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Performance estimation of photovoltaic energy production

Author

Listed:
  • Laura Casula

    (Università degli Studi di Cagliari)

  • Guglielmo D’Amico

    (Università G. D’Annunzio)

  • Giovanni Masala

    (Università degli Studi di Cagliari)

  • Filippo Petroni

    (Università Politecnica delle Marche)

Abstract

This article deals with the production of energy through photovoltaic (PV) panels. The efficiency and quantity of energy produced by a PV panel depend on both deterministic factors, mainly related to the technical characteristics of the panels, and stochastic factors, essentially the amount of incident solar radiation and some climatic variables that modify the efficiency of solar panels such as temperature and wind speed. The main objective of this work is to estimate the energy production of a PV system with fixed technical characteristics through the modeling of the stochastic factors listed above. Besides, we estimate the economic profitability of the plant, net of taxation or subsidiary payment policies, considered taking into account the hourly spot price curve of electricity and its correlation with solar radiation, via vector autoregressive models. Our investigation ends with a Monte Carlo simulation of the models introduced. We also propose the pricing of some quanto options that allow hedging both the price risk and the volumetric risk.

Suggested Citation

  • Laura Casula & Guglielmo D’Amico & Giovanni Masala & Filippo Petroni, 2020. "Performance estimation of photovoltaic energy production," Letters in Spatial and Resource Sciences, Springer, vol. 13(3), pages 267-285, December.
    • Handle: RePEc:spr:lsprsc:v:13:y:2020:i:3:d:10.1007_s12076-020-00258-x
    DOI: 10.1007/s12076-020-00258-x
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    4. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
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    6. Rafal Weron & Florian Ziel, 2018. "Electricity price forecasting," HSC Research Reports HSC/18/08, Hugo Steinhaus Center, Wroclaw University of Technology.
    7. Laura Casula & Guglielmo D'Amico & Giovanni Masala & Filippo Petroni, 2020. "Performance estimation of a wind farm with a dependence structure between electricity price and wind speed," The World Economy, Wiley Blackwell, vol. 43(10), pages 2803-2822, October.
    8. Graditi, G. & Ferlito, S. & Adinolfi, G., 2016. "Comparison of Photovoltaic plant power production prediction methods using a large measured dataset," Renewable Energy, Elsevier, vol. 90(C), pages 513-519.
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    Cited by:

    1. 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.
    2. Larsson, Karl & Green, Rikard & Benth, Fred Espen, 2023. "A stochastic time-series model for solar irradiation," Energy Economics, Elsevier, vol. 117(C).

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    More about this item

    Keywords

    Solar radiation; Climatic variables; Income; Monte Carlo simulation; Electricity price; Quanto option;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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