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Retrofit open-source Control System

 

Combining the advantages of an open source control system with the Windar Photonics LiDAR results in unprecedented AEP gains and load reductions.

 

The system solution is intended as a retrofit solution for the utility market - specifically for wind turbines in the range of 0.6MW to 2.5MW not covered by warranty. The general idea behind the system solution is to combine the separate optimization advantages of the control system technology with the Lidar technology into one complete retrofit solution.

 

Yaw misalignment can be reduced by integrating the LiDAR with the control system, which will significantly reduce loads on the turbine and yield an AEP increase of 1.5% to 2%. Further combining the LiDAR integration with the control system retrofit solution will potentially result in AEP gains of up to 4% to 5%. The further increase in AEP, compared with just integrating the LiDAR with the control system, is due to the system solutions' anticipatory pitch function that reduces power production spikes.

 

The combination of the yaw correction and anticipatory pitch functions will also significantly reduce damaging loads on the wind turbine, hence enhancing the longevity of the asset and reduce maintenance costs. By applying the system solution, the turbine's yaw and pitch strategies will be revised and adjusted according to the newest industry standards and methods to ensure a continuous revenue stream from the asset - both now and in the future.




Customizable Open-Source Software


As the software is open source, all standard application software and codes are transferred to the customer. Furthermore, due to the open source nature of the system solution’s software, it is possible to customize it according to the client's specifications and operational requirements. Hence, during the commissioning period of the pilot turbine, most alarm settings will be determined in cooperation with the
customer. Additionally, all alarms can be reset from the turbine control interface or the SCADA system.


Tried and True Hardware


On the technical level, the system solution offers a high degree of flexibility due to its open source software, while still being based on tried and true hardware that is running in over a thousand wind
turbines. This further means, that it is compatible with the current sensors and actuators.


The hardware modules has been developed with the goal of providing a high degree of reliability in wind environments and to function within extended temperature ranges, extended EMC ranges, and extended ranges of vibration.

Pitching and Power Spikes Explained


To regulate power output to its rated level, a wind turbine must pitch its blades to reduce the aerodynamic effectiveness, or efficiency, of the rotor. Since the wind must pass through the plane of the rotor disc to affect power production, blade pitching is a reactive action to a wind speed increase, thus delayed, and the power level can overshoot the rated level.


Once the blades have been pitched to regulate the maximum power and a reduction in wind speed occurs, the power will drop to a level that is below the
production potential of the turbine before the blades are pitched to the best angle, resulting in an energy loss.


Because of the lag between the time a gust or negative gust passes through the rotor and the reaction to the change in power output by blade pitching, there is a swing in power output about the targeted rated power.

 

This is demonstrated in the above diagram, which shows the instantaneous maximum and minimum recorded on a wind turbine during 10-minute periods. This is a plot of actual data, which has been nondimensionalized to a rated power of 1. The “hunting” action described above results in a rounding of the shape of the upper knee of the power performance curve. The rounding translates into available energy that is not captured.

 

Increasing the power gain


One way to capture this lost energy is to integrate the signal from a nacelle mounted Light Detection and Ranging (LiDAR) system into the turbine’s controller. Using the wind speed, a known distance ahead of the rotor, as measured by the LiDAR system, a control algorithm can be designed so that blade pitching is optimally timed for the varying wind speed arriving at
the rotor plane. This should reduce power variations during power regulation, thereby reducing the rounding of the upper knee of the power curve and result in increased energy capture over time.
 

The below illustration displays the hardware setup of the retrofit sontrol system integrated with the WindEYE ™ :

 

 

 

 


 

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