Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
The paper presents a model to coordinate the predictive-preventive maintenance process of Offshore Wind Farm (OWF) with optimal Vessel Fleet (VF) size support system. The model is presented as a bi-level problem. On the first level, the model coordinates the predictive-preventive maintenance of the OWF and the distributed Power System minimizing the risk of Expected Energy not Supply (EENS). The risk is estimated with a sequential Markov Chain Monte Carlo (MCMC) simulation model. On the second level the model determining the optimal fleet size of vessels to support maintenance activities at OWF.
Rocznik
Tom
Strony
823--830
Opis fizyczny
Bibliogr. 12 poz., rys., tab.
Twórcy
autor
- AGH University of Science and Technology, Kraków, Poland
autor
- AGH University of Science and Technology, Kraków, Poland
Bibliografia
- 1. Alcoba, A.G., Ortega, G., Hendrix, E.M.T., Weare, H., and Haugland, D. (2017). A model for optimal fleet composition of vessels for offshore wind farm maintenance. Procedia Computer Science, 108C, 1512‐1521.
- 2. Aminia, M.H., Kargariane, A., and Karabasoglua, O. (2016). Arima‐based decoupled time series forecasting of electric vehicle charging demand for stochastic power system operation. Electric Power Systems Research, 140, 378‐390.
- 3. Atwa, Y., El‐Saadany, E., Salama, M., Seethapathy, R., Assam, M., and Conti, S. (2011). Adequacy evaluation of distribution system including wind/solar dg during different modes of operation. IEEE Transactions on Power Systems, 26(4), 1945‐1952.
- 4. Billinton, R. and Allan, R. (1996). Reliability evaluation of power systems. 2nd Edition, Plenum Press. New York. ISBN: 0‐306‐45259‐6.
- 5. Billinton, R. and Huang, D. (2006). Peaking unit considerations in generating capacity adequacy assessment. Canadian Conference on Electrical and Computer Engineering, 2006. CCECE ʹ06, Ottawa, May 2006. 386‐389. ISBN: 1‐4244‐0038‐4.
- 6. Florian, M. and Sorensen, J.D. (2017). Risk‐based planning of operation and maintenance for offshore wind farms, 14th deep sea offshore wind R&D conference, EERA Deep‐Wind 2017, 18‐20 January 2017, Trondheim, Norway. Energy Procedia, 137, 261‐272.
- 7. Halvorsen‐Weare, E.E., Norstada, I., Stalhane, M., and Nonas, L.M. (2017). A metaheuristic solution method for optimizing vessel fleet size and mix for maintenance operations at offshore wind farms under uncertainty, 14th deep sea offshore wind R&D conference, EERA Deep‐Wind 2017, 18‐20 January 2017, Trondheim, Norway. Energy Procedia, 137, 531‐538.
- 8. Karki, R., Thapa, S., and Billinton, R. (2012). A simplified risk‐based method for short‐term wind power commitment. IEEE Transactions on Sustainable Energy, 3(3), 498‐505.
- 9. Stalhane, M., amd Elin E. Halvorsen‐Weareb, H.V., Hvattum, L.M., and Nonas, L.M. (2016). Vessel fleet optimization for maintenance operations at offshore wind farms under uncertainty, 13th deep sea offshore wind R&D conference, EERA Deep‐Wind 2016. Energy Procedia, 94, 357‐366.
- 10. Yan, Y., Ding, Y., Guo, C., Wang, R., Cheng, L., and Sun, Y. (2016). Operating reliability analysis of peaking generating units considering start‐up failures and degradation. 2016 Second International Symposium on Stochastic Models in Reliability Engineering, Life Science and Operations Management. 168‐171. ISBN: 978‐1‐4673‐99418/16.
- 11. Zhong, S., Pantelous, A.A., Beer, M., and Zhou, J. (2018). Constrained non‐linear multi‐objective optimization of preventive maintenance scheduling for offshore wind farms. Mechanical Systems and Signal Processing, 104, 347369
- 12. Zhong, S., Pantelous, A.A., Goh, M., and Zhou, J. (2019). A reliability‐and‐cost‐based fuzzy approach to optimize preventive maintenance scheduling for offshore wind farms. Mechanical Systems and Signal Processing, 124, 643663.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-f31f31b2-32ee-4cde-8d69-5d3fd6de716c