Single Objective Optimization Methods in Electrical Power Systems: A Review

Ali Abdulmunim Ibrahim Al-kharaz; Ahmed Bahaaulddin A.Wahhab; Mohammed Fadhil Ibrahim; Shahab Abdulla

doi:10.51173/jt.v5i1.1214

Authors

Ali Abdulmunim Ibrahim Al-kharaz Technical College of Management - Baghdad, Middle Technical University, Baghdad, Iraq.
Ahmed Bahaaulddin A.Wahhab Technical College of Management - Baghdad, Middle Technical University, Baghdad, Iraq.
Mohammed Fadhil Ibrahim Technical College of Management - Baghdad, Middle Technical University, Baghdad, Iraq.
Shahab Abdulla University of Southern Queensland, Ausrtalia

DOI:

https://doi.org/10.51173/jt.v5i1.1214

Keywords:

Single-Objective Optimization, Generator maintenance scheduling, Heuristic, Fuzzy logic, Genetic algorithms

Abstract

Although the scheduling of maintenance tasks for generators is not a new issue, it has recently attracted new attention due to the significant rise in demand for expanding power system size in modern power systems. Generator Maintenance Scheduling (GMS) is a nonlinear optimization problem, highly dimensional and constrained, and determines when power-producing units must undertake well-planned preventative maintenance. The objective function includes binary variables to indicate whether a generator is undergoing maintenance at a given time and is subject to several restrictions described in this paper. However, the biggest concern of GMS is to produce a precise timetable for preventive maintenance of generating units with low cost and high reliability. Despite that, regrettably, a large volume of research works has accomplished solutions towards a model of GMS with the consideration of either maximizing system reliability or minimizing operation costs as an objective of their research work. This is called Single-Objective Problem (SOP), which involves one objective function that needs to be optimized. SOP is solved by Single-Objective Optimization Method (SOOM). The primary purpose of the research is to present a review of SOOM methods used in solving GMS problems.

Downloads

Download data is not yet available.

Author Biographies

Ali Abdulmunim Ibrahim Al-kharaz, Technical College of Management - Baghdad, Middle Technical University, Baghdad, Iraq.

Department of IT

Ahmed Bahaaulddin A.Wahhab, Technical College of Management - Baghdad, Middle Technical University, Baghdad, Iraq.

Department of IT

Mohammed Fadhil Ibrahim, Technical College of Management - Baghdad, Middle Technical University, Baghdad, Iraq.

Department of IT

References

J. Eygelaar, D. P. Lötter, and J. H. van Vuuren, "Generator maintenance scheduling based on the risk of power generating unit failure," Electrical Power and Energy Systems, vol. 95, no. 2018, pp. 83–95, 2018.

J. Eygelaar, "Generator maintenance scheduling based on the expected capability of satisfying energy demand," Doctoral dissertation, Stellenbosch: Stellebosch University, 2018.

Y. Lee, J. Choi, J. Cha, and M. Jung, “Smarter Visual System of Generator Maintenance Scheduling Including Multi-Objective Functions by GA,” IFAC-PapersOnLine, vol. 49, no. 27, pp. 212–217, 2016, doi: 10.1016/j.ifacol.2016.10.685.

El-Amin, I., 2000. Electric generator maintenance scheduling. Maintenance, Modeling and Optimization, pp.55-80.

G. Balaji, R. Balamurugan, and L. Lakshminarasimman, "Fuzzy clustered multi-objective differential evolution for thermal generator maintenance scheduling," International Journal of Intelligent Engineering and Systems, vol. 9, no. 1, pp. 1–13, 2016, doi: 10.22266/ijies2016.0331.01.

B. Lindne, R. Brits, J. van Vuuren, and J. Bekker, "Tradeoffs between levelling the reserve margins and minimizing production cost in generator maintenance scheduling for regulated power systems," International Journal of Electrical Power and Energy Systems, vol. 101, pp. 458–471, 2018, doi: 10.1016/j.ijepes.2018.02.018.

G. Balaji, R. Balamurugan, and L. Lakshminarasimman, "Mathematical approach assisted differential evolution for generator maintenance scheduling," International Journal of Electrical Power and Energy Systems, vol. 82, pp. 508–518, 2016, doi: 10.1016/j.ijepes.2016.04.033.

Moyo, L., Nwulu, N.I., Ekpenyong, U.E. and Bansal, R.C., 2021. A tri-objective model for generator maintenance scheduling. IEEE Access, 9, pp.136384-136394.

Ghorbani, N. and Babaei, E., 2016. Exchange market algorithm for economic load dispatch. International Journal of Electrical Power & Energy Systems, 75, pp.19-27.

