Nuclear Engineering and Technology

Korean Nuclear Society (한국원자력학회)
권호 표지
DOI QR코드

DOI QR Code

Hybrid of the fuzzy logic controller with the harmony search algorithm to PWR in-core fuel management optimization

  • Mahmoudi, Sayyed Mostafa (Department of Energy Engineering & Physics, Amirkabir University of Technology (Tehran Polytechnic)) ;
  • Rad, Milad Mansouri (Department of Energy Engineering & Physics, Amirkabir University of Technology (Tehran Polytechnic)) ;
  • Ochbelagh, Dariush Rezaei (Department of Energy Engineering & Physics, Amirkabir University of Technology (Tehran Polytechnic))
  • Received : 2020.10.05
  • Accepted : 2021.05.09
  • Published : 2021.11.25
Download PDF
⟨ Previous Next ⟩

Abstract

One of the important parts of the in-core fuel management is loading pattern optimization (LPO). The loading pattern optimization as a reasonable design of the in-core fuel management can improve both economic and safe aspects of the nuclear reactor. This work proposes the hybrid of fuzzy logic controller with harmony search algorithm (HS) for loading pattern optimization in a pressurized water reactor. The music improvisation process to find a pleasing harmony is inspiring the harmony search algorithm. In this work, the adjustment of the harmony search algorithm parameters such as the bandwidth and the pitch adjustment rate are increasing performance of the proposed algorithm which is done through a fuzzy logic controller. Hence, membership functions and fuzzy rules are designed to improve the performance of the HS algorithm and achieve optimal results. The objective of the method is finding an optimum core arrangement according to safety and economic aspects such as reduction of power peaking factor (PPF) and increase of effective multiplication factor (Keff). The proposed approach effectiveness has been tried in two cases, Michalewicz's bivariate function problem and NEACRP LWR core. The results show that by using fuzzy harmony search algorithm the value of the fitness function is improved by 15.35%. Finally, with regard to the new solutions proposed in this research it could be used as a trustworthy method for other optimization issues of engineering field.

Keywords

Acknowledgement

The authors would also like to express their gratitude to Dr. Sara Kamalpour for her valuable guidance.

