Nedbringelse af Cost of Energy (CoE) fra vindmøller igennem reduktion af fejl i pitchsy-stemet

The project objective is to increase the uptime of wind turbines by reducing the number of un-planned stops and service due to hydraulic pitch system faults. By gaining a better understanding of the errors that occur and using this to develop better monitoring systems, the aim is to reduce the downtime due to pitch system errors by >15%.

Project description

This project aims to improve the uptime in wind turbines by improving the reliability of the hydraulic system, thus reducing the downtime due to pitch system faults by >15%, lowering the Levelized Cost of Energy and ensuring a more stable supply. This is done by developing and improving methods and knowledge to predict when and why a component is failing and using this information for online monitoring of the systems.


Specifically, the project is organized around a number of work packages, dealing respectively with infor-mation gathering, reliability modelling and lifetime prediction, accelerated testing of components, condition monitoring, fault detection and diagnostics, and fault tolerant control enabling the operating of the system under certain types of faults. The knowledge generated will thus be used to more accurately predict the remaining lifetime, when a system needs servicing, for online monitoring of the systems to plan preventive service (so-called predictive maintenance), and for lifetime design optimization. The results will thus both be implemented through methods and procedures for design and testing of systems, both also in form of on-board diagnostics systems implemented in the pitch system to provide feedback about current state and future service requirements.

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Key figures

Period:
2022 - 2027
Funding year:
2022
Own financial contribution:
11.08 mio. DKK
Grant:
21.96 mio. DKK
Funding rate:
66 %
Project budget:
33.04 mio. DKK

Category

Oprindelig title
Nedbringelse af Cost of Energy (CoE) fra vindmøller igennem reduktion af fejl i pitchsy-stemet
Programme
EUDP
Technology
Wind
Keywords
Kunstig intelligens / maskinlæring Vedvarende energiudvinding
Project type
Forskning Udvikling Demonstration
Case no.
64022-1058

Participants

Aalborg Universitet (Fredrik Bajers Vej) (Main Responsible)
Partners and economy
Partner Subsidy Auto financing
Aalborg Universitet (Fredrik Bajers Vej) 11,80 mio. DKK 1,31 mio. DKK
Danmarks Tekniske Universitet (DTU) 3,16 mio. DKK 0,35 mio. DKK
VESTAS WIND SYSTEMS A/S 1,01 mio. DKK 1,76 mio. DKK
VATTENFALL VINDKRAFT A/S 1,01 mio. DKK 1,52 mio. DKK

Contact

Kontakperson
Henrik C. Pedersen
Comtact information

Adresse: Pontoppidanstræde 111

Tlf.: 9940 9240

Contact email
hcp@energy.aau.dk

Energiforskning.dk - informationportal for danish energytechnology research- og development programs.

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