Cost effective maintenance of wind turbines using components reliability
Wind turbine system reliability is a critical factor. Poor reliability directly affects both the project’s revenue stream through increased operation and maintenance (O&M) costs and reduced availability to generate power due to turbine downtime. This task will develop component level reliability models by using SCADA data together with maintenance logbooks. These models will allow optimizing O&M costs for the whole wind farm.
The previously defined objectives to realize this task are, firstly, to check and improve the existent models in a bigger scenario to assure their functionality, secondly, to define appropriate models for older wind turbines. Most of the published studies are focused on new wind turbines but there are old wind farms that need this kind of studies in order to be optimized, and finally to include the environmental parameters in the models in a proper way. Considering variable affections between the different weather and reliability parameters, in order to define the costs model more accurately including lack of production, main parts of the turbine and the weather conditions. Historical corrective maintenance costs will be used to obtain better results.
The expected outcome should include the following three objectives:
Improved reliability model of the WT components verified with a high amount of data.
Reliability model for older wind turbine components.
O&M cost model based on the reliability model, the weather conditions and historical respective maintenance data.
Enel Green Power (EGP)
Tentative schedule: Spring – Summer 2016
Technical University of Denmark (DTU)
Tentative schedule: Spring – Summer 2017
Reder, M, Gonzalez, E and Melero, JJ (2016) Wind Turbine Failures – Tackling current Problems in Failure Data Analysis, Journal of Physics: Conference Series, 753(072027), DOI: 10.1088/1742-6596/753/7/072027. Full text: http://iopscience.iop.org/article/10.1088/1742-6596/753/7/072027
Gonzalez, E, Reder, M and Melero, JJ (2016) SCADA alarms processing for wind turbine component failure detection, Journal of Physics: Conference Series, 753(072019), DOI: 10.1088/1742-6596/753/7/072019. Full text: http://iopscience.iop.org/article/10.1088/1742-6596/753/7/072019
Reder, M and Melero, JJ (2016) Assessing Wind Speed Effects on Wind Turbine Reliability. In WindEurope Summit 2016, Hamburg. DOI: 10.13140/RG.2.2.11134.59200. Full text: https://www.researchgate.net/publication/308720683_Assessing_Wind_Speed_Effects_on_Wind_Turbine_Reliability
Reder, M, Gonzalez, E and Melero, JJ (2016) Wind Turbine Failures – Tackling current Problems in Failure Data Analysis, The Science of Making Torque from Wind (TORQUE 2016), Munich. Full text: https://www.researchgate.net/publication/308901537_Wind_Turbine_Failures_-Tackling_current_Problems_in_Failure_Data_Analysis
Gonzalez, E, Reder, M and Melero, JJ (2016) SCADA alarms processing for wind turbine component failure detection, The Science of Making Torque from Wind (TORQUE 2016), Munich. Full text: https://www.researchgate.net/publication/309040863_SCADA_alarms_processing_for_wind_turbine_component_failure_detection
L. Colone, M. Reder, J. Tautz-Weinert, J.J. Melero, A. Natarajana, S.J. Watson (2017). Optimisation of Data Acquisition in Wind Turbines with Data-Driven Conversion Functions for Sensor Measurements. IEERA DEEPWIND’2017, 14TH DEEP SEA OFFSHORE WIND R&D CONFERENCE, Trondheim, Norway. Download Poster
Julio J. Melero
Host Institution: Circe