International Journal of Prognostics and Health Management, ISSN 2153-2648, 2016 008 PHM-Based Wind Turbine Maintenance Optimization Using Real Options
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Published
Nov 11, 2020
Xin Lei
Peter A. Sandborn
Abstract
A simulation-based real options analysis (ROA) approach is used to determine the optimum predictive maintenance opportunity for a wind turbine with a remaining useful life (RUL) prediction. When an RUL is predicted for a subsystem in a single turbine using PHM, a predictive maintenance option is triggered that the decision-maker has the flexibility to decide if and when to exercise before the subsystem or turbine fails. The predictive maintenance value paths are simulated by considering the uncertainties in the RUL prediction and wind speed (that govern the turbine’s revenue earning potential). By valuating a series of European options expiring on all possible predictive maintenance opportunities, a series of option values can be obtained, and the optimum predictive maintenance opportunity can be determined. A case study is presented in which the ROA approach is applied to a single turbine.
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Keywords
Wind Turbine, prognostics and health management (PHM), predictive maintenance, maintenance optimization, real options analysis
References
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Andrawus, J., Watson, J., Kishk, M., & Adam, A. (2006). The selection of a suitable maintenance strategy for wind turbines. Wind Engineering, 30(6), 471-486. doi: 10.1260/030952406779994141
Besnard, F., & Bertling, L. (2010). An approach for condition-based maintenance optimization applied to wind turbine blades. IEEE Transactions on Sustainable Energy, 1(2), 77-83. doi: 10.1109/TSTE.2010.2049452
Byon, E., & Ding, Y. (2010). Season-dependent condition-based maintenance for a wind turbine using a partially observed Markov decision process. IEEE Transactions on Power Systems, 25(4), 1823-1834. doi: 10.1109/TPWRS.2010.2043269
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. doi: 10.1177/0037549710376841
Chase, D., Danai, K., Lackner, M., & Manwell, J. (2013). Detection of damage in operating wind turbines by signature distances. International Journal of Prognostics and Health Management, 101-114.
Ciang, C., Lee, J., & Bang, H. (2008). Structural health monitoring for a wind turbine system: A review of damage detection methods. Measurement Science and Technology, 19(12). doi: 10.1088/0957-0233/19/12/122001
Federal Energy Regulation Commission. (2015). Office of Energy Projects Energy Infrastructure Update For December 2014. https://www.ferc.gov/legal/ staffreports/2014/dec-infrastructure.pdf
Fried, L., Qiao, L., Sawyer, S., & Shukla, S. (2014). Global Wind Report Annual Market Update 2014. Brussels: GWEC.
Gloria, P. (2013). Life Cycle Cost Analysis on Wind Turbines. Master thesis. Department of Energy and Environment. Chalmers University of Technology. Gothenburg, Sweden. http://publications.lib.chalmers.se/records/fulltext/179861/179861.pdf
Goossens, H., Blokland, W., & Curran, R. (2011). The development and application of a value-driven aircraft maintenance operations performance assessment model combined with real options analysis. Proceedings of the 11th AIAA Aviation Technology, Integration, and Operations Conference, September 20-22, Virginia Beach, VA. doi:10.2514/6.2011-6992
Haddad, G., Sandborn, P. A., & Pecht, M. G. (2014). Using maintenance options to maximize the benefits of prognostics for wind farms. Wind Energy, 17(5), 775-791. doi:10.1002/we.1610
Hameeda, Z., Honga, Y., Choa, Y., Ahnb, S., & Songc, C. (2009). Condition monitoring and fault detection of wind turbines and related algorithms: A review. Renewable and Sustainable energy reviews, 13(1), 1-39. doi:10.1016/j.rser.2007.05.008
Heredia-Zavoni, E., & Santa-Cruz, S. (2004). Maintenance decisions for offshore structures using real options theory. Proceedings of the ASME 2004 23rd International Conference on Offshore Mechanics and Arctic Engineering, June 20-25, Vancouver, Canada. doi:10.1115/OMAE2004-51467
Hussain, S., & Gabbar, H. (2013). Vibration analysis and time series prediction for wind turbine gearbox prognostics. International Journal of Prognostics and Health Management, 69-79.
