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Optimized Power Management Approach for Photovoltaic Systems with Hybrid Battery-Supercapacitor Storage

Author

Listed:
  • Djamila Rekioua

    (Laboratoire LTII, Université de Bejaia, Bejaia 06000, Algeria)

  • Khoudir Kakouche

    (Laboratoire LTII, Université de Bejaia, Bejaia 06000, Algeria)

  • Abdulrahman Babqi

    (Department of Electrical Engineering, College of Engineering, Taif University, Taif 21944, Saudi Arabia)

  • Zahra Mokrani

    (Laboratoire LTII, Université de Bejaia, Bejaia 06000, Algeria)

  • Adel Oubelaid

    (Laboratoire LTII, Université de Bejaia, Bejaia 06000, Algeria)

  • Toufik Rekioua

    (Laboratoire LTII, Université de Bejaia, Bejaia 06000, Algeria)

  • Abdelghani Azil

    (Laboratoire LTII, Université de Bejaia, Bejaia 06000, Algeria)

  • Enas Ali

    (Faculty of Engineering and Technology, Future University in Egypt, New Cairo 11835, Egypt)

  • Ali H. Kasem Alaboudy

    (Electrical Department, Faculty of Technology and Education, Suez University, Suez 43533, Egypt)

  • Saad A. Mohamed Abdelwahab

    (Electrical Department, Faculty of Technology and Education, Suez University, Suez 43533, Egypt)

Abstract

The paper addresses the ongoing and continuous interest in photovoltaic energy systems (PESs). In this context, the study focuses on an isolated photovoltaic system with hybrid battery-supercapacitor storage (HBSS). The integration of supercapacitors (SCs) in this system is particularly important because of their high specific power density. In photovoltaic (PV) systems, multi-storage systems use two or more energy storage technologies to enhance system performance and flexibility. When batteries and supercapacitors are combined in a PV system, their benefits are maximized and offer a more reliable, efficient, cost-effective energy storage option. In addition, effective multi-storage power management in a PV system needs a solid grasp of the energy storage technologies, load power demand profiles, and the whole system architecture. This work establishes a battery-supercapacitor storage system (HBSS) by combining batteries and supercapacitors. The primary objective is to devise a novel management algorithm that effectively controls the different power sources. The algorithm is designed to manage the charge and discharge cycles of the hybrid battery-supercapacitor energy storage system (HBSS), thereby guaranteeing that the state of charge (SOC) for both batteries and supercapacitors is maintained within the specified range. The proposed management algorithm is designed to be simple, efficient, and light on computational resources. It efficiently handles the energy flow within the HBSS, optimizing the usage of both batteries and supercapacitors based on real-time conditions and energy demands. The proposed method ensures their longevity and maximizes their performance by maintaining the SOC of these energy storage components within the specified limits. Simulation results obtained from applying the management strategy are found to be satisfactory. These results show that the proposed algorithm maintains the SOC of batteries and supercapacitors within the desired range, leading to improved energy management and enhanced system efficiency.

Suggested Citation

  • Djamila Rekioua & Khoudir Kakouche & Abdulrahman Babqi & Zahra Mokrani & Adel Oubelaid & Toufik Rekioua & Abdelghani Azil & Enas Ali & Ali H. Kasem Alaboudy & Saad A. Mohamed Abdelwahab, 2023. "Optimized Power Management Approach for Photovoltaic Systems with Hybrid Battery-Supercapacitor Storage," Sustainability, MDPI, vol. 15(19), pages 1-30, September.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:19:p:14066-:d:1245662
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    References listed on IDEAS

    as
    1. Diana Lemian & Florin Bode, 2022. "Battery-Supercapacitor Energy Storage Systems for Electrical Vehicles: A Review," Energies, MDPI, vol. 15(15), pages 1-13, August.
    2. Maria I. S. Guerra & Fábio M. Ugulino de Araújo & Mahmoud Dhimish & Romênia G. Vieira, 2021. "Assessing Maximum Power Point Tracking Intelligent Techniques on a PV System with a Buck–Boost Converter," Energies, MDPI, vol. 14(22), pages 1-21, November.
    3. Robyns, Benoît & Davigny, Arnaud & Saudemont, Christophe, 2013. "Methodologies for supervision of Hybrid Energy Sources based on Storage Systems – A survey," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 91(C), pages 52-71.
    4. Zhang, Lei & Hu, Xiaosong & Wang, Zhenpo & Sun, Fengchun & Dorrell, David G., 2018. "A review of supercapacitor modeling, estimation, and applications: A control/management perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 1868-1878.
    5. Khaizaran Abdulhussein Al Sumarmad & Nasri Sulaiman & Noor Izzri Abdul Wahab & Hashim Hizam, 2022. "Microgrid Energy Management System Based on Fuzzy Logic and Monitoring Platform for Data Analysis," Energies, MDPI, vol. 15(11), pages 1-19, June.
    6. Noah Lee & Chen Hon Nee & Seong Shan Yap & Kwong Keong Tham & Ah Heng You & Seong Ling Yap & Abdul Kariem Bin Mohd Arof, 2022. "Capacity Sizing of Embedded Control Battery–Supercapacitor Hybrid Energy Storage System," Energies, MDPI, vol. 15(10), pages 1-14, May.
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    Cited by:

    1. Wenhui Zhao & Rong Li & Shuan Zhu, 2024. "Subsidy Policies and Economic Analysis of Photovoltaic Energy Storage Integration in China," Energies, MDPI, vol. 17(10), pages 1-26, May.

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