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

G. Tsekouras, and D. Koutsoyiannis, Stochastic analysis and simulation of hydrometeorological processes associated with wind and solar energy, Renewable Energy, 63, 624–633, doi:10.1016/j.renene.2013.10.018, 2014.



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.

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Our works referenced by this work:

1. D. Koutsoyiannis, Statistical Hydrology, Edition 4, 312 pages, doi:10.13140/RG.2.1.5118.2325, National Technical University of Athens, Athens, 1997.
2. D. Koutsoyiannis, and Th. Xanthopoulos, Engineering Hydrology, Edition 3, 418 pages, doi:10.13140/RG.2.1.4856.0888, National Technical University of Athens, Athens, 1999.
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5. D. Koutsoyiannis, The Hurst phenomenon and fractional Gaussian noise made easy, Hydrological Sciences Journal, 47 (4), 573–595, doi:10.1080/02626660209492961, 2002.
6. D. Koutsoyiannis, Climate change, the Hurst phenomenon, and hydrological statistics, Hydrological Sciences Journal, 48 (1), 3–24, doi:10.1623/hysj., 2003.
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16. G. Tsekouras, C. Ioannou, A. Efstratiadis, and D. Koutsoyiannis, Stochastic analysis and simulation of hydrometeorological processes for optimizing hybrid renewable energy systems, European Geosciences Union General Assembly 2013, Geophysical Research Abstracts, Vol. 15, Vienna, EGU2013-11660, doi:10.13140/RG.2.2.30250.62404, European Geosciences Union, 2013.

Our works that reference this work:

1. A. Efstratiadis, Y. Dialynas, S. Kozanis, and D. Koutsoyiannis, A multivariate stochastic model for the generation of synthetic time series at multiple time scales reproducing long-term persistence, Environmental Modelling and Software, 62, 139–152, doi:10.1016/j.envsoft.2014.08.017, 2014.
2. P. Kossieris, C. Makropoulos, C. Onof, and D. Koutsoyiannis, A rainfall disaggregation scheme for sub-hourly time scales: Coupling a Bartlett-Lewis based model with adjusting procedures, Journal of Hydrology, doi:10.1016/j.jhydrol.2016.07.015, 2016.
3. Y. Markonis, S. C. Batelis, Y. Dimakos, E. C. Moschou, and D. Koutsoyiannis, Temporal and spatial variability of rainfall over Greece, Theoretical and Applied Climatology, doi:10.1007/s00704-016-1878-7, 2016.

Other works that reference this work (this list might be obsolete):

1. Varotsos, C. A., and M. N. Efstathiou, Symmetric scaling properties in global surface air temperature anomalies, Theoretical and Applied Climatology, 10.1007/s00704-014-1274-0, 2014.
2. Abdelaziz, A. Y., Y. G. Hegazy, W. El-Khattam and M.M. Othman, Optimal allocation of stochastically dependent renewable energy based distributed generators in unbalanced distribution networks, Electric Power Systems Research, 119, 34-44, 2015.
3. #Fortuna, L., S. Nunnari and A. Gallo, A typical day based approach to detrend solar radiation time series, MAED '14 Proceedings of the 3rd ACM International Workshop on Multimedia Analysis for Ecological Data, 25-30, ACM New York, NY, USA, 2014.
4. Othman, M.M., A.Y. Abdelaziz, Y. G. Hegazi and W. El-Khattam, Approach for modelling stochastically dependent renewable energy-based generators using diagonal band copula, IET Renewable Power Generation, 9 (7), 809-820, 10.1049/iet-rpg.2014.0205, 2015.
5. Bardsley, E., A finite mixture approach to univariate data simulation with moment matching, Environmental Modelling & Software, 90, 27-33, doi:10.1016/j.envsoft.2016.11.019, 2017.

Tagged under: Hurst-Kolmogorov dynamics, Hydrosystems, Stochastics, Water and energy