Research Article
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Year 2023, Volume: 27 Issue: 2, 361 - 369, 30.04.2023
https://doi.org/10.16984/saufenbilder.1175899

Abstract

References

  • [1] K. Chayakulkheeree, V. Hengsritawat, P. Nantivatana, “Particle swarm optimization based equivalent circuit estimation for on-service three-phase induction motor efficiency assessment,” Engineering Journal, vol. 21, no. 6 Special Issue, pp. 101–110, Oct. 2017.
  • [2] M O. Gülbahçe, M E. Karaaslan, “Estimation of Induction Motor Equivalent Circuit Parameters from Manufacturer’s Datasheet by Particle Swarm Optimization Algorithm for Variable Frequency Drives,” Electrica, vol. 22, no. 1, pp. 16–26, Jan. 2022.
  • [3] A I. Çanakoǧlu, A G. Yetgin, H. Temurtaş, M. Turan, “Induction motor parameter estimation using metaheuristic methods,” Turkish Journal of Electrical Engineering and Computer Sciences, vol. 22, no. 5, pp. 1177–1192, 2014.
  • [4] H R. Mohammadi, A. Akhavan, “Parameter Estimation of Three-Phase Induction Motor Using Hybrid of Genetic Algorithm and Particle Swarm Optimization,” Journal of Engineering, vol. 2014, no. 148204, pp. 1–6, 2014.
  • [5] A. Accetta, F. Alonge, M. Cirrincione, F. D’Ippolito, M. Pucci, A. Sferlazza, “GA-Based Off-Line Parameter Estimation of the Induction Motor Model Including Magnetic Saturation and Iron Losses,” IEEE Open Journal of Industry Applications, vol. 1, no. July, pp. 135–147, 2020.
  • [6] O. Rodríguez-Abreo, J. Rodríguez-Reséndiz, J. M. Álvarez-Alvarado, A. García-Cerezo, “Metaheuristic Parameter Identification of Motors Using Dynamic Response Relations,” Sensors, vol. 22, no. 11, pp. 1–22, 2022.
  • [7] M I. Abdelwanis, R. A. Sehiemy, M A. Hamida, “Hybrid optimization algorithm for parameter estimation of poly-phase induction motors with experimental verification,” Energy and AI, vol. 5, p. 100083, 2021.
  • [8] J. Vukasinovic, M. Milovanovic, N. Arsic, J. Radosavljevic, S. Statkic, “Parameters estimation of double-cage induction motors using a hybrid metaheuristic algorithm,” 2022 21st International Symposium INFOTEH-JAHORINA, 2022, pp. 16–18, 2022.
  • [9] I. Perez, M. Gomez-Gonzalez, F. Jurado, “Estimation of induction motor parameters using shuffled frog-leaping algorithm,” Electrical Engineering, vol. 95, no. 3, pp. 267–275, Sep. 2013.
  • [10] M. Averbukh, Efim Lockshin, “Estimation of the Equivalent Circuit Parameters of Induction Motors by Laboratory Test,” Machines, vol. 9, no. 340, pp. 1–12, 2021.
  • [11] H Y. Mahmoud, H M. Hasanien, A H. Besheer, A Y. Abdelaziz, “Hybrid cuckoo search algorithm and grey wolf optimiser-based optimal control strategy for performance enhancement of HVDC-based offshore wind farms,” IET Generation, Transmission and Distribution, vol. 14, no. 10, pp. 1902–1911, May 2020.
  • [12] S. Mirjalili, S M. Mirjalili, A. Lewis, “Grey Wolf Optimizer,” Advances in Engineering Software, vol. 69, pp. 46–61, Mar. 2014.
  • [13] W. Long, S. Cai, J. Jiao, M. Xu, T. Wu, “A new hybrid algorithm based on grey wolf optimizer and cuckoo search for parameter extraction of solar photovoltaic models,” Energy Convers Manag, vol. 203, p. 112243, Jan. 2020.
  • [14] R K. Khadanga, A. Kumar, S. Panda, “A modified Grey Wolf Optimization with Cuckoo Search Algorithm for load frequency controller design of hybrid power system,” Applied Soft Computing, vol. 124, Jul. 2022.
  • [15] R N. Kalaam, S. M. Muyeen, A. Al-Durra, H. M. Hasanien, K. Al-Wahedi, “Optimisation of controller parameters for grid-tied photovoltaic system at faulty network using artificial neural network-based cuckoo search algorithm,” IET Renewable Power Generation, vol. 11, no. 12, pp. 1517–1526, Oct. 2017.
  • [16] M. Mareli, B. Twala, “An adaptive Cuckoo search algorithm for optimisation,” Applied Computing and Informatics, vol. 14, no. 2. Elsevier B.V., pp. 107–115, Jul. 01, 2018.
  • [17] X. S. Yang, S. Deb, “Cuckoo search via Lévy flights,” 2009 World Congress on Nature and Biologically Inspired Computing, NABIC, 2009, pp. 210–214.
  • [18] P H. Kumar, M. Rudramoorthy, “Distribution network reconfiguration considering DGs using a hybrid CS-GWO algorithm for power loss minimization and voltage profile enhancement,” Indonesian Journal of Electrical Engineering and Informatics, vol. 9, no. 4, pp. 880–906, 2021.
  • [19] H. Xu, X. Liu, J. Su, “An improved grey Wolf optimizer algorithm integrated with Cuckoo Search,” in Proceedings of the 2017 IEEE 9th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS 2017, Nov. 2017, vol. 1, pp. 490–493.
  • [20] A. Bouaddi, R. Rabeh, M. Ferfra, “Load Frequency Control of Autonomous Microgrid System Using Hybrid Fuzzy logic GWO-CS PI Controller,” in 2021 9th International Conference on Systems and Control, ICSC 2021, 2021, pp. 554–559.

