Prof. Denis Thibault
Denis Thibault has been a research scientist at the Institut de recherche d’Hydro-Québec(IREQ) since 1997. He has served since 2023 as the scientific lead for the R&D theme “Behaviour and Digital Twins of Engineering Assets,” to coordinate research efforts dedicated to developing digital twins of Hydro-Québec’s strategic assets.
He is chairman of the Canadian committee of IEC-TC4 on hydraulic turbines and received the IEC 1906 Award in 2022 for his contribution to the development of the standard IEC 63230 on fatigue of hydraulic turbines. He holds a PhD in mechanical engineering from École de Technologie Supérieure and is an adjunct professor at Université Laval since 2020
Day 3: Friday, September 11th | 11:15 – 12:30
Room: Opus
Title: Green Energy Sources, Challenges of Power Generation
Moderator: Prof. Jörg Seume (Leibniz University Hannover, Germany)
Panelists: Dr. Masahiro Uchida (IHI Corporation, Japan), Prof. Denis Thibault (Hydro Quebec, Canada), Rasmus Sinnige (Atlas Copco, Germany), Dr. Larry Wang (MingYang Smart Energy, USA)
Abstract:The global transition toward cleaner energy is reshaping power generation and creating new technical and operational challenges. This panel will explore renewable integration, flexible power generation, emerging technologies and fuels, and the evolving role of gas turbines. Panelists will discuss how the industry can balance sustainability, reliability, energy security, and affordability while meeting growing global energy demand.
Day 3: Friday, September 11th | 10:10 – 10:45
Room: Opus
Title: Digital Twins of Strategic Assets in Power Generation and Transmission
Speaker: Prof. Denis Thibault (Hydro Quebec)
Abstract:
The increasing complexity, aging, and criticality of power generation infrastructures require a paradigm shift in asset management, moving from reactive and experience-based practices toward data-driven, predictive, and prescriptive decision-making. Digital twins have emerged as a foundational technology enabling this transition by coupling physics-based models, advanced analytics, and monitoring data within a common framework.
This keynote presents Hydro-Québec’s research and development vision, scope, and implementation strategy for behavioral digital twins of energy assets, with a particular focus on power generation assets. A digital twin is defined as an evolving virtual representation of a physical asset that integrates high-fidelity simulations, reduced-order models, artificial intelligence, and continuously updated field data to monitor, diagnose, predict, and optimize asset behavior throughout its lifecycle.
The presentation introduces a structured digital twin maturity framework ranging from independent and descriptive models to diagnostic, prognostic, prescriptive, and ultimately autonomous systems. Core enabling components are discussed in relation to operational applications such as anomaly detection, remaining useful life estimation and optimized maintenance. Concrete examples of short- and mid-term implementations are provided, notably digital twins for hydroelectric generating units. The keynote outlines ongoing R&D activities supporting this effort, emphasizing the role of digital twins as a strategic lever for maximizing asset utilization and economically optimizing energy systems.
