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A Novel Hybrid MPPT Technique Based on Harris Hawk Optimization (HHO) and Perturb and Observer (P&O) under Partial and Complex Partial Shading Conditions

Author

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  • Muhammad Annas Hafeez

    (Department of Electrical and Computer Engineering, COMSATS University Islamabad, Lahore 54000, Pakistan)

  • Ahmer Naeem

    (Department of Computer Engineering, Balochistan University of Information Technology, Engineering and Management Sciences, Quetta 87300, Pakistan)

  • Muhammad Akram

    (Department of Software Engineering, Balochistan University of Information Technology, Engineering and Management Sciences, Quetta 87300, Pakistan)

  • Muhammad Yaqoob Javed

    (Department of Electrical and Computer Engineering, COMSATS University Islamabad, Lahore 54000, Pakistan)

  • Aamer Bilal Asghar

    (Department of Electrical and Computer Engineering, COMSATS University Islamabad, Lahore 54000, Pakistan)

  • Yong Wang

    (School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

Photovoltaic (PV) systems have been used extensively worldwide over the past few years due to the mitigation of fossils fuels; it is the best source because of its eco-friendly nature. In PV systems, the main research area concerns its performance under partial shading (PS) and complex partial shading (CPS) conditions. PV sources perform perfectly under ideal conditions, but under practical conditions, their performance depends upon many factors, including shading conditions, temperature, irradiance, and the angle of inclination, which can bring a photovoltaic or solar system into a PS or CPS condition. In these conditions, many power peaks appear, and it is hard to find the global peak among many local peaks. The ability to track the maximum power peak and maintain it to avoid fluctuations depends on the maximum power point tracking (MPPT) technique used in a photovoltaic system. This article is based on the implementation of a hybrid algorithm, combining Harris hawk’s optimization (HHO), a new technique which is based on natural inspiration, and a conventional perturb and observe (P&O) technique. The hybrid technique was tested under different weather conditions in MATLAB Simulink and showed less computational time, a fast convergence speed, and zero oscillations after reaching a power point’s maximum limit. A performance comparison of the hybrid technique was made with bio-inspired particle swarm optimization (PSO), adaptive cuckoo search optimization (ACS), the dragonfly algorithm (DFO), and the water cycle algorithm (WCA). The hybrid technique achieves 99.8% efficiency on average and performs very well among the rest of the competing techniques.

Suggested Citation

  • Muhammad Annas Hafeez & Ahmer Naeem & Muhammad Akram & Muhammad Yaqoob Javed & Aamer Bilal Asghar & Yong Wang, 2022. "A Novel Hybrid MPPT Technique Based on Harris Hawk Optimization (HHO) and Perturb and Observer (P&O) under Partial and Complex Partial Shading Conditions," Energies, MDPI, vol. 15(15), pages 1-18, July.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:15:p:5550-:d:876537
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    References listed on IDEAS

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    1. Tingting Pei & Xiaohong Hao & Qun Gu, 2018. "A Novel Global Maximum Power Point Tracking Strategy Based on Modified Flower Pollination Algorithm for Photovoltaic Systems under Non-Uniform Irradiation and Temperature Conditions," Energies, MDPI, vol. 11(10), pages 1-16, October.
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    Cited by:

    1. Doaa Khodair & Saad Motahhir & Hazem H. Mostafa & Ahmed Shaker & Hossam Abd El Munim & Mohamed Abouelatta & Ahmed Saeed, 2023. "Modeling and Simulation of Modified MPPT Techniques under Varying Operating Climatic Conditions," Energies, MDPI, vol. 16(1), pages 1-20, January.
    2. 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.
    3. Waleed Al Abri & Rashid Al Abri & Hassan Yousef & Amer Al-Hinai, 2022. "A Maximum Power Point Tracker Using the Bald Eagle Search Technique for Grid-Connected Photovoltaic Systems," Energies, MDPI, vol. 15(23), pages 1-16, December.
    4. Bilal Naji Alhasnawi & Basil H. Jasim & Arshad Naji Alhasnawi & Bishoy E. Sedhom & Ali M. Jasim & Azam Khalili & Vladimír Bureš & Alessandro Burgio & Pierluigi Siano, 2022. "A Novel Approach to Achieve MPPT for Photovoltaic System Based SCADA," Energies, MDPI, vol. 15(22), pages 1-29, November.

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