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Optimizing Hybrid Renewable Power Plants: A Comparative Analysis of Wind–Solar Configurations for Northeast Brazil

Author

Listed:
  • Isabella Branco Renolphi

    (Institute of Energy and Environment (IEE), Universidade de São Paulo (USP), São Paulo 05508-900, Brazil)

  • Walquiria N. Silva

    (Institute of Energy and Environment (IEE), Universidade de São Paulo (USP), São Paulo 05508-900, Brazil)

  • Luís Felipe Normandia Lourenço

    (Institute of Energy and Environment (IEE), Universidade de São Paulo (USP), São Paulo 05508-900, Brazil)

  • Bruno Z. D. Malta

    (Escola Politécnica, Universidade de São Paulo (USP), São Paulo 05508-010, Brazil)

  • Thiago S. Andrade

    (Escola Politécnica, Universidade de São Paulo (USP), São Paulo 05508-010, Brazil)

  • Giovani G. T. Vieira

    (Escola Politécnica, Universidade de São Paulo (USP), São Paulo 05508-010, Brazil)

Abstract

The transition to sustainable electricity grids, particularly in countries with high renewable potential, such as Brazil, requires integrated assessments of hybrid and single-source configurations. This study analyzed the technical and economic feasibility of hybrid plants and isolated wind and solar systems in the Brazilian Northeast, focusing on Macaíba (RN) and Casa Nova (BA), regions characterized by high resource availability. The work addresses a gap in the literature by integrating detailed technical modeling and financial analysis of hybrid configurations, considering both local and operational constraints. Hourly simulations were performed using the HyDesign software (v1.1.0), with optimization based on the ratio between net present value (NPV) and invested capital (CAPEX), covering seven different scenarios by location, including hybrid combinations and systems with solar trackers. The results indicated that systems with solar tracking achieved superior economic performance. In Macaíba, the optimal configuration was the hybrid scenario with trackers, which increased the NPV/CAPEX by 27.69% compared to the relevant baseline. In Casa Nova, the best solution was the pure solar plant with trackers, which increased the NPV/CAPEX by 50.0% compared to fixed solar. Hybridization showed moderate gains in scenarios without tracking. It is concluded that while solar trackers are highly beneficial, the optimal plant configuration (pure solar or hybrid) is site-specific and depends on the local renewable resource profile. Notably, battery storage was not economically justified under the evaluated cost assumptions. The study contributes to the planning of renewable projects in contexts of high source complementarity.

Suggested Citation

  • Isabella Branco Renolphi & Walquiria N. Silva & Luís Felipe Normandia Lourenço & Bruno Z. D. Malta & Thiago S. Andrade & Giovani G. T. Vieira, 2025. "Optimizing Hybrid Renewable Power Plants: A Comparative Analysis of Wind–Solar Configurations for Northeast Brazil," Energies, MDPI, vol. 18(20), pages 1-25, October.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:20:p:5329-:d:1767741
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    References listed on IDEAS

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    1. Ioan Cristian Hoarcă & Nicu Bizon & Ioan Sorin Șorlei & Phatiphat Thounthong, 2023. "Sizing Design for a Hybrid Renewable Power System Using HOMER and iHOGA Simulators," Energies, MDPI, vol. 16(4), pages 1-25, February.
    2. Aqib Khan & Mathieu Bressel & Arnaud Davigny & Dhaker Abbes & Belkacem Ould Bouamama, 2025. "Comprehensive Review of Hybrid Energy Systems: Challenges, Applications, and Optimization Strategies," Energies, MDPI, vol. 18(10), pages 1-34, May.
    3. Ana Tereza Andrade Borba & Leonardo Jaime Machado Simões & Thamiles Rodrigues de Melo & Alex Álisson Bandeira Santos, 2024. "Techno-Economic Assessment of a Hybrid Renewable Energy System for a County in the State of Bahia," Energies, MDPI, vol. 17(3), pages 1-18, January.
    4. Kingsley Ukoba & Kehinde O. Olatunji & Eyitayo Adeoye & Tien-Chien Jen & Daniel M. Madyira, 2024. "Optimizing renewable energy systems through artificial intelligence: Review and future prospects," Energy & Environment, , vol. 35(7), pages 3833-3879, November.
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