[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.9708/jksci.2021.26.12.255

An Optimization Model for O&M Planning of Floating Offshore Wind Farm using Mixed Integer Linear Programming

Sang, Min-Gyu (School of Industrial Management and Engineering, Korea University)
Lee, Nam-Kyoung (Smart Convergence Dept., KEPCO Engineering & Construction Co., Inc.)
Shin, Yong-Hyuk (Dept. of Industrial Engineering, Konkuk University)
Lee, Chulung (School of Industrial Management and Engineering, Korea University)
Oh, Young-Jin (Smart Convergence Dept., KEPCO Engineering & Construction Co., Inc.)

Publication Information

Journal of the Korea Society of Computer and Information / v.26, no.12, 2021 , pp. 255-264 More about this Journal

Abstract

In this paper, we propose operations and maintenance (O&M) planning approach for floating offshore wind farm using the mathematical optimization. To be specific, we present a MILP (Mixed Integer Linear Programming that suggests the composition of vessels, technicians, and maintenance works on a weekly basis. We reflect accessibility to wind turbines based on weather data and loss of power generation using the Jensen wake model to identify downtime cost that vary from time to time. This paper also includes a description of two-stage approach for maintenance planning & detailed scheduling and numeric analysis of the number of vessels and technicians on the O&M cost. Finally, the MILP model could be utilized in order to establish the suitable and effective maintenance planning reflecting domestic situation.

Keywords

Offshore Wind Farm; Operations & Maintenance; Integer Programming; Linear Programming; Optimization;

