Modeling Epistemic Uncertainty in Offshore Wind Farm Production Capacity to Reduce Risk

Area of Science:

• Engineering
• Risk Management
• Renewable Energy Systems

Background:

• Offshore wind farm investments require accurate energy production forecasts for risk management.
• Early operational phase predictions are critical due to financial discounting and learning effects.

Purpose of the Study:

• To develop a general model for predicting offshore wind farm energy production capacity under uncertainty.
• To link technical performance uncertainties to the cost of energy generation.
• To assess the value of information in reducing investment risk.

Main Methods:

• A general marked point process model was developed for subassembly failure and restoration times.
• Epistemic uncertainties from design and manufacturing were identified.
• The model captures temporal effects of uncertainties to predict farm availability-informed relative capacity.

Main Results:

• The model predicts farm availability-informed relative capacity, linking technical states to generating capacity.
• Production capacity uncertainties were decomposed to evaluate epistemic uncertainty contributions.
• The approach allows for examining the value of information in risk reduction.

Conclusions:

• The developed model provides a framework for predicting offshore wind farm energy production under uncertainty.
• Linking technical performance to the cost of energy generation aids financial risk management.
• The methodology enables the assessment of information's value in mitigating investment risks.