Abstract
Maintenance of offshore wind turbines is a complex and costly undertaking which acts as a barrier to the development of this source of energy. Factors such as the size of the turbines, the size of the wind farms, their distance from the coast and meteorological conditions make it difficult for the stakeholders to select the optimal maintenance strategy. With the objective of reducing costs and duration of such operations it is important that new maintenance techniques are investigated. In this paper we propose a hybrid model of maintenance that is based on multi-agent systems; this allows for the modelling of systems with dynamic interactions between multiple parts. A multi-criteria decision algorithm has been developed to allow analysis and selection of different maintenance strategies. A cost model that includes maintenance action cost, energy loss and installation of monitoring system cost has been presented. For the purposes of this research we have developed a simulator using NetLogo software and have provided experimental results. The results show that employing the proposed hybrid maintenance strategy could increase wind farm productivity and reduce maintenance cost.
Similar content being viewed by others
References
Ainslie, J. F. (1988). Calculating the flowfield in the wake of wind turbines. Journal of Wind Engineering and Industrial Aerodynamics, 27(1), 213–224.
Ammara, I., Leclerc, C., & Masson, C. (2002). A viscous three-dimensional differential/actuator-disk method for the aerodynamic analysis of wind farms. Journal of Solar Energy Engineering, 124(4), 345–356.
Astariz, S., Perez-Collazo, C., Abanades, J., & Iglesias, G. (2015). Co-located wind-wave farm synergies (operation & maintenance): A case study. Energy Conversion and Management, 91, 63–75.
Babu, J. R., & Jithesh, S. (2008). Breakdown risks in wind energy turbines. Pravartak, the Journal of Insurance and risk Management from National Insurance Academy, Pun, 3, 3–23.
Besnard, F., Fischer, K., & Tjernberg, L. B. (2013). A model for the optimization of the maintenance support organization for offshore wind farms. Sustainable Energy, IEEE Transactions on, 4(2), 443–450.
Braam, H., & Verbruggen, T. W. (2000). R & D NEEDS FOR O & M OF WIND TURBINES
Brennan, F. (2013). Risk based maintenance for offshore wind structures. Procedia CIRP, 11, 296–300.
Burton, T., Jenkins, N., Sharpe, D., & Bossanyi, E. (2011). Wind energy handbook. Chichester: Wiley.
Byon, E., Ntaimo, L., & Ding, Y. (2010). Optimal maintenance strategies for wind turbine systems under stochastic weather conditions. Reliability, IEEE Transactions on, 59(2), 393–404.
Byon, E., Pérez, E., Ding, Y., & Ntaimo, L. (2011). Simulation of wind farm operations and maintenance using discrete event system specification. Simulation, 87(12), 1093–1117.
Cunha, P., Duarte, J. C., & Alting, L. (2004). Development of a productive service module based on a life cycle perspective of maintenance issues. CIRP Annals-Manufacturing Technology, 53(1), 13–16.
Dahane, M., Sahnoun, M., Bettayeb, B., Baudry, D., & Boudhar, H. (2015) Impact of spare parts remanufacturing on the operation and maintenance performance of offshore wind turbines: A multi-agent approach. Journal of Intelligent Manufacturing. doi:10.1007/s10845-015-1154-1
Dimeas, A. L., & Hatziargyriou, N. D. (2005). Operation of a multiagent system for microgrid control. IEEE Transactions on Power Systems PWRS, 20(3), 1447.
Energy, C. (2014). The basic components of a turbine. http://www.coriolis-energy.com/wind_energy/wind_technology.html
Fécamp, E. D. P. D. (2013). Biln carbone du parc éolien en mer au large de fécamp
Feijòo, A. E., Cidràs, J., Dornelas, J. L. G. (1999). Wind speed simulation in wind farms for steady–state security assessment of electrical power systems. IEEE Transactions on Energy conversion, 14(4), 1582–1588.
Fischer, K., Besnard, F., & Bertling, L. (2012). Reliability-centered maintenance for wind turbines based on statistical analysis and practical experience. Energy Conversion, IEEE Transactions on, 27(1), 184–195.
