Details

Title

Development of rapid and reliable cuckoo search algorithm for global maximum power point tracking of solar PV systems in partial shading condition

Journal title

Archives of Control Sciences

Yearbook

2021

Volume

vol. 31

Issue

No 3

Affiliation

Bentata, Khadidja : Laboratory Materials and Sustainable Development (LMDD), Electrical Engineering Department, Faculty of Science and Applied Sciences, University of Bouira, Algeria ; Mohammedi, Ahmed : Electrical Engineering Department, Faculty of Science and Applied Sciences, University of Bouira, Algeria ; Mohammedi, Ahmed : LTII Laboratory, University of Bejaia, Algeria ; Benslimane, Tarak : Electrical Engineering Department, University of M’sila, Algeria ; Benslimane, Tarak : SGRE Laboratory, University of Béchar, Algeria

Authors

Keywords

photovoltaic system ; maximum power point tracking ; partial shading ; cuckoosearch algorithm

Divisions of PAS

Nauki Techniczne

Coverage

495-526

Publisher

Committee of Automatic Control and Robotics PAS

Bibliography

[1] Zhao Zhuoli, Runting Cheng, Baiping Yan, Jiexiong Zhang, Ze- han Zhang, Mingyu Zhang, and Loi Lei Lai: A dynamic particles MPPT method for photovoltaic systems under partial shading conditions. Energy Conversion and Management, 220 (2020), 113070, DOI: 10.1016/j.enconman.2020.113070.
[2] Nabil A. Ahmed and Masafumi Miyatake: A novel maximum power point tracking for photovoltaic applications under partially shaded insolation conditions. Electric Power Systems Research, 78(5), (2008), 777–784, DOI: 10.1016/j.epsr.2007.05.026.
[3] Liqun Liu, Xiaoli Meng, and Chunxia Liu: A review of maximum power point tracking methods of PV power system at uniform and partial shading. Renewable and Sustainable Energy Reviews, 53 (2016), 1500–1507, DOI: 10.1016/j.rser.2015.09.065.
[4] Yanzhi Wang, Xue Lin, Younghyun Kim, Naehyuck Chang, and Mas- soud Pedram: Enhancing efficiency and robustness of a photovoltaic power system under partial shading. Thirteenth International Symposium on Quality Electronic Design (ISQED), Santa Clara USA, (2012), 592–600, DOI: 10.1109/ISQED.2012.6187554.
[5] Ricardo Orduz, Jorge Solorzano, Miguel Ángel Egido, and Ed- uardo Roman: Analytical study and evaluation results of power optimizers for distributed power conditioning in photovoltaic arrays. Progress in Photovoltaics: Research and Applications, 21(3), (2013), 359–373, DOI: 10.1002/pip.1188.
[6] Kashif Ishaque and Zainal Salam: A review of maximum power point tracking techniques of PV system for uniform insolation and partial shading condition. Renewable and Sustainable Energy Reviews, 19 (2013), 475–488, DOI: 10.1016/j.rser.2012.11.032.
[7] Jubaer Ahmed and Zainal Salam: A critical evaluation on maximum power point tracking methods for partial shading in PV systems. Renewable and Sustainable Energy Reviews, 47 (2015), 933–953, DOI: 10.1016/j.rser.2015.03.080.
[8] Ali M. Eltamaly: Performance of MPPT techniques of photovoltaic systems under normal and partial shading conditions. Advances in Renewable Energies and Power Technologies, vol. 1, Solar and Wind Energies, I. Yahyaoui, 2018, Elsevier, Chapter 4, 115–161.
[9] Ali M. Eltamaly: Performance of smart maximum power point tracker under partial shading conditions of photovoltaic systems. Journal ofRenewable and Sustainable Energy, 7(4), (2015), 043141, DOI: 10.1063/1.4929665.
[10] A. Talha, H. Boumaaraf, and O. Bouhali: Evaluation of maximum power point tracking methods for photovoltaic systems. Archives of Control Sciences, 21(2), (2011), 151–165.
[11] Hegazy Rezk and Ali M. Eltamaly: A comprehensive comparison of different MPPT techniques for photovoltaic systems. Solar Energy, 112 (2015), 1–11, DOI: 10.1016/j.solener.2014.11.010.
[12] S. Lyden and M.E. Haque: Maximum power point tracking techniques for photovoltaic systems: A comprehensive review and comparative analysis. Renewable and Sustainable Energy Reviews, 52 (2015): 1504–1518, DOI: 10.1016/j.rser.2015.07.172.
