K. Papoulakos, G. Pollakis, Y. Moustakis, A. Markopoulos, T. Iliopoulou, P. Dimitriadis, D. Koutsoyiannis, and A. Efstratiadis, Simulation of water-energy fluxes through small-scale reservoir systems under limited data availability, Energy Procedia, 125, 405–414, doi:10.1016/j.egypro.2017.08.078, 2017.
We present a stochastic approach accounting for input uncertainties within water-energy simulations. The stochastic paradigm, which allows for quantifying the inherent uncertainty of hydrometeorological processes, becomes even more crucial in case of missing or inadequate information. Our scheme uses simplified conceptual models which are subject to significant uncertainties, to generate the inputs of the overall simulation problem. The methodology is tested in a hypothetical hybrid renewable energy system across the small Aegean island of Astypalaia, comprising a pumped-storage reservoir serving multiple water uses, where both inflows and demands are regarded as random variables as result of stochastic inputs and parameters.
Full text (2324 KB)
Our works referenced by this work:
|1.||D. Koutsoyiannis, Hurst-Kolmogorov dynamics and uncertainty, Journal of the American Water Resources Association, 47 (3), 481–495, doi:10.1111/j.1752-1688.2011.00543.x, 2011.|
|2.||A. Tegos, A. Efstratiadis, and D. Koutsoyiannis, A parametric model for potential evapotranspiration estimation based on a simplified formulation of the Penman-Monteith equation, Evapotranspiration - An Overview, edited by S. Alexandris, 143–165, doi:10.5772/52927, InTech, 2013.|
|3.||A. Efstratiadis, A. D. Koussis, D. Koutsoyiannis, and N. Mamassis, Flood design recipes vs. reality: can predictions for ungauged basins be trusted?, Natural Hazards and Earth System Sciences, 14, 1417–1428, doi:10.5194/nhess-14-1417-2014, 2014.|
|4.||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.|
|5.||A. Efstratiadis, I. Nalbantis, and D. Koutsoyiannis, Hydrological modelling of temporally-varying catchments: Facets of change and the value of information, Hydrological Sciences Journal, 60 (7-8), 1438–1461, doi:10.1080/02626667.2014.982123, 2015.|
|6.||P. Stamou, S. Karali, M. Chalakatevaki, V. Daniil, K. Tzouka, P. Dimitriadis, T. Iliopoulou, P. Papanicolaou, D. Koutsoyiannis, and N. Mamassis, Creating the electric energy mix of a non-connected Aegean island, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, EGU2017-10130-10, doi:10.13140/RG.2.2.36537.77927, European Geosciences Union, 2017.|
Our works that reference this work:
|1.||E. Klousakou, M. Chalakatevaki, P. Dimitriadis, T. Iliopoulou, R. Ioannidis, G. Karakatsanis, A. Efstratiadis, N. Mamassis, R. Tomani, E. Chardavellas, and D. Koutsoyiannis, A preliminary stochastic analysis of the uncertainty of natural processes related to renewable energy resources, Advances in Geosciences, 45, 193–199, doi:10.5194/adgeo-45-193-2018, 2018.|
|2.||N. Mamassis, A. Efstratiadis, P. Dimitriadis, T. Iliopoulou, R. Ioannidis, and D. Koutsoyiannis, Water and Energy, Handbook of Water Resources Management: Discourses, Concepts and Examples, edited by J.J. Bogardi, T. Tingsanchali, K.D.W. Nandalal, J. Gupta, L. Salamé, R.R.P. van Nooijen, A.G. Kolechkina, N. Kumar, and A. Bhaduri, Chapter 20, 617–655, doi:10.1007/978-3-030-60147-8_20, Springer Nature, Switzerland, 2021.|
Other works that reference this work (this list might be obsolete):
|1.||Pouliasis, G., G. A. Torres-Alves, and O. Morales-Napoles, Stochastic modeling of hydroclimatic processes using vine copulas, Water, 13(16), 2156, doi:10.3390/w13162156, 2021.|