IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v306y2022ipas0306261921013180.html
   My bibliography  Save this article

Multi-objective load dispatch for microgrid with electric vehicles using modified gravitational search and particle swarm optimization algorithm

Author

Listed:
  • Zhang, Xizheng
  • Wang, Zeyu
  • Lu, Zhangyu

Abstract

With the increasing proportion of electric vehicles in the automobile market, the negative impact of vehicle’s charging on the power system is gradually increasing. The charging-discharging model of vehicles and the multi-objective optimization model of the load dispatch for the microgrid are established. By combining gravitational search algorithm (GSA) and particle swarm optimization (PSO) algorithm, a hybrid modified GSA-PSO (MGSA-PSO) scheme is proposed to optimize the load dispatch of the microgrid containing electric vehicles. To improve the global search performance of the GSA algorithm, the proposed scheme introduces the global memory capacity of the PSO into the GSA. At the same time, the hybrid algorithm is improved by designing adaptive inertia vector, learning factor and chaotic initialization population. The load dispatch optimization are implemented and analyzed, including the unordered charging strategy, the ordered charging-discharging strategy, and the ordered charging-discharging strategy with distributed generations. The optimization results show that, under the same weight factor, the ordered charging-discharging strategy can reduce 13.38% of the total cost, 78.77% of the microgrid load variance and improve the safety and economy of the grid. In addition, reasonable scheduling of distributed power output power can further reduce the total cost by 14.06% and the load variance by 22.36%. Further, the effectiveness of the proposed scheme is proved by analyzing the influences of different numbers of electric vehicles and different charging models.

