IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v334y2023ics0306261923000673.html
   My bibliography  Save this article

Integrated framework for modeling the interactions of plug-in hybrid electric vehicles aggregators, parking lots and distributed generation facilities in electricity markets

Author

Listed:
  • Firouzi, Mehdi
  • Setayesh Nazar, Mehrdad
  • Shafie-khah, Miadreza
  • Catalão, João P.S.

Abstract

This paper presents an integrated framework for the optimal resilient scheduling of an active distribution system in the day-ahead and real-time markets considering aggregators, parking lots, distributed energy resources, and Plug-in Hybrid Electric Vehicles (PHEVs) interactions. The main contribution of this paper is that the impacts of traffic patterns on the available dispatchable active power of PHEVs in day-ahead and real-time markets are explored. A two stage framework is considered. Each stage consists of a four-level optimization procedure that optimizes the scheduling problems of PHEVs, parking lots and distributed energy resources, aggregators, and active distribution system. The distribution system procures ramp-up and ramp-down services for the upward electricity market in a real-time horizon. The active distribution system can utilize a switching procedure to sectionalize its system into a multi-microgrid system to mitigate the impacts of external shocks. The model was assessed by the 123-bus test system. The proposed algorithm reduced the interruption and operating costs of the 123-bus test system by about 94.56% for the worst-case external shock. Further, the traffic pattern decreased the available ramp-up and ramp-down of parking lots by about 58.61% concerning the no-traffic case.

