A. Efstratiadis, I. Tsoukalas, and D. Koutsoyiannis, Generalized storage-reliability-yield framework for hydroelectric reservoirs, *Hydrological Sciences Journal*, 66 (4), 580–599, doi:10.1080/02626667.2021.1886299, 2021.

[doc_id=2082]

[English]

Although storage-reliability-yield (SRY) relationships have been widely used in the design and planning of water supply reservoirs, their application in hydroelectricity is practically nil. Here, we revisit the SRY analysis and seek its generic configuration for hydroelectric reservoirs, following a stochastic simulation approach. After defining key concepts and tools of conventional SRY studies, we adapt them for hydropower systems, which are subject to several peculiarities. We illustrate that under some reasonable assumptions, the problem can be substantially simplified. Major innovations are the storage-head-energy conversion via the use of a sole parameter, representing the reservoir geometry, and the development of an empirical statistical metric expressing the reservoir performance on the basis of the simulated energy-probability curve. The proposed framework is applied to numerous hypothetical reservoirs at three river sites in Greece, using monthly synthetic inflow data, to provide empirical expressions of reliable energy as a function of reservoir storage and geometry.

Full text is only available to the NTUA network due to copyright restrictions

**Additional material:**

- Preprint (965 KB)

**Our works referenced by this work:**

1. | D. Koutsoyiannis, A generalized mathematical framework for stochastic simulation and forecast of hydrologic time series, Water Resources Research, 36 (6), 1519–1533, doi:10.1029/2000WR900044, 2000. |

2. | D. Koutsoyiannis, The Hurst phenomenon and fractional Gaussian noise made easy, Hydrological Sciences Journal, 47 (4), 573–595, doi:10.1080/02626660209492961, 2002. |

3. | D. Koutsoyiannis, A. Efstratiadis, and G. Karavokiros, A decision support tool for the management of multi-reservoir systems, Journal of the American Water Resources Association, 38 (4), 945–958, doi:10.1111/j.1752-1688.2002.tb05536.x, 2002. |

4. | D. Koutsoyiannis, and A. Economou, Evaluation of the parameterization-simulation-optimization approach for the control of reservoir systems, Water Resources Research, 39 (6), 1170, doi:10.1029/2003WR002148, 2003. |

5. | D. Koutsoyiannis, G. Karavokiros, A. Efstratiadis, N. Mamassis, A. Koukouvinos, and A. Christofides, A decision support system for the management of the water resource system of Athens, Physics and Chemistry of the Earth, 28 (14-15), 599–609, doi:10.1016/S1474-7065(03)00106-2, 2003. |

6. | D. Koutsoyiannis, Reliability concepts in reservoir design, Water Encyclopedia, Vol. 4, Surface and Agricultural Water, edited by J. H. Lehr and J. Keeley, 259–265, doi:10.1002/047147844X.sw776, Wiley, New York, 2005. |

7. | D. Koutsoyiannis, Stochastic simulation of hydrosystems, Water Encyclopedia, Vol. 4, Surface and Agricultural Water, edited by J. H. Lehr and J. Keeley, 421–430, doi:10.1002/047147844X.sw913, Wiley, New York, 2005. |

8. | A. Christofides, A. Efstratiadis, D. Koutsoyiannis, G.-F. Sargentis, and K. Hadjibiros, Resolving conflicting objectives in the management of the Plastiras Lake: can we quantify beauty?, Hydrology and Earth System Sciences, 9 (5), 507–515, doi:10.5194/hess-9-507-2005, 2005. |

9. | D. Koutsoyiannis, and A. Montanari, Statistical analysis of hydroclimatic time series: Uncertainty and insights, Water Resources Research, 43 (5), W05429, doi:10.1029/2006WR005592, 2007. |

10. | D. Koutsoyiannis, C. Makropoulos, A. Langousis, S. Baki, A. Efstratiadis, A. Christofides, G. Karavokiros, and N. Mamassis, Climate, hydrology, energy, water: recognizing uncertainty and seeking sustainability, Hydrology and Earth System Sciences, 13, 247–257, doi:10.5194/hess-13-247-2009, 2009. |

11. | H. Tyralis, and D. Koutsoyiannis, Simultaneous estimation of the parameters of the Hurst-Kolmogorov stochastic process, Stochastic Environmental Research & Risk Assessment, 25 (1), 21–33, 2011. |

12. | 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. |

13. | I. Nalbantis, A. Efstratiadis, E. Rozos, M. Kopsiafti, and D. Koutsoyiannis, Holistic versus monomeric strategies for hydrological modelling of human-modified hydrosystems, Hydrology and Earth System Sciences, 15, 743–758, doi:10.5194/hess-15-743-2011, 2011. |

14. | A. Efstratiadis, A. Tegos, A. Varveris, and D. Koutsoyiannis, Assessment of environmental flows under limited data availability – Case study of the Acheloos River, Greece, Hydrological Sciences Journal, 59 (3-4), 731–750, doi:10.1080/02626667.2013.804625, 2014. |

15. | 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. |

16. | I. Tsoukalas, and C. Makropoulos, A surrogate based optimization approach for the development of uncertainty-aware reservoir operational rules: the case of Nestos hydrosystem, Water Resources Management, 29 (13), 4719–4734, doi:10.1007/s11269-015-1086-8, 2015. |

17. | I. Tsoukalas, A. Efstratiadis, and C. Makropoulos, Stochastic periodic autoregressive to anything (SPARTA): Modelling and simulation of cyclostationary processes with arbitrary marginal distributions, Water Resources Research, 54 (1), 161–185, WRCR23047, doi:10.1002/2017WR021394, 2018. |

18. | I. Tsoukalas, C. Makropoulos, and D. Koutsoyiannis, Simulation of stochastic processes exhibiting any-range dependence and arbitrary marginal distributions, Water Resources Research, 54 (11), 9484–9513, doi:10.1029/2017WR022462, 2018. |

19. | I. Tsoukalas, A. Efstratiadis, and C. Makropoulos, Building a puzzle to solve a riddle: A multi-scale disaggregation approach for multivariate stochastic processes with any marginal distribution and correlation structure, Journal of Hydrology, 575, 354–380, doi:10.1016/j.jhydrol.2019.05.017, 2019. |

20. | D. Koutsoyiannis, Knowable moments for high-order stochastic characterization and modelling of hydrological processes, Hydrological Sciences Journal, 64 (1), 19–33, doi:10.1080/02626667.2018.1556794, 2019. |

21. | D. Koutsoyiannis, Simple stochastic simulation of time irreversible and reversible processes, Hydrological Sciences Journal, 65 (4), 536–551, doi:10.1080/02626667.2019.1705302, 2020. |

22. | I. Tsoukalas, P. Kossieris, and C. Makropoulos, Simulation of non-Gaussian correlated random variables, stochastic processes and random fields: Introducing the anySim R-Package for environmental applications and beyond, Water, 12 (6), 1645, doi:10.3390/w12061645, 2020. |

23. | 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. |

**Tagged under:**
Renewable energy,
Hydrosystems,
Stochastics,
Uncertainty,
Water and energy