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A stochastic simulation model for reliable PV system sizing providing for solar radiation fluctuations

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  • Kaplani, E.
  • Kaplanis, S.

Abstract

The large fluctuations observed in the daily solar radiation profiles affect highly the reliability of the PV system sizing. Increasing the reliability of the PV system requires higher installed peak power (Pm) and larger battery storage capacity (CL). This leads to increased costs, and makes PV technology less competitive. This research paper presents a new stochastic simulation model for stand-alone PV systems, developed to determine the minimum installed Pm and CL for the PV system to be energy independent. The stochastic simulation model developed, makes use of knowledge acquired from an in-depth statistical analysis of the solar radiation data for the site, and simulates the energy delivered, the excess energy burnt, the load profiles and the state of charge of the battery system for the month the sizing is applied, and the PV system performance for the entire year. The simulation model provides the user with values for the autonomy factor d, simulating PV performance in order to determine the minimum Pm and CL depending on the requirements of the application, i.e. operation with critical or non-critical loads. The model makes use of NASA’s Surface meteorology and Solar Energy database for the years 1990–2004 for various cities in Europe with a different climate. The results obtained with this new methodology indicate a substantial reduction in installed peak power and battery capacity, both for critical and non-critical operation, when compared to conventional approaches applied in PV sizing.

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  • Kaplani, E. & Kaplanis, S., 2012. "A stochastic simulation model for reliable PV system sizing providing for solar radiation fluctuations," Applied Energy, Elsevier, vol. 97(C), pages 970-981.
    • Handle: RePEc:eee:appene:v:97:y:2012:i:c:p:970-981
    DOI: 10.1016/j.apenergy.2011.12.016
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    14. Bridier, Laurent & Hernández-Torres, David & David, Mathieu & Lauret, Phillipe, 2016. "A heuristic approach for optimal sizing of ESS coupled with intermittent renewable sources systems," Renewable Energy, Elsevier, vol. 91(C), pages 155-165.
    15. Goel, Sonali & Sharma, Renu, 2017. "Performance evaluation of stand alone, grid connected and hybrid renewable energy systems for rural application: A comparative review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 1378-1389.
    16. Cervantes, Jairo & Choobineh, Fred, 2018. "Optimal sizing of a nonutility-scale solar power system and its battery storage," Applied Energy, Elsevier, vol. 216(C), pages 105-115.
    17. Okoye, Chiemeka Onyeka & Solyalı, Oğuz, 2017. "Optimal sizing of stand-alone photovoltaic systems in residential buildings," Energy, Elsevier, vol. 126(C), pages 573-584.
    18. Raza, Syed Shabbar & Janajreh, Isam & Ghenai, Chaouki, 2014. "Sustainability index approach as a selection criteria for energy storage system of an intermittent renewable energy source," Applied Energy, Elsevier, vol. 136(C), pages 909-920.
    19. Anh Ngoc-Lan Huynh & Ravinesh C. Deo & Duc-Anh An-Vo & Mumtaz Ali & Nawin Raj & Shahab Abdulla, 2020. "Near Real-Time Global Solar Radiation Forecasting at Multiple Time-Step Horizons Using the Long Short-Term Memory Network," Energies, MDPI, vol. 13(14), pages 1-30, July.
    20. Kaplani, E. & Kaplanis, S. & Mondal, S., 2018. "A spatiotemporal universal model for the prediction of the global solar radiation based on Fourier series and the site altitude," Renewable Energy, Elsevier, vol. 126(C), pages 933-942.
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