Suggested Citation

  • Zhang, Xizheng & Wang, Zeyu & Lu, Zhangyu, 2022. "Multi-objective load dispatch for microgrid with electric vehicles using modified gravitational search and particle swarm optimization algorithm," Applied Energy, Elsevier, vol. 306(PA).
    • Handle: RePEc:eee:appene:v:306:y:2022:i:pa:s0306261921013180
    DOI: 10.1016/j.apenergy.2021.118018
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261921013180
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2021.118018?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. Yuan, Zhao & Hesamzadeh, Mohammad Reza, 2017. "Hierarchical coordination of TSO-DSO economic dispatch considering large-scale integration of distributed energy resources," Applied Energy, Elsevier, vol. 195(C), pages 600-615.
    2. Nemati, Mohsen & Braun, Martin & Tenbohlen, Stefan, 2018. "Optimization of unit commitment and economic dispatch in microgrids based on genetic algorithm and mixed integer linear programming," Applied Energy, Elsevier, vol. 210(C), pages 944-963.
    3. Jack N. Barkenbus, 2020. "Prospects for Electric Vehicles," Sustainability, MDPI, vol. 12(14), pages 1-13, July.
    4. Jian, Linni & Zheng, Yanchong & Xiao, Xinping & Chan, C.C., 2015. "Optimal scheduling for vehicle-to-grid operation with stochastic connection of plug-in electric vehicles to smart grid," Applied Energy, Elsevier, vol. 146(C), pages 150-161.
    5. Alberto Escalera & Edgardo D. Castronuovo & Milan Prodanović & Javier Roldán-Pérez, 2019. "Reliability Assessment of Distribution Networks with Optimal Coordination of Distributed Generation, Energy Storage and Demand Management," Energies, MDPI, vol. 12(16), pages 1-17, August.
    6. Ioakimidis, Christos S. & Thomas, Dimitrios & Rycerski, Pawel & Genikomsakis, Konstantinos N., 2018. "Peak shaving and valley filling of power consumption profile in non-residential buildings using an electric vehicle parking lot," Energy, Elsevier, vol. 148(C), pages 148-158.
    7. Marzband, Mousa & Ghadimi, Majid & Sumper, Andreas & Domínguez-García, José Luis, 2014. "Experimental validation of a real-time energy management system using multi-period gravitational search algorithm for microgrids in islanded mode," Applied Energy, Elsevier, vol. 128(C), pages 164-174.
    8. Gandoman, Foad H. & Ahmadi, Abdollah & Bossche, Peter Van den & Van Mierlo, Joeri & Omar, Noshin & Nezhad, Ali Esmaeel & Mavalizadeh, Hani & Mayet, Clément, 2019. "Status and future perspectives of reliability assessment for electric vehicles," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 1-16.
    9. Yinuo Huang & Chuangxin Guo & Yi Ding & Licheng Wang & Bingquan Zhu & Lizhong Xu, 2016. "A Multi-Period Framework for Coordinated Dispatch of Plug-in Electric Vehicles," Energies, MDPI, vol. 9(5), pages 1-16, May.
    10. Zhang, Jingrui & Wu, Yihong & Guo, Yiran & Wang, Bo & Wang, Hengyue & Liu, Houde, 2016. "A hybrid harmony search algorithm with differential evolution for day-ahead scheduling problem of a microgrid with consideration of power flow constraints," Applied Energy, Elsevier, vol. 183(C), pages 791-804.
    11. Liu, Yu & Liu, Congxiao & Ling, Qicheng & Zhao, Xin & Gao, Shan & Huang, Xueliang, 2021. "Toward smart distributed renewable generation via multi-uncertainty featured non-intrusive interactive energy monitoring," Applied Energy, Elsevier, vol. 303(C).
    12. Kavousi-Fard, Abdollah & Abunasri, Alireza & Zare, Alireza & Hoseinzadeh, Rasool, 2014. "Impact of plug-in hybrid electric vehicles charging demand on the optimal energy management of renewable micro-grids," Energy, Elsevier, vol. 78(C), pages 904-915.
    13. Kamankesh, Hamidreza & Agelidis, Vassilios G. & Kavousi-Fard, Abdollah, 2016. "Optimal scheduling of renewable micro-grids considering plug-in hybrid electric vehicle charging demand," Energy, Elsevier, vol. 100(C), pages 285-297.
    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. Javidsharifi, Mahshid & Niknam, Taher & Aghaei, Jamshid & Mokryani, Geev, 2018. "Multi-objective short-term scheduling of a renewable-based microgrid in the presence of tidal resources and storage devices," Applied Energy, Elsevier, vol. 216(C), pages 367-381.
    2. Yamashita, Daniela Yassuda & Vechiu, Ionel & Gaubert, Jean-Paul, 2020. "A review of hierarchical control for building microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 118(C).
    3. Fontenot, Hannah & Dong, Bing, 2019. "Modeling and control of building-integrated microgrids for optimal energy management – A review," Applied Energy, Elsevier, vol. 254(C).
    4. Cagnano, A. & Caldarulo Bugliari, A. & De Tuglie, E., 2018. "A cooperative control for the reserve management of isolated microgrids," Applied Energy, Elsevier, vol. 218(C), pages 256-265.
    5. Li, Shuangqi & Zhao, Pengfei & Gu, Chenghong & Huo, Da & Zeng, Xianwu & Pei, Xiaoze & Cheng, Shuang & Li, Jianwei, 2022. "Online battery-protective vehicle to grid behavior management," Energy, Elsevier, vol. 243(C).
    6. Panda, Debashish & Ramteke, Manojkumar, 2019. "Preventive crude oil scheduling under demand uncertainty using structure adapted genetic algorithm," Applied Energy, Elsevier, vol. 235(C), pages 68-82.
    7. Stennikov, Valery & Barakhtenko, Evgeny & Mayorov, Gleb & Sokolov, Dmitry & Zhou, Bin, 2022. "Coordinated management of centralized and distributed generation in an integrated energy system using a multi-agent approach," Applied Energy, Elsevier, vol. 309(C).
    8. Li, Shuangqi & Gu, Chenghong & Zeng, Xianwu & Zhao, Pengfei & Pei, Xiaoze & Cheng, Shuang, 2021. "Vehicle-to-grid management for multi-time scale grid power balancing," Energy, Elsevier, vol. 234(C).
    9. Juan D. Velásquez & Lorena Cadavid & Carlos J. Franco, 2023. "Intelligence Techniques in Sustainable Energy: Analysis of a Decade of Advances," Energies, MDPI, vol. 16(19), pages 1-45, October.
    10. Samy Faddel & Ali T. Al-Awami & Osama A. Mohammed, 2018. "Charge Control and Operation of Electric Vehicles in Power Grids: A Review," Energies, MDPI, vol. 11(4), pages 1-21, March.
    11. Yang, Zhile & Li, Kang & Foley, Aoife, 2015. "Computational scheduling methods for integrating plug-in electric vehicles with power systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 396-416.
    12. Hou, Rui & Lei, Lei & Jin, Kangning & Lin, Xiaogang & Xiao, Lu, 2022. "Introducing electric vehicles? Impact of network effect on profits and social welfare," Energy, Elsevier, vol. 243(C).
    13. Nikmehr, Nima & Najafi-Ravadanegh, Sajad & Khodaei, Amin, 2017. "Probabilistic optimal scheduling of networked microgrids considering time-based demand response programs under uncertainty," Applied Energy, Elsevier, vol. 198(C), pages 267-279.
    14. Virginia Casella & Daniel Fernandez Valderrama & Giulio Ferro & Riccardo Minciardi & Massimo Paolucci & Luca Parodi & Michela Robba, 2022. "Towards the Integration of Sustainable Transportation and Smart Grids: A Review on Electric Vehicles’ Management," Energies, MDPI, vol. 15(11), pages 1-23, May.
    15. Zheng, Yanchong & Niu, Songyan & Shang, Yitong & Shao, Ziyun & Jian, Linni, 2019. "Integrating plug-in electric vehicles into power grids: A comprehensive review on power interaction mode, scheduling methodology and mathematical foundation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 424-439.
    16. Abdellatif Elmouatamid & Radouane Ouladsine & Mohamed Bakhouya & Najib El Kamoun & Mohammed Khaidar & Khalid Zine-Dine, 2020. "Review of Control and Energy Management Approaches in Micro-Grid Systems," Energies, MDPI, vol. 14(1), pages 1-30, December.
    17. Singh, Kamini & Singh, Anoop, 2022. "Behavioural modelling for personal and societal benefits of V2G/V2H integration on EV adoption," Applied Energy, Elsevier, vol. 319(C).
    18. Keshta, H.E. & Ali, A.A. & Saied, E.M. & Bendary, F.M., 2019. "Real-time operation of multi-micro-grids using a multi-agent system," Energy, Elsevier, vol. 174(C), pages 576-590.
    19. Zhang, Jingrui & Wu, Yihong & Guo, Yiran & Wang, Bo & Wang, Hengyue & Liu, Houde, 2016. "A hybrid harmony search algorithm with differential evolution for day-ahead scheduling problem of a microgrid with consideration of power flow constraints," Applied Energy, Elsevier, vol. 183(C), pages 791-804.
    20. García-Triviño, Pablo & Torreglosa, Juan P. & Fernández-Ramírez, Luis M. & Jurado, Francisco, 2016. "Control and operation of power sources in a medium-voltage direct-current microgrid for an electric vehicle fast charging station with a photovoltaic and a battery energy storage system," Energy, Elsevier, vol. 115(P1), pages 38-48.

    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:306:y:2022:i:pa:s0306261921013180. 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.