IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i5p2870-d761962.html
   My bibliography  Save this article

Decreasing the Battery Recharge Time if Using a Fuzzy Based Power Management Loop for an Isolated Micro-Grid Farm

Author

Listed:
  • Habib Kraiem

    (Department of Electrical Engineering, College of Engineering, Northern Border University, Arar 73222, Saudi Arabia)

  • Aymen Flah

    (Processes, Energy, Environment and Electrical Systems (Code: LR18ES34), National Engineering School of Gabès, University of Gabès, Gabès 6072, Tunisia)

  • Naoui Mohamed

    (Processes, Energy, Environment and Electrical Systems (Code: LR18ES34), National Engineering School of Gabès, University of Gabès, Gabès 6072, Tunisia)

  • Mohamed H. B. Messaoud

    (Processes, Energy, Environment and Electrical Systems (Code: LR18ES34), National Engineering School of Gabès, University of Gabès, Gabès 6072, Tunisia)

  • Essam A. Al-Ammar

    (Department of Electrical Engineering, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia)

  • Ahmed Althobaiti

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

  • Abdullah Alhumaidi Alotaibi

    (Department of Science and Technology, College of Ranyah, Taif University, Taif 21944, Saudi Arabia)

  • Michał Jasiński

    (Faculty of Electrical Engineering, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland)

  • Vishnu Suresh

    (Faculty of Electrical Engineering, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland)

  • Zbigniew Leonowicz

    (Faculty of Electrical Engineering, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland)

  • Elżbieta Jasińska

    (Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland)

Abstract

An isolated micro-grid has different requirements from the traditional power grids. Several energy sources may be linked for the purpose of sharing load demand without being linked to the grid. The isolated micro-grid is made up of at least one energy generator, an energy storage system, and a load portion. Because there are several energy sources and a range of models, the power flow must be managed to ensure the safety of all hardware. Monitoring the flow of power from multiple energy sources necessitates adherence to many parameters and other requirements. As a result, the goal of this work is to identify a worthwhile solution for providing the appropriate portions with the necessary power while also obtaining the necessary energy from other sources. The approach is based on the fuzzy logic controller, which is an intelligent technology. This regulator is used in an efficient process that tries to control all of the equipment in the isolated micro-grid under investigation. The MATLAB/Simulink platform is employed for simulating this proposed system, and then, the depicted results were discussed and compared. Showing the traditional relay control, the standard PI regulator, and a neural control combination process, the achieved results prove that it is possible to reduce the battery recharge time to half; if the proposed fuzzy controller is used. Then, the established controller specifications have been used for evaluating the energy performances of the hybrid energy system under a real case situation in a specific location in the world. Consequently, the obtained results prove that this proposal power management system will be largely beneficial for such energy storage applications and an energy yield can be assured during all climatic conditions and specifications.

