Maximise production without being exposed to operational variability

Wind farm operations rely on sensitive aerodynamic, mechanical and electrical balances, where wind conditions, control strategies, turbine behaviour and grid constraints directly impact energy production and asset availability.

Even minor deviations can lead to reduced yield, repeated shutdowns, increased mechanical stress or premature component degradation.

Indao transforms data from turbines, control systems, electrical substations and environmental conditions into reliable operational indicators and concrete recommendations.

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Why wind farm operations are different

Energy assets exposed to a variable environment, where performance and reliability must remain under control.

Fluctuating energy resource

Wind variability requires continuous adaptation of control and production strategies

Highly stressed mechanical systems

Gearboxes, generators and blades are subject to dynamic loads directly impacting their lifetime

Distributed and remote operations

Multiple turbines and limited access make early detection of deviations essential

The challenges you face

  • Energy yield: maximise actual production relative to available wind potential
  • Turbine availability: reduce unplanned downtime linked to mechanical or electrical drifts
  • Proactive maintenance: anticipate degradation affecting gearboxes, generators or pitch/yaw systems
  • Grid integration: maintain production stability despite grid constraints
  • Environmental performance: reduce mechanical stress and extend asset lifetime

The limits of your current tools

  • Analysis often limited to individual turbine indicators
  • Difficulty distinguishing wind-related losses from operational inefficiencies
  • Fixed-threshold alarms not suited to aerodynamic dynamics
  • Performance analysis often carried out after production drops
  • Limited tools to correlate environmental conditions with mechanical behaviour

What Indao delivers in practice

We design advanced analytics solutions that genuinely improve wind farm operations, with AI as a support : explainable, controlled and field-oriented.

Real-time tracking of production considering wind conditions, operating regimes and grid constraints
Continuous estimation of performance losses and deviations impacting energy production
Analysis of interactions between environmental conditions, turbine settings and mechanical behaviour
Identification of control strategies improving overall production while limiting equipment stress
Structured historisation of performance to support inter-turbine benchmarking and long-term analysis
Seamless connection to existing systems (farm SCADA, grid supervision, maintenance systems) without disrupting operations

What you gain

Operational results, not just more dashboards

Optimised energy production

Early identification of losses
→ better utilisation of wind potential

Increased turbine availability

Anticipation of mechanical drifts
→ reduced unplanned downtime

More targeted maintenance

Prioritisation of interventions based on real production impact

Extended equipment lifetime

Reduced mechanical stress through more precise control strategies

More robust operational decisions

Clear understanding of interactions between wind, settings and performance

Controlled integration

Progressive, secure deployment aligned with existing practices

See clearly. Act decisively. Optimise sustainably.

Decisions that have already proven their impact

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Want to make decisions differently?

Let’s explore how your data can become a concrete operational lever.

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Whatever your activity in the energy sector

Concrete levers at the core of processes

Cogeneration

Optimise thermal and electrical control to maximise overall efficiency and energy valorisation

HVAC

Dynamically adjust heating and cooling production based on real needs to reduce consumption and deviations

Green hydrogen

Improve operating condition stability and energy efficiency of production units

Boilers

Optimise combustion and thermal efficiency to reduce energy losses and improve operational stability