IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v3y1993i8p951-960.html
   My bibliography  Save this article

A procedure for evaluating the influence of weather Markovianity on the storage behaviour of solar systems

Author

Listed:
  • Ratto, C.F.
  • Festa, R.

Abstract

The simultaneous behaviour of correlated inflows and storage states is described by means of a bivariate Markov chain which takes into account the serial correlation of inflows on the assumption that they can be described by a first order Markov process. To do this, we use the Storage Theory, developed by hydraulic engineers in the fifties and sixties: this theory appears to be a powerful and general tool for studying the behaviour of solar energy and wind energy systems with a time-constant of the order of some days. Expressions are given which allow the evaluation of the overspill of energy which occurs when the storage is full, and evaluation of the energy which has to be provided to the user by an auxiliary system when the storage is empty. In particular, we discuss the role of the permanency of weather conditions on the behaviour of the storage on a daily basis.

Suggested Citation

  • Ratto, C.F. & Festa, R., 1993. "A procedure for evaluating the influence of weather Markovianity on the storage behaviour of solar systems," Renewable Energy, Elsevier, vol. 3(8), pages 951-960.
    • Handle: RePEc:eee:renene:v:3:y:1993:i:8:p:951-960
    DOI: 10.1016/0960-1481(93)90057-N
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/096014819390057N
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/0960-1481(93)90057-N?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. Festa, R. & Jain, S. & Ratto, C.F., 1992. "Stochastic modelling of daily global irradiation," Renewable Energy, Elsevier, vol. 2(1), pages 23-34.
    2. Callegari, M. & Festa, R. & Ratto, C.F., 1992. "Stochastic modelling of daily beam irradiation," Renewable Energy, Elsevier, vol. 2(6), pages 611-624.
    Full references (including those not matched with items on IDEAS)

    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. Maafi, A. & Adane, A., 1998. "Analysis of the performances of the first-order two-state Markov model using solar radiation properties," Renewable Energy, Elsevier, vol. 13(2), pages 175-193.
    2. Kamal, Lalarukh & Jafri, Yasmin Zahra, 1999. "Stochastic modeling and generation of synthetic sequences of hourly global solar irradiation at Quetta, Pakistan," Renewable Energy, Elsevier, vol. 18(4), pages 565-572.
    3. Zervas, P.L. & Sarimveis, H. & Palyvos, J.A. & Markatos, N.C.G., 2008. "Prediction of daily global solar irradiance on horizontal surfaces based on neural-network techniques," Renewable Energy, Elsevier, vol. 33(8), pages 1796-1803.
    4. Festa, R. & Jain, S. & Ratto, C.F., 1992. "Stochastic modelling of daily global irradiation," Renewable Energy, Elsevier, vol. 2(1), pages 23-34.
    5. Ballestrín, Jesús & Polo, Jesús & Martín-Chivelet, Nuria & Barbero, Javier & Carra, Elena & Alonso-Montesinos, Joaquín & Marzo, Aitor, 2022. "Soiling forecasting of solar plants: A combined heuristic approach and autoregressive model," Energy, Elsevier, vol. 239(PE).
    6. Kaplanis, S.N., 2006. "New methodologies to estimate the hourly global solar radiation; Comparisons with existing models," Renewable Energy, Elsevier, vol. 31(6), pages 781-790.
    7. Craggs, C & Conway, E & Pearsall, N.M, 1999. "Stochastic modelling of solar irradiance on horizontal and vertical planes at a northerly location," Renewable Energy, Elsevier, vol. 18(4), pages 445-463.
    8. Kaplanis, S. & Kaplani, E., 2007. "A model to predict expected mean and stochastic hourly global solar radiation I(h;nj) values," Renewable Energy, Elsevier, vol. 32(8), pages 1414-1425.
    9. Youcef Ettoumi, F. & Mefti, A. & Adane, A. & Bouroubi, M.Y., 2002. "Statistical analysis of solar measurements in Algeria using beta distributions," Renewable Energy, Elsevier, vol. 26(1), pages 47-67.
    10. Callegari, M. & Festa, R. & Ratto, C.F., 1992. "Stochastic modelling of daily beam irradiation," Renewable Energy, Elsevier, vol. 2(6), pages 611-624.

    More about this item

    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:renene:v:3:y:1993:i:8:p:951-960. 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/renewable-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.