IDEAS home Printed from https://ideas.repec.org/a/eee/matcom/v131y2017icp172-189.html
   My bibliography  Save this article

Methodology for technical and economic assessment of electric vehicles integration in distribution grid

Author

Listed:
  • Bouallaga, Anouar
  • Davigny, Arnaud
  • Courtecuisse, Vincent
  • Robyns, Benoit

Abstract

This paper proposes a methodology to design a supervision system (SS) based on Fuzzy and Boolean logics. In the first stage, a graphical modeling tool is used to facilitate the analysis and the determination of Fuzzy–Boolean algorithm linked to the test system. To improve the performance of the proposed SS a genetic algorithm (GA) is implemented in the second stage. The SS objective is used to control electric vehicles (EVs) load in order to minimize the energy transmission costs (ETC) of the distribution system operator (DSO). To achieve this goal, it is necessary to promote local consumption of wind and photovoltaic (PV) power by coordinating them with EVs load, maximize EVs charging during cheaper energy periods and reduce subscribed power exceeding. The performance of the SS is shown by numerical simulation results using Matlab/Simulink. Finally, a Matlab–PowerFactory co-simulation framework is proposed in order to assess supervision system influence on the technical aspects of a real test grid.

Suggested Citation

  • Bouallaga, Anouar & Davigny, Arnaud & Courtecuisse, Vincent & Robyns, Benoit, 2017. "Methodology for technical and economic assessment of electric vehicles integration in distribution grid," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 131(C), pages 172-189.
  • Handle: RePEc:eee:matcom:v:131:y:2017:i:c:p:172-189
    DOI: 10.1016/j.matcom.2016.05.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378475416300805
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.matcom.2016.05.003?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. Robyns, Benoît & Davigny, Arnaud & Saudemont, