IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v319y2022ics030626192200592x.html
   My bibliography  Save this article

Power flow management of hybrid system in smart grid requirements using ITSA-MOAT approach

Author

Listed:
  • Logeswaran, T.
  • Senthil Raja, M.
  • Beevi Sahul Hameed, Jennathu
  • Abdulrahim, Mahabuba

Abstract

A power flow management (PFM) concept of Photovoltaic/Fuel Cell/Battery/Super capacitor in smart grid (SG) system is proposed in this paper. The proposed system controls the photovoltaic (PV) system, battery storage, fuel cell (FC) and super capacitor (SC). The proposed control system is the combination of Improved Tunicate Swarm Optimization (ITSA) and Multi Objective Artificial Tree (MOAT), hence it is called ITSA-MOAT method. Here, ITSA is building up the control pulses of the inverter using the energy exchange assortment between the source and load side. Here, the composition of multi-objective function is considered according to the obtainable source power and several specified grid produced by the active power and reactive power. To acquire the online control pulses, MOAT is utilized based on the variants of power. Moreover, the global state of charge (SoC) of energy storages and load demand are considered. The ITSA-MOAT method is implemented in MATLAB/Simulink platform. By then, the experimental results of the proposed method are analyzed with the existing methods.

Suggested Citation

  • Logeswaran, T. & Senthil Raja, M. & Beevi Sahul Hameed, Jennathu & Abdulrahim, Mahabuba, 2022. "Power flow management of hybrid system in smart grid requirements using ITSA-MOAT approach," Applied Energy, Elsevier, vol. 319(C).
  • Handle: RePEc:eee:appene:v:319:y:2022:i:c:s030626192200592x
    DOI: 10.1016/j.apenergy.2022.119228
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S030626192200592X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2022.119228?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Chang Ye & Shihong Miao & Qi Lei & Yaowang Li, 2016. "Dynamic Energy Management of Hybrid Energy Storage Systems with a Hierarchical Structure," Energies, MDPI, vol. 9(6), pages 1-15, May.
    2. Jacob, Ammu Susanna & Banerjee, Rangan & Ghosh, Prakash C., 2018. "Sizing of hybrid energy storage system for a PV based microgrid through design space approach," Applied Energy, Elsevier, vol. 212(C), pages 640-653.
    3. Alessandro Serpi & Mario Porru & Alfonso Damiano, 2017. "An Optimal Power and Energy Management by Hybrid Energy Storage Systems in Microgrids," Energies, MDPI, vol. 10(11), pages 1-21, November.
    4. Nge, Chee Lim & Ranaweera, Iromi U. & Midtgård, Ole-Morten & Norum, Lars, 2019. "A real-time energy management system for smart grid integrated photovoltaic generation with battery storage," Renewable Energy, Elsevier, vol. 130(C), pages 774-785.
    5. Muruganantham, B. & Gnanadass, R. & Padhy, N.P., 2017. "Challenges with renewable energy sources and storage in practical distribution systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 125-134.
    6. Aktas, Ahmet & Erhan, Koray & Özdemir, Sule & Özdemir, Engin, 2018. "Dynamic energy management for photovoltaic power system including hybrid energy storage in smart grid applications," Energy, Elsevier, vol. 162(C), pages 72-82.
    7. Chong, Lee Wai & Wong, Yee Wan & Rajkumar, Rajprasad Kumar & Rajkumar, Rajpartiban Kumar & Isa, Dino, 2016. "Hybrid energy storage systems and control strategies for stand-alone renewable energy power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 174-189.
    8. Mohagheghi, Erfan & Gabash, Aouss & Alramlawi, Mansour & Li, Pu, 2018. "Real-time optimal power flow with reactive power dispatch of wind stations using a reconciliation algorithm," Renewable Energy, Elsevier, vol. 126(C), pages 509-523.
    9. Alipour, Manijeh & Zare, Kazem & Seyedi, Heresh, 2018. "A multi-follower bilevel stochastic programming approach for energy management of combined heat and power micro-grids," Energy, Elsevier, vol. 149(C), pages 135-146.
    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. Jeyaraj, Thavamani & Ponnusamy, Arul & Selvaraj, Dhamodharan, 2025. "Hybrid renewable energy systems stability analysis through future advancement technique: A review," Applied Energy, Elsevier, vol. 383(C).

