How to make more money from your Wind Farm

Inaccurate generation forecasts trigger severe market imbalance penalties that cut directly into wind farm revenue. Join Delfos and WPred to see how combining predictive asset monitoring with site-calibrated weather forecasting reduces these penalties and protects your margins.

Key takeaways

What you'll learn

Cut Penalty Exposure

Leave with a framework to calculate how much inaccurate day-ahead forecasting is costing your bottom line, and how to reduce it.

Forecast with Precision

See how combining numerical weather models with site data and power curve calibration improves prediction accuracy.

Catch Problems Early

Use AI-driven monitoring across turbine subsystems to detect anomalies before they cause downtime.

Close the Loop

Learn how feeding maintenance data from Delfos back into WPred's forecasting models keeps output at peak levels.

Protect People and Equipment

See how lightning detection gives site personnel time to respond before severe weather hits, and how 500m alerts help you understand if turbines need urgent maintenance and inspection.

Speakers

Who's presenting

Kate Abarbanel

Commercial Planning, WPred

Helps wind farm owner-operators with day-ahead market positioning and revenue strategy across global electricity markets.

Kelly Foran

Lead Data Scientist, WPred

Works on high-resolution numerical weather modeling, complex terrain calibration, and severe weather risk detection.

Nathianne Andrade

Head of Data Science, Delfos

Wind resource engineer by background. Leads Delfos's AI and machine learning platform for turbine component health and predictive maintenance.

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host team

Meet Our Speakers

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