EVERGREEN

Joint Journal of Novel Carbon Resource Sciences and Green Asia Strategy

ISSN:2189-0420 (Print until Mar 2020)
ISSN:2432-5953 (Online)

SCImago Journal & Country Rank

Open Access
Scopus
Google Scholar
Crossref
SCImago Journal & Country Rank
4.3
2024CiteScore
 
69th percentile
Powered by Scopus
Metrics by SCOPUS 2024
CiteScore
4.3
SJR
0.391
SNIP
1.192

Development of Optimized Maintenance Scheduling Model for Coal-Fired Power Plant Boiler

N Fazreen A Fuzi1, Firas Basim Ismail2, Hussein A Kazem1, Miqdam T. Chaichan3,4,*
1Power Generation Unit, Institute of Power Engineering (IPE),, Universiti Tenaga Nasional (UNITEN), Malaysia, Malaysia
2Power Generation Unit, Institute of Power Engineering (IPE), Malaysia, Universiti Tenaga Nasional (UNITEN),, Malaysia
3Energy and Renewable Energies Technology Centre, University of Technology-Iraq, Iraq
4Energy and Renewable Energies Technology Centre, University of Technology- Iraq, Iraq
*Author to whom correspondence should be addressed:
E-mail: miqdam.t..chaichan.example@university.edu (MTC)
Evergreen, Vol. 12, Iss. 02, pp. 701–714, 2025
DOI: 10.5109/7363469
Creative Commons Attribution 4.0 International Creative Commons Attribution 4.0 International
Received: April 30, 2024 | Revised: March 03, 2025 | Accepted: April 21, 2025 | Published: June 2025
Abstract
Efficient maintenance scheduling for coal-fired power plant boilers requires systematic approaches due to frequent upkeep needs. Computing intelligence, a subset of AI, aids in gaining insights. Optimization methods like MILP and PSO rely on constraints and variables to minimize or maximize objectives. This study applied MILP and PSO to address maintenance optimization. Mathematical formulations were devised specifically for these methods to tackle boiler maintenance scheduling effectively.
Keywords
Particle Swarm Optimization (PSO) ; Coal-fired power plant boiler ; maintenance scheduling model ; Mixed Integer Linear Programming (MILP)
Available Repositories
Journal DOI Zenodo Archive
Share Article
Article Metrics
--
Views
--
Downloads
--
Citations
Export Citation
BibTeX RIS Semantic Scholar CrossRef Mendeley Google Scholar
Full Text
Download PDF
References
  1. 1) R. Peters, J. Berlekamp, C. Kabiri, B.A. Kaplin, K. Tockner, C. Zarfl, "Sustainable pathways towards universal renewable electricity access in Africa". Nature Reviews Earth & Environment, 1-15 (2024) doi:10.1038/s43017-023-00501-1
  2. 2) J.C. Minx, J. Hilaire, F. Müller-Hansen, G. Nemet, F. Diluiso, R.M. Andrew, C. Ayas, N. Bauer, S.L. Bi, L. Clarke, and F. Creutzig F., "Coal transitions—part 2: phase-out dynamics in global long-term mitigation scenarios". Environmental Research Letters, 19(3) 033002 (2024) doi:10.1088/1748-9326/ad24cd
  3. 3) A. Wahid, D. R. Mustafida, and Y. A. Husnil, "Exergy analysis of coal-fired power plants in ultra-supercritical technology versus integrated gasification combined cycle," EVERGREEN Joint Journal of Novel Carbon Resource Sciences & Green Asia Strategy, 7(1) 32-42 (2020) doi:10.5109/2740939
  4. 4) B. Dziejarski, R. Krzyżyńska, and K. Andersson, "Current status of carbon capture, utilization, and storage technologies in the global economy: A survey of technical assessment." Fuel 342, 127776 (2023) doi:10.1016/j.fuel.2023.127776
