2.4 Turbine and generator lifetime
Turbine and generator lifetime
Turbine and generator lifetime
Turbine and generator lifetime
In order to enable the transition from traditional and condition-based strategies toward predictive strategies, the aim of this task is to develop, test and verify methods and models for turbine and generator lifetime qualification and estimation.
Evaluation of hydro turbine and generator (remaining) lifetime and maintenance/refurbishment decisions are traditionally based on condition-based methods utilizing the results of inspections carried out either according to a regular schedule (time-based) or on demand (e.g. after specific events or when other observations or measurement indicate an fault).
The results form Task 2.4 can be used for development of models for evaluation, and especially continuous (online) evaluation, of the ageing and consumed lifetime of the major components in hydropower stations. This will allow for application of predictive maintenance strategies by carrying out maintenance and inspections when the ageing and lifetime models indicate that predefined limits are reached.
Furthermore, integration of such models in e.g. production planning and reinvestment analysis will allow for optimization of power production plans and reinvestment decisions.
The aim is to be able to take into account the actual technical condition of the components and their further degradation in planning and decision making, and to finally quantify (lifetime) risks and costs as a function of operation and reinvestment decisions.
The lifetime of turbines and generators depend on different factors such as operating conditions, design and external factors and stresses. The qualitative effects of many of these factors are well-known and have been the subject of earlier research activities. However, the quantification of these effects on the ageing and the lifetime of the turbine and the generator are still issues for further research. Furthermore, the effects of some factors, such as fast voltage transients on the generator insulation lifetime, have not been addressed by comprehensive studies before.
The work in this work package will focus on the description and quantification of some of the main factors influencing ageing and lifetime of turbine and generator. The focus of the activities in Task 2.4 will be on fatigue lifetime of hydro turbines and ageing and lifetime of hydropower generator winding insulation systems. The knowledge from Task 2.4 will support the work in WP3 on developing tools for remaining useful life and failure probability estimation (Task 3.2).
Some of the Task 2.4 results may directly be used in Task 3.2 and finally be integrated with tools for optimal power production and investment decisions.
Conference Proceedings 2018
Conference Proceedings 2018
Welte, Thomas Michael; Foros, Jørn; Nielsen, M.H.; Adsten, M. MonitorX – Experience from a Norwegian-Swedish research project on industry 4.0 and digitalization applied to fault detection and maintenance of hydropower plants. I: Hydro 2018 - Progress through partnership, Gdansk, Poland, 15-17 October 2018. : International journal on hydropower and dams 2018 ISBN 0-000-00001-9.
ENERGISINT
Sanz-Bobi, M.A.; Welte, Thomas Michael; Eilertsen, L. Anomaly indicators for Kaplan turbine components based on patterns of normal behavior. Safety and Reliability – Safe Societies in a Changing World. Proceedings of ESREL 2018
Master thesis
Master thesis
Contact
Contact
Maren Istad
About the project
About the project
Full project title: Turbine and generator lifetime
Duration: 2017-2022
Object: The primary aim is to develop, test and verify methods and models for turbine and generator lifetime qualification and estimation.
R&D Partners: Sintef, NTNU, Uppsala university, Vattenfall. Comillas Pontifical University, Madrid.
Associated projects: Hydrogenerator Stator Winding Insulation Assessment (KPN 255099), High head Francis turbines (KPN 254987), MonitorX (IPN 245317).
Researchers working on the project: Maren Istad, Arne Nysveen, Espen Eberg, Ole Gunnar Dahlhaug, Eivind Solvang, Arnt Ove Eggen, Henrik Enoksen, Jørn Foros, Sverre Hvidsten.
PhD working on the project: Hossein Ehya
Master students associated with the project: Douglas Okafor Chukwuekwe, Kari Gjerde Jørstad, Ingrid Linnea Groth, Johan Henrik Holm Ebbing.