IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i12p2949-d1415323.html
   My bibliography  Save this article

Intelligent Type-2 Fuzzy Logic Controller for Hybrid Microgrid Energy Management with Different Modes of EVs Integration

Author

Listed:
  • Tawfiq Aljohani

    (Department of Electrical Engineering, College of Engineering at Yanbu, Taibah University, Yanbu 41911, Saudi Arabia)

Abstract

The rapid integration of renewable energy sources (RES) and the electrification of transportation have significantly transformed modern energy infrastructures, emphasizing the need for efficient and flexible energy management systems. This study presents an intelligent, variable-fed, Type-2 Fuzzy Logic Controller (IT2FLC) designed for optimal management of Hybrid Microgrid (HMG) energy systems, specifically considering different modes of Electric Vehicles (EVs) integration. The necessity of this study arises from the challenges posed by fluctuating renewable energy outputs and the uncoordinated charging practices of EVs, which can lead to grid instability and increased operational costs. The proposed IT2FLC is based on comprehensive mathematical modeling that captures complex interactions among HMG components, including Doubly Fed Induction Generator (DFIG) units, photovoltaic (PV) systems, utility AC power, and EV batteries. Utilizing a yearly dataset for simulation, this work examines the HMG’s flexibility and adaptability under dynamic conditions managed by the proposed intelligent controller. A Simulink-based model is built for this study to replicate the dynamical operation of the HMG and test the precise and real-time decision-making capability of the proposed IT2FLC. The results demonstrate the IT2FLC’s superior performance, achieving a substantial cost avoidance of nearly $3,750,000 and efficient energy balance, affirming its potential to sustain optimal energy utilization under stochastic conditions. Additionally, the results attest that the proposed IT2FLC significantly enhances the resilience and economic feasibility of hybrid microgrids, achieving a balanced energy exchange with the utility grid and efficient utilization of EV batteries, proving to be a superior solution for optimal operation of hybrid grids.

Suggested Citation

  • Tawfiq Aljohani, 2024. "Intelligent Type-2 Fuzzy Logic Controller for Hybrid Microgrid Energy Management with Different Modes of EVs Integration," Energies, MDPI, vol. 17(12), pages 1-26, June.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:12:p:2949-:d:1415323
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/12/2949/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/17/12/2949/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dominic Savio Abraham & Balaji Chandrasekar & Narayanamoorthi Rajamanickam & Pradeep Vishnuram & Venkatesan Ramakrishnan & Mohit Bajaj & Marian Piecha & Vojtech Blazek & Lukas Prokop, 2023. "Fuzzy-Based Efficient Control of DC Microgrid Configuration for PV-Energized EV Charging Station," Energies, MDPI, vol. 16(6), pages 1-17, March.
    2. Bhatti, Abdul Rauf & Salam, Zainal, 2018. "A rule-based energy management scheme for uninterrupted electric vehicles charging at constant price using photovoltaic-grid system," Renewable Energy, Elsevier, vol. 125(C), pages 384-400.
    3. Ramadoss Janarthanan & R. Uma Maheshwari & Prashant Kumar Shukla & Piyush Kumar Shukla & Seyedali Mirjalili & Manoj Kumar, 2021. "Intelligent Detection of the PV Faults Based on Artificial Neural Network and Type 2 Fuzzy Systems," Energies, MDPI, vol. 14(20), pages 1-19, October.
    Full references (including those not matched with items on IDEAS)