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. doi: 10.1179/174892406X163397
IRENA Secretariat. (2012). Renewable Energy Technologies: Cost Analysis Series. Abu Dhabi: IRENA.
Jin, X., Li, L., & Ni, J. (2009). Option model for joint production and preventive maintenance system. International Journal of Production Economics, 119(2), 347-353. doi:10.1016/j.ijpe.2009.03.005
Joshi, D., Belgaum, I., & Jangamshetti, S. (2009). A novel method to estimate the O&M costs for the financial planning of the wind power projects based on wind speed - A case study. IEEE Transactions on Energy Conversion, 25(1), 161-167. doi: 10.1109/TEC.2009.2032591
Kodukula, P., & Papudesu, C. (2006). Project Valuation Using Real Options. Fort Lauderdale: J. Ross Publishing, Inc.
Koide, Y., Kaito, K., & Abe, M. (2001). Life-cycle cost analysis of bridges where the real options are considered. Proceedings of the Current and Future Trends in Bridge Design, Construction and Maintenance, 387-395. doi: 10.1680/caftibdcam2.30916.0041
Koutoulakos, E. (2008). Wind Turbine Reliability Characteristics and Offshore Availability Assessment. Master thesis, Delft University of Technology, Delft, Netherlands. http://www.lr.tudelft.nl/fileadmin/Faculteit/LR/Organisatie/Afdelingen_en_Leerstoelen/Afdeling_AEWE/Wind_Energy/Education/Masters_Projects/Finished_Master_projects/doc/Efstathios_Koutoulakos_r.pdf
Kumar, S., Chow, T. W., & Pecht, M. (2010). Approach to fault identification for electronic products using Mahalanobis distance. IEEE Transactions on Instrumentation and Measurement, 59(8), 2055-2064. doi: 10.1109/TIM.2009.2032884
Lei, X., Sandborn, P. A., Goudarzi, N., & Bruck, M. A. (2015). PHM based predictive maintenance option model for offshore wind farm O&M optimization. Proceedings of the Annual Conference of the PHM Society, October 18-24, San Diego, CA.
Manwell, J., McGowan, J., & Rogers, A. (2009). Wind Energy Explained: Theory, Design and Application, 2th ed. UK: Wiley.
National Data Buoy Center. (2013). Station 44009 (LLNR 168) - DELAWARE BAY 26 NM Southeast of Cape May, NJ. http://www.ndbc.noaa.gov/station_history.php?
station=44009
Nielsen, J., & Sørensen, J. (2011). On risk-based operation and maintenance of offshore wind turbine components. Reliability Engineering & System Safety, 96(1), 218-229. doi:10.1016/j.ress.2010.07.007
Nijssen, R. (2006). Fatigue Life Prediction and Strength Degradation of Wind Turbine Rotor Blade Composites. Doctoral Dissertation. Department of Aerospace Engineering. Delft University of Technology, Delft, Netherlands. http://repository.tudelft.nl/view/ir/uuid:e33139ca-e181-4c62-87dc-23e55010eac8/
Niknam, S., Thomas, T., Hines, W., & Sawhney, R. (2013). Analysis of acoustic emission data for bearings subject to unbalance. International Journal of Prognostics and Health Management, 80-89.