Parameter Estimation of Induction Motors using Hybrid GWO-CS Algorithm

Year 2023, Volume: 27 Issue: 2, 361 - 369, 30.04.2023
https://doi.org/10.16984/saufenbilder.1175899

Abstract

This study investigates a hybrid algorithm between Grey Wolf Optimization (GWO) and Cuckoo Search (CS) algorithms to find the parameters of induction motors. The parameters of the induction motor have been estimated by using the data supplied by the manufacturer. The problem for parameter estimation of the induction motor is formulated as an optimization problem. Then, the optimization problem is solved by using GWO and hybrid algorithm based on GWO and CS algorithms for the estimation of induction motor parameters. Numerical results show that both algorithms are capable of solving the optimization problem for finding the parameters of induction motor. Also, two algorithms and other algorithms such as Differential Evolution (DE), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Shuffled Frog-Leaping Algorithm (SFLA), and Modified Shuffled Frog-Leaping Algorithm (MSFLA) are compared for the problem. The results show that the hybrid GWO-CS algorithm gives a smaller objective value and closer torque value to the manufacturer’s data than the GWO algorithm and several algorithms for motor 1. Hybrid GWO-CS algorithm gives nearly the same results with GWO algorithm for motor 2.

References

  • [1] K. Chayakulkheeree, V. Hengsritawat, P. Nantivatana, “Particle swarm optimization based equivalent circuit estimation for on-service three-phase induction motor efficiency assessment,” Engineering Journal, vol. 21, no. 6 Special Issue, pp. 101–110, Oct. 2017.
  • [2] M O. Gülbahçe, M E. Karaaslan, “Estimation of Induction Motor Equivalent Circuit Parameters from Manufacturer’s Datasheet by Particle Swarm Optimization Algorithm for Variable Frequency Drives,” Electrica, vol. 22, no. 1, pp. 16–26, Jan. 2022.
  • [3] A I. Çanakoǧlu, A G. Yetgin, H. Temurtaş, M. Turan, “Induction motor parameter estimation using metaheuristic methods,” Turkish Journal of Electrical Engineering and Computer Sciences, vol. 22, no. 5, pp. 1177–1192, 2014.
  • [4] H R. Mohammadi, A. Akhavan, “Parameter Estimation of Three-Phase Induction Motor Using Hybrid of Genetic Algorithm and Particle Swarm Optimization,” Journal of Engineering, vol. 2014, no. 148204, pp. 1–6, 2014.
  • [5] A. Accetta, F. Alonge, M. Cirrincione, F. D’Ippolito, M. Pucci, A. Sferlazza, “GA-Based Off-Line Parameter Estimation of the Induction Motor Model Including Magnetic Saturation and Iron Losses,” IEEE Open Journal of Industry Applications, vol. 1, no. July, pp. 135–147, 2020.
  • [6] O. Rodríguez-Abreo, J. Rodríguez-Reséndiz, J. M. Álvarez-Alvarado, A. García-Cerezo, “Metaheuristic Parameter Identification of Motors Using Dynamic Response Relations,” Sensors, vol. 22, no. 11, pp. 1–22, 2022.
  • [7] M I. Abdelwanis, R. A. Sehiemy, M A. Hamida, “Hybrid optimization algorithm for parameter estimation of poly-phase induction motors with experimental verification,” Energy and AI, vol. 5, p. 100083, 2021.
  • [8] J. Vukasinovic, M. Milovanovic, N. Arsic, J. Radosavljevic, S. Statkic, “Parameters estimation of double-cage induction motors using a hybrid metaheuristic algorithm,” 2022 21st International Symposium INFOTEH-JAHORINA, 2022, pp. 16–18, 2022.
  • [9] I. Perez, M. Gomez-Gonzalez, F. Jurado, “Estimation of induction motor parameters using shuffled frog-leaping algorithm,” Electrical Engineering, vol. 95, no. 3, pp. 267–275, Sep. 2013.
  • [10] M. Averbukh, Efim Lockshin, “Estimation of the Equivalent Circuit Parameters of Induction Motors by Laboratory Test,” Machines, vol. 9, no. 340, pp. 1–12, 2021.
  • [11] H Y. Mahmoud, H M. Hasanien, A H. Besheer, A Y. Abdelaziz, “Hybrid cuckoo search algorithm and grey wolf optimiser-based optimal control strategy for performance enhancement of HVDC-based offshore wind farms,” IET Generation, Transmission and Distribution, vol. 14, no. 10, pp. 1902–1911, May 2020.
  • [12] S. Mirjalili, S M. Mirjalili, A. Lewis, “Grey Wolf Optimizer,” Advances in Engineering Software, vol. 69, pp. 46–61, Mar. 2014.
  • [13] W. Long, S. Cai, J. Jiao, M. Xu, T. Wu, “A new hybrid algorithm based on grey wolf optimizer and cuckoo search for parameter extraction of solar photovoltaic models,” Energy Convers Manag, vol. 203, p. 112243, Jan. 2020.
  • [14] R K. Khadanga, A. Kumar, S. Panda, “A modified Grey Wolf Optimization with Cuckoo Search Algorithm for load frequency controller design of hybrid power system,” Applied Soft Computing, vol. 124, Jul. 2022.
  • [15] R N. Kalaam, S. M. Muyeen, A. Al-Durra, H. M. Hasanien, K. Al-Wahedi, “Optimisation of controller parameters for grid-tied photovoltaic system at faulty network using artificial neural network-based cuckoo search algorithm,” IET Renewable Power Generation, vol. 11, no. 12, pp. 1517–1526, Oct. 2017.
  • [16] M. Mareli, B. Twala, “An adaptive Cuckoo search algorithm for optimisation,” Applied Computing and Informatics, vol. 14, no. 2. Elsevier B.V., pp. 107–115, Jul. 01, 2018.
  • [17] X. S. Yang, S. Deb, “Cuckoo search via Lévy flights,” 2009 World Congress on Nature and Biologically Inspired Computing, NABIC, 2009, pp. 210–214.
  • [18] P H. Kumar, M. Rudramoorthy, “Distribution network reconfiguration considering DGs using a hybrid CS-GWO algorithm for power loss minimization and voltage profile enhancement,” Indonesian Journal of Electrical Engineering and Informatics, vol. 9, no. 4, pp. 880–906, 2021.
  • [19] H. Xu, X. Liu, J. Su, “An improved grey Wolf optimizer algorithm integrated with Cuckoo Search,” in Proceedings of the 2017 IEEE 9th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS 2017, Nov. 2017, vol. 1, pp. 490–493.
  • [20] A. Bouaddi, R. Rabeh, M. Ferfra, “Load Frequency Control of Autonomous Microgrid System Using Hybrid Fuzzy logic GWO-CS PI Controller,” in 2021 9th International Conference on Systems and Control, ICSC 2021, 2021, pp. 554–559.
There are 20 citations in total.

