| Digital twins
continually updated national water-conservation map capable of running simulations for flood control, drought mitigation and resource allocation across potentially thousands of water bodies. One flagship example is the Xiaolangdi Water Conservancy Project on the Yellow River. There, a digital twin dam model was used to run flood-control drills, amplifying a known 2021 flood scenario by 10 % to stress-test the system and develop emergency response proposals for operators.
Why digital twins matter and what they deliver 1. Improved operations and asset optimisation For ageing hydropower plants, digital twins offer a way to modernise operations without major physical upgrades. Operators can monitor performance in real- time, spot inefficiencies, test alternative regimes (e.g. different flow rates or turbine settings) and predict which maintenance tasks are critical, minimising downtime and maximising output.
2. Predictive maintenance and reliability By integrating sensor data, control-system outputs and detailed models of mechanical and hydraulic behaviour, digital twins can detect early signs of wear, vibration anomalies, abnormal flows or cavitation risk, long before it leads to equipment failure or downtime. This not only reduces maintenance costs but avoids unplanned outages and improves safety.
3. Simulation and training without risk Simulating “what-if” scenarios in a virtual twin enables operators to rehearse procedures, optimise responses, and train staff, all without endangering people or equipment, or interrupting production. The dual-twin setup at Røldal-Suldal enables exactly that.
4. Better water and environmental management Extending digital twin applications beyond the plant, into water basins, river systems, reservoirs etc, opens the door to integrated water resources management. As demonstrated in China, real-time, system-wide digital twins enable flood risk management, drought response, water allocation planning, and climate- resilience modelling, functions that complement hydropower operations.
5. Flexibility, scalability and modernisation pathway Digital twins don’t necessarily require replacing hardware; many implementations leverage existing infrastructure and simply augment it with sensors, data collection, and modelling. This makes them particularly attractive for operators of older dams who may lack the capital for large-scale refurbishments, but need smarter, more reliable, data-driven operations.
Challenges and practical constraints Of course, like any technology, digital twins
for hydropower face several challenges. ● Data infrastructure and latency: As seen at Røldal- Suldal, using cloud-based databases can introduce latency (15–60 seconds). For many monitoring and control tasks this may be acceptable – but for real- time safety-critical operations, it could pose a risk.
● Complexity of modelling: A full hydropower plant includes hydraulic, mechanical, electrical and control subsystems, each requiring accurate physics-based models. Some academic work shows that building comprehensive digital twin models remains difficult, especially for complex plants.
● Sensor reliability and data integration: A digital twin is only as reliable as the data fed into it. Sensor malfunctions or mis-calibration can compromise output. Some research uses the twin itself to detect sensor anomalies, but this requires careful calibration and validation.
● Scaling beyond individual plants: Extending the twin concept from single hydropower plants to entire watersheds or national water systems introduces significant complexity: interoperability, data governance, consistent sensor networks, cross-agency collaboration, and often very high computational demands.
● Resource requirements and institutional inertia: Despite long-term benefits, initial investments (in sensors, data platforms, modelling effort)and the challenge of adapting legacy systems may deter some operators. The institutional change required to integrate digital twins into routine operations also should not be underestimated.
The road ahead Emerging literature and recent projects suggest that
digital twins will not only stay relevant but increase in importance, as hydropower systems evolve and integrate with other renewables, storage and grid management. A 2025 review of digital twins in renewable energy
systems notes a growing interest in using DTs across solar, wind, hydro and hybrid plants, covering all phases from design and commissioning, through operations and maintenance, to end-of-life optimization. In addition, the combination of digital twins with advanced control algorithms – such as reinforcement learning – could enable smarter, adaptive management of hydropower assets and their integration with other grid resources. For example, a future-proof “standard architecture” for power-system digital twins might support not only plant- level monitoring but also grid-wide coordination, hybrid energy mix planning, environmental management, and long-term sustainability assessments. Finally, by coupling hydropower digital twins with
water-management twins at basin or national scale, as demonstrated in China, operators and regulators could gain a holistic view: generation, resource availability, flood and drought risks, and climate-driven variability. Digital twin technology is proving to be more than just a buzzword in hydropower, it is rapidly becoming a practical tool for enhancing efficiency, reliability, resilience and environmental stewardship. Whether at a single plant like Røldal-Suldal, or across
entire river basins and water infrastructures as in China, or as part of modernisation efforts in the US, digital twins offer operators the chance to see and manage their systems in a whole new way. They combine real-time monitoring, anomaly detection, predictive maintenance, and scenario simulation, enabling safer, smarter, and more adaptive hydropower operations. For an industry facing aging infrastructure, climate uncertainty and growing demands, digital twins may be one of the most powerful tools in the modernization toolbox. But implementation must be thoughtful: ensuring
reliable sensors, robust data architecture, accurate modelling, and operational integration. As research and pilot projects continue, the hope is that digital twins will evolve from pilot tools into standard practice – helping to usher hydropower into a more sustainable, efficient and flexible future.
References
https://www.rehydro.eu/2025/04/ 23/virtual-powerplants-for- monitoring-and-control-a-digital- twin-for-roldal-suldal-kraftverkene/
https://www.hydro.org/powerhouse/ article/how-digital-twins-can- transform-hydropower-operations/
https://swissnex.org/china/articles/ how-digital-twins-are-transforming- chinas-water-management/
www.waterpowermagazine.com | January 2026 | 17
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