energy-utilities
Operations
representative

Dynamic Wind Turbine Yaw & Pitch Optimization for Annual Energy Production

An IPP renewable energy operator managing a 450MW offshore wind farm featuring 60 high-capacity wind turbines operating under complex turbulent wind wake conditions.

Runs onSantulan

increase in net Annual Energy Production (AEP), generating: 3.4%increase in net Annual Energy Production (AEP), generating
reduction in mechanical gearbox and blade fatigue stress: 15%reduction in mechanical gearbox and blade fatigue stress

How the work runs

The pressure that made this worth automating, the steps the system runs, and what came out the other side.

Pressure & Trigger Points

Upwind turbines created turbulent wake vortices that reduced wind speed and energy yield for downstream turbines by up to 12%.
Static factory yaw and pitch control curves failed to adapt to real-time micro-turbulent wind direction shifts.
Aerodynamic fatigue stress on turbine blades accelerated mechanical gearbox wear, driving up offshore maintenance costs.

The run · 5 operational steps

Click any step to inspect telemetry signals, model reasoning, and governance gates.

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Real-Time Wake & Wind Flow Analytics

Santulan models complex farm-wide wake interactions using real- time SCADA and LiDAR wind vector telemetry.

Input Signal:

Real-time operational telemetry & queue

Reasoning Pattern:

MCP grounded vector inference

Governance Gate:

Policy constrained with audit write-back

Verified Business Outcomes

3.4% increase in net Annual Energy Production (AEP), generating $1.8M in additional annual electricity revenue.
15% reduction in mechanical gearbox and blade fatigue stress, extending offshore maintenance intervals.
Zero downtime recorded during extreme wind direction shifts.

Capabilities this relies on

signal ingestion
forecasting
anomaly detection
scenario simulation
alert routing

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