Grant: Alliance Grants
Université Laval
$306,913.00
Modelling and Diagnostic of Anomalies in Francis Turbines MD-FRANCIS
FY 2024-25
Summary
Hydroelectricity is a reliable and renewable energy source that is vital to Canada's energy transition. The operational flexibility of hydraulic turbines is used to compensate for fluctuating electricity production from intermittent energy sources, such as solar and wind. However, this flexibility impacts the turbine's residual life because they are now required to operate more often in off-design conditions and to undergo more frequent start and stop sequences. Hydraulic turbines' already excellent reliability must be improved to play their role in Canada's energy transition scenarios.
With the five-year MD-Francis research program, the Heki Hydropower Innovation Center aims to study the operational impacts of anomalies in the hydraulic channels of Francis turbines to improve their detection and diagnosis. MD-Francis is a joint research effort by the members of the Hydraulic Machine Research Consortium, a partnership started in 2007 which currently includes four universities (Université Laval, Polytechnique Montréal, École de Technologie Supérieure, Polytechnical University of Catalonia) and six industrial partners (Hydro-Québec, Andritz Hydro, GE Vernova, Voith Hydro, EDF, and Vattenfall).
MD-Francis focuses on conducting experimental and numerical investigations into anomalies associated with vibrations and high strain levels observed in model-scale Francis turbines. The corresponding model, mirroring a turbine in operation in Canada, is installed on the Heki test platform at Université Laval. It will be modified to replicate specific anomalies, such as runner damage to examine their impact on the fluid-structure dynamics of the turbine. The gathered data will contribute to developing various technologies, including detection and diagnostic strategies for specific anomalies, creation of reduced order models, and simulation techniques to predict the influence of anomalies on fluid-structure interactions affecting the runner. Ultimately, MD-Francis aims to facilitate the integration of predictive maintenance systems in Francis turbines. This should result in minimized maintenance downtimes, enhanced operational flexibility, and a more efficient utilization of this crucial renewable energy source.
Program
Alliance Grants
Recipient
Location
Quebec, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
597456-2024
Name nom
Houde, Sebastien S
Department département
Génie mécanique
Organization id
51
Institution établissement
Université Laval
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2024
Award amount
306913
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
300
Area of application group en
Energy resources
Area of application group fr
Ressources d'énergie
Area of application en
Energy resources (including production, exploration, processing, distribution and use)
Area of application fr
Ressources d'énergie (production, exploration, traitement, distribution et utilisation de l'énergie)
Research subject code
2100
Research subject group en
Mechanical engineering
Research subject group fr
Génie mécanique
Research subject en
Mechanical engineering
Research subject fr
Génie mécanique
Field of research list names en
Not available
Field of research list names fr
Non disponible
Socioeconomic objective list names en
Not available
Socioeconomic objective list names fr
Non disponible
Application title
Modelling and Diagnostic of Anomalies in Francis Turbines MD-FRANCIS
Keywords
anomaly detection; fluid-structure interactions; hydraulic turbine; reduced order models; simulations
Application summary
Hydroelectricity is a reliable and renewable energy source that is vital to Canada's energy transition. The operational flexibility of hydraulic turbines is used to compensate for fluctuating electricity production from intermittent energy sources, such as solar and wind. However, this flexibility impacts the turbine's residual life because they are now required to operate more often in off-design conditions and to undergo more frequent start and stop sequences. Hydraulic turbines' already excellent reliability must be improved to play their role in Canada's energy transition scenarios.
With the five-year MD-Francis research program, the Heki Hydropower Innovation Center aims to study the operational impacts of anomalies in the hydraulic channels of Francis turbines to improve their detection and diagnosis. MD-Francis is a joint research effort by the members of the Hydraulic Machine Research Consortium, a partnership started in 2007 which currently includes four universities (Université Laval, Polytechnique Montréal, École de Technologie Supérieure, Polytechnical University of Catalonia) and six industrial partners (Hydro-Québec, Andritz Hydro, GE Vernova, Voith Hydro, EDF, and Vattenfall).
MD-Francis focuses on conducting experimental and numerical investigations into anomalies associated with vibrations and high strain levels observed in model-scale Francis turbines. The corresponding model, mirroring a turbine in operation in Canada, is installed on the Heki test platform at Université Laval. It will be modified to replicate specific anomalies, such as runner damage to examine their impact on the fluid-structure dynamics of the turbine. The gathered data will contribute to developing various technologies, including detection and diagnostic strategies for specific anomalies, creation of reduced order models, and simulation techniques to predict the influence of anomalies on fluid-structure interactions affecting the runner. Ultimately, MD-Francis aims to facilitate the integration of predictive maintenance systems in Francis turbines. This should result in minimized maintenance downtimes, enhanced operational flexibility, and a more efficient utilization of this crucial renewable energy source.