Performance of Deep Learning Techniques for Forecasting PV Power Generation: A Case Study on a 1.5 MWp Floating PV Power Plant
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- Jirada Gosumbonggot & Goro Fujita, 2019. "Global Maximum Power Point Tracking under Shading Condition and Hotspot Detection Algorithms for Photovoltaic Systems," Energies, MDPI, vol. 12(5), pages 1-23, March.
- Watcharakorn Pinthurat & Branislav Hredzak, 2021. "Distributed Control Strategy of Single-Phase Battery Systems for Compensation of Unbalanced Active Powers in a Three-Phase Four-Wire Microgrid," Energies, MDPI, vol. 14(24), pages 1-17, December.
- Joshuva Arockia Dhanraj & Ali Mostafaeipour & Karthikeyan Velmurugan & Kuaanan Techato & Prem Kumar Chaurasiya & Jenoris Muthiya Solomon & Anitha Gopalan & Khamphe Phoungthong, 2021. "An Effective Evaluation on Fault Detection in Solar Panels," Energies, MDPI, vol. 14(22), pages 1-14, November.
- Promphak Dawan & Kobsak Sriprapha & Songkiate Kittisontirak & Terapong Boonraksa & Nitikorn Junhuathon & Wisut Titiroongruang & Surasak Niemcharoen, 2020. "Comparison of Power Output Forecasting on the Photovoltaic System Using Adaptive Neuro-Fuzzy Inference Systems and Particle Swarm Optimization-Artificial Neural Network Model," Energies, MDPI, vol. 13(2), pages 1-18, January.
- Wang, Kejun & Qi, Xiaoxia & Liu, Hongda, 2019. "A comparison of day-ahead photovoltaic power forecasting models based on deep learning neural network," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
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- Lanre Olatomiwa & Omowunmi Mary Longe & Toyeeb Adekunle Abd’Azeez & James Garba Ambafi & Kufre Esenowo Jack & Ahmad Abubakar Sadiq, 2023. "Optimal Planning and Deployment of Hybrid Renewable Energy to Rural Healthcare Facilities in Nigeria," Energies, MDPI, vol. 16(21), pages 1-24, October.
- Isaac Gallardo & Daniel Amor & Álvaro Gutiérrez, 2023. "Recent Trends in Real-Time Photovoltaic Prediction Systems," Energies, MDPI, vol. 16(15), pages 1-17, July.
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Keywords
floating PV power plant; deep learning techniques; short-term PV power forecasting; PV generation; neural networks;All these keywords.
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