Suggested Citation

  • Firouzi, Mehdi & Setayesh Nazar, Mehrdad & Shafie-khah, Miadreza & Catalão, João P.S., 2023. "Integrated framework for modeling the interactions of plug-in hybrid electric vehicles aggregators, parking lots and distributed generation facilities in electricity markets," Applied Energy, Elsevier, vol. 334(C).
  • Handle: RePEc:eee:appene:v:334:y:2023:i:c:s0306261923000673
    DOI: 10.1016/j.apenergy.2023.120703
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261923000673
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2023.120703?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Moghaddam, Saeed Zolfaghari & Akbari, Tohid, 2018. "Network-constrained optimal bidding strategy of a plug-in electric vehicle aggregator: A stochastic/robust game theoretic approach," Energy, Elsevier, vol. 151(C), pages 478-489.
    2. Wu, Yuankai & Tan, Huachun & Peng, Jiankun & Zhang, Hailong & He, Hongwen, 2019. "Deep reinforcement learning of energy management with continuous control strategy and traffic information for a series-parallel plug-in hybrid electric bus," Applied Energy, Elsevier, vol. 247(C), pages 454-466.
    3. Zhang, Zhendong & He, Hongwen & Guo, Jinquan & Han, Ruoyan, 2020. "Velocity prediction and profile optimization based real-time energy management strategy for Plug-in hybrid electric buses," Applied Energy, Elsevier, vol. 280(C).
    4. Wu, Chuantao & Chen, Cen & Ma, Yuncong & Li, Feiyu & Sui, Quan & Lin, Xiangning & Wei, Fanrong & Li, Zhengtian, 2022. "Enhancing resilient restoration of distribution systems utilizing electric vehicles and supporting incentive mechanism," Applied Energy, Elsevier, vol. 322(C).
    5. Bostan, Alireza & Nazar, Mehrdad Setayesh & Shafie-khah, Miadreza & Catalão, João P.S., 2020. "An integrated optimization framework for combined heat and power units, distributed generation and plug-in electric vehicles," Energy, Elsevier, vol. 202(C).
    6. Hosseinnia, Hamed & Modarresi, Javad & Nazarpour, Daryoush, 2020. "Optimal eco-emission scheduling of distribution network operator and distributed generator owner under employing demand response program," Energy, Elsevier, vol. 191(C).
    7. Zakernezhad, Hamid & Nazar, Mehrdad Setayesh & Shafie-khah, Miadreza & Catalão, João P.S., 2021. "Optimal resilient operation of multi-carrier energy systems in electricity markets considering distributed energy resource aggregators," Applied Energy, Elsevier, vol. 299(C).
    8. Hussain, Akhtar & Bui, Van-Hai & Kim, Hak-Man, 2019. "Microgrids as a resilience resource and strategies used by microgrids for enhancing resilience," Applied Energy, Elsevier, vol. 240(C), pages 56-72.
    9. Zakernezhad, Hamid & Setayesh Nazar, Mehrdad & Shafie-khah, Miadreza & Catalão, João P.S., 2022. "Optimal scheduling of an active distribution system considering distributed energy resources, demand response aggregators and electrical energy storage," Applied Energy, Elsevier, vol. 314(C).
    10. Silva, Jéssica Alice A. & López, Juan Camilo & Arias, Nataly Bañol & Rider, Marcos J. & da Silva, Luiz C.P., 2021. "An optimal stochastic energy management system for resilient microgrids," Applied Energy, Elsevier, vol. 300(C).
    11. Mehrjerdi, Hasan & Hemmati, Reza, 2020. "Coordination of vehicle-to-home and renewable capacity resources for energy management in resilience and self-healing building," Renewable Energy, Elsevier, vol. 146(C), pages 568-579.
    12. Luo, Yugong & Zhu, Tao & Wan, Shuang & Zhang, Shuwei & Li, Keqiang, 2016. "Optimal charging scheduling for large-scale EV (electric vehicle) deployment based on the interaction of the smart-grid and intelligent-transport systems," Energy, Elsevier, vol. 97(C), pages 359-368.
    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. Chen, Yuanyi & Hu, Simon & Zheng, Yanchong & Xie, Shiwei & Yang, Qiang & Wang, Yubin & Hu, Qinru, 2024. "Coordinated optimization of logistics scheduling and electricity dispatch for electric logistics vehicles considering uncertain electricity prices and renewable generation," Applied Energy, Elsevier, vol. 364(C).
    2. Nazar, Mehrdad Setayesh & Jafarpour, Pourya & Shafie-khah, Miadreza & Catalão, João P.S., 2024. "Optimal planning of self-healing multi-carriers energy systems considering integration of smart buildings and parking lots energy resources," Energy, Elsevier, vol. 286(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. Rahimi Sadegh, Ainollah & Setayesh Nazar, Mehrdad & Shafie-khah, Miadreza & Catalão, João P.S., 2022. "Optimal resilient allocation of mobile energy storages considering coordinated microgrids biddings," Applied Energy, Elsevier, vol. 328(C).
    2. Zhang, Xi & Dong, Zihang & Huangfu, Fenyu & Ye, Yujian & Strbac, Goran & Kang, Chongqing, 2024. "Strategic dispatch of electric buses for resilience enhancement of urban energy systems," Applied Energy, Elsevier, vol. 361(C).
