IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2023i1p25-d1303703.html
   My bibliography  Save this article

Efficient Microgrid Management with Meerkat Optimization for Energy Storage, Renewables, Hydrogen Storage, Demand Response, and EV Charging

Author

Listed:
  • Hossein Jokar

    (Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz 7155713876, Iran)

  • Taher Niknam

    (Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz 7155713876, Iran)

  • Moslem Dehghani

    (Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz 7155713876, Iran)

  • Ehsan Sheybani

    (School of Information Systems and Management, Muma College of Business, University of South Florida, Tampa, FL 33620, USA)

  • Motahareh Pourbehzadi

    (School of Information Systems and Management, Muma College of Business, University of South Florida, Tampa, FL 33620, USA)

  • Giti Javidi

    (School of Information Systems and Management, Muma College of Business, University of South Florida, Tampa, FL 33620, USA)

Abstract

Within microgrids (MGs), the integration of renewable energy resources (RERs), plug-in hybrid electric vehicles (PHEVs), combined heat and power (CHP) systems, demand response (DR) initiatives, and energy storage solutions poses intricate scheduling challenges. Coordinating these diverse components is pivotal for optimizing MG performance. This study presents an innovative stochastic framework to streamline energy management in MGs, covering proton exchange membrane fuel cell–CHP (PEMFC-CHP) units, RERs, PHEVs, and various storage methods. To tackle uncertainties in PHEV and RER models, we employ the robust Monte Carlo Simulation (MCS) technique. Challenges related to hydrogen storage strategies in PEMFC-CHP units are addressed through a customized mixed-integer nonlinear programming (MINLP) approach. The integration of intelligent charging protocols governing PHEV charging dynamics is emphasized. Our primary goal centers on maximizing market profits, serving as the foundation for our optimization endeavors. At the heart of our approach is the Meerkat Optimization Algorithm (MOA), unraveling optimal MG operation amidst the intermittent nature of uncertain parameters. To amplify its exploratory capabilities and expedite global optima discovery, we enhance the MOA algorithm. The revised summary commences by outlining the overall goal and core algorithm, followed by a detailed explanation of optimization points for each MG component. Rigorous validation is executed using a conventional test system across diverse planning horizons. A comprehensive comparative analysis spanning varied scenarios establishes our proposed method as a benchmark against existing alternatives.

