IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i20p7689-d945983.html
   My bibliography  Save this article

Energy Management System for Grid-Connected Nanogrid during COVID-19

Author

Listed:
  • Saif Jamal

    (Department of Electrical and Electronics Engineering, College of Engineering, Universiti Tenaga Nasional, Kajang 43000, Selangor, Malaysia)

  • Jagadeesh Pasupuleti

    (Institute of Sustainable Energy, Universiti Tenaga Nasional, Kajang 43000, Selangor, Malaysia)

  • Nur Azzammudin Rahmat

    (Department of Electrical Power Engineering, Universiti Tenaga National, Kajang 43000, Selangor, Malaysia)

  • Nadia M. L. Tan

    (Key Laboratory of More Electric Aircraft Technology of Zhejiang Province, University of Nottingham Ningbo China, Ningbo 315100, China)

Abstract

An effective energy management system (EMS) was designed based on the Stateflow (SF) approach for a grid-connected nanogrid (NG) composed of a photovoltaic (PV) array with a battery bank and supercapacitor (SC) energy storage system (ESS). The PV energy system, battery bank and SC (ESS), dual active bridge DC/DC converters, DC/AC inverters, control algorithms, and controllers were developed to test the operation of the NG. The average and high-frequency power components are separated using frequency division of the ESS power utilizing a low-pass filter; the average power is absorbed by the battery bank, while the high-frequency power is absorbed by the SC. The aim of this paper is to design an EMS to manage the energy of a grid-connected NG system considering the availability of the PV array, ESS, and demand requirements. Different scenarios of operation were tested to check the EMS behaviour during the day with a random demand profile, including: (1) a PV array with the grid supplying the load without an EMS; (2) a PV array, batteries, and the grid supplying the load with an EMS; (3) a PV array, batteries, an SC, and the grid supplying the load with an EMS; (4) a PV array, batteries, an SC, and the grid supplying the load with an EMS, with load profile reduction by 20% due to COVID-19. As per the simulation results, the proposed EMS enables the flow of power in the NG system and demonstrates the impact on the ESS by minimising carbon emissions via a reduction in grid consumption. Furthermore, the SF method is regarded as a helpful alternative to popular design approaches employing conventional software tools.

Suggested Citation

  • Saif Jamal & Jagadeesh Pasupuleti & Nur Azzammudin Rahmat & Nadia M. L. Tan, 2022. "Energy Management System for Grid-Connected Nanogrid during COVID-19," Energies, MDPI, vol. 15(20), pages 1-20, October.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:20:p:7689-:d:945983
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/20/7689/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/20/7689/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Elkin Edilberto Henao-Bravo & Carlos Andrés Ramos-Paja & Andrés Julián Saavedra-Montes & Daniel González-Montoya & Julián Sierra-Pérez, 2020. "Design Method of Dual Active Bridge Converters for Photovoltaic Systems with High Voltage Gain," Energies, MDPI, vol. 13(7), pages 1-31, April.
    2. Zakaria, A. & Ismail, Firas B. & Lipu, M.S. Hossain & Hannan, M.A., 2020. "Uncertainty models for stochastic optimization in renewable energy applications," Renewable Energy, Elsevier, vol. 145(C), pages 1543-1571.
    3. Roslan, M.F. & Hannan, M.A. & Jern Ker, Pin & Begum, R.A. & Indra Mahlia, TM & Dong, Z.Y., 2021. "Scheduling controller for microgrids energy management system using optimization algorithm in achieving cost saving and emission reduction," Applied Energy, Elsevier, vol. 292(C).
    4. Marvin Barivure Sigalo & Ajit C. Pillai & Saptarshi Das & Mohammad Abusara, 2021. "An Energy Management System for the Control of Battery Storage in a Grid-Connected Microgrid Using Mixed Integer Linear Programming," Energies, MDPI, vol. 14(19), pages 1-14, September.
    5. Sara J. Ríos & Daniel J. Pagano & Kevin E. Lucas, 2021. "Bidirectional Power Sharing for DC Microgrid Enabled by Dual Active Bridge DC-DC Converter," Energies, MDPI, vol. 14(2), pages 1-24, January.
    6. Saif Jamal & Nadia M. L. Tan & Jagadeesh Pasupuleti, 2021. "A Review of Energy Management and Power Management Systems for Microgrid and Nanogrid Applications," Sustainability, MDPI, vol. 13(18), pages 1-31, September.
    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. Michał Gocki & Agnieszka Jakubowska-Ciszek & Piotr Pruski, 2022. "Comparative Analysis of a New Class of Symmetric and Asymmetric Supercapacitors Constructed on the Basis of ITO Collectors," Energies, MDPI, vol. 16(1), pages 1-16, December.

