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A Novel TSA-PSO Based Hybrid Algorithm for GMPP Tracking under Partial Shading Conditions

Author

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  • Abhishek Sharma

    (Department of Electrical and Electronics Engineering, Ariel University, Ariel 40700, Israel
    Department of Electrical and Electronics Engineering, University of Petroleum and Energy Studies, Dehradun 248007, India)

  • Abhinav Sharma

    (Department of Electrical and Electronics Engineering, University of Petroleum and Energy Studies, Dehradun 248007, India)

  • Vibhu Jately

    (Department of Electrical and Electronics Engineering, University of Petroleum and Energy Studies, Dehradun 248007, India)

  • Moshe Averbukh

    (Department of Electrical and Electronics Engineering, Ariel University, Ariel 40700, Israel)

  • Shailendra Rajput

    (Department of Electrical and Electronics Engineering, Ariel University, Ariel 40700, Israel
    Department of Physics, University Centre for Research and Development, Chandigarh University, Mohali 140431, India)

  • Brian Azzopardi

    (MCAST Energy Research Group (MCAST Energy), Institute of Engineering and Transport, Malta College of Arts, Science and Technology (MCAST), Triq Kordin, PLA 9032 Paola, Malta)

Abstract

In this paper, a new hybrid TSA-PSO algorithm is proposed that combines tunicate swarm algorithm (TSA) with the particle swarm optimization (PSO) technique for efficient maximum power extraction from a photovoltaic (PV) system subjected to partial shading conditions (PSCs). The performance of the proposed algorithm was enhanced by incorporating the PSO algorithm, which improves the exploitation capability of TSA. The response of the proposed TSA-PSO-based MPPT was investigated by performing a detailed comparative study with other recently published MPPT algorithms, such as tunicate swarm algorithm (TSA), particle swarm optimization (PSO), grey wolf optimization (GWO), flower pollination algorithm (FPA), and perturb and observe (P&O). A quantitative and qualitative analysis was carried out based on three distinct partial shading conditions. It was observed that the proposed TSA-PSO technique had remarkable success in locating the maximum power point and had quick convergence at the global maximum power point. The presented TSA-PSO MPPT algorithm achieved a PV tracking efficiency of 97.64%. Furthermore, two nonparametric tests, Friedman ranking and Wilcoxon rank-sum, were also employed to validate the effectiveness of the proposed TSA-PSO MPPT method.

Suggested Citation

  • Abhishek Sharma & Abhinav Sharma & Vibhu Jately & Moshe Averbukh & Shailendra Rajput & Brian Azzopardi, 2022. "A Novel TSA-PSO Based Hybrid Algorithm for GMPP Tracking under Partial Shading Conditions," Energies, MDPI, vol. 15(9), pages 1-21, April.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:9:p:3164-:d:802719
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    References listed on IDEAS

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    1. Mahsa Z. Farahmand & M. E. Nazari & S. Shamlou & Miadreza Shafie-khah, 2021. "The Simultaneous Impacts of Seasonal Weather and Solar Conditions on PV Panels Electrical Characteristics," Energies, MDPI, vol. 14(4), pages 1-19, February.
    2. Yao, Xing & Yi, Bowen & Yu, Yang & Fan, Ying & Zhu, Lei, 2020. "Economic analysis of grid integration of variable solar and wind power with conventional power system," Applied Energy, Elsevier, vol. 264(C).
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    Cited by:

    1. Sy Ngo & Chian-Song Chiu & Thanh-Dong Ngo, 2022. "A Novel Horse Racing Algorithm Based MPPT Control for Standalone PV Power Systems," Energies, MDPI, vol. 15(20), pages 1-18, October.
    2. Hsen Abidi & Lilia Sidhom & Ines Chihi, 2023. "Systematic Literature Review and Benchmarking for Photovoltaic MPPT Techniques," Energies, MDPI, vol. 16(8), pages 1-45, April.
    3. Muhammad Mateen Afzal Awan & Aamer Bilal Asghar & Muhammad Yaqoob Javed & Zsolt Conka, 2023. "Ordering Technique for the Maximum Power Point Tracking of an Islanded Solar Photovoltaic System," Sustainability, MDPI, vol. 15(4), pages 1-19, February.
    4. Haoming Liu & Muhammad Yasir Ali Khan & Xiaoling Yuan, 2023. "Hybrid Maximum Power Extraction Methods for Photovoltaic Systems: A Comprehensive Review," Energies, MDPI, vol. 16(15), pages 1-64, July.
    5. Amit Kumar Sharma & Rupendra Kumar Pachauri & Sushabhan Choudhury & Ahmad Faiz Minai & Majed A. Alotaibi & Hasmat Malik & Fausto Pedro García Márquez, 2023. "Role of Metaheuristic Approaches for Implementation of Integrated MPPT-PV Systems: A Comprehensive Study," Mathematics, MDPI, vol. 11(2), pages 1-48, January.
    6. Ahmed G. Abo-Khalil & Ibrahim I. El-Sharkawy & Ali Radwan & Saim Memon, 2023. "Influence of a Hybrid MPPT Technique, SA-P&O, on PV System Performance under Partial Shading Conditions," Energies, MDPI, vol. 16(2), pages 1-17, January.
    7. Miao Zhang & Keyu Zhuang & Tong Zhao & Xianli Chen & Jingze Xue & Zheng Qiao & Shuai Cui & Yunlong Gao, 2022. "Bus Voltage Control of Photovoltaic Grid Connected Inverter Based on Adaptive Linear Active Disturbance Rejection," Energies, MDPI, vol. 15(15), pages 1-20, July.

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