Improving the Efficiency of Wind Turbines with an Intelligent Measurement and Control System


The Challenge: Building a system to measure and control the behavior of a wind turbine blade to improve the efficiency of wind turbines. The main challenge was developing an advanced measurement and control system that worked in a limited amount of space in a rough environment inside the three windturbine blades. The three blades needed to acquire data and communicate with each other at 100 Hz to fine-tune the control of each blade. The data also needed to be stored and displayed on a server on the ground. Lastly, the system had to be scalable and versatile to handle changing specifications as the project progressed.                                                

The Solution: Using NI CompactRIO, NI EtherCAT, and NI industrial controllers as well as NI LabVIEW system design software to build an intelligent measurement and control system that helped us further optimize the efficiency of our wind turbines.


Wind Energy Development

As energy consumption soars, where are the fuels that will meet the demand? Fossil fuels are a finite resource. The natural replacement is sweeping freely around the earth—wind. Wind is renewable, predictable, fast to install, clean, and commercially viable. We have the data to support our prediction that, by 2020, as much as 10 percent of the world’s electricity consumption will be satisfied by wind energy. Additionally, we have the confidence to say that wind power is an industry on par with oil and gas.

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Figure 1. Vestas Windmill

Vestas is dedicated exclusively to wind energy, and is one of the clear leaders in its development. We have discovered many wind energy innovations, and this time we were studying the behavior of windturbine blades. We wanted to measure and control the blades to optimize our wind turbines. This was challenging because there were multiple real-time measurement and control tasks. The environment was challenging, too, because we needed to fit the system into the interior of a windturbine blade, and it needed to fulfill the environmental requirements for a machine that works in harsh weather conditions.

System Requirements

We wanted a versatile system that was easy to modify and maintain. With our current system, some measurement parts needed to be installed in a way that would require a lot of work to reconfigure later if the requirements changed. Imagine the maintenance challenge in a windturbine. You really don’t want to climb to the top of the tower just to modify the code of the system after it is installed. Also, the system was built in the interior of the windturbine blade, so you would be forced to stop the system before you could access the hardware. This is why we needed a system that we could program from the ground. The software-defined hardware platform offered by NI CompactRIO was a good choice for this.

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Figure 2. TheSystem Installed in the Interior of a Windmill Blade

The system needed to measure different kinds of sensors and run advanced algorithms for the measurement data in real time, and, based on those results, control the blades. To make it even more challenging, we wanted it to reuse data from all three blades at the same time.

System Architecture

We used NI CompactRIO hardware and NI LabVIEW system design software to build this extremely challenging measurement and control system. Because of the challenging architecture of the project, we decided to work with National Instruments Gold Alliance Partner CIM Industrial Systems A/S to design the architecture and deliver the solution. We have worked with CIM on similar projects, and we were confident they could address our challenge.

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Figure 3. The Measurement and Control System High-Level Architecture

CIM designed the hardware architecture with multiple NI cRIO-9025 real-time embedded controllers, NI 9144 EtherCAT expansion chassis, and NI 3110 industrial controller systems with multiple measurement channels (Figure 3). We had one master controller that could handle all communication between different controllers inside the blades and the Vestas HUB controller. Data was acquired using NI Scan Engine technology so that we could access the data of the six EtherCAT chassis at 100 Hz. The data was filtered, scaled, and sent to the two other blades and the master controller at the same rate using controller area network (CAN) and NI-XNET. Upon receiving similar information from the neighboring blades, the blade controller could control the blade using a combination of feedforward and proportional integral derivitive (PID) control.

To cope with the prospect of evolving and changing specifications, CIM opted for modular event-based code so that every software component within the target could run independently. This greatly reduced testing time and provided flexibility as modules were changed, removed, enabled, or disabled to cope with ongoing hardware modifications and changes in CAN or TCP/IP protocol or to simply ignore the dreaded broken RUN-arrow.


We had demanding requirements and a tough schedule for this complex measurement and control system, and in the end, we exceeded some of those requirements. The NI CompactRIO software-defined hardware platform was a good fit for our needs. We built a flexible and versatile system which could be reconfigured; as new demands arose. The measurements we made were valuable. The amount of data and the rate it was acquired at helped us observe elusive phenomena such as second and third-order harmonics. The determinism and synchronicity of the system enabled the fast control loop needed for the project execution. The lessons learned from this project will help us further optimize the efficiency of our wind turbines.

The NI CompactRIO and LabVIEW platform has chosen to be a robust and versatile platform, which will continue to use. The flexibility of the systems, make the platform well suited for measurement and control projects, where the scope is not always completely defined from the onset of the project.

Author Information: 
Niels Anker Olesen, Vestas Technology

Bjarke DahlMadsen, CIM