//AWESOME contributions to the WindEurope Conference & Exhibition 2017

AWESOME contributions to the WindEurope Conference & Exhibition 2017

WindEurope hosted its annual Conference & Exhibition (https://windeurope.org/confex2017/ ) from 28-30 November 2017 in Amsterdam. This event is one of the biggest gatherings of the wind energy community worldwide and attracted more than 7300 participants, 280 exhibitors and 400 presenters. The conference consisted of 39 sessions with 190 speakers and 200 posters.

This year, ‘Supply chain, logistics and O&M’ evolved as the most discussed topic. The AWESOME consortium contributed to this with five oral and one poster presentations in four different sessions, namely ‘To extend lifetime or to repower: the options, risks and benefits’, ‘Big data and data security in wind O&M’, ‘Predicting fatigue and lifetime of operating wind assets’ and ‘Using data to optimise performance’. All sessions received large attention confirming the interest of the wind industry for the topics of lifetime extension, failure prediction, big data and O&M optimisation.

Lisa Ziegler (Ramboll, NTNU) presented results from a recent study on ‘Lifetime extension of onshore wind turbines: A review covering Germany, Spain, Denmark and the UK’. This project was a collaboration with Elena González (CIRCE) and Tim Rubert (University of Strathclyde). The researchers compiled a comprehensive review on technical, economic, and legal aspects in the four countries mentioned. In addition, 24 guideline-based interviews were performed with key market players. Learn more in the journal paper and the poster.

Maik Reder (CIRCE) discussed his study titled ‘Modelling wind turbine failures based on weather conditions’. A generic wind turbine failure model based on environmental data taken from the turbines’ SCADA systems and meteorological masts located inside the wind farm was presented. The influence of different weather parameters on main wind turbine components was discussed. Learn more in the paper and the poster.

Lorenzo Colone (DTU) presented his work on ‘A multivariate approach to anomaly detection of main wind turbine components’. The research focused on how to turn performance output from monitoring systems to detect failure in main wind turbine components into quantities to measure its reliability, and how the processing of the error models actually affects such reliability. Learn more in the poster.

Nurseda Yildirim Yürüşen (CIRCE) discussed ‘The financial benefits of various catastrophic failure prevention strategies in a wind farm: two market studies (UK-Spain)’. This work was done in collaboration with Jannis Tautz-Weinert (LBORO) and consisted of performance and revenue analyses of a wind turbine affected by blade replacements. The consequences of imperfect maintenance and different electricity market dynamics were evaluated. Learn more in the paper and poster.

Estefania Artigao Andicoberry (UCLM) presented her work on ‘Condition monitoring of a wind turbine doubly-fed induction generator through current signature analysis’. In this study, an in-service wind turbine equipped with a doubly-fed induction generator (DFIG) has been analysed through current signature analysis. Faulty components related with gearbox damage have been identified on the spectral analysis of stator currents, and electrical rotor unbalance from the rotor analysis. The objective of the work is to contribute towards condition monitoring of wind turbines and hence to optimise O&M related activities. Learn more in the paper.

Elena Gonzalez (CIRCE) presentation was entitled ‘On the use of high-frequency SCADA data for improved wind turbine performance monitoring’. This work, performed in collaboration with the University of Strathclyde, advocates the use of raw SCADA data of high resolution instead of 10‑minute aggregated signals, as it is in the current industry practice. An empirical probabilistic approach is suggested to model normal performance and evidence for monitoring at higher resolutions is provided. In a practical example, transitional events of abnormal operation related to incipient faults are effectively detected. Learn more in the paper and poster.


By | 2018-03-12T12:18:25+00:00 December 19th, 2017|News|