B. G. Lindner, "Bi-objective Generator Maintenance Scheduling for a National Power Utility,",2017.

C. Blum and G. R. Raidl, Artificial Intelligence : Foundations, Theory, and Algorithms Hybrid Metaheuristics Powerful Tools for Optimization, 2016.

N. Bali and H. Labdelaoui, "Optimal Generator Maintenance Scheduling Using a Hybrid Metaheuristic Approach," International Journal of Computational Intelligence and Applications, vol. 14, no. 02, pp. 1550011–1 to 1550011–11, 2015, doi: 10.1142/S146902681550011X.

G. Balaji, R. Balamurugan, and L. Lakshminarasimman, "Generator maintenance scheduling in power systems using metaheuristic-based hybrid approaches," ARPN Journal of Engineering and Applied Sciences, vol. 10, no. 22, pp. 10566–10577, 2015.

A. Ahmad and D. P. Kothari, "A REVIEW OF RECENT ADVANCES IN GENERATOR MAINTENANCE SCHEDULING," Electric Machines & Power Systems, vol. 26, no. 4, pp. 373–387, 1998, doi 10.1080/07313569808955829.

M. Gendreau, J. E. Mendoza, and L. Rousseau, "Maintenance Scheduling in the Electricity Industry : A Literature Review Aurélien Froger Maintenance Scheduling in the Electricity Industry : A Literature Review," no. October 2014.

G. R. Raidl, T. Baumhauer, and B. Hu, "Boosting an exact logic-based benders decomposition approach by variable neighborhood search," Electronic Notes in Discrete Mathematics, vol. 47, pp. 149–156, 2015, doi: 10.1016/j.endm.2014.11.020.

R. Singh, A. Kainthola, and T. N. Singh, "Estimation of elastic constant of rocks using an ANFIS approach," Applied Soft Computing Journal, vol. 12, no. 1, pp. 40–45, 2012, doi: 10.1016/j.asoc.2011.09.010.

M. Charest and J. A. Ferland, "Preventive maintenance scheduling of power generating units," Annals of Operations Research, vol. 41, no. 1993, pp. 185–206, 1993, doi: 10.1007/BF02023074.

X. Yu and M. Gen, Introduction to Evolutionary Algorithms. 2010.

M. M. Alobaedy, "Hybrid Ant Colony System algorithm for static and dynamic job scheduling in grid computing," UUM, 2015.

A. Volkanovski, B. Mavko, T. Boševski, A. Čauševski, and M. Čepin, "Genetic algorithm optimization of the maintenance scheduling of generating units in a power system," Reliability Engineering and System Safety, vol. 93, no. 6, pp. 779–789, 2008, doi: 10.1016/j.ress.2007.03.027.

G. Balaji, R. Balamurugan, and L. Lakshminarasimman, "Reliability based Generator Maintenance Scheduling using Integer Coded Differential Evolution Algorithm," International Journal of Computer Applications, vol. 131, no. 6, pp. 27–38, 2015, doi: 10.5120/ijca2015907473.

P. G. Majeed and S. Kumar, "Genetic algorithms in intrusion detection systems: A SURVEY," 2014.

X. S. Yang, Nature-Inspired Optimization Algorithms, no. March. 2014.

J. Hartmann, T. Makuschewitz, E. M. Frazzon, Bernd, and Scholz-Reiter, A genetic algorithm for the integrated scheduling of production and transport systems, vol. 45, no. 1. 2014.

M. Gen, W. Zhang, L. Lin, and J. Jo, Recent Advances in Multiobjective Genetic Algorithms for Manufacturing Scheduling Problems. 2014.

L. Singh and S. Singh, A genetic algorithm for scheduling workflow applications in unreliable cloud environment, vol. 335. 2014.

R. Storn and K. Price, "Differential Evolution – A simple and efficient heuristic for global optimization over continuous spaces," Journal ofGlobal Optimization, vol. 11, pp. 341–359, 1997, doi: 10.1071/AP09004.

G. Zäpfel, R. Braune, and M. Bögl, Metahuristics Search Concepts. 2010.

M. Gendreau and J.-Y. Potvin, Handbook of Metaheuristics, vol. 157. 2010.

X. Zhang et al., "3D Protein structure prediction with genetic tabu search algorithm," BMC Systems Biology, vol. 4, no. SUPPL. 1, pp. 1–9, 2010, doi 10.1186/1752-0509-4-S1-S6.

V. Gazi and K. M. Passino, swarm stability and optimization. 2011.

C. Pintea, Advances in Bio-inspired Computing for Combinatorial Optimization Problems. 2014.

C. P. Lim and L. C. Jain, innovations in swarm intelligence, vol. 91. 2009.

L. Manuel, M. Maur, and M. M. De Oca, "Parameter Adaptation in Ant Colony Optimization Thomas St u," no. January 2010, doi 10.1007/978-3-642-21434-9.

