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A simplified model for the estimation of energy production of PV systems

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  • Aste, Niccolò
  • Del Pero, Claudio
  • Leonforte, Fabrizio
  • Manfren, Massimiliano

Abstract

The potential of solar energy is far higher than any other renewable source, although several limits exist. In detail the fundamental factors that must be analyzed by investors and policy makers are the cost-effectiveness and the production of PV power plants, respectively, for the decision of investment schemes and energy policy strategies. Tools suitable to be used even by non-specialists, are therefore becoming increasingly important. Many research and development effort have been devoted to this goal in recent years.

Suggested Citation

  • Aste, Niccolò & Del Pero, Claudio & Leonforte, Fabrizio & Manfren, Massimiliano, 2013. "A simplified model for the estimation of energy production of PV systems," Energy, Elsevier, vol. 59(C), pages 503-512.
    • Handle: RePEc:eee:energy:v:59:y:2013:i:c:p:503-512
    DOI: 10.1016/j.energy.2013.07.004
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    3. Woo-Gyun Shin & Ju-Young Shin & Hye-Mi Hwang & Chi-Hong Park & Suk-Whan Ko, 2022. "Power Generation Prediction of Building-Integrated Photovoltaic System with Colored Modules Using Machine Learning," Energies, MDPI, vol. 15(7), pages 1-17, April.
    4. Kovač, Marko & Stegnar, Gašper & Al-Mansour, Fouad & Merše, Stane & Pečjak, Andrej, 2019. "Assessing solar potential and battery instalment for self-sufficient buildings with simplified model," Energy, Elsevier, vol. 173(C), pages 1182-1195.
    5. Dias, César Luiz de Azevedo & Castelo Branco, David Alves & Arouca, Maurício Cardoso & Loureiro Legey, Luiz Fernando, 2017. "Performance estimation of photovoltaic technologies in Brazil," Renewable Energy, Elsevier, vol. 114(PB), pages 367-375.
    6. Diego A. Flores-Hernández & Alberto Luviano-Juárez & Norma Lozada-Castillo & Octavio Gutiérrez-Frías & César Domínguez & Ignacio Antón, 2021. "Optimal Strategy for the Improvement of the Overall Performance of Dual-Axis Solar Tracking Systems," Energies, MDPI, vol. 14(22), pages 1-24, November.
    7. Del Pero, Claudio & Aste, Niccolò & Leonforte, Fabrizio, 2021. "The effect of rain on photovoltaic systems," Renewable Energy, Elsevier, vol. 179(C), pages 1803-1814.
    8. Raul Rotar & Sorin Liviu Jurj & Robert Susany & Flavius Opritoiu & Mircea Vladutiu, 2021. "Global Energy Production Computation of a Solar-Powered Smart Home Automation System Using Reliability-Oriented Metrics," Energies, MDPI, vol. 14(9), pages 1-23, April.
    9. Luigi Rubino & Guido Rubino & Raffaele Esempio, 2023. "Linear Programming-Based Power Management for a Multi-Feeder Ultra-Fast DC Charging Station," Energies, MDPI, vol. 16(3), pages 1-17, January.
    10. Barone, G. & Buonomano, A. & Cipolla, G. & Forzano, C. & Giuzio, G.F. & Russo, G., 2024. "Designing aggregation criteria for end-users integration in energy communities: Energy and economic optimisation based on hybrid neural networks models," Applied Energy, Elsevier, vol. 371(C).
    11. Francesco Mancini & Benedetto Nastasi, 2020. "Solar Energy Data Analytics: PV Deployment and Land Use," Energies, MDPI, vol. 13(2), pages 1-18, January.
    12. Sorin Liviu Jurj & Raul Rotar & Flavius Opritoiu & Mircea Vladutiu, 2021. "Improving the Solar Reliability Factor of a Dual-Axis Solar Tracking System Using Energy-Efficient Testing Solutions," Energies, MDPI, vol. 14(7), pages 1-19, April.
    13. Lukač, Niko & Seme, Sebastijan & Žlaus, Danijel & Štumberger, Gorazd & Žalik, Borut, 2014. "Buildings roofs photovoltaic potential assessment based on LiDAR (Light Detection And Ranging) data," Energy, Elsevier, vol. 66(C), pages 598-609.

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