IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v72y2014icp393-404.html
   My bibliography  Save this article

Mathematical approach to the characterization of daily energy balance in autonomous photovoltaic solar systems

Author

Listed:
  • Casares, F.J.
  • Lopez-Luque, R.
  • Posadillo, R.
  • Varo-Martinez, M.

Abstract

Sizing SAPV techniques try to assess the reliability of the system from the stochastic simulation of the energy balance. This stochastic simulation implies the generation, for an extended period of time, of the main state variables of the physical equations describing the energy balance of the system, that is, the energy delivered to the load and the energy stored in the batteries. Most of these methods consider the daily load as a constant over the year and control the variables indicating the reliability associated with the supply of power to the load. Furthermore, these methods rely on previous random models for generating solar radiation data and, since the approximations of the simulation methods are asymptotic, when more precise reliability indicators are required, the simulation period needs to be extended.

Suggested Citation

  • Casares, F.J. & Lopez-Luque, R. & Posadillo, R. & Varo-Martinez, M., 2014. "Mathematical approach to the characterization of daily energy balance in autonomous photovoltaic solar systems," Energy, Elsevier, vol. 72(C), pages 393-404.
    • Handle: RePEc:eee:energy:v:72:y:2014:i:c:p:393-404
    DOI: 10.1016/j.energy.2014.05.053
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544214006197
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2014.05.053?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mellit, A. & Kalogirou, S.A. & Hontoria, L. & Shaari, S., 2009. "Artificial intelligence techniques for sizing photovoltaic systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(2), pages 406-419, February.
    2. Mellit, A. & Benghanem, M. & Arab, A. Hadj & Guessoum, A., 2005. "An adaptive artificial neural network model for sizing stand-alone photovoltaic systems: application for isolated sites in Algeria," Renewable Energy, Elsevier, vol. 30(10), pages 1501-1524.
    3. Jakhrani, Abdul Qayoom & Othman, Al-Khalid & Rigit, Andrew Ragai Henry & Samo, Saleem Raza & Kamboh, Shakeel Ahmed, 2012. "A novel analytical model for optimal sizing of standalone photovoltaic systems," Energy, Elsevier, vol. 46(1), pages 675-682.
    4. Labed, S. & Lorenzo, E., 2004. "The impact of solar radiation variability and data discrepancies on the design of PV systems," Renewable Energy, Elsevier, vol. 29(7), pages 1007-1022.
    5. Mellit, Adel & Kalogirou, Soteris A. & Drif, Mahmoud, 2010. "Application of neural networks and genetic algorithms for sizing of photovoltaic systems," Renewable Energy, Elsevier, vol. 35(12), pages 2881-2893.
    6. Fragaki, A. & Markvart, T., 2008. "Stand-alone PV system design: Results using a new sizing approach," Renewable Energy, Elsevier, vol. 33(1), pages 162-167.
    7. Mellit, A. & Benghanem, M. & Kalogirou, S.A., 2007. "Modeling and simulation of a stand-alone photovoltaic system using an adaptive artificial neural network: Proposition for a new sizing procedure," Renewable Energy, Elsevier, vol. 32(2), pages 285-313.
    8. Posadillo, R. & López Luque, R., 2008. "Approaches for developing a sizing method for stand-alone PV systems with variable demand," Renewable Energy, Elsevier, vol. 33(5), pages 1037-1048.
    9. Bartoli, B & Cuomo, V & Fontana, F & Serio, C & Silvestrini, V, 1984. "The design of photovoltaic plants: An optimization procedure," Applied Energy, Elsevier, vol. 18(1), pages 37-47.
    10. Wissem, Zghal & Gueorgui, Kantchev & Hédi, Kchaou, 2012. "Modeling and technical–economic optimization of an autonomous photovoltaic system," Energy, Elsevier, vol. 37(1), pages 263-272.
    11. Chen, Shin-Guang, 2012. "An efficient sizing method for a stand-alone PV system in terms of the observed block extremes," Applied Energy, Elsevier, vol. 91(1), pages 375-384.
    12. Posadillo, R. & López Luque, R., 2008. "A sizing method for stand-alone PV installations with variable demand," Renewable Energy, Elsevier, vol. 33(5), pages 1049-1055.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ana Garcia-Bernabeu & Antonio Benito & Mila Bravo & David Pla-Santamaria, 2016. "Photovoltaic power plants: a multicriteria approach to investment decisions and a case study in western Spain," Annals of Operations Research, Springer, vol. 245(1), pages 163-175, October.
    2. Shang, Ce & Srinivasan, Dipti & Reindl, Thomas, 2016. "Generation-scheduling-coupled battery sizing of stand-alone hybrid power systems," Energy, Elsevier, vol. 114(C), pages 671-682.
    3. Haiyan Yao & Aung Thinzar, 2023. "Lithium-ion battery equalization circuit and control strategy for photovoltaic energy storage applications," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 18, pages 341-347.