Suggested Citation

  • Habib Kraiem & Aymen Flah & Naoui Mohamed & Mohamed H. B. Messaoud & Essam A. Al-Ammar & Ahmed Althobaiti & Abdullah Alhumaidi Alotaibi & Michał Jasiński & Vishnu Suresh & Zbigniew Leonowicz & Elżbiet, 2022. "Decreasing the Battery Recharge Time if Using a Fuzzy Based Power Management Loop for an Isolated Micro-Grid Farm," Sustainability, MDPI, vol. 14(5), pages 1-21, March.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:5:p:2870-:d:761962
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/5/2870/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/5/2870/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Reshma Gopi, R. & Sreejith, S., 2018. "Converter topologies in photovoltaic applications – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 1-14.
    2. Hossein Moayedi & Amir Mosavi, 2021. "Double-Target Based Neural Networks in Predicting Energy Consumption in Residential Buildings," Energies, MDPI, vol. 14(5), pages 1-25, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sajjad Miran & Muhammad Tamoor & Tayybah Kiren & Faakhar Raza & Muhammad Imtiaz Hussain & Jun-Tae Kim, 2022. "Optimization of Standalone Photovoltaic Drip Irrigation System: A Simulation Study," Sustainability, MDPI, vol. 14(14), pages 1-20, July.
    2. Abdallah El Zerk & Mohammed Ouassaid, 2023. "Real-Time Fuzzy Logic Based Energy Management System for Microgrid Using Hardware in the Loop," Energies, MDPI, vol. 16(5), pages 1-21, February.
    3. Muhammad Majid Gulzar, 2023. "Maximum Power Point Tracking of a Grid Connected PV Based Fuel Cell System Using Optimal Control Technique," Sustainability, MDPI, vol. 15(5), pages 1-18, February.
    4. Michał Jasiński & Arsalan Najafi & Tomasz Sikorski & Paweł Kostyła & Jacek Rezmer, 2022. "Operation of an Energy Storage System Integrated with a Photovoltaic System and an Industrial Customer under Different Real and Pseudo-Real Profiles," Energies, MDPI, vol. 15(21), pages 1-27, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Weng-Hooi Tan & Junita Mohamad-Saleh, 2023. "Critical Review on Interrelationship of Electro-Devices in PV Solar Systems with Their Evolution and Future Prospects for MPPT Applications," Energies, MDPI, vol. 16(2), pages 1-37, January.
    2. Md Ohirul Qays & Yonis Buswig & Md Liton Hossain & Ahmed Abu-Siada, 2020. "Active Charge Balancing Strategy Using the State of Charge Estimation Technique for a PV-Battery Hybrid System," Energies, MDPI, vol. 13(13), pages 1-16, July.
    3. Reza Alayi & Mahdi Mohkam & Seyed Reza Seyednouri & Mohammad Hossein Ahmadi & Mohsen Sharifpur, 2021. "Energy/Economic Analysis and Optimization of On-Grid Photovoltaic System Using CPSO Algorithm," Sustainability, MDPI, vol. 13(22), pages 1-16, November.
    4. Guohong Lai & Guoping Zhang & Shaowu Li, 2024. "An MPPT Control Strategy Based on Current Constraint Relationships for a Photovoltaic System with a Battery or Supercapacitor," Energies, MDPI, vol. 17(16), pages 1-31, August.
    5. Julio López Seguel & Seleme I. Seleme & Lenin M. F. Morais, 2022. "Comparative Study of Buck-Boost, SEPIC, Cuk and Zeta DC-DC Converters Using Different MPPT Methods for Photovoltaic Applications," Energies, MDPI, vol. 15(21), pages 1-26, October.
    6. Michał Jasiński & Arsalan Najafi & Tomasz Sikorski & Paweł Kostyła & Jacek Rezmer, 2022. "Operation of an Energy Storage System Integrated with a Photovoltaic System and an Industrial Customer under Different Real and Pseudo-Real Profiles," Energies, MDPI, vol. 15(21), pages 1-27, November.
    7. Yang, Yiran & Li, Gang & Luo, Tao & Al-Bahrani, Mohammed & Al-Ammar, Essam A. & Sillanpaa, Mika & Ali, Shafaqat & Leng, Xiujuan, 2023. "The innovative optimization techniques for forecasting the energy consumption of buildings using the shuffled frog leaping algorithm and different neural networks," Energy, Elsevier, vol. 268(C).
    8. Loke Kok Foong & Binh Nguyen Le, 2022. "Teaching–Learning–Based Optimization (TLBO) in Hybridized with Fuzzy Inference System Estimating Heating Loads," Energies, MDPI, vol. 15(21), pages 1-20, November.
    9. Shaowu Li, 2021. "Circuit Parameter Range of Photovoltaic System to Correctly Use the MPP Linear Model of Photovoltaic Cell," Energies, MDPI, vol. 14(13), pages 1-27, July.
    10. Shaik Nyamathulla & Dhanamjayulu Chittathuru, 2023. "A Review of Multilevel Inverter Topologies for Grid-Connected Sustainable Solar Photovoltaic Systems," Sustainability, MDPI, vol. 15(18), pages 1-44, September.
    11. Ali Bughneda & Mohamed Salem & Anna Richelli & Dahaman Ishak & Salah Alatai, 2021. "Review of Multilevel Inverters for PV Energy System Applications," Energies, MDPI, vol. 14(6), pages 1-23, March.
    12. Shaowu Li & Kunyi Chen & Qin Li & Qing Ai, 2022. "A Variable-Weather-Parameter MPPT Method Based on Equation Solution for Photovoltaic System with DC Bus," Energies, MDPI, vol. 15(18), pages 1-25, September.
    13. 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.
    14. Hossein Gholizadeh & Reza Sharifi Shahrivar & Mir Reza Hashemi & Ebrahim Afjei & Saman A. Gorji, 2021. "Design and Implementation a Single-Switch Step-Up DC-DC Converter Based on Cascaded Boost and Luo Converters," Energies, MDPI, vol. 14(12), pages 1-18, June.
    15. Hossein Gholizadeh & Saman A. Gorji & Ebrahim Afjei & Dezso Sera, 2021. "Design and Implementation of a New Cuk-Based Step-Up DC–DC Converter," Energies, MDPI, vol. 14(21), pages 1-18, October.
    16. Hossein Moayedi & Bao Le Van, 2022. "Feasibility of Harris Hawks Optimization in Combination with Fuzzy Inference System Predicting Heating Load Energy Inside Buildings," Energies, MDPI, vol. 15(23), pages 1-17, December.
    17. Qingpeng Cao & Moses Olabhele Esangbedo & Sijun Bai & Caroline Olufunke Esangbedo, 2019. "Grey SWARA-FUCOM Weighting Method for Contractor Selection MCDM Problem: A Case Study of Floating Solar Panel Energy System Installation," Energies, MDPI, vol. 12(13), pages 1-30, June.
    18. Jianwen Cao & Bizhong Xia & Jie Zhou, 2021. "An Active Equalization Method for Lithium-ion Batteries Based on Flyback Transformer and Variable Step Size Generalized Predictive Control," Energies, MDPI, vol. 14(1), pages 1-25, January.
    19. Hou, D. & Evins, R., 2024. "A protocol for developing and evaluating neural network-based surrogate models and its application to building energy prediction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 193(C).
    20. Yunho Kim & Yunha Park & Hyuncheol Seo & Jungha Hwang, 2023. "Load Prediction Algorithm Applied with Indoor Environment Sensing in University Buildings," Energies, MDPI, vol. 16(2), pages 1-14, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:5:p:2870-:d:761962. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.