Optimise Machine Performance TRIZ Cases

See how axial plasma actuators suppress leakage flow in blower shrouds without strict clearance

A delayed storage-assist control strategy helps hydraulic turbines handle large power setpoint changes faster while limiting instability and storage size.

Historical and real-time fatigue loads guide turbine power allocation to meet grid limits while balancing wear and maintenance across the farm.

Feed-in tariff signals shift wind turbine operating points to balance power output, structural wear, and profitable operation.

A unified controller adjusts wind turbine blade angle to raise combined wind and shadow-effect energy output over forecast intervals.

Historical and real-time turbine fatigue data guide power allocation under grid limits, balancing loads and lowering maintenance costs.

Real-time adjustment of rotor speed, generator torque, and gearbox ratio stabilizes offshore wind output to satisfy grid scheduling.

An iterative degradation function updates wind turbine power coefficient control to match blade erosion or icing and reduce energy losses.

When processor load spikes in a wind energy installation, prioritized task throttling preserves minimum control service levels without oversized capacity.

When controller load spikes, ranked wind turbine tasks are deferred or reduced to minimum service levels so critical control keeps running.

Dynamic mode decomposition captures nonlinear wind turbine behavior from limited data, enabling fast wind farm frequency control with less parameter upkeep.

Dynamic control balances noise-reduced wind turbine output with IGBT life tracking, maximizing energy and triggering maintenance alerts.

Adaptive MPPT load selection helps fluid turbines sustain power output under low-flow conditions while keeping DC output grid compliant.

Coordinated head and flow-rate control keeps the turbine operating point in range, reducing cavitation and avoiding unstable generator control.

Switching between DC operating ranges lets fluid turbine controllers sustain MPPT, low-flow efficiency, and grid-compliant output.

Closed-loop TSR tracking updates the wind turbine power coefficient from operating data to match blade degradation and improve partial-load output.

Dual-level control with a direct-drive linear motor-generator improves wave energy extraction under multi-frequency, fast-changing sea states.

A distributed PSO scheme lets each turbine share local wake data with neighbors to improve wind farm power extraction with lower control load.

Actuated vanes and extendable jibs adjust to shifting wind direction to stabilize torque and improve power output in less space.

Baseline power and operability curves link wind turbine underproduction to operating anomalies for faster root cause detection and control feedback.

A hybrid controller combines MPC with simpler routines to improve wind turbine control in real time without exceeding onboard computing limits.

A controller reconfigures variable-speed pump-turbine clusters and flow paths to keep hydraulic machinery near peak efficiency across wide service conditions.

Combining MPC with non-optimizing control routines enables real-time wind turbine actuation without excessive computing power.

Independent speed control and valve-switched flow paths keep hydraulic rotating machinery efficient across wide service conditions while reducing wear.

A wake prediction model adjusts individual blade pitch before partial wake overlap, reducing asymmetric rotor loads on downstream turbines.

A hydraulic pressure-drop network converts wave energy peak spikes into heat, cutting generator oversizing while smoothing WEC power output.

Identifies underperforming wind turbines from state and control data without power curves, enabling faster farm-level energy optimization.

Adaptive constraint scheduling uses predicted tower and operating behavior to improve gust response, reduce loading, and sustain power output.

Using operating data from nearby turbines, this case predicts downwind wind changes early enough to adjust pitch and power and reduce fatigue loads.

A fatigue-aware control schedule varies wind turbine power over time to balance energy capture with component lifetime.

Existing turbine sensor data is combined into site-specific flow and load models to revise control and maintenance, cutting downtime and cost.

Operability-curve comparison and baseline change detection connect wind turbine underperformance with paired-variable anomalies for control feedback.

A wind turbine can start sooner by counting simulative starts from real-time wind speed checks instead of waiting for continuous threshold exceedance.

Real-time GAMS optimization balances steam and condensate, then updates boiler, turbine, and motor set-points to cut energy and maintenance costs.

Splitting wind farm control variables into broadcast and unit-specific packets enables faster updates while preserving individual turbine control.

Split wind farm control variables into broadcast and unit-specific packets to keep fast updates without overloading transmission or processing.

Multiple nacelle and tower accelerometers improve tower position and thrust estimation for better oscillation damping and load control.

When wind sensors or upload paths fail, neighboring turbine data and matched historical records keep yaw control active and power output stable.

Individual turbine power reductions are optimized by available power and ramp capability, enabling stable synchronous recovery without overshoot.

Existing turbine signals drive automatic yaw correction to reduce misalignment losses and avoid extra wind direction sensors.

Analog start counts let wind turbines start sooner from intermittent threshold wind speeds, improving wind energy use and power output.

Sensor-driven control values adapt wind turbines to local conditions, boosting power output while reducing controller complexity and maintenance.

A wind turbine adjusts real-time operating modes against lifetime-consumption deviation to balance energy output and turbine longevity.

Real-time turbulence, air density, temperature, and shear data adjust turbine operating curves to raise yield within load and noise limits.

Airflow through the turbine tower cools power cables and sets dynamic current limits from temperature and flow data to raise output safely.

Real-time pitch and rotor speed control prevents blade stall and negative lift during sudden wind shifts without turbine shutdown.

Usage-based supervisory control tracks fatigue and extreme loads to adjust turbine operation, balancing energy output with lower maintenance cost.

Separating the wing from a torpedo-housed generator lets the kite sweep figure-8 currents for stronger energy capture without losing maneuverability.

Model predictive pitch control balances load reduction and energy production in wind turbines to improve bearing life and power quality.

An MPC-based pitch controller predicts turbine states to cut fluctuating loads while limiting bearing wear and preserving energy production.

Cluster-wide parameter distributions adjust turbine trigger thresholds to cut false alarms while protecting power production and equipment.