    3. Huang, Ruchen & He, Hongwen & Zhao, Xuyang & Wang, Yunlong & Li, Menglin, 2022. "Battery health-aware and naturalistic data-driven energy management for hybrid electric bus based on TD3 deep reinforcement learning algorithm," Applied Energy, Elsevier, vol. 321(C).
    4. Gonzalez-Reina, Antonio Enrique & Garcia-Torres, Felix & Girona-Garcia, Victor & Sanchez-Sanchez-de-Puerta, Alvaro & Jimenez-Romero, F.J. & Jimenez-Hornero, Jorge E., 2024. "Cooperative model predictive control for avoiding critical instants of energy resilience in networked microgrids," Applied Energy, Elsevier, vol. 369(C).
    5. Dong, Peng & Zhao, Junwei & Liu, Xuewu & Wu, Jian & Xu, Xiangyang & Liu, Yanfang & Wang, Shuhan & Guo, Wei, 2022. "Practical application of energy management strategy for hybrid electric vehicles based on intelligent and connected technologies: Development stages, challenges, and future trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    6. Zakernezhad, Hamid & Setayesh Nazar, Mehrdad & Shafie-khah, Miadreza & Catalão, João P.S., 2022. "Optimal scheduling of an active distribution system considering distributed energy resources, demand response aggregators and electrical energy storage," Applied Energy, Elsevier, vol. 314(C).
    7. Wang, Chong & Ju, Ping & Wu, Feng & Pan, Xueping & Wang, Zhaoyu, 2022. "A systematic review on power system resilience from the perspective of generation, network, and load," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    8. Tobajas, Javier & Garcia-Torres, Felix & Roncero-Sánchez, Pedro & Vázquez, Javier & Bellatreche, Ladjel & Nieto, Emilio, 2022. "Resilience-oriented schedule of microgrids with hybrid energy storage system using model predictive control," Applied Energy, Elsevier, vol. 306(PB).
    9. Zheng, Yanchong & Wang, Yubin & Yang, Qiang, 2023. "Bidding strategy design for electric vehicle aggregators in the day-ahead electricity market considering price volatility: A risk-averse approach," Energy, Elsevier, vol. 283(C).
    10. Hussain Abdalla Sajwani & Bassel Soudan & Abdul Ghani Olabi, 2024. "Empowering Sustainability: Understanding Determinants of Consumer Investment in Microgrid Technology in the UAE," Energies, MDPI, vol. 17(9), pages 1-28, May.
    11. Deng Xu & Yong Long, 2019. "The Impact of Government Subsidy on Renewable Microgrid Investment Considering Double Externalities," Sustainability, MDPI, vol. 11(11), pages 1-15, June.
    12. 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.
    13. Shafqat Jawad & Junyong Liu, 2020. "Electrical Vehicle Charging Services Planning and Operation with Interdependent Power Networks and Transportation Networks: A Review of the Current Scenario and Future Trends," Energies, MDPI, vol. 13(13), pages 1-24, July.
    14. Antoine Boche & Clément Foucher & Luiz Fernando Lavado Villa, 2022. "Understanding Microgrid Sustainability: A Systemic and Comprehensive Review," Energies, MDPI, vol. 15(8), pages 1-29, April.
    15. Matteo Acquarone & Claudio Maino & Daniela Misul & Ezio Spessa & Antonio Mastropietro & Luca Sorrentino & Enrico Busto, 2023. "Influence of the Reward Function on the Selection of Reinforcement Learning Agents for Hybrid Electric Vehicles Real-Time Control," Energies, MDPI, vol. 16(6), pages 1-22, March.
    16. Soheil Mohseni & Alan C. Brent & Daniel Burmester, 2020. "Community Resilience-Oriented Optimal Micro-Grid Capacity Expansion Planning: The Case of Totarabank Eco-Village, New Zealand," Energies, MDPI, vol. 13(15), pages 1-29, August.
    17. Huang, Chunjun & Zong, Yi & You, Shi & Træholt, Chresten & Zheng, Yi & Wang, Jiawei & Zheng, Zixuan & Xiao, Xianyong, 2023. "Economic and resilient operation of hydrogen-based microgrids: An improved MPC-based optimal scheduling scheme considering security constraints of hydrogen facilities," Applied Energy, Elsevier, vol. 335(C).
    18. Yang, Ningkang & Han, Lijin & Xiang, Changle & Liu, Hui & Li, Xunmin, 2021. "An indirect reinforcement learning based real-time energy management strategy via high-order Markov Chain model for a hybrid electric vehicle," Energy, Elsevier, vol. 236(C).
    19. Navid Shirzadi & Hadise Rasoulian & Fuzhan Nasiri & Ursula Eicker, 2022. "Resilience Enhancement of an Urban Microgrid during Off-Grid Mode Operation Using Critical Load Indicators," Energies, MDPI, vol. 15(20), pages 1-15, October.
    20. Angel Recalde & Ricardo Cajo & Washington Velasquez & Manuel S. Alvarez-Alvarado, 2024. "Machine Learning and Optimization in Energy Management Systems for Plug-In Hybrid Electric Vehicles: A Comprehensive Review," Energies, MDPI, vol. 17(13), pages 1-39, June.

    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:334:y:2023:i:c:s0306261923000673. 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.