Software-driven cost cutting and performance optimisation of wind turbines

Wind turbines are fascinating, not only due to their size, but also because of their hi-tech combination of large-scale mechanics, power engineering, sensors, and sophisticated software. Yet the wind turbine business is no different from any other industry, with fierce competition and a strong focus on optimisation and cost cutting. Software plays an important part in this game.

  • Published: 5. November 2019
  • By: Morten Fogtmann and Anthony Roberts for TechPeople
  • Company: Techpeople
Optimised Wind Turbines

With all the buzz surrounding sustainable energy you would think being in the wind turbine business could be compared to winning the lottery. Far from it: The global wind turbine industry is under considerable pressure, with only a handful of manufacturers making a profit.

Why? Because governments are gradually reducing their subsidies expecting renewable energy to become competitive on its own. Subsequently, competition is fierce and development engineers are working tirelessly to find new ways to cut production costs while increasing the output and the durability of each new generation of wind turbines.

Levelised Cost of Energy

So, although software developers come at a comparatively high price for wind turbine manufacturers, their work is crucial for cost savings in the long run. They continuously find ways to reduce what the energy sector refers to as LCoE, Levelised Cost of Energy, being the summary measure of the overall competitiveness of different energy generating technologies.

Software is a key component in this effort. Software is an important tool for optimising cost in the wind industry, on many levels and touching on all parts of a wind turbine: tower, nacelle, hub, rotor, and power electronics.

TechPeople is a long-standing partner of the Danish wind industry and TechPeople software engineers are contributing to numerous projects using software to optimize the design and the output of wind turbines. However, due to the competitive situation in the sector, many of these projects are subject to Non Disclosure Agreements. That is why this article will be focusing not so much on specific projects as on presenting a high-level view of the challenges and achievements in using software as a cost-optimising tool in the wind industry.

Turning hardware into software

Eliminating a piece of hardware and replacing it with software is a well-known cost-saving measure in many industries. It is done in the wind industry as well. As an example, a hardware counter module monitoring the toothed ring to measure speed and angle of the hub can be replaced by transferring the hardware functionality into FPGA code.

Optimising the structure of the tower

In building wind turbine towers, the amount of steel needed is an important cost factor. The tower must be able to cope with the pressure on the rotor blades, dependent on wind speeds in the specific area where the wind turbine is deployed.

The blades can be pitched to manage the pressure against the tower, adjusting to different wind speeds, and changing the angle of the rotors towards the wind. This reduces wind pressure and subsequently reduces the need for steel used in the tower. Furthermore, the pitch system allows the turbine to operate in conditions where a turbine with fixed wings would be forced to shut down to protect itself. The pitch system of a state-of-the-art wind turbine is controlled by a distributed real-time system enabling the wings to pitch very quickly.

You can even pitch each rotor blade separately and make it pitch automatically when it passes the tower, to reduce stress on the tower resulting from the change in wind characteristics when the blade passes the tower. This increases the lifespan of the wind turbine.

What is a distributed real-time system?

A distributed real-time system consists of a number of (computer) nodes that are interconnected by a real-time communication network. Most distributed real-time systems are embedded in larger systems, like a mobile phone, a car or a wind turbine, interacting closely with their physical environment. The performance of such a system depends not only on the logical results of the computation but also on the exact time these results are produced. Many applications are safety or mission critical, so fault tolerance and reliability are crucial features.

A distributed real-time system can contribute to optimization and cost saving by enabling a device to react immediately to outside input and thus achieve a higher degree of efficiency and performance.

Sensor fusion

A modern wind turbine is equipped with a vast number of sensors measuring e.g. speed, temperature, vibration, light etc. Without sensors, wind turbines would be less safe, more costly to operate, and have lifetimes less than the 25 years they are expected to run. Furthermore, wind turbine operators rely on accurate data about every turbine and its components, to secure operational safety and efficient maintenance. As an example, dedicated sensors can detect sparks produced by faulty machinery, to prevent fire.


