IntelliWind: Intelligent systems for autonomous Wind power plant operations

At a glance

• Most wind farms are still operated without the use of artificial intelligence. However, in light of the growing number of turbines and shortage of skilled workers, largely autonomous operation will prove necessary in the future.
• The training of engineers is not yet designed with this in mind – the required broad, multidisciplinary skill set is not being taught.
• Here, the international joint project IntelliWind comes in: the aim is to train the next generation of multidisciplinary researchers, who will develop intelligent systems that support autonomous wind power plant (WPP) operation.

The challenge

The operation of wind farms is heading toward a bottleneck: in the future, higher numbers of wind turbines will contribute to a climate-friendly energy supply. However, there is already a shortage of qualified specialists for their operation and maintenance, and the situation is set to worsen in the foreseeable future. In addition, the fact that wind farms are often difficult to reach – especially offshore ones – makes deployments at the farms expensive and time-consuming.

The solution to both problems is largely autonomous operation of the farms. However, this requires the employment of decision models and advanced AI technologies which do not yet reflect the state of the art. The engineers involved require a broad, multidisciplinary skill set to be able to develop them successfully. However, current education systems are not yet designed to provide specialists with such a broad range of skills at the necessary competence level.

The solution

Here, the European joint project IntelliWind comes in. It is pursuing both a research and a training focus. The primary aim is to train the next generation of multidisciplinary researchers, who will develop intelligent systems that support autonomous wind power plant (WPP) operation. 16 doctoral candidates will be employed by the different project partners to deliver answers to specific research issues with industrial applications. The aim of the research project is to reduce the role of humans considerably.

Thematically, IntelliWind is focusing on a number of key areas, including:

• obtaining and processing reliable data and methods for the assessment of the current status of the turbines as well as a portfolio of available mitigation measures and their effects;
• definition of clear criteria for the assessment of the robustness, uncertainties, and reliability of these AI technologies; and
• development of an AI decision-making process spanning the whole chain from information processing to insights right up to optimal business decisions.

One of the doctoral candidates will be employed at Fraunhofer IWES. The focus of the work here is on the improvement of data quality and its evaluation. 

The added value

First, IntelliWind will lead to more effective operation of wind farms. AI-supported decision-making processes will free up human resources for other tasks. In addition, the project will trigger a change in thinking regarding the training of future engineers in the field of wind energy – away from traditional engineering tasks and toward design, analysis, and interaction with automatic machine algorithms.