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Wind and Solar Energy Generation Potential Features in the Extreme Northern Amazon Using Reanalysis Data

Author

Listed:
  • Jean Souza dos Reis

    (SENAI Institute of Innovation—Renewable Energies, Av. Capitão Mor-Gouveia, 2770-Lagoa Nova, Natal 59063-400, Brazil)

  • Nícolas de Assis Bose

    (SENAI Institute of Innovation—Renewable Energies, Av. Capitão Mor-Gouveia, 2770-Lagoa Nova, Natal 59063-400, Brazil
    Institute of Geosciences, Federal University of Rio Grande do Sul, Av. Bento Gonçalves, 9500, Bairro Agronomia, Porto Alegre 91501-970, Brazil)

  • Ana Cleide Bezerra Amorim

    (SENAI Institute of Innovation—Renewable Energies, Av. Capitão Mor-Gouveia, 2770-Lagoa Nova, Natal 59063-400, Brazil)

  • Vanessa de Almeida Dantas

    (SENAI Institute of Innovation—Renewable Energies, Av. Capitão Mor-Gouveia, 2770-Lagoa Nova, Natal 59063-400, Brazil)

  • Luciano Andre Cruz Bezerra

    (SENAI Institute of Innovation—Renewable Energies, Av. Capitão Mor-Gouveia, 2770-Lagoa Nova, Natal 59063-400, Brazil)

  • Leonardo de Lima Oliveira

    (SENAI Institute of Innovation—Renewable Energies, Av. Capitão Mor-Gouveia, 2770-Lagoa Nova, Natal 59063-400, Brazil)

  • Samira de Azevedo Emiliavaca

    (SENAI Institute of Innovation—Renewable Energies, Av. Capitão Mor-Gouveia, 2770-Lagoa Nova, Natal 59063-400, Brazil)

  • Maria de Fátima Alves de Matos

    (SENAI Institute of Innovation—Renewable Energies, Av. Capitão Mor-Gouveia, 2770-Lagoa Nova, Natal 59063-400, Brazil)

  • Nickollas Elias Targino Pereira

    (SENAI Institute of Innovation—Renewable Energies, Av. Capitão Mor-Gouveia, 2770-Lagoa Nova, Natal 59063-400, Brazil)

  • Raniere Rodrigues Melo de Lima

    (SENAI Institute of Innovation—Renewable Energies, Av. Capitão Mor-Gouveia, 2770-Lagoa Nova, Natal 59063-400, Brazil)

  • Antonio Marcos de Medeiros

    (SENAI Institute of Innovation—Renewable Energies, Av. Capitão Mor-Gouveia, 2770-Lagoa Nova, Natal 59063-400, Brazil)

Abstract

This article examines the potential for wind and solar energy generation in the state of Amapá, Brazil, using ERA5 data from between 1991 and 2020. Key metrics considered include wind power density, capacity factor, photovoltaic potential, and concentrated solar power output. Analyses revealed pronounced wind speeds offshore during summer and in continental regions during spring. Solar irradiance was notably higher in the spring. Differences in wind potential were observed between northern and southern offshore areas. Concentrated solar power efficiency and photovoltaic potential were influenced by location and cloud cover, respectively. Overall, summer presents the best offshore wind energy potential, while spring is optimal for onshore solar energy in Amapá. This study underscores the importance of understanding local climatic patterns when planning energy installations in the region.

Suggested Citation

  • Jean Souza dos Reis & Nícolas de Assis Bose & Ana Cleide Bezerra Amorim & Vanessa de Almeida Dantas & Luciano Andre Cruz Bezerra & Leonardo de Lima Oliveira & Samira de Azevedo Emiliavaca & Maria de F, 2023. "Wind and Solar Energy Generation Potential Features in the Extreme Northern Amazon Using Reanalysis Data," Energies, MDPI, vol. 16(22), pages 1-27, November.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:22:p:7671-:d:1283917
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    References listed on IDEAS

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    1. Ulazia, Alain & Sáenz, Jon & Ibarra-Berastegi, Gabriel & González-Rojí, Santos J. & Carreno-Madinabeitia, Sheila, 2019. "Global estimations of wind energy potential considering seasonal air density changes," Energy, Elsevier, vol. 187(C).
    2. Migoya, Emilio & Crespo, Antonio & Jiménez, Ángel & García, Javier & Manuel, Fernando, 2007. "Wind energy resource assessment in Madrid region," Renewable Energy, Elsevier, vol. 32(9), pages 1467-1483.
    3. Dasari, Hari Prasad & Desamsetti, Srinivas & Langodan, Sabique & Attada, Raju & Kunchala, Ravi Kumar & Viswanadhapalli, Yesubabu & Knio, Omar & Hoteit, Ibrahim, 2019. "High-resolution assessment of solar energy resources over the Arabian Peninsula," Applied Energy, Elsevier, vol. 248(C), pages 354-371.
    4. Pallabazzer, Rodolfo, 2004. "Previsional estimation of the energy output of windgenerators," Renewable Energy, Elsevier, vol. 29(3), pages 413-420.
    5. Aissatou Ndiaye & Mounkaila Saley Moussa & Cheikh Dione & Windmanagda Sawadogo & Jan Bliefernicht & Laouali Dungall & Harald Kunstmann, 2022. "Projected Changes in Solar PV and Wind Energy Potential over West Africa: An Analysis of CORDEX-CORE Simulations," Energies, MDPI, vol. 15(24), pages 1-22, December.
    6. Liu, Fa & Sun, Fubao & Liu, Wenbin & Wang, Tingting & Wang, Hong & Wang, Xunming & Lim, Wee Ho, 2019. "On wind speed pattern and energy potential in China," Applied Energy, Elsevier, vol. 236(C), pages 867-876.
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