IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v63y2014icp624-633.html
   My bibliography  Save this article

Stochastic analysis and simulation of hydrometeorological processes associated with wind and solar energy

Author

Listed:
  • Tsekouras, Georgios
  • Koutsoyiannis, Demetris

Abstract

The current model for energy production, based on the intense use of fossil fuels, is both unsustainable and environmentally harmful and consequently, a shift is needed in the direction of integrating the renewable energy sources into the energy balance. However, these energy sources are unpredictable and uncontrollable as they strongly depend on time varying and uncertain hydrometeorological variables such as wind speed, sunshine duration and solar radiation. To study the design and management of renewable energy systems we investigate both the properties of marginal distributions and the dependence properties of these natural processes, including possible long-term persistence by estimating and analyzing the Hurst coefficient. To this aim we use time series of wind speed and sunshine duration retrieved from European databases of daily records. We also study a stochastic simulation framework for both wind and solar systems using the software system Castalia, which performs multivariate and multi-time-scale stochastic simulation, in order to conduct simultaneous generation of synthetic time series of wind speed and sunshine duration, on yearly, monthly and daily scale.

Suggested Citation

  • Tsekouras, Georgios & Koutsoyiannis, Demetris, 2014. "Stochastic analysis and simulation of hydrometeorological processes associated with wind and solar energy," Renewable Energy, Elsevier, vol. 63(C), pages 624-633.
  • Handle: RePEc:eee:renene:v:63:y:2014:i:c:p:624-633
    DOI: 10.1016/j.renene.2013.10.018
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148113005491
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2013.10.018?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. Alvarez-Ramirez, Jose & Alvarez, Jesus & Dagdug, Leonardo & Rodriguez, Eduardo & Carlos Echeverria, Juan, 2008. "Long-term memory dynamics of continental and oceanic monthly temperatures in the recent 125 years," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(14), pages 3629-3640.
    2. Kavasseri, Rajesh G. & Nagarajan, Radhakrishnan, 2005. "A multifractal description of wind speed records," Chaos, Solitons & Fractals, Elsevier, vol. 24(1), pages 165-173.
    3. Rehman, S. & Siddiqi, A.H., 2009. "Wavelet based hurst exponent and fractal dimensional analysis of Saudi climatic dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 40(3), pages 1081-1090.
    4. D'Andrade, Kendall, 1992. "The End of an Era," Business Ethics Quarterly, Cambridge University Press, vol. 2(3), pages 379-389, July.
    5. Carta, J.A. & Ramírez, P. & Velázquez, S., 2009. "A review of wind speed probability distributions used in wind energy analysis: Case studies in the Canary Islands," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(5), pages 933-955, June.
    6. Harrouni, S. & Guessoum, A., 2009. "Using fractal dimension to quantify long-range persistence in global solar radiation," Chaos, Solitons & Fractals, Elsevier, vol. 41(3), pages 1520-1530.
    7. Sulaiman, M.Yusof & Hlaing Oo, W.M & Abd Wahab, Mahdi & Zakaria, Azmi, 1999. "Application of beta distribution model to Malaysian sunshine data," Renewable Energy, Elsevier, vol. 18(4), pages 573-579.
    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. Ringkjøb, Hans-Kristian & Haugan, Peter M. & Nybø, Astrid, 2020. "Transitioning remote Arctic settlements to renewable energy systems – A modelling study of Longyearbyen, Svalbard," Applied Energy, Elsevier, vol. 258(C).
    2. Sakki, G.K. & Tsoukalas, I. & Kossieris, P. & Makropoulos, C. & Efstratiadis, A., 2022. "Stochastic simulation-optimization framework for the design and assessment of renewable energy systems under uncertainty," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    3. Liang, Zhengtang & Liang, Jun & Zhang, Li & Wang, Chengfu & Yun, Zhihao & Zhang, Xu, 2015. "Analysis of multi-scale chaotic characteristics of wind power based on Hilbert–Huang transform and Hurst analysis," Applied Energy, Elsevier, vol. 159(C), pages 51-61.
    4. Santos, E.C.O. & Guedes, E.F. & Zebende, G.F. & da Silva Filho, A.M., 2022. "Autocorrelation of wind speed: A sliding window approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    5. Athanasios Zisos & Georgia-Konstantina Sakki & Andreas Efstratiadis, 2023. "Mixing Renewable Energy with Pumped Hydropower Storage: Design Optimization under Uncertainty and Other Challenges," Sustainability, MDPI, vol. 15(18), pages 1-21, September.