  5. 5) N. Bahman, M. Al-Khalifa, S. Al Baharna, Z. Abdulmohsen, and E. Khan, "Review of carbon capture and storage technologies in selected industries: potentials and challenges". Reviews in Environmental Science and Bio/Technology, 22(2) 451-470 (2023) doi:10.1007/s11157-023-09649-0
  6. 6) Y. He, S. Guo, P. Dong, D. Lv, and J. Zhou, "Feasibility analysis of decarbonizing coal-fired power plants with 100% renewable energy and flexible green hydrogen production". Energy Conversion and Management, 290 117232 (2023) doi:10.1016/j.enconman.2023.117232
  7. 7) H.A. Kazem, M.T. Chaichan, A.H. Al-Waeli, and K. Sopian, "Evaluation of aging and performance of grid-connected photovoltaic system northern Oman: Seven years’ experimental study." Solar Energy, 207 1247-1258 (2020) doi:10.1016/j.solener.2020.07.061
  8. 8) J.J. Anderson, D. Rode, H. Zhai, and P. Fischbeck, "Transitioning to a carbon-constrained world: Reductions in coal-fired power plant emissions through unit-specific, least-cost mitigation frontiers". Applied Energy, 288 116599 (2021) doi:10.1016/j.apenergy.2021.116599
  9. 9) J.L. Fan, J. Fu, X. Zhang, K. Li, W. Zhou, K. Hubacek, J. Urpelainen, S. Shen, S. Chang, S. Guo, and X. Lu, "Co-firing plants with retrofitted carbon capture and storage for power-sector emissions mitigation". Nature Climate Change, 13(8) 807-815 (2023) doi:10.1038/s41558-023-01736-y
  10. 10) J. Bhadu, J. Bhamu, and P. Saraswat, "An analytic hierarchy process (AHP) approach for prioritizing the industries 4.0 technologies (I4. 0T). EVERGREEN Joint Journal of Novel Carbon Resource Sciences & Green Asia Strategy, 10(02) 667-675 (2023) doi:10.5109/6792813
  11. 11) V. Gupta and A. Jayant, "A novel hybrid MCDM approach followed by fuzzy DEMATEL-ANP-TOPSIS to evaluate Low Carbon Suppliers," EVERGREEN Joint Journal of Novel Carbon Resource Sciences & Green Asia Strategy, 8(3) 544-555 (2021) doi:10.5109/4491640
  12. 12) S. Ignat, "Power plants maintenance optimization based on CBM techniques," 2nd IFAC Work. Converg. Inf. Technol. Control Methods with Power Syst., 46(6) 64-68 (2013) doi:10.3182/20130522-3-RO-035.00031
  13. 13) International Atomic Energy Agency, "Nuclear Energy Series: Maintenance Optimization Programme for Nuclear Power Plants," 2018. [Online]. Available: http://www.iaea.org/Publications/index.html
  14. 14) S. J. Huang, "Generator maintenance scheduling: A fuzzy system approach with genetic enhancement," Electr. Power Syst. Res., 41(3) 233-239 (1997) doi:10.1016/s0378-7796(96)01194-7
  15. 15) S. O. Oyedepo and F. R. Olayiwola, "A Study of implementation of preventive maintenance programme in Nigeria power industry – Egbin thermal power plant, case study". Energy Power Eng., 03(03) 207-220 (2011) doi:10.4236/epe.2011.33027
  16. 16) J. Wang, X. Ren, T. Li, Q. Zhao, H. Dai, Y., Guo, and J. Yan, "Multi-objective optimization and multi-criteria evaluation framework for the design of distributed multi-energy system: A case study in industrial park." Journal of Building Engineering, 88 109138 (2024) doi:10.1016/j.jobe.2024.109138
  17. 17) M.A. Nemitallah, M.A. Nabhan, M. Alowaifeer, A. Haeruman, F. Alzahrani, M.A. Habib, M. Elshafei, M.I. Abouheaf, M. Aliyu, and M. Alfarraj, "Artificial intelligence for control and optimization of boilers’ performance and emissions: A review." Journal of Cleaner Production, 417 138109 (2023) doi:10.1016/j.jclepro.2023.138109
