THE PROJECT

MEEVCE's objectives

The main objective of this project is to generate the necessary knowledge to obtain an evolutionary methodology for extending the useful life of wind power components in actual operating conditions.

Sub-Targets

  • 1Generating advanced models to predict post-manufacturing conditions, the level of degradation during operation and the behaviour associated with such degradation in wind components and the global system (turbine).

  • 2Devising, developing, designing and operating procedures or reduced-scale test benches, to reproduce degradation mechanisms that occur in actual conditions and validate advanced prediction models in a controlled and economically viable way.

  • 3Developing a methodology to generate digital twins of wind turbine components, considering: (i) post-fabrication conditions at the start of their life; (ii) level of degradation; and (iii) the behaviour associated with such level of degradation during their life.

  • 4Obtaining a holistic multi-component model that includes degradation impact on a turbine in an evolutionary way. This will allow a better understanding of the interactions between components, and the impact of their degradation on the behaviour of the wing turbine and the rest of the components.

Technological scope

Components

Each partner will focus on the study and evolutionary modelling of a critical wind component.

BLADE
Aerodynamics Erosion
BEARING
Temple Degradation
GEARBOX
Hardening/Tempering Contact Wear
SHAFT
Aerodynamics Erosion

WIND TURBINE

Critical components

Degradation mechanisms

  • Critical component
    BLADE
      Degradation mechanisms
    • Aerodynamics
    • Erosion
  • Critical component
    GEARBOX
      Degradation mechanisms
    • Hardening/Tempering
    • Contact
    • Wear
  • Critical component
    BEARING
      Degradation mechanisms
    • Temple
    • Degradation
  • Critical component
    SHAFT
      Degradation mechanisms
    • Hardening/Tempering
    • Fatigue

Although focused on different components, the technologies to be studied are common, and there is a clear shared interest in the different technologies covered by the project:

Hardening and Tempering

The hardening and tempering process, in its furnace or induction heating variants, will be addressed by IKERLAN, CEIT and BEARINN. This technology is associated with all metal components subject to severe contact, and is therefore of common interest for shafts, gears and bearings.

Wear

Wear is a common degradation phenomenon for all turbine rotor components. This is degradation phenomenon which is not considered catastrophic and therefore, prediction models have not been developed yet at a very advanced level in the wind sector, even though it has a significant impact on the behaviour of the turbine. Blade wear, to be studied by MONDRAGON UNIBERTSITATEA, modifies the turbine aerodynamic behaviour, which in turn alters the loads borne by the rest of the components. Gear wear (IKERLAN), bearing wear (BEARINN) or shaft wear (CEIT) are directly linked with the ability and resistance of these components to transmit torque and thus, mechanical power to the electrical generator.

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Levels of analysis

THE METHODOLOGY PROPOSED BY MEEVCE WILL INVOLVE A LIFE EXTENSION ANALYSIS AT THREE SCALES:

03
UPPER
SCALE
+03
A holistic turbine model integrating digital twins of each component to consider the degradation level of each component and the impact of that degradation on the rest of the components and the machine.

02
INTERMEDIATE SCALE
+02
A Digital Twin of each component fed by advanced models which will be able to predict the post-fabrication conditions, degradation level and behaviour associated with this degradation level of a component in operation.

01
LOWER SCALE
+01
Advanced models to understand and predict physical phenomena associated with the main degradation mechanisms of components and their experimental validation by means of laboratory-scale testing.

Life extension during operation requires closing the loop in an evolutionary way, considering how loads and interactions between components vary in order to update their condition.

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Expected results

  • 1Advanced models to understand and predict the physical phenomena associated with the main degradation mechanisms and their experimental validation.

  • 2A digital twin of each component capable of predicting the post-fabrication state, the level of degradation and behaviour associated with such level of degradation.

  • 3A holistic turbine model integrating digital twins of each component to consider the degradation level of each component and the impact of that degradation on the rest of the components and the machine.

Main indicators

12

indexed scientific journals

10

potential transfer agreements with companies

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Activities

Evolutionary methodology for life extension of wind turbine components

Activity 1

Loads and Interaction
between components

MEEVCE

Activity 4

Evolutionary
Digital Twin for components

Activity 2

Advanced predictive
Models

Activity 3

Reduced-scale
Tests

Activity 5

Diffusion and transfer

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