    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. Chang, Tian-Pau & Ko, Hong-Hsi & Liu, Feng-Jiao & Chen, Pai-Hsun & Chang, Ying-Pin & Liang, Ying-Hsin & Jang, Horng-Yuan & Lin, Tsung-Chi & Chen, Yi-Hwa, 2012. "Fractal dimension of wind speed time series," Applied Energy, Elsevier, vol. 93(C), pages 742-749.
    2. Liang, Zhengtang & Liang, Jun & Zhang, Li & Wang, Chengfu & Yun, Zhihao & Zhang, Xu, 2015. "Analysis of multi-scale chaotic characteristics of wind power based on Hilbert–Huang transform and Hurst analysis," Applied Energy, Elsevier, vol. 159(C), pages 51-61.
    3. dos Anjos, Priscilla Sales & da Silva, Antonio Samuel Alves & Stošić, Borko & Stošić, Tatijana, 2015. "Long-term correlations and cross-correlations in wind speed and solar radiation temporal series from Fernando de Noronha Island, Brazil," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 90-96.
    4. Zárate-Miñano, Rafael & Milano, Federico, 2016. "Construction of SDE-based wind speed models with exponentially decaying autocorrelation," Renewable Energy, Elsevier, vol. 94(C), pages 186-196.
    5. Botelho, D.F. & de Oliveira, L.W. & Dias, B.H. & Soares, T.A. & Moraes, C.A., 2022. "Integrated prosumers–DSO approach applied in peer-to-peer energy and reserve tradings considering network constraints," Applied Energy, Elsevier, vol. 317(C).
    6. Ju-Young Shin & Changsam Jeong & Jun-Haeng Heo, 2018. "A Novel Statistical Method to Temporally Downscale Wind Speed Weibull Distribution Using Scaling Property," Energies, MDPI, vol. 11(3), pages 1-27, March.
    7. Ren, Jinfu & Liu, Yang & Liu, Jiming, 2023. "Chaotic behavior learning via information tracking," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    8. Francisco Gerardo Benavides-Bravo & Dulce Martinez-Peon & Ángela Gabriela Benavides-Ríos & Otoniel Walle-García & Roberto Soto-Villalobos & Mario A. Aguirre-López, 2021. "A Climate-Mathematical Clustering of Rainfall Stations in the Río Bravo-San Juan Basin (Mexico) by Using the Higuchi Fractal Dimension and the Hurst Exponent," Mathematics, MDPI, vol. 9(21), pages 1-11, October.
    9. Omoyele, Olalekan & Hoffmann, Maximilian & Koivisto, Matti & Larrañeta, Miguel & Weinand, Jann Michael & Linßen, Jochen & Stolten, Detlef, 2024. "Increasing the resolution of solar and wind time series for energy system modeling: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    10. Amirinia, Gholamreza & Mafi, Somayeh & Mazaheri, Said, 2017. "Offshore wind resource assessment of Persian Gulf using uncertainty analysis and GIS," Renewable Energy, Elsevier, vol. 113(C), pages 915-929.
    11. Aruna Kanagaraj & Kumudini Devi Raguru Pandu, 2020. "Investigations of Various Market Models in a Deregulated Power Environment Using ACOPF," Energies, MDPI, vol. 13(9), pages 1-17, May.
    12. Méndez-Gordillo, Alma Rosa & Cadenas, Erasmo, 2021. "Wind speed forecasting by the extraction of the multifractal patterns of time series through the multiplicative cascade technique," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    13. Nagarajan, Radhakrishnan & Kavasseri, Rajesh G., 2005. "Minimizing the effect of periodic and quasi-periodic trends in detrended fluctuation analysis," Chaos, Solitons & Fractals, Elsevier, vol. 26(3), pages 777-784.
    14. Han, Qinkai & Wang, Tianyang & Chu, Fulei, 2022. "Nonparametric copula modeling of wind speed-wind shear for the assessment of height-dependent wind energy in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    15. Stosic, Tatijana & Telesca, Luciano & Stosic, Borko, 2021. "Multiparametric statistical and dynamical analysis of angular high-frequency wind speed time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    16. Rodriguez-Hernandez, O. & Jaramillo, O.A. & Andaverde, J.A. & del Río, J.A., 2013. "Analysis about sampling, uncertainties and selection of a reliable probabilistic model of wind speed data used on resource assessment," Renewable Energy, Elsevier, vol. 50(C), pages 244-252.
    17. Mostafaeipour, Ali, 2010. "Productivity and development issues of global wind turbine industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(3), pages 1048-1058, April.
    18. Shen, Xin & Chen, Jin-Ge & Zhu, Xiao-Cheng & Liu, Peng-Yin & Du, Zhao-Hui, 2015. "Multi-objective optimization of wind turbine blades using lifting surface method," Energy, Elsevier, vol. 90(P1), pages 1111-1121.
    19. de Benicio, Rosilda B. & Stošić, Tatijana & de Figueirêdo, P.H. & Stošić, Borko D., 2013. "Multifractal behavior of wild-land and forest fire time series in Brazil," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6367-6374.
    20. Thiago B. Murari & Aloisio S. Nascimento Filho & Marcelo A. Moret & Sergio Pitombo & Alex A. B. Santos, 2020. "Self-Affine Analysis of ENSO in Solar Radiation," Energies, MDPI, vol. 13(18), pages 1-17, September.

    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:63:y:2014:i:c:p:624-633. 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.