Application of the Semi-Markov Processes to Model the Enercon E82-2 Preventive Wind Turbine Maintenance System
The share of wind energy in the energy mix is continuously increasing. However, a very important issue associated with its generation is the high failure rate of wind turbines. This situation particularly concerns large wind turbines, which are expensive and have a lower tolerance for system damage...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-12-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/17/1/199 |
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| author | Mirosław Szubartowski Klaudiusz Migawa Sylwester Borowski Andrzej Neubauer Ľubomír Hujo Beáta Kopiláková |
| author_facet | Mirosław Szubartowski Klaudiusz Migawa Sylwester Borowski Andrzej Neubauer Ľubomír Hujo Beáta Kopiláková |
| author_sort | Mirosław Szubartowski |
| collection | DOAJ |
| description | The share of wind energy in the energy mix is continuously increasing. However, a very important issue associated with its generation is the high failure rate of wind turbines. This situation particularly concerns large wind turbines, which are expensive and have a lower tolerance for system damage caused by various failures and faults. Vulnerable components include sensors, electronic control units, electrical systems, hydraulic systems, generators, gearboxes, rotor blades, and so on. As a result, significant emphasis is placed on improving the reliability, availability, and productivity of wind turbines. It is extremely important to detect and identify abnormalities as early as possible and predict potential failures and damages and the remaining useful life of components. One way to ensure turbine efficiency is to plan and implement preventive repairs. This work shows a semi-Markov model of a preventive maintenance system based on Enercon E82-2 wind turbines. The system’s performance quality is evaluated based on profit over time and an asymptotic availability coefficient. The developed model establishes formulas describing the efficiency functions and formulates the conditions for the existence of extremes (maxima) of these functions. Computational examples provided at the end of the paper illustrate the obtained research results. A preventive maintenance model is developed that can be applied to wind turbine hazard prevention (determining optimal times for wind turbine preventive maintenance). |
| first_indexed | 2024-03-08T15:07:46Z |
| format | Article |
| id | doaj.art-bdc92b7e8090403ab5c9c916c85cd56a |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-08T15:07:46Z |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-bdc92b7e8090403ab5c9c916c85cd56a2024-01-10T14:56:12ZengMDPI AGEnergies1996-10732023-12-0117119910.3390/en17010199Application of the Semi-Markov Processes to Model the Enercon E82-2 Preventive Wind Turbine Maintenance SystemMirosław Szubartowski0Klaudiusz Migawa1Sylwester Borowski2Andrzej Neubauer3Ľubomír Hujo4Beáta Kopiláková5Faculty of Mechanical Engineering, Bydgoszcz University of Sciences and Technology, 85-795 Bydgoszcz, PolandFaculty of Mechanical Engineering, Bydgoszcz University of Sciences and Technology, 85-795 Bydgoszcz, PolandFaculty of Mechanical Engineering, Bydgoszcz University of Sciences and Technology, 85-795 Bydgoszcz, PolandFaculty of Mechanical Engineering, Cuiavian University in Włocławek, 87-800 Włocławek, PolandFaculty of Special Technology, Trenčianska Univerzita Alexandra Dubčeka v Trenčíne, 911 50 Trencin, SlovakiaFaculty of Special Technology, Trenčianska Univerzita Alexandra Dubčeka v Trenčíne, 911 50 Trencin, SlovakiaThe share of wind energy in the energy mix is continuously increasing. However, a very important issue associated with its generation is the high failure rate of wind turbines. This situation particularly concerns large wind turbines, which are expensive and have a lower tolerance for system damage caused by various failures and faults. Vulnerable components include sensors, electronic control units, electrical systems, hydraulic systems, generators, gearboxes, rotor blades, and so on. As a result, significant emphasis is placed on improving the reliability, availability, and productivity of wind turbines. It is extremely important to detect and identify abnormalities as early as possible and predict potential failures and damages and the remaining useful life of components. One way to ensure turbine efficiency is to plan and implement preventive repairs. This work shows a semi-Markov model of a preventive maintenance system based on Enercon E82-2 wind turbines. The system’s performance quality is evaluated based on profit over time and an asymptotic availability coefficient. The developed model establishes formulas describing the efficiency functions and formulates the conditions for the existence of extremes (maxima) of these functions. Computational examples provided at the end of the paper illustrate the obtained research results. A preventive maintenance model is developed that can be applied to wind turbine hazard prevention (determining optimal times for wind turbine preventive maintenance).https://www.mdpi.com/1996-1073/17/1/199wind turbineage-replacementprofit per unit timeavailabilitysemi-Markov processespreventive maintenance |
| spellingShingle | Mirosław Szubartowski Klaudiusz Migawa Sylwester Borowski Andrzej Neubauer Ľubomír Hujo Beáta Kopiláková Application of the Semi-Markov Processes to Model the Enercon E82-2 Preventive Wind Turbine Maintenance System Energies wind turbine age-replacement profit per unit time availability semi-Markov processes preventive maintenance |
| title | Application of the Semi-Markov Processes to Model the Enercon E82-2 Preventive Wind Turbine Maintenance System |
| title_full | Application of the Semi-Markov Processes to Model the Enercon E82-2 Preventive Wind Turbine Maintenance System |
| title_fullStr | Application of the Semi-Markov Processes to Model the Enercon E82-2 Preventive Wind Turbine Maintenance System |
| title_full_unstemmed | Application of the Semi-Markov Processes to Model the Enercon E82-2 Preventive Wind Turbine Maintenance System |
| title_short | Application of the Semi-Markov Processes to Model the Enercon E82-2 Preventive Wind Turbine Maintenance System |
| title_sort | application of the semi markov processes to model the enercon e82 2 preventive wind turbine maintenance system |
| topic | wind turbine age-replacement profit per unit time availability semi-Markov processes preventive maintenance |
| url | https://www.mdpi.com/1996-1073/17/1/199 |
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