Suggested Citation

  • Hossein Jokar & Taher Niknam & Moslem Dehghani & Ehsan Sheybani & Motahareh Pourbehzadi & Giti Javidi, 2023. "Efficient Microgrid Management with Meerkat Optimization for Energy Storage, Renewables, Hydrogen Storage, Demand Response, and EV Charging," Energies, MDPI, vol. 17(1), pages 1-23, December.
    • Handle: RePEc:gam:jeners:v:17:y:2023:i:1:p:25-:d:1303703
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/1/25/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/1/25/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gao, Chong & Lin, Junjie & Zeng, Jianfeng & Han, Fengwu, 2022. "Wind-photovoltaic co-generation prediction and energy scheduling of low-carbon complex regional integrated energy system with hydrogen industry chain based on copula-MILP," Applied Energy, Elsevier, vol. 328(C).
    2. Han, Xiaojuan & Zhang, Hua & Yu, Xiaoling & Wang, Lina, 2016. "Economic evaluation of grid-connected micro-grid system with photovoltaic and energy storage under different investment and financing models," Applied Energy, Elsevier, vol. 184(C), pages 103-118.
    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. Tang, Bao-Jun & Cao, Xi-Lin & Li, Ru & Xiang, Zhi-Bo & Zhang, Sen, 2024. "Economic and low-carbon planning for interconnected integrated energy systems considering emerging technologies and future development trends," Energy, Elsevier, vol. 302(C).
    2. Kiki Ayu & Akilu Yunusa-Kaltungo, 2020. "A Holistic Framework for Supporting Maintenance and Asset Management Life Cycle Decisions for Power Systems," Energies, MDPI, vol. 13(8), pages 1-32, April.
    3. Santiago, Isabel & Palacios-Garcia, Emilio J. & Gonzalez-Redondo, Miguel & Arenas-Ramos, Victoria & Simon, Bernardo & Hayes, Barry P. & Moreno-Munoz, Antonio, 2024. "Assessment of generation capacity and economic viability of photovoltaic systems on urban buildings in southern Spain: A socioeconomic, technological, and regulatory analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 203(C).
    4. Wu, Zhongqun & Yang, Chan & Zheng, Ruijin, 2022. "Developing a holistic fuzzy hierarchy-cloud assessment model for the connection risk of renewable energy microgrid," Energy, Elsevier, vol. 245(C).
    5. Han, Fengwu & Zeng, Jianfeng & Lin, Junjie & Gao, Chong, 2023. "Multi-stage distributionally robust optimization for hybrid energy storage in regional integrated energy system considering robustness and nonanticipativity," Energy, Elsevier, vol. 277(C).
    6. Bornapour, Mosayeb & Hooshmand, Rahmat-Allah & Parastegari, Moein, 2019. "An efficient scenario-based stochastic programming method for optimal scheduling of CHP-PEMFC, WT, PV and hydrogen storage units in micro grids," Renewable Energy, Elsevier, vol. 130(C), pages 1049-1066.
    7. Firouzi, Afshin & Meshkani, Ali, 2021. "Risk-based optimization of the debt service schedule in renewable energy project finance," Utilities Policy, Elsevier, vol. 70(C).
    8. Hou, Hui & Xue, Mengya & Xu, Yan & Xiao, Zhenfeng & Deng, Xiangtian & Xu, Tao & Liu, Peng & Cui, Rongjian, 2020. "Multi-objective economic dispatch of a microgrid considering electric vehicle and transferable load," Applied Energy, Elsevier, vol. 262(C).
    9. Mehdi Dhifli & Abderezak Lashab & Josep M. Guerrero & Abdullah Abusorrah & Yusuf A. Al-Turki & Adnane Cherif, 2020. "Enhanced Intelligent Energy Management System for a Renewable Energy-Based AC Microgrid," Energies, MDPI, vol. 13(12), pages 1-18, June.
    10. Wang, L.L. & Xian, R.C. & Jiao, P.H. & Chen, J.J. & Chen, Y. & Liu, H.G., 2024. "Multi-timescale optimization of integrated energy system with diversified utilization of hydrogen energy under the coupling of green certificate and carbon trading," Renewable Energy, Elsevier, vol. 228(C).
    11. Li, Longxi & Cao, Xilin, 2022. "Comprehensive effectiveness assessment of energy storage incentive mechanisms for PV-ESS projects based on compound real options," Energy, Elsevier, vol. 239(PA).
    12. Huang, Shangjiu & Lu, Hao & Chen, Maozhi & Zhao, Wenjun, 2023. "Integrated energy system scheduling considering the correlation of uncertainties," Energy, Elsevier, vol. 283(C).
    13. Bornapour, Mosayeb & Hooshmand, Rahmat-Allah & Khodabakhshian, Amin & Parastegari, Moein, 2017. "Optimal stochastic coordinated scheduling of proton exchange membrane fuel cell-combined heat and power, wind and photovoltaic units in micro grids considering hydrogen storage," Applied Energy, Elsevier, vol. 202(C), pages 308-322.
    14. Every, Jeremy & Li, Li & Dorrell, David G., 2017. "Leveraging smart meter data for economic optimization of residential photovoltaics under existing tariff structures and incentive schemes," Applied Energy, Elsevier, vol. 201(C), pages 158-173.
    15. Federica Cucchiella & Idiano D’Adamo & Massimo Gastaldi, 2017. "The Economic Feasibility of Residential Energy Storage Combined with PV Panels: The Role of Subsidies in Italy," Energies, MDPI, vol. 10(9), pages 1-18, September.
    16. Yang, Changhui & Fu, Yuting & He, Lijun & Jiang, Qi & Cui, Yangyu, 2024. "Real options analysis for regional investment decisions of household PV-ESS in China," Energy, Elsevier, vol. 293(C).
    17. Yong Long & Chengrong Pan & Yu Wang, 2018. "Research on a Microgrid Subsidy Strategy Based on Operational Efficiency of the Industry Chain," Sustainability, MDPI, vol. 10(5), pages 1-26, May.
    18. Vu Ba Hau & Munir Husein & Il-Yop Chung & Dong-Jun Won & William Torre & Truong Nguyen, 2018. "Analyzing the Impact of Renewable Energy Incentives and Parameter Uncertainties on Financial Feasibility of a Campus Microgrid," Energies, MDPI, vol. 11(9), pages 1-24, September.
    19. Han, Fengwu & Zeng, Jianfeng & Lin, Junjie & Zhao, Yunlong & Gao, Chong, 2023. "A stochastic hierarchical optimization and revenue allocation approach for multi-regional integrated energy systems based on cooperative games," Applied Energy, Elsevier, vol. 350(C).
    20. Laws, Nicholas D. & Anderson, Kate & DiOrio, Nicholas A. & Li, Xiangkun & McLaren, Joyce, 2018. "Impacts of valuing resilience on cost-optimal PV and storage systems for commercial buildings," Renewable Energy, Elsevier, vol. 127(C), pages 896-909.

    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:2023:i:1:p:25-:d:1303703. 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.