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. 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).
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    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. Younes Zahraoui & Tarmo Korõtko & Argo Rosin & Saad Mekhilef & Mehdi Seyedmahmoudian & Alex Stojcevski & Ibrahim Alhamrouni, 2024. "AI Applications to Enhance Resilience in Power Systems and Microgrids—A Review," Sustainability, MDPI, vol. 16(12), pages 1-35, June.
    3. 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).
    4. 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).
    5. Saima Akhtar & Sulman Shahzad & Asad Zaheer & Hafiz Sami Ullah & Heybet Kilic & Radomir Gono & Michał Jasiński & Zbigniew Leonowicz, 2023. "Short-Term Load Forecasting Models: A Review of Challenges, Progress, and the Road Ahead," Energies, MDPI, vol. 16(10), pages 1-29, May.
    6. Angel L. Cedeño & Reinier López Ahuar & José Rojas & Gonzalo Carvajal & César Silva & Juan C. Agüero, 2022. "Model Predictive Control for Photovoltaic Plants with Non-Ideal Energy Storage Using Mixed Integer Linear Programming," Energies, MDPI, vol. 15(17), pages 1-21, September.
    7. 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).
    8. Liu, Jiejie & Li, Yao & Ma, Yanan & Qin, Ruomu & Meng, Xianyang & Wu, Jiangtao, 2023. "Two-layer multiple scenario optimization framework for integrated energy system based on optimal energy contribution ratio strategy," Energy, Elsevier, vol. 285(C).
    9. 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.
    10. Can Ding & Yiyuan Zhou & Qingchang Ding & Kaiming Li, 2022. "Integrated Carbon-Capture-Based Low-Carbon Economic Dispatch of Power Systems Based on EEMD-LSTM-SVR Wind Power Forecasting," Energies, MDPI, vol. 15(5), pages 1-27, February.
    11. 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.
    12. Bhabasis Mohapatra & Binod Kumar Sahu & Swagat Pati & Mohit Bajaj & Vojtech Blazek & Lukas Prokop & Stanislav Misak & Mosleh Alharthi, 2022. "Real-Time Validation of a Novel IAOA Technique-Based Offset Hysteresis Band Current Controller for Grid-Tied Photovoltaic System," Energies, MDPI, vol. 15(23), pages 1-26, November.
    13. 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).
    14. Işık, Cem & Kuziboev, Bekhzod & Ongan, Serdar & Saidmamatov, Olimjon & Mirkhoshimova, Mokhirakhon & Rajabov, Alibek, 2024. "The volatility of global energy uncertainty: Renewable alternatives," Energy, Elsevier, vol. 297(C).
    15. 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.
    16. Huang, Mengdi & Chang, Jianxia & Guo, Aijun & Zhao, Mingzhe & Ye, Xiangmin & Lei, Kaixuan & Peng, Zhiwen & Wang, Yimin, 2023. "Cascade hydropower stations optimal dispatch considering flexible margin in renewable energy power system," Energy, Elsevier, vol. 285(C).
    17. Zhou, Xu & Ma, Zhongjing & Zou, Suli & Zhang, Jinhui, 2022. "Consensus-based distributed economic dispatch for Multi Micro Energy Grid systems under coupled carbon emissions," Applied Energy, Elsevier, vol. 324(C).
    18. 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).
    19. Alizadeh, Ali & Kamwa, Innocent & Moeini, Ali & Mohseni-Bonab, Seyed Masoud, 2023. "Energy management in microgrids using transactive energy control concept under high penetration of Renewables; A survey and case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 176(C).
    20. 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.

    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.