References

  1. E. Guk, N. Kalkan, The importance of nuclear energy for the expansion of world, Advances in Energy Research 3 (2) (2015), 071. https://doi.org/10.12989/eri.2015.3.2.071
  2. A. Yamamoto, A quantitative comparison of loading pattern optimization methods for in-core fuel management of PWR, J. Nucl. Sci. Technol. 34 (4) (1997) 339-347. https://doi.org/10.1080/18811248.1997.9733673
  3. S. Mahmoudi, M. Aghaie, M. Bahonar, N. Poursalehi, A novel optimization method, Gravitational Search Algorithm (GSA), for PWR core optimization, Ann. Nucl. Energy 95 (2016) 23-34. https://doi.org/10.1016/j.anucene.2016.04.035
  4. M. Aghaie, S.M. Mahmoudi, A novel multi objective loading pattern optimization by gravitational search algorithm (GSA) for WWER1000 core, Prog. Nucl. Energy 93 (2016) 1-11. https://doi.org/10.1016/j.pnucene.2016.07.014
  5. M. Aghaie, S.M. Mahmoudi, Multi objective loading pattern optimization of PWRs with Fuzzy logic controller based Gravitational Search Algorithm, Nucl. Eng. Des. 322 (2017) 1-13. https://doi.org/10.1016/j.nucengdes.2017.06.036
  6. M. Jamalipour, M. Gharib, R. Sayareh, F. Khoshahval, PWR power distribution flattening using quantum particle swarm intelligence, Ann. Nucl. Energy 56 (2013) 143-150. https://doi.org/10.1016/j.anucene.2013.01.026
  7. A. Naserbegi, M. Aghaie, S.M. Mahmoudi, PWR core pattern optimization using grey wolf algorithm based on artificial neural network, Prog. Nucl. Energy 129 (2020) 103505. https://doi.org/10.1016/j.pnucene.2020.103505
  8. N. Poursalehi, M. Nejati-Zadeh, A. Minuchehr, Electromagnetism mechanism for enhancing the refueling cycle length of a WWER-1000, Nuclear Engineering and Technology 49 (1) (2017) 43-53. https://doi.org/10.1016/j.net.2016.08.012
  9. Y. Rahmani, Reloading pattern optimization of VVER-1000 reactors in transient cycles using genetic algorithm, Ann. Nucl. Energy 108 (2017) 24-41. https://doi.org/10.1016/j.anucene.2017.04.035
  10. R. Gharari, N. Poursalehi, M. Abbasi, M. Aghaie, Implementation of Strength Pareto evolutionary algorithm II in the multiobjective burnable poison placement optimization of KWU pressurized water reactor, Nuclear Engineering and Technology 48 (5) (2016) 1126-1139. https://doi.org/10.1016/j.net.2016.04.004
  11. R. Akbari, D. Rezaei Ochbelagh, A. Gharib, J.R. Maiorino, F. D'Auria, Small modular reactor full scope core optimization using Cuckoo Optimization Algorithm, Prog. Nucl. Energy 122 (2020) 103271. https://doi.org/10.1016/j.pnucene.2020.103271
  12. S. Kamalpour, H. Khalafi, SMART reactor core design optimization based on FCM fuel, Nucl. Eng. Des. 372 (2021) 110970. https://doi.org/10.1016/j.nucengdes.2020.110970
  13. T. Park, H. Joo, C.H. Kim, Performance Analysis of Discontinuous Penalty Function Based Multi-Objective Simulated Annealing for Multi-Cycle Problems, vol. 104, 2011, pp. 904-905.
  14. T. Park, H. Joo, C. Kim, H.C. Lee, Multiobjective loading pattern optimization by simulated annealing employing discontinuous penalty function and screening technique, Nucl. Sci. Eng. 162 (2009).
  15. T. Park, H. Joo, H.J. Shim, C.H. Kim, The rearrangement method for generating a new loading pattern set in multi-objective simulated annealing for multi-cycle optimization problems 105 (2011) 831-832.
  16. Z.W. Geem, J.H. Kim, G.V. Loganathan, A new heuristic optimization algorithm, harmony search, simulation 76 (2) (2001) 60-68. https://doi.org/10.1177/003754970107600201
  17. B. Jeddi, V. Vahidinasab, A modified harmony search method for environmental/economic load dispatch of real-world power systems, Energy Convers. Manag. 78 (2014) 661-675. https://doi.org/10.1016/j.enconman.2013.11.027
  18. S.M. Mahmoudi, A. Maleki, D. Rezaei Ochbelagh, Optimization of a hybrid energy system with/without considering back-up system by a new technique based on fuzzy logic controller, Energy Convers. Manag. 229 (2021) 113723. https://doi.org/10.1016/j.enconman.2020.113723
  19. E. Khorram, M. Jaberipour, Harmony search algorithm for solving combined heat and power economic dispatch problems, Energy Convers. Manag. 52 (2) (2011) 1550-1554. https://doi.org/10.1016/j.enconman.2010.10.017
  20. M. Fesanghary, E. Damangir, I. Soleimani, Design optimization of shell and tube heat exchangers using global sensitivity analysis and harmony search algorithm, Appl. Therm. Eng. 29 (5-6) (2009) 1026-1031. https://doi.org/10.1016/j.applthermaleng.2008.05.018
  21. M. Aghaie, T. Nazari, A. Zolfaghari, A. Minuchehr, A. Shirani, Investigation of PWR core optimization using harmony search algorithms, Ann. Nucl. Energy 57 (2013) 1-15. https://doi.org/10.1016/j.anucene.2013.01.046
  22. N. Poursalehi, A. Zolfaghari, A. Minuchehr, Differential harmony search algorithm to optimize PWRs loading pattern, Nucl. Eng. Des. 257 (2013) 161-174. https://doi.org/10.1016/j.nucengdes.2013.01.020
  23. T. Nazari, M. Aghaie, A. Zolfaghari, A. Minuchehr, A. Norouzi, WWER core pattern enhancement using adaptive improved harmony search, Nucl. Eng. Des. 254 (2013) 23-32. https://doi.org/10.1016/j.nucengdes.2012.08.018
  24. H. Finnemann, A. Galati, NEACRP 3 D LWR Core Transient Benchmark- Final Specifications, NEACRP-L-335(Rev. 1), Nuclear Energy Agency Committee on Reactor Physics, Jan. 1992.
  25. T. Downar, Y. Xu, T. Kozlowski, D. Carlson, PARCS V2. 7 US NRC Core Neutronics Simulator User Manual, Purdue University, 2006.
  26. K.S. Lee, Z.W. Geem, A new structural optimization method based on the harmony search algorithm, Comput. Struct. 82 (9-10) (2004) 781-798. https://doi.org/10.1016/j.compstruc.2004.01.002
  27. S.M. Mahmoudi, M. Aghaie, Evaluation of fuzzy based HS and GSA on reloading cycle length optimization of PWR nuclear power plant, Ann. Nucl. Energy 134 (2019) 1-10. https://doi.org/10.1016/j.anucene.2019.05.058
  28. K. Pandiarajan, C. Babulal, Fuzzy harmony search algorithm based optimal power flow for power system security enhancement, Int. J. Electr. Power Energy Syst. 78 (2016) 72-79. https://doi.org/10.1016/j.ijepes.2015.11.053
  29. Z. Michalewicz, Genetic Algorithms+ Data Structures= Evolution Programs, Springer Science & Business Media 2013.