    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. Rupesh Jha & Mattia Forato & Satya Prakash & Hemant Dashora & Giuseppe Buja, 2022. "An Analysis-Supported Design of a Single Active Bridge (SAB) Converter," Energies, MDPI, vol. 15(2), pages 1-22, January.
    2. Yin, Sihua & Yang, Haidong & Xu, Kangkang & Zhu, Chengjiu & Zhang, Shaqing & Liu, Guosheng, 2022. "Dynamic real–time abnormal energy consumption detection and energy efficiency optimization analysis considering uncertainty," Applied Energy, Elsevier, vol. 307(C).
    3. Silva, Ana R. & Pousinho, H.M.I. & Estanqueiro, Ana, 2022. "A multistage stochastic approach for the optimal bidding of variable renewable energy in the day-ahead, intraday and balancing markets," Energy, Elsevier, vol. 258(C).
    4. Lim, Juin Yau & Teng, Sin Yong & How, Bing Shen & Nam, KiJeon & Heo, SungKu & Máša, Vítězslav & Stehlík, Petr & Yoo, Chang Kyoo, 2022. "From microalgae to bioenergy: Identifying optimally integrated biorefinery pathways and harvest scheduling under uncertainties in predicted climate," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    5. Ali Dargahi & Khezr Sanjani & Morteza Nazari-Heris & Behnam Mohammadi-Ivatloo & Sajjad Tohidi & Mousa Marzband, 2020. "Scheduling of Air Conditioning and Thermal Energy Storage Systems Considering Demand Response Programs," Sustainability, MDPI, vol. 12(18), pages 1-13, September.
    6. Yan, Rujing & Wang, Jiangjiang & Wang, Jiahao & Tian, Lei & Tang, Saiqiu & Wang, Yuwei & Zhang, Jing & Cheng, Youliang & Li, Yuan, 2022. "A two-stage stochastic-robust optimization for a hybrid renewable energy CCHP system considering multiple scenario-interval uncertainties," Energy, Elsevier, vol. 247(C).
    7. Xiong, Kang & Hu, Weihao & Cao, Di & Li, Sichen & Zhang, Guozhou & Liu, Wen & Huang, Qi & Chen, Zhe, 2023. "Coordinated energy management strategy for multi-energy hub with thermo-electrochemical effect based power-to-ammonia: A multi-agent deep reinforcement learning enabled approach," Renewable Energy, Elsevier, vol. 214(C), pages 216-232.
    8. Silva, Jéssica Alice A. & López, Juan Camilo & Guzman, Cindy Paola & Arias, Nataly Bañol & Rider, Marcos J. & da Silva, Luiz C.P., 2023. "An IoT-based energy management system for AC microgrids with grid and security constraints," Applied Energy, Elsevier, vol. 337(C).
    9. Imed Khabbouchi & Dhaou Said & Aziz Oukaira & Idir Mellal & Lyes Khoukhi, 2023. "Machine Learning and Game-Theoretic Model for Advanced Wind Energy Management Protocol (AWEMP)," Energies, MDPI, vol. 16(5), pages 1-15, February.
    10. Elkholy, M.H. & Metwally, Hamid & Farahat, M.A. & Senjyu, Tomonobu & Elsayed Lotfy, Mohammed, 2022. "Smart centralized energy management system for autonomous microgrid using FPGA," Applied Energy, Elsevier, vol. 317(C).
    11. Fan, Dongming & Ren, Yi & Feng, Qiang & Liu, Yiliu & Wang, Zili & Lin, Jing, 2021. "Restoration of smart grids: Current status, challenges, and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    12. Park, Jun Woo & Im, Soo Ik & Lee, Ki Bong, 2023. "Techno-economic optimization of novel energy-efficient solvent deasphalting process using CO2 as a stripping agent," Energy, Elsevier, vol. 263(PB).
    13. Rosato, Antonello & Panella, Massimo & Andreotti, Amedeo & Mohammed, Osama A. & Araneo, Rodolfo, 2021. "Two-stage dynamic management in energy communities using a decision system based on elastic net regularization," Applied Energy, Elsevier, vol. 291(C).
    14. Deveci, Kaan & Güler, Önder, 2020. "A CMOPSO based multi-objective optimization of renewable energy planning: Case of Turkey," Renewable Energy, Elsevier, vol. 155(C), pages 578-590.
    15. Mohammadpour Shotorbani, Amin & Zeinal-Kheiri, Sevda & Chhipi-Shrestha, Gyan & Mohammadi-Ivatloo, Behnam & Sadiq, Rehan & Hewage, Kasun, 2021. "Enhanced real-time scheduling algorithm for energy management in a renewable-integrated microgrid," Applied Energy, Elsevier, vol. 304(C).
    16. Yan, Zhe & Zhang, Yongming & Liang, Runqi & Jin, Wenrui, 2020. "An allocative method of hybrid electrical and thermal energy storage capacity for load shifting based on seasonal difference in district energy planning," Energy, Elsevier, vol. 207(C).
    17. Aritra Ghosh, 2022. "Recent Advances in Renewable Energy and Clean Energy," Energies, MDPI, vol. 15(9), pages 1-2, April.
    18. Innocent Kamwa & Leila Bagherzadeh & Atieh Delavari, 2023. "Integrated Demand Response Programs in Energy Hubs: A Review of Applications, Classifications, Models and Future Directions," Energies, MDPI, vol. 16(11), pages 1-21, May.
    19. Pereira, Luan D.L. & Yahyaoui, Imene & Fiorotti, Rodrigo & de Menezes, Luíza S. & Fardin, Jussara F. & Rocha, Helder R.O. & Tadeo, Fernando, 2022. "Optimal allocation of distributed generation and capacitor banks using probabilistic generation models with correlations," Applied Energy, Elsevier, vol. 307(C).
    20. Edmonds, Lawryn & Derby, Melanie & Hill, Mary & Wu, Hongyu, 2021. "Coordinated operation of water and electricity distribution networks with variable renewable energy and distribution locational marginal pricing," Renewable Energy, Elsevier, vol. 177(C), pages 1438-1450.

    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:15:y:2022:i:20:p:7689-:d:945983. 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.