Nordahl, M. (2011). The Development of a Life Cycle Cost Model for an Offshore Wind Farm. Master thesis. Department of Applied Mechanics, Chalmers University of Technology, Göteborg, Sweden. http://publications.lib.chalmers.se/records/fulltext/152402.pdf
Paida, M. (2012). Life-Cycle Cost Analysis of a Wind Park. Master Thesis. Department of Structural Engineering, National Technical University of Athens, Athens, Greece. http://publications.lib.chalmers.se/records/fulltext/179861/179861.pdf
Pazouki, E., Bahrami, H., & Choi, S. (2014). Condition based maintenance optimization of wind turbine system using degradation prediction. Proceedings of the 2014 IEEE Power & Energy Society General Meeting, July 27-31, National Harbor, MD. doi: 10.1109/PESGM.2014.6939918
Philips, J., Morgan, C., & Jacquemin, J. (2006). Evaluating O&M strategies for offshore wind farms through simulation-the impact of wave climatology. Proceedings of the OWEMES, April 20-22, Civitavecchia, Italy.
Plumley, C., Wilson, G., Kenyon, A., Andrew, Z., Quail, F., & Athena, Z. (2012). Diagnostics and prognostics utilizing dynamic Bayesian networks applied to a wind turbine gearbox. Proceedings of the International Conference on Condition Monitoring and Machine Failure Prevention Technologies, June 12-14, London, UK.
Qu, Y., Bechhoefer, E., He, D., & Zhu, J. (2013). A new acoustic emission sensor based gear fault detection approach. International Journal of Prognostics and Health Management, 32-45.
Rademakers, L., Braam, H., Obdam, T., Frohböse, P., & Kruse, N. (2008). Tools for Estimating Operation and Maintenance Costs of Offshore Wind Farms: State-of-the-Art. ECN. https://www.ecn.nl/docs/library/report/2008/m08026.pdf
Rademakers, L., Braam, H., Zaaijer, M., & Bussel, G. (2003). Assessment and Optimisation of Operation and Maintenance of Offshore Wind Turbines. ECN. https://www.ecn.nl/fileadmin/ecn/units/wind/docs/dowec/2003-EWEC-O_M.pdf
Rodrigues, L. R. & Yoneyama, T. (2013). Maintenance planning optimization based on PHM information and spare parts availability. Proceedings of the Annual Conference of the PHM Society, October 14-17, New Orleans, LA.
Sankararaman, S. & Goebel, K. (2013). Why is the Remaining Useful Life Prediction Uncertain? Proceedings of the Annual Conference of the PHM Society, October 14-17, New Orleans, LA.
Santa-Cruz, S. & Heredia-Zavoni, E. (2011). Maintenance and decommissioning real options models for life-cycle cost-benefit analysis of offshore platforms. Structure and Infrastructure Engineering, 7(10), 733-745. doi: 10.1080/15732470902842903
Tamilselvan, P., Wang, P., Sheng, S., & Twomey, J. (2013). A two-stage diagnosis framework for wind turbine gearbox condition monitoring. International Journal of Prognostics and Health Management, 21-31.
Tchakoua, P., Wamkeue, R., Ouhrouche, M., Slaoui-Hasnaoui, F., Tameghe, T. A., & Ekemb, G. (2014). Wind turbine condition monitoring: State-of-the-art review, new trends, and future challenges. Energies, 7(4), 2595-2630. doi:10.3390/en7042595
Tchakoua, P., Wamkeue, R., Tameghe, T., & Ekemb, G. (2013). A review of concepts and methods for wind turbines condition monitoring. Proceedings of 2013 World Congress on Computer and Information Technology, June 22-24, Sousse, Tunisia. doi: 10.1109/WCCIT.2013.6618706
Tian, Z., Jin, T., Wu, B., & Ding, F. (2011). Condition based maintenance optimization for wind power generation systems under continuous monitoring. Renewable Energy, 36(5), 1502-1509. doi:10.1016/j.renene.2010.10.028
Tian, Z., Zhang, Y., & Cheng, J. (2011). Condition based maintenance optimization for multi-component Systems. Proceedings of the Annual Conference of the PHM Society, September 25-29, Montreal, Canada.