H. N. K. Al-Behadili, K. R. Ku-Mahamud, and R. Sagban, "Ant colony optimization algorithm for rule-based classification: Issues and potential solutions," Journal of Theoretical and Applied Information Technology, vol. 96, no. 21, pp. 7139–7150, 2018.

R. Gan, Q. Guo, H. Chang, and Y. Yi, "Improved ant colony optimization algorithm for the traveling salesman problems," Journal of Systems Engineering and Electronics, vol. 21, no. 2, pp. 329–333, 2014, doi: 10.3969/j.issn.1004-4132.2010.02.025.

A. M. Jabbar, K. R. Ku-Mahamud, and R. Sagban, "Ant-based sorting and ACO-based clustering approaches: A review," in In 2018 IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE), 2018, no. July, pp. 217–223, doi: 10.1109/ISCAIE.2018.8405473.

G. Abbas, J. Gu, U. Farooq, A. Raza, M. U. Asad, and M. El-Hawary, "Solution of an economic dispatch problem through Particle Swarm Optimization: A detailed survey – part II," IEEE Access, vol. 5, pp. 24426–24445, 2017, doi: 10.1109/ACCESS.2017.2768522.

X. Yang, Recent Advances in Swarm Intelligence and Evolutionary Computation. 2015.

E.-G. Talbi, A Unified Taxonomy of Hybrid Metaheuristics with Mathematical Programming, Constraint Programming and Machine Learning, 2013.

Y. Su and R. Chi, "Multi-objective particle swarm-differential evolution algorithm," Neural Computing and Applications, vol. 28, no. 2, pp. 407–418, 2015, doi: 10.1007/s00521-015-2073-y.

T. O. Ting, X. Yang, S. Cheng, and K. Huang, "Hybrid Metaheuristic Algorithms: Past, Present, and Future," In Recent advances in swarm intelligence and evolutionary computation, no. January, pp. 71–83, 2015, doi 10.1007/978-3-319-13826-8.

M. Alardhi and A. W. Labib, "Preventive maintenance scheduling of multi-cogeneration plants using integer programming," Journal of the Operational Research Society, vol. 59, no. 4, pp. 503–509, 2008, doi: 10.1057/palgrave.jors.2602386.

G. A. Bakirtzis, P. N. Biskas, and V. Chatziathanasiou, "Generation expansion planning by MILP considering mid-term scheduling decisions," Electric Power Systems Research, vol. 86, pp. 1–40, 2012, doi: 10.1016/j.epsr.2011.12.008.

N. M. Tabari, A. M. Ranjbar, and N. Sadati, "Promoting the optimal maintenance schedule of generating facilities in open systems," in In Proceedings. International Conference on Power System Technology, 2002, vol. 1, pp. 641–645, doi: 10.1109/ICPST.2002.1053621.

R. Tonić and M. Rakić, "Annual preventive maintenance scheduling for thermal units in an electric power system," Yugoslav Journal of Operations Research, vol. 20, no. 2, pp. 261–273, 2010, doi: 10.2298/YJOR1002261T.

K.-Y. Huang and H.-T. Yang, "Effective algorithm for handling constraints in generator maintenance scheduling," in IEE Proceedings - Generation, Transmission and Distribution, 2002, vol. 149, no. 3, pp. 274–282, doi: 10.1049/ip-gtd:20020214.

I. Kuzle, H. Pandžić, and M. Brezovec, "Hydro Generating Units Maintenance Scheduling Using Benders Decomposition," Technical Gazette, vol. 17, no. 2, pp. 145–152, 2010, doi: 10.1117/12.624407.

K. H. Chung, B. H. Kim, and D. Hur, "Distributed implementation of generation scheduling algorithm on interconnected power systems," Energy Conversion and Management, vol. 52, no. 12, pp. 3457–3464, 2011, doi: 10.1016/j.enconman.2010.10.006.

Muthana, S.A. and Ku-Mahamud, K.R., 2021. Generator Maintenance Scheduling Models for Electrical Power Systems: A Review. Int. J. Electr. Electron. Eng. Telecommun, 10(5), pp.307-318.

M. Buljubasic and H. Gavranovic, "Orchestrating Constrained Programming and Local Search to Solve a Large Scale Energy Management Problem," in Proceedings of the Federated Conference on Computer Science and Information System, 2012, pp. 371–378.

F. Brandt, R. Bauer, M. Völker, and A. Cardeneo, "A constraint programming-based approach to a large-scale energy management problem with varied constraints," Journal of Scheduling, vol. 16, no. 6, pp. 629–648, 2013, doi: 10.1007/s10951-012-0281-1.

S. Kheawhom, "Efficient constraint handling scheme for differential evolutionary algorithm in solving chemical engineering optimization problem," Journal of Industrial and Engineering Chemistry, vol. 16, no. 4, pp. 620–628, 2010, doi: 10.1016/j.jiec.2010.03.004.