Also, increased processing capabilities lead to new ways of using sensors,
including using them for other tasks than they were designed for.


Also, increased processing capabilities lead to new ways of using sensors, including using them for other tasks than they were designed for. For instance, data from a wind speed sensor can detect ice on the rotor blades. With multi-sensor data fusion you can design sophisticated fault detection systems with a higher diagnostic accuracy than individual sensors, with an array of vibrational, acoustic, temperature etc. sensors monitoring gearboxes, blades, and other mission critical parts of the wind turbine.

What is multi-sensor data fusion?

Multi-sensor data fusion refers to combining observations from a number of different sensor types to monitor complex machinery e.g. self-driving vehicles, based on the assumption that evaluating data from disparate sources leads to a more precise result than if the sources were used individually. In a sense, multi-sensor data fusion tries to replicate the work performed by the human brain, weaving diverse input together to form a complex picture, taking advantage of different “points-of-view”. Multi-sensor data fusion is widely used in robotics and can utilize techniques like pattern recognition, artificial intelligence and statistical estimation.

Wind turbines need electricity to run

It may come as a surprise to many, but wind turbines need electricity to run. Not only do they produce energy, they consume energy as well, so they need back-up power supply, for instance for starting up again after shutdown due to strong winds. Restarting a modern wind turbine is a complex task. You have to re-calibrate the wind turbine and synchronize it to the grid, before releasing the brake.

Offshore turbines in particular have to be designed to use as little power as possible produced by their diesel generators, to make fuel supply last as long as possible and keep expensive re-filling at a minimum. Software is used to optimise the energy consumption of the turbines.

Adjusting wind turbines to national requirements

Manufacturing wind turbines is a global business, so manufacturers use much manpower to adjust their products to local legal and environmental requirements. This also goes for the lights on top of the turbines. They have to be adapted to local requirements, both when it comes to light intensity, colour and frequency. In some places the lights have to blink 24/7, elsewhere only at night or only when airplanes are approaching.

Detecting airplanes requires a radar system, and similar measures are taken for “bat detection”.

Bats and wind turbines don’t go well together, and in many countries bats are protected animals. To prevent them collide with the rotor blades, a bat detecting system stops the wind turbine when bats are detected in the vicinity. The reason for choosing these seemingly extreme measures is that a bat detection system makes it possible to deploy wind turbines in areas where it would be otherwise prohibited.

How does a bat detection system work?

Wind turbines can be a lethal threat to bats. Not only do they risk direct collision, but also the high air pressure differences in the area surrounding the turning blades can cause internal injuries.

One form of bat protection strategy is to limit the operating period of the turbine based on time of day and year, as research shows, that bats are most active within two hours of sunset and in temperatures between 19 and 21 degrees. The disadvantage is a reduction in operating time and thus power production. Another approach would be to place hyper-sensitive microphones around the turbines to detect the ultrasound signals bats use to orient and forage. The ultrasound signals are then analysed, and according to the specific bat species identified and its behavioural pattern the operation of the wind turbine shifts to bat-mode, e.g. changing rotor speed, changing the pitch angle of the rotor blades etc. In this way the turbine can still produce energy while reducing the risk of bat encounters.

Also, bat deterrent systems are being developed that use ultrasonic speakers to discourage bats from approaching operating wind turbines. The speakers produce ultrasonic sound in a range of frequencies that negate the bat’s own signals. Bats send out ultrasound signals and use the reflections of these signals to navigate and find insects etc. The deterrent system sends out a signal that masks the bat’s return signal, so that it cannot locate any prey in the airspace surrounding the turbine rotors.

Competition continues

Nothing indicates, that the competition in the wind sector will diminish in coming years. So, probably the world will run out of fossil fuel before software engineers in the wind energy business will run out of challenges. Software will continue to play a crucial role in cost cutting and optimisation, including utilizing Machine Learning and Artificial Intelligence, together with an ever-increasing number of sensors for control and monitoring. Also, with wind turbines getting larger and larger, and offshore wind farms moving further away from land, much remains to be done.