IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i21p15405-d1269718.html

Review of a Comprehensive Analysis of Planning, Functionality, Control, and Protection for Direct Current Microgrids

Author

Listed:
  • Satyajit Mohanty

    (School of Electrical Engineering, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India)

  • Ankit Bhanja

    (School of Electrical Engineering, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India)

  • Shivam Prakash Gautam

    (TIFAC-CORE, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India)

  • Dhanamjayulu Chittathuru

    (School of Electrical Engineering, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India)

  • Santanu Kumar Dash

    (TIFAC-CORE, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India)

  • Mrutyunjaya Mangaraj

    (Department of Electrical & Electronics Engineering, SRM University, Amaravati 522502, Andhra Pradesh, India)

  • Ravikumar Chinthaginjala

    (School of Electronics Engineering, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India)

  • Abdullah M. Alamri

    (Department of Geology & Geophysics, King Saud University, Riyadh 11451, Saudi Arabia)

Abstract

Microgrids have emerged as a feasible solution for consumers, comprising Distributed Energy Resources (DERs) and local loads within a smaller geographical area. They are capable of operating either autonomously or in coordination with the main power grid. As compared to Alternating Current (AC) microgrid, Direct Current (DC) microgrid helps with grid modernisation, which enhances the integration of Distributed and Renewable energy sources, which promotes energy efficiency and reduces losses. The integration of energy storage systems (ESS) into microgrids has garnered significant attention due to the capability of ESS to store energy during periods of low demand and then provide it during periods of high demand. This research includes planning, operation, control, and protection of the DC microgrid. At the beginning of the chapter, a quick explanation of DC microgrids and their advantages over AC microgrids is provided, along with a thorough evaluation of the various concerns, control techniques, challenges, solutions, applications, and overall management prospects associated with this integration. Additionally, this study provides an analysis of future trends and real-time applications, which significantly contributes to the development of a cost-effective and durable energy storage system architecture with an extended lifespan for renewable microgrids. Therefore, providing a summary of the anticipated findings of this scholarly paper contributes to the advancement of a techno-economic and efficient integration of ESS with a prolonged lifespan for the use of green microgrids.

