Stochastic Wind Park Modelling and Maintenance Scheduling under Uncertainty
Abstract
In this thesis, my main objective was to enable improved decision making for the scheduling of maintenance for offshore wind farms. The decisions depend on many factors which are subject to uncertainty.
The factors were studied in this thesis and it was identified where variations and uncertainty should be accounted for. Subsequently, an in depth analysis of two factors was conducted. A set of indicators were defined, which can be used to monitor a wind farm’s performance in terms of production, reliability, maintenance, finances and safety. The presented indicators enable the comparison of different maintenance strategies.
Weather was identified as an influential factor. Different methods for weather modeling have been presented and discussed as well as the influence of weather forecasts studied. The duration of maintenance actions - the repair time - was also identified as influential to the decision making.
Multiple ways to incorporate the repair time into decision support models have been presented and discussed. The included case studies confirm the importance of including the variation of the repair times as an input to maintenance scheduling models.
Following the identification and investigation of influential factors, a novel method for decision support has been presented. The included case study indicates a possible alternative maintenance strategy for future energy prices.
The findings from the previous chapters were integrated into a serious game that can be both used as a teaching tool for newcomers to the wind industry and as a general outreach tool. The thesis concludes with recommendations for future work.
Has parts
Paper 1: Seyr, Helene; Muskulus, Michael. Decision Support Models for Operations and Maintenance for Offshore Wind Farms: A Review. Applied Sciences 2019 ;Volum 9.(2) https://doi.org/10.3390/app9020278 This is an open access article distributed under the Creative Commons Attribution License (CC BY 4.0)Paper 2: Seyr, Helene; Muskulus, Michael. Safety Indicators for the Marine Operations in the Installation and Operating Phase of an Offshore Wind Farm. Energy Procedia 2016 ;Volum 94. s. 72-81 https://doi.org/10.1016/j.egypro.2016.09.200 This is an open access article under the CC BY-NC-ND license
Paper 3: Gonzalez, Elena; Nanos, Emmanouil; Seyr, Helene; Valldecabres, Laura; Yürüşen, Nurseda Y.; Smolka, Ursula; Muskulus, Michael; Melero, Julio. Key performance indicators for wind farm operation and maintenance. Energy Procedia 2017 ;Volum 137. s. 559-570 https://doi.org/10.1016/j.egypro.2017.10.385 This is an open access article under the CC BY-NC-ND license
Paper 4: Seyr, Helene; Muskulus, Michael. Interaction of repair time distributions with a weather model. I: Proceedings of the 29th International Congress on Condition Monitoring and Diagnostics Engineering Management (COMADEM 2016). COMADEM International 2016
Paper 5: Seyr, Helene; Muskulus, Michael. Value of information of repair times for o shore wind farm maintenance planning. Journal of Physics: Conference Series 2016 ;Volum 753 https://doi.org/10.1088/1742-6596/753/9/092009
Paper 6: Seyr, Helene; Barros, Anne; Muskulus, Michael. The Impact of Maintenance Duration on the Downtime of an Offshore Wind Farm - Alternating Renewal Process. I: Proceedings of the 30th International Congress & Exhibition on Condition Monitoring and Diagnostic Engineering Management Comadem 2017. Preston, UK: University of Central Lancashire 2017
Paper 7: Seyr, Helene; Muskulus, Michael. How does accuracy of weather forecasts influence the maintenance cost in offshore wind farms?. I: The Proceedings of the twenty-seventh (2017) International Ocean and Polar Engineering Conference - ISOPE 2017. International Society of Offshore & Polar Engineers 2017 ISBN 978-1-880653-97-5. s. 621-625
Paper 8: Seyr, Helene; Muskulus, Michael. Using a Langevin model for the simulation of environmental conditions in an offshore wind farm. Journal of Physics: Conference Series 2018 ;Volum 1104. https://doi.org/10.1088/1742-6596/1104/1/012023 Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence (CC BY 3.0)
Paper 9: Seyr, Helene; Muskulus, Michael. Use of Markov decision processes in the evaluation of corrective maintenance scheduling policies for offshore wind farms. Energies 2019 ;Volum 12.(15) https://doi.org/10.3390/en12152993 This is an open access article distributed under the Creative Commons Attribution License (CC BY 4.0)
Paper 10: Dornhelm, Esther; Seyr, Helene; Muskulus, Michael. Vindby—A Serious OffshoreWind Farm Design Game. Energies 2019 ;Volum 12.(8) http://doi.org/doi:10.3390/en12081499 This is an open access article distributed under the Creative Commons Attribution License (CC BY 4.0)