    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. Li, Shuangqi & Zhao, Pengfei & Gu, Chenghong & Huo, Da & Zeng, Xianwu & Pei, Xiaoze & Cheng, Shuang & Li, Jianwei, 2022. "Online battery-protective vehicle to grid behavior management," Energy, Elsevier, vol. 243(C).
    2. Muhammad Kashif Rafique & Zunaib Maqsood Haider & Khawaja Khalid Mehmood & Muhammad Saeed Uz Zaman & Muhammad Irfan & Saad Ullah Khan & Chul-Hwan Kim, 2018. "Optimal Scheduling of Hybrid Energy Resources for a Smart Home," Energies, MDPI, vol. 11(11), pages 1-19, November.
    3. Asaad Mohammad & Ramon Zamora & Tek Tjing Lie, 2020. "Integration of Electric Vehicles in the Distribution Network: A Review of PV Based Electric Vehicle Modelling," Energies, MDPI, vol. 13(17), pages 1-20, September.
    4. Ren, Haoshan & Ma, Zhenjun & Fai Norman Tse, Chung & Sun, Yongjun, 2022. "Optimal control of solar-powered electric bus networks with improved renewable energy on-site consumption and reduced grid dependence," Applied Energy, Elsevier, vol. 323(C).
    5. Jiao, Feixiang & Zou, Yuan & Zhang, Xudong & Zhang, Bin, 2022. "Online optimal dispatch based on combined robust and stochastic model predictive control for a microgrid including EV charging station," Energy, Elsevier, vol. 247(C).
    6. Zou, Wenke & Sun, Yongjun & Gao, Dian-ce & Zhang, Xu & Liu, Junyao, 2023. "A review on integration of surging plug-in electric vehicles charging in energy-flexible buildings: Impacts analysis, collaborative management technologies, and future perspective," Applied Energy, Elsevier, vol. 331(C).
    7. Aree Wangsupphaphol & Surachai Chaitusaney, 2022. "Subsidizing Residential Low Priority Smart Charging: A Power Management Strategy for Electric Vehicle in Thailand," Sustainability, MDPI, vol. 14(10), pages 1-15, May.
    8. Beaufils, Timothé & Pineau, Pierre-Olivier, 2019. "Assessing the impact of residential load profile changes on electricity distribution utility revenues under alternative rate structures," Utilities Policy, Elsevier, vol. 61(C).
    9. Alzahrani, Ahmad & Sajjad, Khizar & Hafeez, Ghulam & Murawwat, Sadia & Khan, Sheraz & Khan, Farrukh Aslam, 2023. "Real-time energy optimization and scheduling of buildings integrated with renewable microgrid," Applied Energy, Elsevier, vol. 335(C).
    10. Rücker, Fabian & Schoeneberger, Ilka & Wilmschen, Till & Sperling, Dustin & Haberschusz, David & Figgener, Jan & Sauer, Dirk Uwe, 2022. "Self-sufficiency and charger constraints of prosumer households with vehicle-to-home strategies," Applied Energy, Elsevier, vol. 317(C).
    11. Ramzi Saidi & Jean-Christophe Olivier & Mohamed Machmoum & Eric Chauveau, 2021. "Cascaded Centered Moving Average Filters for Energy Management in Multisource Power Systems with a Large Number of Devices," Energies, MDPI, vol. 14(12), pages 1-21, June.
    12. Vamsi Krishna Reddy, Aala Kalananda & Venkata Lakshmi Narayana, Komanapalli, 2022. "Meta-heuristics optimization in electric vehicles -an extensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    13. Kameswara Satya Prakash Oruganti & Chockalingam Aravind Vaithilingam & Gowthamraj Rajendran & Ramasamy A, 2019. "Design and Sizing of Mobile Solar Photovoltaic Power Plant to Support Rapid Charging for Electric Vehicles," Energies, MDPI, vol. 12(18), pages 1-22, September.
    14. Konara, K.M.S.Y. & Kolhe, Mohan & Sharma, Arvind, 2020. "Power flow management controller within a grid connected photovoltaic based active generator as a finite state machine using hierarchical approach with droop characteristics," Renewable Energy, Elsevier, vol. 155(C), pages 1021-1031.
    15. Udeh, Godfrey T. & Michailos, Stavros & Ingham, Derek & Hughes, Kevin J. & Ma, Lin & Pourkashanian, Mohamed, 2022. "A modified rule-based energy management scheme for optimal operation of a hybrid PV-wind-Stirling engine integrated multi-carrier energy system," Applied Energy, Elsevier, vol. 312(C).
    16. Sun, Chu & Ali, Syed Qaseem & Joos, Geza & Paquin, Jean-Nicolas & Montenegro, Juan Felipe Patarroyo, 2023. "Design and CHIL testing of microgrid controller with general rule-based dispatch," Applied Energy, Elsevier, vol. 345(C).
    17. Bhuiyan, Erphan A. & Hossain, Md. Zahid & Muyeen, S.M. & Fahim, Shahriar Rahman & Sarker, Subrata K. & Das, Sajal K., 2021. "Towards next generation virtual power plant: Technology review and frameworks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    18. Benamar Bouyeddou & Fouzi Harrou & Bilal Taghezouit & Ying Sun & Amar Hadj Arab, 2022. "Improved Semi-Supervised Data-Mining-Based Schemes for Fault Detection in a Grid-Connected Photovoltaic System," Energies, MDPI, vol. 15(21), pages 1-22, October.
    19. Chao-Tsung Ma, 2019. "System Planning of Grid-Connected Electric Vehicle Charging Stations and Key Technologies: A Review," Energies, MDPI, vol. 12(21), pages 1-22, November.
    20. Matej Tkac & Martina Kajanova & Peter Bracinik, 2023. "A Review of Advanced Control Strategies of Microgrids with Charging Stations," Energies, MDPI, vol. 16(18), pages 1-25, September.

    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:jeners:v:17:y:2024:i:12:p:2949-:d:1415323. 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.