Verbruggen, T. W. (2003). Wind Turbine Operation and Maintenance Based on Condition Monitoring WT-Omega. ECN. https://www.ecn.nl/docs/library/report/ 2003/c03047.pdf
Vestas. (2013). 3 MW Platform. http://pdf.directindustry.
com/pdf/vestas/3-mwplatform/20680-398713.html
Yang, W., Sheng, S., & Court, R. (2012). Operational Conditional Independent Criteria Dedicated to Monitoring Wind Turbine Generators. NREL. http://www.nrel.gov/docs/fy12osti/55195.pdf
Andrawus, J., Watson, J., Kishk, M., & Adam, A. (2006). The selection of a suitable maintenance strategy for wind turbines. Wind Engineering, 30(6), 471-486. doi: 10.1260/030952406779994141
Besnard, F., & Bertling, L. (2010). An approach for condition-based maintenance optimization applied to wind turbine blades. IEEE Transactions on Sustainable Energy, 1(2), 77-83. doi: 10.1109/TSTE.2010.2049452
Byon, E., & Ding, Y. (2010). Season-dependent condition-based maintenance for a wind turbine using a partially observed Markov decision process. IEEE Transactions on Power Systems, 25(4), 1823-1834. doi: 10.1109/TPWRS.2010.2043269
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. doi: 10.1177/0037549710376841
Chase, D., Danai, K., Lackner, M., & Manwell, J. (2013). Detection of damage in operating wind turbines by signature distances. International Journal of Prognostics and Health Management, 101-114.
Ciang, C., Lee, J., & Bang, H. (2008). Structural health monitoring for a wind turbine system: A review of damage detection methods. Measurement Science and Technology, 19(12). doi: 10.1088/0957-0233/19/12/122001
Federal Energy Regulation Commission. (2015). Office of Energy Projects Energy Infrastructure Update For December 2014. https://www.ferc.gov/legal/ staffreports/2014/dec-infrastructure.pdf
Fried, L., Qiao, L., Sawyer, S., & Shukla, S. (2014). Global Wind Report Annual Market Update 2014. Brussels: GWEC.
Gloria, P. (2013). Life Cycle Cost Analysis on Wind Turbines. Master thesis. Department of Energy and Environment. Chalmers University of Technology. Gothenburg, Sweden. http://publications.lib.chalmers.se/records/fulltext/179861/179861.pdf
Goossens, H., Blokland, W., & Curran, R. (2011). The development and application of a value-driven aircraft maintenance operations performance assessment model combined with real options analysis. Proceedings of the 11th AIAA Aviation Technology, Integration, and Operations Conference, September 20-22, Virginia Beach, VA. doi:10.2514/6.2011-6992
Haddad, G., Sandborn, P. A., & Pecht, M. G. (2014). Using maintenance options to maximize the benefits of prognostics for wind farms. Wind Energy, 17(5), 775-791. doi:10.1002/we.1610
Hameeda, Z., Honga, Y., Choa, Y., Ahnb, S., & Songc, C. (2009). Condition monitoring and fault detection of wind turbines and related algorithms: A review. Renewable and Sustainable energy reviews, 13(1), 1-39. doi:10.1016/j.rser.2007.05.008
Heredia-Zavoni, E., & Santa-Cruz, S. (2004). Maintenance decisions for offshore structures using real options theory. Proceedings of the ASME 2004 23rd International Conference on Offshore Mechanics and Arctic Engineering, June 20-25, Vancouver, Canada. doi:10.1115/OMAE2004-51467
Hussain, S., & Gabbar, H. (2013). Vibration analysis and time series prediction for wind turbine gearbox prognostics. International Journal of Prognostics and Health Management, 69-79.
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. doi: 10.1179/174892406X163397
IRENA Secretariat. (2012). Renewable Energy Technologies: Cost Analysis Series. Abu Dhabi: IRENA.