[13] Zainal Salam, Jubaer Ahmed, and Benny S. Merugu: The application of soft computing methods for MPPT of PV system: A technological and status review. Applied Energy, 107 (2013), 135–148, DOI: 10.1016/j.apenergy.2013.02.008.
[14] Hassan M.H. Farh, Mohamed F. Othman, and Ali M. Eltamaly: Maximum power extraction from grid-connected PV system. Saudi Arabia Smart Grid (SASG), (2017), 1–6, DOI: 10.1109/SASG.2017.8356498.
[15] Seyedali Mirjalili, Seyed Mohammad Mirjalili, and Andrew Lewis: GreyWolf optimizer. Advances in Engineering Software, 69 (2014), 46–61, DOI: 10.1016/j.advengsoft.2013.12.007.
[16] Sabrina Titri, Cherif Larbes, Kamal Youcef Toumi, and Karima Be- natchba: A new MPPT controller based on the ant colony optimization algorithm for photovoltaic systems under partial shading conditions. Applied Soft Computing, 58 (2017), 465–479, DOI: 10.1016/j.asoc.2017.05.017.
[17] Lian Lian Jiang, Douglas L. Maskell, and Jagdish C. Patra:Anovel ant colony optimization-based maximum power point tracking for photovoltaic systems under partially shaded conditions. Energy and Buildings, 58 (2013), 227–236, DOI: 10.1016/j.enbuild.2012.12.001.
[18] Lian Lian Jiang, R. Srivatsan, and Douglas L. Maskell: Computational intelligence techniques for maximum power point tracking in PV systems: A review. Renewable and Sustainable Energy Reviews, 85 (2018), 14–45, DOI: 10.1016/j.rser.2018.01.006.
[19] Ali M. Eltamaly and Hassan M.H. Farh: Dynamic global maximum power point tracking of the PV systems under variant partial shading using hybrid GWO-FLC. Solar Energy, 177 (2019), 306–316, DOI: 10.1016/j.solener.2018.11.028.
[20] Jubaer Ahmed and Zainal Salam: A maximum power point tracking (MPPT) for PV system using cuckoo search with partial shading capability. Applied Energy, 119 (2014), 118–130, DOI: 10.1016/j.apenergy.2013.12.062.
[21] Xin-She Yang and Suash Deb: Cuckoo search via Lévy flights. 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), Coimbatore, India (2009), 210–214, DOI: 10.1109/NABIC.2009.5393690.
[22] Jubaer Ahmed and Zainal Salam: A soft computing MPPT for PV system based on cuckoo search algorithm. 4th International Conference on Power Engineering, Energy and Electrical Drives, Istanbul, Turkey, (2013), 558– 562, DOI: 10.1109/PowerEng.2013.6635669.
[23] Ahmed A. El Baset, A. El Halim, Naggar H. , and Ahmed A. El Sattar: A comparative study between perturb and observe and cuckoo search algorithm for maximum power point tracking. 21st International Middle East Power Systems Conference (MEPCON), Cairo, Egypt, (2019), 716–723, DOI: 10.1109/MEPCON47431.2019.9008210.
[24] Filippo Spertino and Jean Sumaili Akilimali: Are manufacturing I–V mismatch and reverse currents key factors in large photovoltaic arrays? IEEE Transactions on Industrial Electronics, 56(11), (2009), 4520–4531, DOI: 10.1109/TIE.2009.2025712.
[25] M. Drif, P.J. Perez, J. Aguilera, and J.D. Aguilar: A new estimation method of irradiance on a partially shaded PV generator in grid-connected photovoltaic systems. Renewable Energy, 33(9), (2008), 2048–2056, DOI: 10.1016/j.renene.2007.12.010.
[26] Bidyadhar Subudhi and Raseswari Pradhan: A comparative study on maximum power point tracking techniques for photovoltaic power systems. IEEE Transactions on Sustainable Energy, 4(1), (2012), 89–98, DOI: 10.1109/TSTE.2012.2202294.
[27] Kashif Ishaque and Zainal Salam:AcomprehensiveMATLAB Simulink PV system simulator with partial shading capability based on two-diode model. Solar Energy, 85(9), (2011), 2217–2227, DOI: 10.1016/j.solener.2011.06.008.
[28] Mohamed I.Mosaad, M. Osama Abed el-Raouf, Mahmoud A. Al- Ahmar, and Fahd A. Banakher: Maximum power point tracking of PV system based cuckoo search algorithm; review and comparison. Energy Procedia, 162 (2019), 117–126, DOI: 10.1016/j.egypro.2019.04.013.