Gundegjerde, C., Halvorsen, I. B., Halvorsen-Weare, E. E., Hvattum, L. M., & Nonås, L. M. (2015). A stochastic fleet size and mix model for maintenance operations at offshore wind farms. Transportation Research Part C: Emerging Technologies, 52, 74–92.
Haddad, G., Sandborn, P., & Pecht, M. (2014). Using maintenance options to maximize the benefits of prognostics for wind farms. Wind Energy, 17(5), 775–791.
Hau, E., & Von Renouard, H. (2013). Wind turbines: Fundamentals, technologies, application, economics. Berlin: Springer.
Henderson, A. R., Morgan, C., Smith, H. C., Barthelmie, R. J., & Boesmans, B. (2003). Offshore wind energy in Europe—a review of the state-of-the-art. Wind energy, 6(1), 35–52.
Herbert, G. J., Iniyan, S., & Amutha, D. (2014). A review of technical issues on the development of wind farms. Renewable and Sustainable Energy Reviews, 32, 619–641.
Hyers, R., McGowan, J., Sullivan, K., Manwell, J., & Syrett, B. (2006). Condition monitoring and prognosis of utility scale wind turbines. Energy Materials, 1(3), 187–203.
Ivan Pineda, S. A., Moccia, J., & Wilkes, J. (2014). Wind in power 2013 (February):1–12.
Jensen, N. O. (1983). A note on wind generator interaction
Karki, R., & Patel, J. (2009). Reliability assessment of a wind power delivery system. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 223(1), 51–58. doi:10.1243/1748006XJRR218.
Kim, H., Singh, C., & Sprintson, A. (2012). Simulation and estimation of reliability in a wind farm considering the wake effect. Sustainable Energy, IEEE Transactions on, 3(2), 274–282.
Kooijman, H., Lindenburg, C., Winkelaar, D., & van der Hooft, E. (2003). Dowec 6 mw pre-design. Energy Research Center of the Netherlands (ECN).
Larsen, G. C. (1988). A simple wake calculation procedure (Risø-M; No. 2760). http://orbit.dtu.dk/files/55567186/ris_m_2760.pdf.
Lau, B. C. P., Ma E. W. M., & Pecht, M. (2012). Review of offshore wind turbine failures and fault prognostic methods. In Proceedings of the IEEE 2012 prognostics and system health management conference (PHM-2012 Beijing) (pp. 1–5). doi:10.1109/PHM.2012.6228954
Liyanage, J. P. (2008). Integrated e-operations-e-maintenance: Applications in north sea offshore assets. In Complex system maintenance handbook (pp. 585–609). Springer.
Lu, B., Li, Y., Wu, X., & Yang, Z. (2009). A review of recent advances in wind turbine condition monitoring and fault diagnosis. In Power electronics and machines in wind applications, 2009 (PEMWA 2009) (pp. 1–7). IEEE.
Mustafee, N., Sahnoun, M., Smart, A., & Godsiff, P. (2015). An application of distributed simulation for hybrid modeling of offshore wind farms. In Proceedings of the 2015 ACM SIGSIM/PADS conference on principles of advanced discrete simulation, June 10–12, 2015, London (pp.171–172). New York, NY: ACM. doi:10.1145/2769458.2769492.
Nielsen, J. J., & Sørensen, J. D. (2011). On risk-based operation and maintenance of offshore wind turbine components. Reliability Engineering & System Safety, 96(1), 218–229.
Nilsson, J., & Bertling, L. (2007). Maintenance management of wind power systems using condition monitoring systems mdash;life cycle cost analysis for two case studies. Energy Conversion, IEEE Transactions on, 22(1), 223–229. doi:10.1109/TEC.2006.889623.
Palanci, A. (2011). Leak-free hydraulic fittings prevent vibration failure. Windpower Engineering for Parker Hannifin. Cleveland: WTWH Media, Inc.
Pérez, M., García, E., Morant, F., Correcher, A., & Quiles, E. (2010). Optimal maintenance system for offshore wind turbines. In International conference on renewable energies and power quality (ICREPQ10). Granada (Spain), 23th to 25th March.
Perveen, R., Kishor, N., & Mohanty, S. R. (2014). Off-shore wind farm development: Present status and challenges. Renewable and Sustainable Energy Reviews, 29, 780–792.
