A reverse engineering approach across small hydropower plants: a hidden treasure of hydrological data?

G.-K. Sakki, I. Tsoukalas, and A. Efstratiadis, A reverse engineering approach across small hydropower plants: a hidden treasure of hydrological data?, Hydrological Sciences Journal, 67 (1), 94–106, doi:10.1080/02626667.2021.2000992, 2022.



The limited availability of hydrometric data makes the design, management, and real-time operation of water systems a difficult task. Here, we propose a generic stochastic framework for the so-called inverse problem of hydroelectricity, using energy production data from small hydropower plants (SHPPs) to retrieve the upstream inflows. In this context, we investigate the alternative configurations of water-energy transformations across SHPPs of negligible storage capacity, which are subject to multiple uncertainties. We focus on two key sources, i.e. observational errors in energy production and uncertain efficiency curves of turbines. In order to extract the full hydrograph, we also extrapolate the high and low flows outside of the range of operation of turbines, by employing empirical rules for representing the rising and falling limbs of the simulated hydrographs. This framework is demonstrated to a real-world system at Evinos river basin, Greece. By taking advantage of the proposed methodology, SHPPs may act as potential hydrometric stations and improve the existing information in poorly gauged areas.

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Our works referenced by this work:

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Our works that reference this work:

1. K.-K. Drakaki, G.-K. Sakki, I. Tsoukalas, P. Kossieris, and A. Efstratiadis, Day-ahead energy production in small hydropower plants: uncertainty-aware forecasts through effective coupling of knowledge and data, Advances in Geosciences, 56, 155–162, doi:10.5194/adgeo-56-155-2022, 2022.
2. V.-E. K. Sarantopoulou, G. J. Tsekouras, A. D. Salis, D. E. Papantonis, V. Riziotis, G. Caralis, K.-K. Drakaki, G.-K. Sakki, A. Efstratiadis, and K. X. Soulis, Optimal operation of a run-of-river small hydropower plant with two hydro-turbines, 2022 7th International Conference on Mathematics and Computers in Sciences and Industry (MCSI), Marathon Beach, Athens, 80–88, doi:10.1109/MCSI55933.2022.00020, 2022.
3. G.-K. Sakki, I. Tsoukalas, P. Kossieris, C. Makropoulos, and A. Efstratiadis, Stochastic simulation-optimisation framework for the design and assessment of renewable energy systems under uncertainty, Renewable and Sustainable Energy Reviews, 168, 112886, doi:10.1016/j.rser.2022.112886, 2022.
4. A. Zisos, G.-K. Sakki, and A. Efstratiadis, Mixing renewable energy with pumped hydropower storage: Design optimization under uncertainty and other challenges, Sustainability, 15 (18), 13313, doi:10.3390/su151813313, 2023.
5. E. Dimitriou, A. Efstratiadis, I. Zotou, A. Papadopoulos, T. Iliopoulou, G.-K. Sakki, K. Mazi, E. Rozos, A. Koukouvinos, A. D. Koussis, N. Mamassis, and D. Koutsoyiannis, Post-analysis of Daniel extreme flood event in Thessaly, Central Greece: Practical lessons and the value of state-of-the-art water monitoring networks, Water, 16 (7), 980, doi:10.3390/w16070980, 2024.

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

1. Garrett, K. P., R. A. McManamay, and A. Witt, Harnessing the power of environmental flows: Sustaining river ecosystem integrity while increasing energy potential at hydropower dams, Renewable and Sustainable Energy Reviews, 173(1), 113049, doi:10.1016/j.rser.2022.113049, 2023.

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