Jin, X., Li, L., & Ni, J. (2009). Option model for joint production and preventive maintenance system. International Journal of Production Economics, 119(2), 347-353. doi:10.1016/j.ijpe.2009.03.005
Joshi, D., Belgaum, I., & Jangamshetti, S. (2009). A novel method to estimate the O&M costs for the financial planning of the wind power projects based on wind speed - A case study. IEEE Transactions on Energy Conversion, 25(1), 161-167. doi: 10.1109/TEC.2009.2032591
Kodukula, P., & Papudesu, C. (2006). Project Valuation Using Real Options. Fort Lauderdale: J. Ross Publishing, Inc.
Koide, Y., Kaito, K., & Abe, M. (2001). Life-cycle cost analysis of bridges where the real options are considered. Proceedings of the Current and Future Trends in Bridge Design, Construction and Maintenance, 387-395. doi: 10.1680/caftibdcam2.30916.0041
Koutoulakos, E. (2008). Wind Turbine Reliability Characteristics and Offshore Availability Assessment. Master thesis, Delft University of Technology, Delft, Netherlands. http://www.lr.tudelft.nl/fileadmin/Faculteit/LR/Organisatie/Afdelingen_en_Leerstoelen/Afdeling_AEWE/Wind_Energy/Education/Masters_Projects/Finished_Master_projects/doc/Efstathios_Koutoulakos_r.pdf
Kumar, S., Chow, T. W., & Pecht, M. (2010). Approach to fault identification for electronic products using Mahalanobis distance. IEEE Transactions on Instrumentation and Measurement, 59(8), 2055-2064. doi: 10.1109/TIM.2009.2032884
Lei, X., Sandborn, P. A., Goudarzi, N., & Bruck, M. A. (2015). PHM based predictive maintenance option model for offshore wind farm O&M optimization. Proceedings of the Annual Conference of the PHM Society, October 18-24, San Diego, CA.
Manwell, J., McGowan, J., & Rogers, A. (2009). Wind Energy Explained: Theory, Design and Application, 2th ed. UK: Wiley.
National Data Buoy Center. (2013). Station 44009 (LLNR 168) - DELAWARE BAY 26 NM Southeast of Cape May, NJ. http://www.ndbc.noaa.gov/station_history.php?
station=44009
Nielsen, J., & Sørensen, J. (2011). On risk-based operation and maintenance of offshore wind turbine components. Reliability Engineering & System Safety, 96(1), 218-229. doi:10.1016/j.ress.2010.07.007
Nijssen, R. (2006). Fatigue Life Prediction and Strength Degradation of Wind Turbine Rotor Blade Composites. Doctoral Dissertation. Department of Aerospace Engineering. Delft University of Technology, Delft, Netherlands. http://repository.tudelft.nl/view/ir/uuid:e33139ca-e181-4c62-87dc-23e55010eac8/
Niknam, S., Thomas, T., Hines, W., & Sawhney, R. (2013). Analysis of acoustic emission data for bearings subject to unbalance. International Journal of Prognostics and Health Management, 80-89.
Nordahl, M. (2011). The Development of a Life Cycle Cost Model for an Offshore Wind Farm. Master thesis. Department of Applied Mechanics, Chalmers University of Technology, Göteborg, Sweden. http://publications.lib.chalmers.se/records/fulltext/152402.pdf
Paida, M. (2012). Life-Cycle Cost Analysis of a Wind Park. Master Thesis. Department of Structural Engineering, National Technical University of Athens, Athens, Greece. http://publications.lib.chalmers.se/records/fulltext/179861/179861.pdf
Pazouki, E., Bahrami, H., & Choi, S. (2014). Condition based maintenance optimization of wind turbine system using degradation prediction. Proceedings of the 2014 IEEE Power & Energy Society General Meeting, July 27-31, National Harbor, MD. doi: 10.1109/PESGM.2014.6939918
Philips, J., Morgan, C., & Jacquemin, J. (2006). Evaluating O&M strategies for offshore wind farms through simulation-the impact of wave climatology. Proceedings of the OWEMES, April 20-22, Civitavecchia, Italy.
