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AWESOME project releases the 1st Joint Industry Workshop Scientific report


The 1st Joint Industrial Workshop of the project was held in Berlin from 16th to 19th of February 2016. It was the first public activity of AWESOME and was attended not only by the members of the project consortium but also by professionals of the wind industry. The aim of this short of workshop was to identify and present the main barriers and issues that the O&M of wind farms is facing, in order to make a deep analysis and present solutions to overcome these and future problems.

The Workshop was divided into two different parts. On the first day, the industry partners presented problems of their interest in a round-table shaped session. As a result of the session, two problems were selected and presented to the fellows:

>> Use of measurement data for cost-effective O&M
>> Definition of Key Performance Indicators for O&M

The second part of the workshop was devoted to the work of the fellows on the industry proposals. They spent the next two days working on them. During this time, they split into two groups, each one working on a different problem. Brain storming and work group techniques were used in order to provide answers to the raised questions. Finally, they wrote a final report containing their contributions and conclusions.

This document represents the outcomes of the 1st Joint Industrial Workshop of the AWESOME project. It contains two reports giving answers to the problems presented by the industry partners.


On the way to reducing maintenance costs, the industry goes towards gathering large amounts of monitoring data from wind farms. However, a lack of capabilities to interpret the data for condition-based maintenance is observed. Current experiences make it questionable if the trend towards more sensor applications is effective for cost reduction. Further development is needed to identify which monitoring investments are beneficial. Through creative brainstorming, an innovative research idea was developed which focuses on the identification of synergies between measurements of different physical parameters. The goal is to build data-driven conversion functions between measurements in order to understand which sensors are important and which dispensable. This leads to an economic benefit by banishing unnecessary monitoring equipment but also increases the accuracy of health assessment of wind turbine components through improved understanding of sensor signals. This report outlines the research idea and gives a brief suggestion on an analysis approach, benefits, challenges, and future work.



This report presents research on suitable KPIs for the Operations and Maintenance phase of a wind power project in a theoretical and systematic way. The goal is to establish the basis for a discussion that exceeds the empirical approach of the current practice in the industry and give an insight into a more systematic set of tools, with the aim to influence both industry and academia to continue this effort. The goal of this research is to find metrics that can be identified, measured, reported and managed so that a wind farm’s operation can be assessed quickly and efficiently by all of the stakeholders involved.

Before analysing the currently used KPIs from the industry stakeholders, the KPIs properties that should have were defined and as a conclusion they should be relevant, specific, measurable, comparable, traceable in time, standardised and easy to understand. Moreover, they should be able to trigger changes and the set of KPIs achieving this should be minimal. The main purpose of a KPI is to directly provide information relevant to performance and to provide information on controllable factors that are appropriate for decision-making.

Subsequently, the KPIs of each defined category were evaluated focusing on both the ones used in industry and the ones reported in the literature. In doing so, it was found that the there is no agreement in which KPIs should be used for the defined purposes and that there is not a well-defined KPI-set in the industry sector. Then the existing KPIs and their properties were analysed and the result was that not all the evaluated KPIs fulfil the defined properties. Finally, a list of KPIs selected from the set of existing KPIs was proposed based on the analysis and discussion.