Electric Vehicles and Biofuels Synergies in the Brazilian Energy System," Energies, MDPI, vol. 13(17), pages 1-22, August.
    16. Shirizadeh, Behrang & Quirion, Philippe, 2022. "The importance of renewable gas in achieving carbon-neutrality: Insights from an energy system optimization model," Energy, Elsevier, vol. 255(C).
    17. Gorre, Jachin & Ortloff, Felix & van Leeuwen, Charlotte, 2019. "Production costs for synthetic methane in 2030 and 2050 of an optimized Power-to-Gas plant with intermediate hydrogen storage," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    18. Shirizadeh, Behrang & Quirion, Philippe, 2021. "Low-carbon options for the French power sector: What role for renewables, nuclear energy and carbon capture and storage?," Energy Economics, Elsevier, vol. 95(C).
    19. Hoelzen, J. & Silberhorn, D. & Schenke, F. & Stabenow, E. & Zill, T. & Bensmann, A. & Hanke-Rauschenbach, R., 2025. "H2-powered aviation – Optimized aircraft and green LH2 supply in air transport networks," Applied Energy, Elsevier, vol. 380(C).
    20. Valencia-Díaz, Alejandro & Toro, Eliana M. & Hincapié, Ricardo A., 2025. "Optimal planning and management of the energy–water–carbon nexus in hybrid AC/DC microgrids for sustainable development of remote communities," Applied Energy, Elsevier, vol. 377(PB).

    More about this item

    Keywords

    wind speed; PARX; covariance; ENSO;
    All these keywords.

    Statistics

    Access and download statistics

    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:gam:jforec:v:7:y:2025:i:1:p:13-:d:1609971. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.