Suggested Citation

  • Satyajit Mohanty & Ankit Bhanja & Shivam Prakash Gautam & Dhanamjayulu Chittathuru & Santanu Kumar Dash & Mrutyunjaya Mangaraj & Ravikumar Chinthaginjala & Abdullah M. Alamri, 2023. "Review of a Comprehensive Analysis of Planning, Functionality, Control, and Protection for Direct Current Microgrids," Sustainability, MDPI, vol. 15(21), pages 1-28, October.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:21:p:15405-:d:1269718
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/21/15405/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/21/15405/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mansouri, Seyed Amir & Rezaee Jordehi, Ahmad & Marzband, Mousa & Tostado-Véliz, Marcos & Jurado, Francisco & Aguado, José A., 2023. "An IoT-enabled hierarchical decentralized framework for multi-energy microgrids market management in the presence of smart prosumers using a deep learning-based forecaster," Applied Energy, Elsevier, vol. 333(C).
    2. Tayab, Usman Bashir & Zia, Ali & Yang, Fuwen & Lu, Junwei & Kashif, Muhammad, 2020. "Short-term load forecasting for microgrid energy management system using hybrid HHO-FNN model with best-basis stationary wavelet packet transform," Energy, Elsevier, vol. 203(C).
    3. Zhou, Bo & Ai, Xiaomeng & Fang, Jiakun & Yao, Wei & Zuo, Wenping & Chen, Zhe & Wen, Jinyu, 2019. "Data-adaptive robust unit commitment in the hybrid AC/DC power system," Applied Energy, Elsevier, vol. 254(C).
    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. Jiang, Sufan & Gao, Shan & Pan, Guangsheng & Zhao, Xin & Liu, Yu & Guo, Yasen & Wang, Sicheng, 2020. "A novel robust security constrained unit commitment model considering HVDC regulation," Applied Energy, Elsevier, vol. 278(C).
    2. Leni Kusmiyati & Anjar Priyono, 2021. "The strategy for combining online and offline business model for MSMEs," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 10(4), pages 406-419, June.
    3. Qu, Zhijian & Xu, Juan & Wang, Zixiao & Chi, Rui & Liu, Hanxin, 2021. "Prediction of electricity generation from a combined cycle power plant based on a stacking ensemble and its hyperparameter optimization with a grid-search method," Energy, Elsevier, vol. 227(C).
    4. Dong, Jizhe & Han, Shunjie & Shao, Xiangxin & Tang, Like & Chen, Renhui & Wu, Longfei & Zheng, Cunlong & Li, Zonghao & Li, Haolin, 2021. "Day-ahead wind-thermal unit commitment considering historical virtual wind power data," Energy, Elsevier, vol. 235(C).
    5. Arash Moradzadeh & Sahar Zakeri & Maryam Shoaran & Behnam Mohammadi-Ivatloo & Fazel Mohammadi, 2020. "Short-Term Load Forecasting of Microgrid via Hybrid Support Vector Regression and Long Short-Term Memory Algorithms," Sustainability, MDPI, vol. 12(17), pages 1-17, August.
    6. Hu, Rong & Zhou, Kaile & Lu, Xinhui, 2025. "Integrated loads forecasting with absence of crucial factors," Energy, Elsevier, vol. 322(C).
    7. Bardeeniz, Santi & Panjapornpon, Chanin & Fongsamut, Chalermpan & Ngaotrakanwiwat, Pailin & Hussain, Mohamed Azlan, 2024. "Energy efficiency characteristics analysis for process diagnosis under anomaly using self-adaptive-based SHAP guided optimization," Energy, Elsevier, vol. 309(C).
    8. Zhu, Yansong & Liu, Jizhen & Hu, Yong & Xie, Yan & Zeng, Deliang & Li, Ruilian, 2024. "Distributionally robust optimization model considering deep peak shaving and uncertainty of renewable energy," Energy, Elsevier, vol. 288(C).
    9. Jiang, Sufan & Wu, Chuanshen & Gao, Shan & Pan, Guangsheng & Liu, Yu & Zhao, Xin & Wang, Sicheng, 2022. "Robust frequency risk-constrained unit commitment model for AC-DC system considering wind uncertainty," Renewable Energy, Elsevier, vol. 195(C), pages 395-406.
    10. Lei, Yu & Ali, Mazhar & Khan, Imran Ali & Yinling, Wang & Mostafa, Aziz, 2024. "Presenting a model for decentralized operation based on the internet of things in a system multiple microgrids," Energy, Elsevier, vol. 293(C).
    11. Chintan Patel & Tanmoy Malakar & S. Sreejith, 2023. "Assessment of Converter Performance in Hybrid AC-DC Power System under Optimal Power Flow with Minimum Number of DC Link Control Variables," Energies, MDPI, vol. 16(15), pages 1-20, August.
    12. Li, Peiran & Zhang, Haoran & Wang, Xin & Song, Xuan & Shibasaki, Ryosuke, 2020. "A spatial finer electric load estimation method based on night-light satellite image," Energy, Elsevier, vol. 209(C).
    13. Sekhar, Charan & Dahiya, Ratna, 2023. "Robust framework based on hybrid deep learning approach for short term load forecasting of building electricity demand," Energy, Elsevier, vol. 268(C).
    14. Si, Fangyuan & Han, Yinghua & Zhao, Qiang & Wang, Jinkuan, 2020. "Cost-effective operation of the urban energy system with variable supply and demand via coordination of multi-energy flows," Energy, Elsevier, vol. 203(C).
    15. Han, Gao & Pan, Haiyang & Liu, Yanming & Li, Qian & Wang, Ping, 2025. "A methodology for integrating hydrogen refueling stations in multi-microgrids and coordination of distribution systems and transmission system," Energy, Elsevier, vol. 322(C).
    16. Haiyan Zheng & Liying Huang & Ran Quan, 2023. "Mixed-Integer Conic Formulation of Unit Commitment with Stochastic Wind Power," Mathematics, MDPI, vol. 11(2), pages 1-16, January.
    17. 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.
    18. Pantelis Kostis & Hasan Dinçer & Serhat Yüksel, 2023. "Knowledge-Based Energy Investments of European Economies and Policy Recommendations for Sustainable Development," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 14(3), pages 2630-2662, September.
    19. Mobarak Abumohsen & Amani Yousef Owda & Majdi Owda, 2023. "Electrical Load Forecasting Using LSTM, GRU, and RNN Algorithms," Energies, MDPI, vol. 16(5), pages 1-31, February.
    20. Bagheritabar, Mahmoud & Hakimi, Seyed Mehdi & Derakhshan, Ghasem & Rezaee Jordehi, Ahmad, 2025. "A three-stage optimization framework for unlocking demand-side flexibility in highly renewable electricity grids," Energy, Elsevier, vol. 320(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:gam:jsusta:v:15:y:2023:i:21:p:15405-:d:1269718. 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.