    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. Aktas, Ahmet & Erhan, Koray & Özdemir, Sule & Özdemir, Engin, 2018. "Dynamic energy management for photovoltaic power system including hybrid energy storage in smart grid applications," Energy, Elsevier, vol. 162(C), pages 72-82.
    2. Jessica C. A. Sousa & Thiago M. Soares & Jonathan M. Tabora & Hugo G. Lott, 2025. "Design of a Controller for Supercapacitor’s Bidirectional High-Gain Interleaved Converter," Energies, MDPI, vol. 18(10), pages 1-26, May.
    3. Jiang, Yinghua & Kang, Lixia & Liu, Yongzhong, 2019. "A unified model to optimize configuration of battery energy storage systems with multiple types of batteries," Energy, Elsevier, vol. 176(C), pages 552-560.
    4. Luta, Doudou N. & Raji, Atanda K., 2019. "Optimal sizing of hybrid fuel cell-supercapacitor storage system for off-grid renewable applications," Energy, Elsevier, vol. 166(C), pages 530-540.
    5. Al Essa, Mohammed Jasim M., 2019. "Home energy management of thermostatically controlled loads and photovoltaic-battery systems," Energy, Elsevier, vol. 176(C), pages 742-752.
    6. Pablo Gabriel Rullo & Ramon Costa-Castelló & Vicente Roda & Diego Feroldi, 2018. "Energy Management Strategy for a Bioethanol Isolated Hybrid System: Simulations and Experiments," Energies, MDPI, vol. 11(6), pages 1-25, May.
    7. Masaki, Mukalu Sandro & Zhang, Lijun & Xia, Xiaohua, 2019. "A hierarchical predictive control for supercapacitor-retrofitted grid-connected hybrid renewable systems," Applied Energy, Elsevier, vol. 242(C), pages 393-402.
    8. Pan Wu & Wentao Huang & Nengling Tai & Zhoujun Ma & Xiaodong Zheng & Yong Zhang, 2019. "A Multi-Layer Coordinated Control Scheme to Improve the Operation Friendliness of Grid-Connected Multiple Microgrids," Energies, MDPI, vol. 12(2), pages 1-21, January.
    9. He, Yi & Guo, Su & Dong, Peixin & Wang, Chen & Huang, Jing & Zhou, Jianxu, 2022. "Techno-economic comparison of different hybrid energy storage systems for off-grid renewable energy applications based on a novel probabilistic reliability index," Applied Energy, Elsevier, vol. 328(C).
    10. He, Yi & Guo, Su & Zhou, Jianxu & Song, Guotao & Kurban, Aynur & Wang, Haowei, 2022. "The multi-stage framework for optimal sizing and operation of hybrid electrical-thermal energy storage system," Energy, Elsevier, vol. 245(C).
    11. Nyong-Bassey, Bassey Etim & Giaouris, Damian & Patsios, Charalampos & Papadopoulou, Simira & Papadopoulos, Athanasios I. & Walker, Sara & Voutetakis, Spyros & Seferlis, Panos & Gadoue, Shady, 2020. "Reinforcement learning based adaptive power pinch analysis for energy management of stand-alone hybrid energy storage systems considering uncertainty," Energy, Elsevier, vol. 193(C).
    12. Banguero, Edison & Correcher, Antonio & Pérez-Navarro, Ángel & García, Emilio & Aristizabal, Andrés, 2020. "Diagnosis of a battery energy storage system based on principal component analysis," Renewable Energy, Elsevier, vol. 146(C), pages 2438-2449.
    13. Xu, Xiao & Hu, Weihao & Cao, Di & Liu, Wen & Huang, Qi & Hu, Yanting & Chen, Zhe, 2021. "Enhanced design of an offgrid PV-battery-methanation hybrid energy system for power/gas supply," Renewable Energy, Elsevier, vol. 167(C), pages 440-456.
    14. Mohamed Ali Zdiri & Tawfik Guesmi & Badr M. Alshammari & Khalid Alqunun & Abdulaziz Almalaq & Fatma Ben Salem & Hsan Hadj Abdallah & Ahmed Toumi, 2022. "Design and Analysis of Sliding-Mode Artificial Neural Network Control Strategy for Hybrid PV-Battery-Supercapacitor System," Energies, MDPI, vol. 15(11), pages 1-20, June.
    15. Erfan Mohagheghi & Mansour Alramlawi & Aouss Gabash & Pu Li, 2018. "A Survey of Real-Time Optimal Power Flow," Energies, MDPI, vol. 11(11), pages 1-20, November.
    16. Jingpeng Yue & Zhijian Hu & Amjad Anvari-Moghaddam & Josep M. Guerrero, 2019. "A Multi-Market-Driven Approach to Energy Scheduling of Smart Microgrids in Distribution Networks," Sustainability, MDPI, vol. 11(2), pages 1-16, January.
    17. Lan, Penghang & Chen, She & Li, Qihang & Li, Kelin & Wang, Feng & Zhao, Yaoxun, 2024. "Intelligent hydrogen-ammonia combined energy storage system with deep reinforcement learning," Renewable Energy, Elsevier, vol. 237(PB).
    18. Pereira, Géssica Michelle dos Santos & Weigert, Gabriela Rosalee & Macedo, Pablo Lopes & Silva, Kiane Alves e & Segura Salas, Cresencio Silvio & Gonçalves, Antônio Maurício de Matos & Nascimento, Hebe, 2022. "Quasi-dynamic operation and maintenance plan for photovoltaic systems in remote areas: The framework of Pantanal-MS," Renewable Energy, Elsevier, vol. 181(C), pages 404-416.
    19. Günther, Sebastian & Bensmann, Astrid & Hanke-Rauschenbach, Richard, 2025. "Representative energy management strategies for hybrid energy storage systems derived from a meta-review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 216(C).
    20. Liu, Jia & Chen, Xi & Yang, Hongxing & Li, Yutong, 2020. "Energy storage and management system design optimization for a photovoltaic integrated low-energy building," Energy, Elsevier, vol. 190(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:eee:appene:v:319:y:2022:i:c:s030626192200592x. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.