Details

Primary Language English
Subjects Electrical Engineering
Journal Section Research Articles
Authors

Selcuk Emiroglu 0000-0001-7319-8861

Publication Date April 30, 2023
Submission Date September 15, 2022
Acceptance Date January 30, 2023
Published in Issue Year 2023 Volume: 27 Issue: 2

Cite

APA Emiroglu, S. (2023). Parameter Estimation of Induction Motors using Hybrid GWO-CS Algorithm. Sakarya University Journal of Science, 27(2), 361-369. https://doi.org/10.16984/saufenbilder.1175899
AMA Emiroglu S. Parameter Estimation of Induction Motors using Hybrid GWO-CS Algorithm. SAUJS. April 2023;27(2):361-369. doi:10.16984/saufenbilder.1175899
Chicago Emiroglu, Selcuk. “Parameter Estimation of Induction Motors Using Hybrid GWO-CS Algorithm”. Sakarya University Journal of Science 27, no. 2 (April 2023): 361-69. https://doi.org/10.16984/saufenbilder.1175899.
EndNote Emiroglu S (April 1, 2023) Parameter Estimation of Induction Motors using Hybrid GWO-CS Algorithm. Sakarya University Journal of Science 27 2 361–369.
IEEE S. Emiroglu, “Parameter Estimation of Induction Motors using Hybrid GWO-CS Algorithm”, SAUJS, vol. 27, no. 2, pp. 361–369, 2023, doi: 10.16984/saufenbilder.1175899.
ISNAD Emiroglu, Selcuk. “Parameter Estimation of Induction Motors Using Hybrid GWO-CS Algorithm”. Sakarya University Journal of Science 27/2 (April 2023), 361-369. https://doi.org/10.16984/saufenbilder.1175899.
JAMA Emiroglu S. Parameter Estimation of Induction Motors using Hybrid GWO-CS Algorithm. SAUJS. 2023;27:361–369.
MLA Emiroglu, Selcuk. “Parameter Estimation of Induction Motors Using Hybrid GWO-CS Algorithm”. Sakarya University Journal of Science, vol. 27, no. 2, 2023, pp. 361-9, doi:10.16984/saufenbilder.1175899.
Vancouver Emiroglu S. Parameter Estimation of Induction Motors using Hybrid GWO-CS Algorithm. SAUJS. 2023;27(2):361-9.