  18. 18) A.M. Ghaithan, M. Kondkari, A. Mohammed, and A.M. Attia, "Optimal design of concentrated solar power-based hydrogen refueling station: Mixed integer linear programming approach." International Journal of Hydrogen Energy, 86 703-718 (2024) doi:10.1016/j.ijhydene.2024.08.451
  19. 19) D.H. Dinh, P. Do, and B. Iung, "Reliability modeling and opportunistic maintenance optimization for a multicomponent system with structural dependence. Reliability Engineering & System Safety, 241 109708 (2024) doi:10.1016/j.ress.2023.109708
  20. 20) S. Singla, D. Mangla, P. Panwar, and S.Z. Taj, "Reliability optimization of a degraded system under preventive maintenance using genetic algorithm." Journal of Mechanics of Continua and Mathematical Sciences, 19(1) 1-14 (2024) doi:10.26782/jmcms.2024.01.00001
  21. 21) Y. Wang, T. Xia, Y. Xu, Y. Ding, M. Zheng, E. Pan, and L. Xi, "Joint optimization of flexible job shop scheduling and preventive maintenance under high-frequency production switching." International Journal of Production Economics, 269 109163 (2024) doi:10.1016/j.ijpe.2024.109163
  22. 22) C. K. Wing, A. H. Mohammed, and M. N. Abdullah, "A review of maintenance priority setting methods". Int. J. Real Estate Stud., 10(2) 1-43 (2016)
  23. 23) O. Obodeh, "Optimal maintenance scheduling of thermal power unıts in a restructured nigerian power system". J. Mech. Eng. Res., 5 (8) 145-153 (2014) doi:10.5897/jmer2013.0292
  24. 24) M. C. Carnero and A. Gómez, "Maintenance strategy selection in electric power distribution systems". Energy, 129 255-272 (2017) doi:10.1016/j.energy.2017.04.100
  25. 25) P. Breeze, "Steam Turbines and Generators," in Coal-Fired Generation, Elsevier, 33-39 (2015)
  26. 26) Boiler Maintenance Team (TNBJ), "Report - M1 MOH Oct 2017 - Boiler Maintenance Section (BMS) Report.pdf," 2017
  27. 27) Boiler Maintenance Team (TNBJ), "Report - M1 MOH Oct 2017 - Boiler Maintenance Section (BMS) Workplan.pdf," 2017
  28. 28) D. Berdie, M. Osaci, I. Muscalagiu, and C. Barz, "A combined approach of AHP and TOPSIS methods applied in the field of integrated software systems". IOP Conf. Ser. Mater. Sci. Eng., 200(1) (2017) doi:10.1088/1757-899X/200/1/012041
  29. 29) J. Franek et al., "The analytic hierarchy process," Int. J. Adv. Eng. Res. Stud., 45(1) 256-258 (2015) doi:10.1016/0377-2217(90)90209-t
  30. 30) S. Zaim, A. Turkyílmaz, M. F. Acar, U. Al-Turki, and O. F. Demirel, "Maintenance strategy selection using AHP and ANP algorithms: A case study," J. Qual. Maint. Eng., 18(1) 16-29 (2012) doi:10.1108/13552511211226166
  31. 31) R. Perzina and J. Ramík, "Microsoft Excel as a tool for solving multicriteria decision problems". Procedia Comput. Sci., 35(C) 1455-1463 (2014) doi:10.1016/j.procs.2014.08.206
  32. 32) K. Al-Subhi, "Application of the AHP in project management," Int. J. Proj. Manag., 19(1) 19-27 (2001) doi:10.1016/S0263-7863(99)00038-1
  33. 33) T. Ganesh and P. Reddy, "Testing the consistency of subjective weights in goal programming – the analytical hierarchy process approach". Am. J. Appl. Math. Stat., 2(3) 92-95 (2014) doi:10.12691/ajams-2-3-2
  34. 34) H.K. Lee, S.B. Kim, E.S. Lee, and I.B. Lee, "MILP scheduling model for multipurpose batch processes considering various intermediate storage policies," Korean J. Chem. Eng., 18(4) 422-427 (2001) doi:10.1007/BF02698285
  35. 35) A. Floudas and X. Lin, "Mixed integer linear programming in process scheduling: Modeling, algorithms, and applications," Ann. Oper. Res., 139(1) 131-162 (2005) doi:10.1007/s10479-005-3446-x