Citations & Related Records

Reference

1	Sankaranarayanan, V., Maintenance-Wind Energy Production, 2015.
2	Stalhane, M., Vefsnmo, H., Halvorsen-Weare, E. E., Hvattum, L. M., & Nonas, L. M., Vessel fleet optimization for maintenance operations at offshore wind farms under uncertainty, Energy Procedia, 94, 357-366, 2016. DOI: 10.1016/j.egypro.2016.09.195 DOI
3	Suryadarma, E. H. E., Ai, T. J., Bawono, B., & Siswantoro, A. T., Improving Bimetal Bond Quality Between Cast Steel and Aluminum Alloys Using Response Surface Methodology, International Journal of Metalcasting, 1-10, 2021. DOI: 10.1007/s40962-021-00687-4 DOI
4	Zhang, Z., Multi-ACO Application in Routing and Scheduling Optimization of Maintenance Fleet (RSOMF) Based on Conditions for Offshore Wind Farms, Journal of Power and Energy Engineering, 6(10), 20, 2018. DOI: 10.4236/jpee.2018.610002 DOI
5	Parashar, A. and Swankar, K.K., A Genetic Algorithm Approach to Solve Unit Commitment Problem, IOSR Journal of Electrical and Electronics Engineering, 7, 60-64, 2013. DOI: 10.9790/1676-0736064 DOI
6	Irawan, C. A., Eskandarpour, M., Ouelhadj, D., & Jones, D., Simulation-based optimisation for stochastic maintenance routing in an offshore wind farm, European Journal of Operational Research, 289(3), 912-926, 2021. DOI: 10.1016/j.ejor.2019.08.032 DOI
7	Stock-Williams, C., & Swamy, S. K., Automated daily maintenance planning for offshore wind farms, Renewable Energy, 133, 1393-1403, 2019. DOI: 10.1016/j.renene.2018.08.112 DOI
8	Stalhane, M., Bolstad, K. H., Joshi, M., & Hvattum, L. M., A dual-level stochastic fleet size and mix problem for offshore wind farm maintenance operations, INFOR: Information Systems and Operational Research, 59(2), 257-289, 2021. DOI: 10.1080/03155986.2020.1857629 DOI
9	Gonzalez-Longatt, F., Wall, P., & Terzija, V., Wake effect in wind farm performance: Steady-state and dynamic behavior, Renewable Energy, 39(1), 329-338, 2012. DOI: 10.1016/j.renene.2011.08.053 DOI
10	Ilkyeong Moon, Byungsoo Kim, Hoontae Kim, Yongwon Seo, & Chulung Lee, Operations Management, Life and Power Press, 2016.
11	Halvorsen-Weare, E. E., Gundegjerde, C., Halvorsen, I. B., Hvattum, L. M., & Nonas, L. M., Vessel fleet analysis for maintenance operations at offshore wind farms, Energy Procedia, 35, 167-176, 2013. DOI: 10.1016/j.egypro.2013.07.170 DOI
12	Elkinton, C., Manwell, J., & McGowan, J., Offshore wind farm layout optimization (OWFLO) project: Preliminary results, 44th AIAA aerospace sciences meeting and exhibit, 2006. DOI: 10.2514/6.2006-998
13	The DTU 10MW Reference Wind Turbine Project Site, https://rwt.windenergy.dtu.dk/dtu10mw/dtu-10mw-rwt
14	Gurobi Optimizer. Available at: https://www.gurobi.com/products/gurobi-optimizer. [Accessed: 1 November 2021].
15	Kaldellis, J. K., & Apostolou, D., Life cycle energy and carbon footprint of offshore wind energy. Comparison with onshore counterpart, Renewable Energy, 108, 72-84, 2017. DOI: 10.1016/j.renene.2017.02.039 DOI
16	Jensen, N.O., "A Note on Wind Generator Interaction", RISO-M-2411, Riso National Lab, 1983.
17	G.Rinaldi, P.R Thies, R.Walker& L.Johanning, A decision support model to optimise the operation and maintenance strategies of an offshore renewable energy farm, Ocean Engineering, 145, 250-262, 2013. DOI: 10.1016/j.oceaneng.2017.08.019 DOI
18	Halvorsen-Weare, E. E., Norstad, I., Stalhane, M., & Nonas, L.M., A metaheuristic solution method for optimizing vessel fleet size and mix for maintenance operations at offshore wind farms under uncertainty, Energy Procedia, 137, 531-538, 2017. DOI: 10.1016/j.egypro.2017.10.382 DOI
19	Dinwoodie, I., McMillan, D., Revie, M., Lazakis, I., & Dalgic, Y., Development of a combined operational and strategic decision support model for offshore wind, Energy Procedia, 35, 157-166, 2013. DOI: 10.1016/j.egypro.2013.07.169 DOI
20	Dalgic, Y., Lazakis, I., Dinwoodie, I., McMillan, D., & Revie, M., Advanced logistics planning for offshore wind farm operation and maintenance activities, Ocean Engineering, 101, 211-226, 2015. DOI: 10.1016/j.oceaneng.2015.04.040 DOI
21	A.Gutierrez-Alcoba, E.M.T.Hendrix, G.Ortega, E.E.Halvorsen-We are & D.Hauglandc, On offshore wind farm maintenance scheduling for decision support on vessel fleet composition, European Journal of Operational Research, 279, 124-131, 2019. DOI: 10.1016/j.ejor.2019.04.020 DOI
22	Besnard, F., On optimal maintenance management for wind power systems (Doctoral dissertation, KTH), 2009.
23	Rademakers, L. W. M. M., Braam, H., Obdam, T. S., & vd Pieterman, R. P., Operation and maintenance cost estimator (OMCE) to estimate the future O&M costs of offshore wind farms, European Offshore Wind 2009 Conference (Vol. 1, pp. 14-16), 2009.
24	The European terminology standard, SS-EN 13306, p.36, 2001.
25	Offshore Wind Farm in Asia, POSRI Issue Report, 1-18, 2018.
26	Jae-Kyeong Jang, Mi-Ho Park & Jong-Po Park, Comparison of O&M Performance of Offshore Wind Farms Based on Improved Accessibility and Reliability of Large Parts, Journal of Wind Energy, 11(3), 40-51, 2020. DOI: 10.33519/kwea.2020.11.3.005 DOI
27	Walford, C. A., Wind turbine reliability: understanding and minimizing wind turbine operation and maintenance costs (No. SAND2006-1100), Sandia National Laboratories, 2006.