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A Novel Horse Racing Algorithm Based MPPT Control for Standalone PV Power Systems

Author

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  • Sy Ngo

    (Institute of Engineering and Technology, Thu Dau Mot University, Thu Dau Mot 7500, Vietnam)

  • Chian-Song Chiu

    (Department of Electrical Engineering, Chung Yuan Christian University, Taoyuan 230314, Taiwan)

  • Thanh-Dong Ngo

    (Institute of Engineering and Technology, Thu Dau Mot University, Thu Dau Mot 7500, Vietnam)

Abstract

This paper proposes a novel maximum power point tracking (MPPT) method inspired by the horse racing game for standalone photovoltaic (PV) power systems, such that the highest PV power conversion efficiency is obtained. From the horse racing game rules, we develop the horse racing algorithm (HRA) with the qualifying stage and final ranking stage. The MPP can be searched even if there exist multiple local MPPs for the PV power system. Moreover, from the proposed horse racing algorithm, the calculation is reduced, so that the transient searching points are less than traditional methods, i.e., the transient oscillation is less during the MPPT control. Therefore, the HRA based MPPT method avoids local maximum power traps and achieves the MPP quickly even if considering partial shading influence and varying environment for PV panels. Evidence of the accuracy and effectiveness of the proposed HRA method is exhibited by simulation results. These results are also compared with typical particle swarm optimization (PSO) and grey wolf optimization (GWO) methods and shown better convergence time as well as transient oscillation. Within the range from 0.34 to 0.58 s, the proposed method has effectively tracked the global maximum power point, which is from 0.42 to 0.48 s faster than the conventional PSO technique and from 0.36 to 0.74 s faster than the GWO method. Finally, the obtained findings proved the effectiveness and superiority of the proposed HRA technique through experimental results. The fast response in terms of good transient oscillation and global power tracking time of the proposed method are from 0.40 to 1.0 s, while the PSO and GWO methods are from 1.56 to 1.6 s and from 1.9 to 2.2 s, respectively.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:20:p:7498-:d:939932
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    References listed on IDEAS

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    1. Noureddine Bouarroudj & Djamel Boukhetala & Vicente Feliu-Batlle & Fares Boudjema & Boualam Benlahbib & Bachir Batoun, 2019. "Maximum Power Point Tracker Based on Fuzzy Adaptive Radial Basis Function Neural Network for PV-System," Energies, MDPI, vol. 12(14), pages 1-19, July.
    2. 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.
    3. Hongyang He & Zhigang Lu & Xiaoqiang Guo & Changli Shi & Dongqiang Jia & Chao Chen & Josep M. Guerrero, 2022. "Optimized Control Strategy for Photovoltaic Hydrogen Generation System with Particle Swarm Algorithm," Energies, MDPI, vol. 15(4), pages 1-17, February.
    4. Ibrahim Al-Wesabi & Zhijian Fang & Hassan M. Hussein Farh & Abdullrahman A. Al-Shamma’a & Abdullah M. Al-Shaalan & Tarek Kandil & Min Ding, 2022. "Cuckoo Search Combined with PID Controller for Maximum Power Extraction of Partially Shaded Photovoltaic System," Energies, MDPI, vol. 15(7), pages 1-26, March.
    5. Sampath Kumar Vankadara & Shamik Chatterjee & Praveen Kumar Balachandran & Lucian Mihet-Popa, 2022. "Marine Predator Algorithm (MPA)-Based MPPT Technique for Solar PV Systems under Partial Shading Conditions," Energies, MDPI, vol. 15(17), pages 1-16, August.
    6. Nouman Akram & Laiq Khan & Shahrukh Agha & Kamran Hafeez, 2022. "Global Maximum Power Point Tracking of Partially Shaded PV System Using Advanced Optimization Techniques," Energies, MDPI, vol. 15(11), pages 1-29, May.
    7. Ezhilmaran Ranganathan & Rajasekar Natarajan, 2022. "Spotted Hyena Optimization Method for Harvesting Maximum PV Power under Uniform and Partial-Shade Conditions," Energies, MDPI, vol. 15(8), pages 1-26, April.
    8. Novie Ayub Windarko & Muhammad Nizar Habibi & Bambang Sumantri & Eka Prasetyono & Moh. Zaenal Efendi & Taufik, 2021. "A New MPPT Algorithm for Photovoltaic Power Generation under Uniform and Partial Shading Conditions," Energies, MDPI, vol. 14(2), pages 1-22, January.
    9. Danandeh, M.A. & Mousavi G., S.M., 2018. "Comparative and comprehensive review of maximum power point tracking methods for PV cells," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2743-2767.
    10. Kuei-Hsiang Chao & Muhammad Nursyam Rizal, 2021. "A Hybrid MPPT Controller Based on the Genetic Algorithm and Ant Colony Optimization for Photovoltaic Systems under Partially Shaded Conditions," Energies, MDPI, vol. 14(10), pages 1-17, May.
    11. Shahzad Ahmed & Hafiz Mian Muhammad Adil & Iftikhar Ahmad & Muhammad Kashif Azeem & Zil e Huma & Safdar Abbas Khan, 2020. "Supertwisting Sliding Mode Algorithm Based Nonlinear MPPT Control for a Solar PV System with Artificial Neural Networks Based Reference Generation," Energies, MDPI, vol. 13(14), pages 1-24, July.
    12. Abdelilah Chalh & Aboubakr El Hammoumi & Saad Motahhir & Abdelaziz El Ghzizal & Umashankar Subramaniam & Aziz Derouich, 2020. "Trusted Simulation Using Proteus Model for a PV System: Test Case of an Improved HC MPPT Algorithm," Energies, MDPI, vol. 13(8), pages 1-12, April.
    13. Slimane Hadji & Jean-Paul Gaubert & Fateh Krim, 2018. "Real-Time Genetic Algorithms-Based MPPT: Study and Comparison (Theoretical an Experimental) with Conventional Methods," Energies, MDPI, vol. 11(2), pages 1-17, February.
    14. Manoharan Premkumar & Umashankar Subramaniam & Thanikanti Sudhakar Babu & Rajvikram Madurai Elavarasan & Lucian Mihet-Popa, 2020. "Evaluation of Mathematical Model to Characterize the Performance of Conventional and Hybrid PV Array Topologies under Static and Dynamic Shading Patterns," Energies, MDPI, vol. 13(12), pages 1-37, June.
    15. Mingrui Zhang & Zheyang Chen & Li Wei, 2019. "An Immune Firefly Algorithm for Tracking the Maximum Power Point of PV Array under Partial Shading Conditions," Energies, MDPI, vol. 12(16), pages 1-15, August.
    16. CH Hussaian Basha & C Rani, 2020. "Different Conventional and Soft Computing MPPT Techniques for Solar PV Systems with High Step-Up Boost Converters: A Comprehensive Analysis," Energies, MDPI, vol. 13(2), pages 1-27, January.
    17. Ali M. Eltamaly, 2021. "An Improved Cuckoo Search Algorithm for Maximum Power Point Tracking of Photovoltaic Systems under Partial Shading Conditions," Energies, MDPI, vol. 14(4), pages 1-26, February.
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    1. Miao Zhang & Keyu Zhuang & Tong Zhao & Jingze Xue & Yunlong Gao & Shuai Cui & Zheng Qiao, 2022. "MPPT Control Algorithm Based on Particle Swarm Optimization and Adaptive Linear Active Disturbance Rejection Control," Energies, MDPI, vol. 15(23), pages 1-19, November.

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