  36. 36) M. J. Alves and J. Clímaco, "A review of interactive methods for multiobjective integer and mixed-integer programming," Eur. J. Oper. Res., 180(1) 99-115 (2007) doi:10.1016/j.ejor.2006.02.033
  37. 37) Q. P. Zheng, J. Wang, and A. L. Liu, "Stochastic optimization for unit commitment - A review". IEEE Trans. Power Syst., 30(4) 1913-1924 (2015) doi:10.1109/TPWRS.2014.2355204
  38. 38) O. P. Rahi, A. K. Chandel, and M. G. Sharma, "Optimization of hydro power plant design by Particle Swarm Optimization (PSO)," Procedia Eng., 30 418-425 (2012) doi:10.1016/j.proeng.2012.01.880
  39. 39) S. Ebbesen, P. Kiwitz, and L. Guzzella, "A generic particle swarm optimization Matlab function," Proc. Am. Control Conf., 1519-1524 (2012) doi:10.1109/acc.2012.6314697
  40. 40) N.K. Maurya, V. Rastogi, and P. Singh, ''Experimental and computational investigation on mechanical properties of reinforced additive manufactured component'', EVERGREEN Joint Journal of Novel Carbon Resource Sciences &Green Asia Strategy, 6(3) 207-214 (2019) doi:10.5109/2349296
  41. 41) M.K. Loganathan and O.P. Gandhi, "Maintenance cost minimization of manufacturing systems using PSO under reliability constraint," Int. J. Syst. Assur. Eng. Manag., 7(1) 47-61 (2016) doi:10.1007/s13198-015-0374-2
  42. 42) M. Heleno, S. Mashayekh, M. Stadler, G. Cardoso, and R. De Luís, "Optimal sizing and placement of distributed generation: MILP vs PSO comparison in a real microgrid application." In 19th International Conference on Intelligent System Application to Power Systems, (2017)
  43. 43) R.K. Kim, M.B. Glick, K.R. Olson, and Y.S. Kim, "MILP-PSO combined optimization algorithm for an islanded microgrid scheduling with detailed battery ESS efficiency model and policy considerations." Energies, 13(8), p.1898 (2020) doi:10.3390/en13081898
  44. 44) A.M. Abd, R.N. Zehawi, and R.H. Ali, "Particle Swarm Optimization and Tree Models (M5P) as cost estimation tool for construction project." Mathematical Modelling of Engineering Problems, 11(9) 2303-2311 (2024) doi:10.18280/mmep.110903
  45. 45) T.Z. Khalaf, H. Çağlar, A. Çağlar, and A.N. Hanoon, "Particle swarm optimization based approach for estimation of costs and duration of construction projects." Civil Engineering Journal, 6(2) 384-401 (2020) doi:10.28991/cej-2020-03091478
  46. 46) M.N. Alam, "Codes in MATLAB for training artificial neural network using particle swarm optimization," ResearchGate, 1-16 (2016) doi:10.13140/RG.2.1.2579.3524
  47. 47) J.G. Grase, A. Maneengam, P.L.V. Kumar, and J. Alanya-Beltran, "Design and implementation of machine learning modelling through adaptive Hybrid Swarm Optimization Techniques for machine management". EVERGREEN Joint Journal of Novel Carbon Resource Sciences & Green Asia Strategy, 10(02) 1120-1126 (2023) doi:10.5109/6793672
  48. 48) S. Solanke and V. Gaval, "Tribological studies of different bioimplant materials for orthopedic application using Taguchi experimental design". Tribologia - Finnish Journal of Tribology, 38(3-4), 4-14 (2021) doi:10.30678/fjt.103070
  49. 49) S.G. Solanke and V.R. Gaval, "Optimization of wet sliding wear parameters of Titanium grade 2 and grade 5 bioimplant materials for orthopedic application using Taguchi method". J Met Mater Miner, 30(3) 113-120 (2020) doi:10.14456/jmmm.2020.44
Other Papers in This Issue