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Artificial Intelligence Techniques for Solar Irradiance and PV Modeling and Forecasting

Author

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  • Fouzi Harrou

    (Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia)

  • Ying Sun

    (Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia)

  • Bilal Taghezouit

    (Centre de Développement des Energies Renouvelables, CDER, B.P. 62, Route de l’Observatoire, Algiers 16340, Algeria)

  • Abdelkader Dairi

    (Computer Science Department, University of Science and Technology of Oran-Mohamed Boudiaf, USTO-MB, BP 1505, El Mnaouar, Bir El Djir 10587, Algeria)

Abstract

Solar Photovoltaic (PV) systems represent key and transformative technology at the forefront of the global shift towards sustainable energy solutions [...]

Suggested Citation

  • Fouzi Harrou & Ying Sun & Bilal Taghezouit & Abdelkader Dairi, 2023. "Artificial Intelligence Techniques for Solar Irradiance and PV Modeling and Forecasting," Energies, MDPI, vol. 16(18), pages 1-5, September.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:18:p:6731-:d:1244326
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    References listed on IDEAS

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    1. Sajid Sarwar & Muhammad Annas Hafeez & Muhammad Yaqoob Javed & Aamer Bilal Asghar & Krzysztof Ejsmont, 2022. "A Horse Herd Optimization Algorithm (HOA)-Based MPPT Technique under Partial and Complex Partial Shading Conditions," Energies, MDPI, vol. 15(5), pages 1-22, March.
    2. Elmamoune Halassa & Lakhdar Mazouz & Abdellatif Seghiour & Aissa Chouder & Santiago Silvestre, 2023. "Revolutionizing Photovoltaic Systems: An Innovative Approach to Maximum Power Point Tracking Using Enhanced Dandelion Optimizer in Partial Shading Conditions," Energies, MDPI, vol. 16(9), pages 1-23, April.
    3. Faris E. Alfaris, 2023. "A Sensorless Intelligent System to Detect Dust on PV Panels for Optimized Cleaning Units," Energies, MDPI, vol. 16(3), pages 1-17, January.
    4. Wilson Castillo-Rojas & Fernando Medina Quispe & César Hernández, 2023. "Photovoltaic Energy Forecast Using Weather Data through a Hybrid Model of Recurrent and Shallow Neural Networks," Energies, MDPI, vol. 16(13), pages 1-25, July.
    5. Fouzi Harrou & Bilal Taghezouit & Sofiane Khadraoui & Abdelkader Dairi & Ying Sun & Amar Hadj Arab, 2022. "Ensemble Learning Techniques-Based Monitoring Charts for Fault Detection in Photovoltaic Systems," Energies, MDPI, vol. 15(18), pages 1-28, September.
    6. Jesús Polo & Nuria Martín-Chivelet & Miguel Alonso-Abella & Carlos Sanz-Saiz & José Cuenca & Marina de la Cruz, 2023. "Exploring the PV Power Forecasting at Building Façades Using Gradient Boosting Methods," Energies, MDPI, vol. 16(3), pages 1-12, February.
    7. Jingwei Zhang & Zenan Yang & Kun Ding & Li Feng & Frank Hamelmann & Xihui Chen & Yongjie Liu & Ling Chen, 2022. "Modeling of Photovoltaic Array Based on Multi-Agent Deep Reinforcement Learning Using Residuals of I–V Characteristics," Energies, MDPI, vol. 15(18), pages 1-17, September.
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    Cited by:

    1. Latifa A. Yousef & Hibba Yousef & Lisandra Rocha-Meneses, 2023. "Artificial Intelligence for Management of Variable Renewable Energy Systems: A Review of Current Status and Future Directions," Energies, MDPI, vol. 16(24), pages 1-27, December.

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