Plumley, C., Wilson, G., Kenyon, A., Andrew, Z., Quail, F., & Athena, Z. (2012). Diagnostics and prognostics utilizing dynamic Bayesian networks applied to a wind turbine gearbox. Proceedings of the International Conference on Condition Monitoring and Machine Failure Prevention Technologies, June 12-14, London, UK.
Qu, Y., Bechhoefer, E., He, D., & Zhu, J. (2013). A new acoustic emission sensor based gear fault detection approach. International Journal of Prognostics and Health Management, 32-45.
Rademakers, L., Braam, H., Obdam, T., Frohböse, P., & Kruse, N. (2008). Tools for Estimating Operation and Maintenance Costs of Offshore Wind Farms: State-of-the-Art. ECN. https://www.ecn.nl/docs/library/report/2008/m08026.pdf
Rademakers, L., Braam, H., Zaaijer, M., & Bussel, G. (2003). Assessment and Optimisation of Operation and Maintenance of Offshore Wind Turbines. ECN. https://www.ecn.nl/fileadmin/ecn/units/wind/docs/dowec/2003-EWEC-O_M.pdf
Rodrigues, L. R. & Yoneyama, T. (2013). Maintenance planning optimization based on PHM information and spare parts availability. Proceedings of the Annual Conference of the PHM Society, October 14-17, New Orleans, LA.
Sankararaman, S. & Goebel, K. (2013). Why is the Remaining Useful Life Prediction Uncertain? Proceedings of the Annual Conference of the PHM Society, October 14-17, New Orleans, LA.
Santa-Cruz, S. & Heredia-Zavoni, E. (2011). Maintenance and decommissioning real options models for life-cycle cost-benefit analysis of offshore platforms. Structure and Infrastructure Engineering, 7(10), 733-745. doi: 10.1080/15732470902842903
Tamilselvan, P., Wang, P., Sheng, S., & Twomey, J. (2013). A two-stage diagnosis framework for wind turbine gearbox condition monitoring. International Journal of Prognostics and Health Management, 21-31.
Tchakoua, P., Wamkeue, R., Ouhrouche, M., Slaoui-Hasnaoui, F., Tameghe, T. A., & Ekemb, G. (2014). Wind turbine condition monitoring: State-of-the-art review, new trends, and future challenges. Energies, 7(4), 2595-2630. doi:10.3390/en7042595
Tchakoua, P., Wamkeue, R., Tameghe, T., & Ekemb, G. (2013). A review of concepts and methods for wind turbines condition monitoring. Proceedings of 2013 World Congress on Computer and Information Technology, June 22-24, Sousse, Tunisia. doi: 10.1109/WCCIT.2013.6618706
Tian, Z., Jin, T., Wu, B., & Ding, F. (2011). Condition based maintenance optimization for wind power generation systems under continuous monitoring. Renewable Energy, 36(5), 1502-1509. doi:10.1016/j.renene.2010.10.028
Tian, Z., Zhang, Y., & Cheng, J. (2011). Condition based maintenance optimization for multi-component Systems. Proceedings of the Annual Conference of the PHM Society, September 25-29, Montreal, Canada.
Verbruggen, T. W. (2003). Wind Turbine Operation and Maintenance Based on Condition Monitoring WT-Omega. ECN. https://www.ecn.nl/docs/library/report/ 2003/c03047.pdf
Vestas. (2013). 3 MW Platform. http://pdf.directindustry.
com/pdf/vestas/3-mwplatform/20680-398713.html
Yang, W., Sheng, S., & Court, R. (2012). Operational Conditional Independent Criteria Dedicated to Monitoring Wind Turbine Generators. NREL. http://www.nrel.gov/docs/fy12osti/55195.pdf
Section
Technical Papers