ReStroK

  Project flow diagram Copyright: © CWD  

Reduction of electricity generation costs using historical and current operating and service data of onshore wind turbines

The aim of the "ReStroK" project is to merge and analyse operating data, service reports and data on the turbine configuration of wind turbines in order to derive concrete recommendations for action for service technicians and operators with the aim of generating economic added value.

In order to enable a largely automated and scalable evaluation, the data available in different forms and qualities must be structured, merged and entered into a database system. Both current and historical data are considered. By transferring "Industry 4.0" approaches (extensive digitisation and networking, real-time data analysis, merging of heterogeneous data sets) to the needs of the wind energy sector, previously untapped potential can be tapped.

Three use cases will be implemented in the project. Based on the results of evaluation strategies that are developed and applied, maintenance activities are initiated and coordinated (use case I), the remaining service life of individual turbines is calculated (use case II) and the turbine behaviour in the wind farm network is investigated (use case III). An app-based software demonstrator will be developed to present the analysis results of the three use cases. Furthermore, a simulation game for the qualification of technicians and operators will be introduced. In addition to the necessary data, the industrial partners contribute their industry-specific know-how for the evaluation of fault events and abnormal operating states. This knowledge is combined with the research methods of the research institutions. Furthermore, extensive measurement data of a generic research wind turbine are available.

The project results enable companies in the fields of maintenance and operational management to increase their efficiency. The results are primarily available in the form of software, guidelines and descriptions of algorithms. They are made available under an open source license and can be integrated into ongoing business processes at a manageable cost.

Coordinator:

FIR an der RWTH Aachen e.V.
Campus-Boulevard 55
52074 Aachen

Duration:

01.05.2019 - 30.04.2022

Funded project partners:

Forschungsinstitut für Rationalisierung an der RWTH e.V. Hoffmeister GmbH PSM Windservice GmbH & Co. KG
 
 

Associated project partners:

Stadtwerke Aachen AG
 
 

Project funded by:

European Regional Development Fund EFRE.NRW 2014-2020