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Adaptive Turbine Replacement Improves Hydropower Flexibility in a Changing Climate

Adaptive Turbine Replacement Improves Hydropower Flexibility in a Changing Climate

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Authors

Veysel YILDIZ, Nathalie Voisin, MARTA ZANIOLO 

Abstract

Hydropower Plants (HP) will operate under new conditions as water regimes shift, reservoir operating rules evolve, and the grid requires flexible balancing of wind and solar.
HP turbine systems are traditionally designed to operate at the highest efficiency within narrow ranges of flow and reservoir levels while deviations from design conditions can degrade HP efficiency and trigger failures, especially in aging infrastructure.
Turbine replacements typically occur every 35 to 50 years, offering a rare opportunity to modernize turbine designs by adjusting turbine head and discharge capacity to fit new conditions, rather than replicating legacy designs. The central challenge is to determine when to replace instead of extending lifetime of existing fleet, which system signals indicate the need for redesign, and which configurations will deliver the most robust gains.


This study introduces HyTUNE (Hydropower Turbine Upgrade and Next-generation Planning), a dynamic decision-support tool that integrates basin hydrology, plant hydraulics, and adaptive optimization to guide turbine replacement timing and configuration. HyTUNE shifts planning from reactive, end-of-life replacement toward proactive, information-driven strategies. The framework learns from evolving system states, identifies threshold conditions where adjustments in head or capacity improve performance, and prescribes phased interventions that balance energy production, reliability, and cost under uncertainty.

Application to the Hoover Hydropower Plant demonstrates that HyTUNE’s adaptive policies consistently outperformed conventional reactive strategies across diverse hydrologic futures.
HyTUNE is of considerable practical relevance as hydropower systems worldwide confront the dual challenge of modernization and adaptation to future uncertainty and demand growth.

DOI

https://doi.org/10.31223/X54B7R

Subjects

Engineering

Keywords

hydropower, optimization, hydropower modernization, decision tree

Dates

Published: 2026-05-11 16:50

Last Updated: 2026-05-11 16:50

License

CC BY Attribution 4.0 International

Additional Metadata

Data Availability:
https://doi.org/10.5281/zenodo.18058173

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