Bureau Veritas featured in GWEC’s 2026 Global Wind Reports

Context

Wind farms across Europe are reaching 15–25 years of operation, facing declining performance, rising maintenance costs and increasing pressure to modernise.

A key challenge for asset owners is to determine whether to:

• continue operation,
• partially repower, or
• fully repower their assets — 
  based on reliable, bankable data rather than assumptions.

The challenge

A wind farm in the Iberian Peninsula (30 turbines, 0.85 MW each) showed signs of underperformance.

Initial expectations suggested moderate degradation — but a deeper analysis was needed to understand:

• the true performance losses
• the root causes (component ageing, wake effects, terrain misalignment)
• the economic viability of repowering

Bureau Veritas approach

Through Solida (BV company), a data-driven SCADA analysis was conducted using over 5 years of operational data.

Key actions included:

• Establishing a reliable performance baseline without new measurement campaigns
• Identifying wake interactions and terrain effects
• Removing data noise (interannual variability)
• Simulating modern turbine layouts to assess repowering potential

Key findings

The analysis revealed critical insights:

• Actual long-term degradation was higher than expected, with capacity factors declining by nearly 10%
• Wake effects and site conditions were significantly impacting performance
• Original turbine design assumptions were no longer optimal under real conditions
• SCADA data showed consistent underperformance across multiple turbines

Impact & value

The study enabled the asset owner to:

• Build a bankable understanding of long-term performance trends
• Quantify the financial upside of modernisation
• Reduce uncertainty before major investment decisions
• Align repowering strategy with current regulatory frameworks

Result: a clear pathway to maximise energy output and asset value

Key takeaway

• Repowering decisions must be based on real operational data, not assumptions
• Data-driven analysis reveals hidden inefficiencies and unlocks significant performance and financial gains. 

Context

Offshore wind is scaling rapidly, but so are cost pressures. While the industry often focuses on inflation, supply chains and financing, a key driver of project economics remains underestimated: quality.

Although not always visible in cost models, quality issues significantly impact delays, rework, operational performance and ultimately LCOE (Levelized Cost of Energy).

The challenge

As offshore projects grow in size and complexity, risks are increasing:

• Larger, more complex infrastructures
• Global and less mature supply chains
• Harsh and demanding offshore environments

In this context, even small quality deviations can escalate into major operational and financial impacts, affecting both project costs and energy production.

Bureau Veritas approach

Bureau Veritas supports developers with a proactive, data-driven quality management approach, powered by AI and digital tools across the full project lifecycle:

• Design phase: advanced modelling reduces uncertainty and strengthens engineering decisions
• Manufacturing: AI-driven inspection (computer vision) improves defect detection and traceability
• Construction: digital tools and drone inspections ensure real-time quality control
• Operations: predictive maintenance using real-time data prevents failures and reduces downtime

Key findings

The analysis highlights several critical insights:

• Many of the most costly failures originate early (design, manufacturing, logistics)
• Subsea cable failures remain a major financial and operational risk
• Quality issues directly impact both:  
  • costs (repairs, delays, insurance)
  • energy production (downtime, performance losses)
• Traditional reactive approaches are no longer sufficient

Impact & value

By shifting to proactive quality management, developers can:

• Reduce failure rates and maintenance costs
• Increase asset availability and performance
• Improve risk visibility across the lifecycle
• Lower the realised LCOE

Result: better project execution and stronger long-term profitability

Key takeaway

• Quality is a key driver of offshore wind performance and cost efficiency
• Leveraging AI, digitalisation and predictive approaches enables developers to anticipate risks, optimise performance and reduce lifecycle costs.