Petković, D., Ab Hamid, S. H., Ćojbašić, Ž., & Pavlović, N. T. (2014). Adapting project management method and anfis strategy for variables selection and analyzing wind turbine wake effect. Natural Hazards, 74(2), 463–475.
Radakovič, M., Obitko, M., & Mařík, V. (2012). Dynamic explicitly specified behaviors in distributed agent-based industrial solutions. Journal of Intelligent Manufacturing, 23(6), 2601–2621.
Rademakers, L., Braam, H., Zaaijer, M. B., & Energy, S. W. (2003). Assessment and optimisation of operation and maintenance of offshore wind turbines.
Sahnoun, M., Baudry, D., Louis, A., & Mazari, B. (2014a) Modelisation d’un plan de maintenance basee sur les systemes multi-agents pour leseoliennes offshore.
Sahnoun, M., Bettayeb, B., Bassetto, S. J., & Tollenaere, M. (2014b). Simulation-based optimization of sampling plans to reduce inspections while mastering the risk exposure in semiconductor manufacturing. Journal of Intelligent Manufacturing. doi:10.1007/s10845-014-0956-x
Sahnoun, M., Godsiff, P., Baudry, D., Louis, A., & Mazari, B. (2014c) Modelling of maintenance strategy of offshore wind farms based multi-agent system. In CIE44 & ISSM14 (44th international conference on computers & industrial engineering & 9th international symposiom on intelligent manufacturing and service systems) (591, pp. 2406–2420).
Santos, P., Maudes, J., & Bustillo, A. (2015). Identifying maximum imbalance in datasets for fault diagnosis of gearboxes. Journal of Intelligent Manufacturing. doi:10.1007/s10845-015-1110-0
Sheng, S. (2013). Report on wind turbine subsystem reliability–a survey of various databases. National Renewable Energy Laboratory, Golden, CO, Tech Rep NREL/PR-5000-59111.
Stenberg, A., & Holttinen, H. (2010). Analysing failure statistics of wind turbines in finland. In European wind energy conference (pp. 20–23).
Tavner, P. (2012). Offshore wind turbines: Reliability, availability & maintenance. IET Renewable Energy Series.
Taylor, J. H., Sayda, & A. F. (2008). Prototype design of a multi-agent system for integrated control and asset management of petroleum production facilities. In American control conference (pp. 4350–4357). IEEE.
Thornton, E. B., & Guza, R. (1983). Transformation of wave height distribution. Journal of Geophysical Research: Oceans (1978–2012), 88(C10), 5925–5938.
Tian, Z., Lin, D., & Wu, B. (2012). Condition based maintenance optimization considering multiple objectives. Journal of Intelligent Manufacturing, 23(2), 333–340.
Tisue, S., & Wilensky, U. (2004). Netlogo: A simple environment for modeling complexity. In International conference on complex systems (pp. 16–21).
Trappey, A., Trappey, C., & Ni, W. C. (2013). A multi-agent collaborative maintenance platform applying game theory negotiation strategies. Journal of Intelligent Manufacturing, 24(3), 613–623. doi:10.1007/s10845-011-0606-5.
Van de Pieterman, R., Braam, H., Obdam, T., Rademakers, L., & van der Zee, T. (2011). Optimisation of maintenance strategies for offshore wind farms. In The offshore 2011 conference
Zhang, X., & Wang, W. (2009). Wind farm and wake effect modeling for simulation of a studied power system. In Power systems conference and exposition. PSCE’09 (pp. 1–6). IEEE: IEEE/PES.
Zhou, W., Yang, H., & Fang, Z. (2006). Wind power potential and characteristic analysis of the pearl river delta region, china. Renewable Energy, 31(6), 739–753. doi:10.1016/j.renene.2005.05.006.
Acknowledgments
Acknowledgement is made to European Union for the support of this research through the European Program INTERREG IVA France-Channel-UK by funding project entitled MER Innovate.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Sahnoun, M., Baudry, D., Mustafee, N. et al. Modelling and simulation of operation and maintenance strategy for offshore wind farms based on multi-agent system . J Intell Manuf 30, 2981–2997 (2019). https://doi.org/10.1007/s10845-015-1171-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10845-015-1171-0