Digital Twin & Asset Management

Developing methodologies to elevate the capability level of Digital Twins from 0-2 to 3-5 (autonomy).

Work Package 4 is lead by Adil Rasheed from NTNU. Its focus areas are Digital twin for wind energy, optimal farm control and asset management.

Anticipated results:

  • High level of physical realism in DTs
  • Max. power production with min. asset degradation
  • Probabilistic predictive maintenance

Hypothesis

Digital Twin with high level of realism will be a paradigm shift for informed decision making

Methodology and research tasks

Digital Twin adapted for wind energy

Framework development, optimised sensor placement, novel modelling paradigm.

Optimal Park Control

Holistic Modelling, Combined optimisation for energy production, asset degradation and its integration into the power grid, evaluation of farm control strategies.

Asset Management

Condition Monitoring (CM), Predictive Maintanance and improved strategies for life extension.

Informed public engagement

Augmented reality will be employed to inform the public of future impacts (WP5.3) of the upcoming wind farm.