    4. Zhou, Jian & Tsianikas, Stamatis & Birnie, Dunbar P. & Coit, David W., 2019. "Economic and resilience benefit analysis of incorporating battery storage to photovoltaic array generation," Renewable Energy, Elsevier, vol. 135(C), pages 652-662.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Khatib, Tamer & Mohamed, Azah & Sopian, K., 2013. "A review of photovoltaic systems size optimization techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 454-465.
    2. Rawat, Rahul & Kaushik, S.C. & Lamba, Ravita, 2016. "A review on modeling, design methodology and size optimization of photovoltaic based water pumping, standalone and grid connected system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1506-1519.
    3. Jakhrani, Abdul Qayoom & Othman, Al-Khalid & Rigit, Andrew Ragai Henry & Samo, Saleem Raza & Kamboh, Shakeel Ahmed, 2012. "A novel analytical model for optimal sizing of standalone photovoltaic systems," Energy, Elsevier, vol. 46(1), pages 675-682.
    4. Ridha, Hussein Mohammed & Gomes, Chandima & Hizam, Hashim & Ahmadipour, Masoud & Heidari, Ali Asghar & Chen, Huiling, 2021. "Multi-objective optimization and multi-criteria decision-making methods for optimal design of standalone photovoltaic system: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    5. Sarhan, Ameen & Hizam, Hashim & Mariun, Norman & Ya'acob, M.E., 2019. "An improved numerical optimization algorithm for sizing and configuration of standalone photo-voltaic system components in Yemen," Renewable Energy, Elsevier, vol. 134(C), pages 1434-1446.
    6. Posadillo, R. & López Luque, R., 2008. "Approaches for developing a sizing method for stand-alone PV systems with variable demand," Renewable Energy, Elsevier, vol. 33(5), pages 1037-1048.
    7. Mellit, Adel & Kalogirou, Soteris A. & Drif, Mahmoud, 2010. "Application of neural networks and genetic algorithms for sizing of photovoltaic systems," Renewable Energy, Elsevier, vol. 35(12), pages 2881-2893.
    8. Erdinc, O. & Uzunoglu, M., 2012. "Optimum design of hybrid renewable energy systems: Overview of different approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(3), pages 1412-1425.
    9. Mandelli, Stefano & Brivio, Claudio & Colombo, Emanuela & Merlo, Marco, 2016. "A sizing methodology based on Levelized Cost of Supplied and Lost Energy for off-grid rural electrification systems," Renewable Energy, Elsevier, vol. 89(C), pages 475-488.
    10. Zarzo, Manuel & Martí, Pau, 2011. "Modeling the variability of solar radiation data among weather stations by means of principal components analysis," Applied Energy, Elsevier, vol. 88(8), pages 2775-2784, August.
    11. Alberto-Jesus Perea-Moreno & Quetzalcoatl Hernandez-Escobedo & Javier Garrido & Joel Donaldo Verdugo-Diaz, 2018. "Stand-Alone Photovoltaic System Assessment in Warmer Urban Areas in Mexico," Energies, MDPI, vol. 11(2), pages 1-13, January.
    12. Ullah, Hayat & Kamal, Ijlal & Ali, Ayesha & Arshad, Naveed, 2018. "Investor focused placement and sizing of photovoltaic grid-connected systems in Pakistan," Renewable Energy, Elsevier, vol. 121(C), pages 460-473.
    13. Youssef, Ayman & El-Telbany, Mohammed & Zekry, Abdelhalim, 2017. "The role of artificial intelligence in photo-voltaic systems design and control: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 72-79.
    14. Bhandari, Binayak & Lee, Kyung-Tae & Lee, Caroline Sunyong & Song, Chul-Ki & Maskey, Ramesh K. & Ahn, Sung-Hoon, 2014. "A novel off-grid hybrid power system comprised of solar photovoltaic, wind, and hydro energy sources," Applied Energy, Elsevier, vol. 133(C), pages 236-242.
    15. Khalilpour, Rajab & Vassallo, Anthony, 2016. "Planning and operation scheduling of PV-battery systems: A novel methodology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 194-208.
    16. Khalilpour, Rajab & Vassallo, Anthony, 2015. "Leaving the grid: An ambition or a real choice?," Energy Policy, Elsevier, vol. 82(C), pages 207-221.
    17. Khalilpour, Kaveh Rajab & Vassallo, Anthony, 2016. "Technoeconomic parametric analysis of PV-battery systems," Renewable Energy, Elsevier, vol. 97(C), pages 757-768.
    18. Zhou, Jian & Tsianikas, Stamatis & Birnie, Dunbar P. & Coit, David W., 2019. "Economic and resilience benefit analysis of incorporating battery storage to photovoltaic array generation," Renewable Energy, Elsevier, vol. 135(C), pages 652-662.
    19. 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.
    20. Ren, Zhengen & Paevere, Phillip & Chen, Dong, 2019. "Feasibility of off-grid housing under current and future climates," Applied Energy, Elsevier, vol. 241(C), pages 196-211.

    More about this item

    Keywords

    SAPV; LLP; Aguiar matrixes; PV sizing;
    All these keywords.

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:72:y:2014:i:c:p:393-404. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.