[29] Bo Yang, JingboWang, Xiaoshun Zhang, Tao Yu, Wei Yao, Hongchun Shu, Fang Zeng, and Liming Sun: Comprehensive overview of metaheuristic algorithm applications on PV cell parameter identification. Energy Conversion and Management, 208 (2020), 112595, DOI: 10.1016/j.enconman.2020.112595.
[30] Tong Kang, Jiangang Yao, Min Jin, Shengjie Yang, and Thanh Long Duong: A novel improved cuckoo search algorithm for parameter estimation of photovoltaic (PV) models. Energies, 11(5), (2018), 1060, DOI: 10.3390/en11051060.
[31] S. Walton, O. Hassan, K. Morgan, and M.R. Brown: Modified cuckoo search: a new gradient free optimisation algorithm. Chaos, Solitons & Fractals, 44(9), (2011), 710718, DOI: 10.1016/j.chaos.2011.06.004.
[32] Amir Hossein Gandomi, Xin-She Yang, and Amir Hossein Alavi: Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems. Engineering with Computers, 29(1), (2013), 17–35, DOI: 10.1007/s00366-011-0241-y.
[33] Abdesslem Layeb: A novel quantum inspired cuckoo search for knapsack problems. International Journal of Bio-Inspired Computation, 3(5), (2011), 297–305, DOI: 10.1504/IJBIC.2011.042260.
[34] Ehsan Valian, Saeed Tavakoli, Shahram Mohanna, and Atiyeh Haghi: Improved cuckoo search for reliability optimization problems. Computers & Industrial Engineering, 64(1), (2013), 459–468, DOI: 10.1016/j.cie.2012.07.011.
[35] Xiangtao Li, Jianan Wang, and Minghao Yin: Enhancing the performance of cuckoo search algorithm using orthogonal learning method. Neural Computing and Applications, 24(6), (2014), 1233–1247, DOI: 10.1007/s00521-013-1354-6.
[36] Hui Wang, Wenjun Wang, Hui Sun, Zhihua Cui, Shahryar Rahna- mayan, and Sanyou Zeng: A new cuckoo search algorithm with hybrid strategies for flow shop scheduling problems. Soft Computing, 21(15), (2017), 4297–4307, DOI: 10.1007/s00500-016-2062-9.
[37] Wang Jianzhou, He Jiang, Yujie Wu, and Yao Dong: Forecasting solar radiation using an optimized hybrid model by cuckoo search algorithm. Energy, 81 (2015), 627–644, DOI: 10.1016/j.energy.2015.01.006.
[38] Wen Long, Shaohong Cai, Jianjun Jiao, Ming Xu, and Tiebin Wu: A new hybrid algorithm based on grey wolf optimizer and cuckoo search for parameter extraction of solar photovoltaic models. Energy Conversion and Management, 203 (2020), 112243, DOI: 10.1016/j.enconman.2019.112243.
[39] Diego Oliva, Ahmed A. Ewees, Mohamed Abd El Aziz, Aboul Ella Hassanien, and Marco Perez-Cisneros: A chaotic improved artificial bee colony for parameter estimation of photovoltaic cells. Energies, 10(7), (2017), 865, DOI: 10.3390/en10070865.
[40] Xiaofang Yuan, Yuqing He, and Liangjiang Liu: Parameter extraction of solar cell models using chaotic asexual reproduction optimization. Neural Computing and Applications, 26(5), (2015), 1227–1239, DOI: 10.1007/s00521-014-1795-6.
[41] Xiaofang Yuan, Yongzhong Xiang, and Yuqing He: Parameter extraction of solar cell models using mutative-scale parallel chaos optimization algorithm. Solar Energy, 108 (2014), 238–251, DOI: 10.1016/j.solener.2014.07.013.
[42] Alireza Askarzadeh and Alireza Rezazadeh: Artificial bee swarm optimization algorithm for parameters identification of solar cell models. Applied Energy, 102 (2013), 943–949, DOI: 10.1016/j.apenergy.2012.09.052.
[43] Santhan Kumar Cherukuri and Srinivasa Rao Rayapudi: Enhanced grey wolf optimizer based MPPT algorithm of PV system under partial shaded condition. International Journal of Renewable Energy Development, 6(3), (2017), 203–212, DOI: 10.14710/ijred.6.3.203-212.
[44] Adeel Feroz Mirza, Qiang Ling, M. Yaqoob Javed, and Majad Man- soor: Novel MPPT techniques for photovoltaic systems under uniform irradiance and Partial shading. Solar Energy, 184 (2019), 628–648, DOI: 10.1016/j.solener.2019.04.034.

Date

2021.09.27

Type

Article

Identifier

DOI: 10.24425/acs.2021.138690
×