H. Sun, Y. Huang, and K. Huang, "A New Algorithm for Power System Scheduling Problems," in Eighth International Conference on Intelligent Systems Design and Applications, 2008, pp. 36–40, doi: 10.1109/ISDA.2008.200.

J. T. Saraiva, M. L. Pereira, V. T. Mendes, and J. C. Sousa, "A Simulated Annealing based approach to solve the generator maintenance scheduling problem," Electric Power Systems Research, vol. 81, no. 7, pp. 1283–1291, 2011, doi: 10.1016/j.epsr.2011.01.013.

J. Sugimoto, A. M. Isa, and R. Yokoyama, "Profit-oriented Thermal Unit Maintenance Scheduling under Competitive Environment," in In 2007 IEEE Power Engineering Society General Meeting, 2007, pp. 1–6.

A. Vlachos, "Rank-Based Ant Colony Algorithm For A Thermal Generator Maintenance Scheduling Problem," WSEAS Transactions on Circuits & Systems, vol. 12, no. 9, pp. 273–285, 2013.

M. Fattahi, M. Mahootchi, H. Mosadegh, and F. Fallahi, "A new approach for maintenance scheduling of generating units in electrical power systems based on their operational hours," Computers & Operations Research, vol. 50, pp. 61–79, 2014.

U. E. Ekpenyong, J. Zhang, and X. X. Centre, "An improved robust model for generator maintenance scheduling," Electric Power Systems Research, vol. 92, pp. 29–36, 2012.

Ismail, F.B., Randhawa, G.S., Al-Bazi, A. and Alkahtani, A.A., 2023. Intelligent Optimization Systems for Maintenance Scheduling of Power Plant Generators. Information Sciences Letters, 12(3), pp.1319-1332.

N. Kumarappan and P. Suriya, "Hybrid GA / SA Based Generation Maintenance Scheduling with Line Flow Constraints in Power Market," in In 2010 Joint International Conference on Power Electronics, Drives, and Energy Systems & 2010 Power India, 2010, pp. 1–8.

T. Jayabarathi, S. Chalasani, and Z. A. Shaik, "Hybrid Differential Evolution and Particle Swarm Optimization Based Solutions to Short Term Hydro Thermal Scheduling," WSEAS TRANSACTIONS on POWER SYSTEMS, vol. 2, no. 11, pp. 245–254, 2007.

E. Reihani, M. O. Buygi, and M. Banejad, "Generation Maintenance Scheduling Using Hybrid Evolutionary Approach," in The International Conference on Electrical Engineering 2008, 2008, pp. 1–7.

E. B. Schlünz and J. H. van Vuuren, "THE APPLICATION OF A COMPUTERIZED DECISION SUPPORT SYSTEM FOR GENERATOR MAINTENANCE SCHEDULING: A SOUTH AFRICAN CASE STUDY," south African Journal of Industrial Engineering, vol. 23, no. 2, pp. 169–179, 2012.

G. G. Samuel and C. C. A. Rajan, "Hybrid Particle Swarm Optimization – Genetic Algorithm and Particle Swarm Optimization – Evolutionary Programming for Long-term Generation Maintenance Scheduling," in International Conference on Renewable Energy and Sustainable Energy [ICRESE'13], 2013, pp. 227–232.

D. K. Mohanta, P. K. Sadhu, and R. Chakrabarti, "Fuzzy reliability evaluation of captive power plant maintenance scheduling incorporating uncertain forced outage rate and load representation," Electric Power Systems Research, vol. 72, no. 1, pp. 73–84, 2004, doi: 10.1016/j.epsr.2004.04.001.

D. K. Mohanta, P. K. Sadhu, and R. Chakrabarti, "Fuzzy Markov model for determination of fuzzy state probabilities of generating units including the effect of maintenance scheduling," IEEE Transactions on Power Systems, vol. 20, no. 4, pp. 2117–2124, 2005, doi: 10.1109/TPWRS.2005.857932.

R.-C. Leou and S.-A. Yih, "A flexible unit maintenance scheduling using fuzzy 0-1 integer programming," in In 2000 Power Engineering Society Summer Meeting (Cat. No. 00CH37134), 2000, vol. 4, pp. 2551–2555.

Liu, S., Liu, J., Ye, W., Yang, N., Zhang, G., Zhong, H., Kang, C., Jiang, Q., Song, X., Di, F. and Gao, Y., 2023. Real-time scheduling of renewable power systems through planning-based reinforcement learning. arXiv preprint arXiv:2303.05205.

Pinninti, S. and Sura, S.R., 2023. Renewables based dynamic cost-effective optimal scheduling of distributed generators using teaching–learning-based optimization. International Journal of System Assurance Engineering and Management, pp.1-21.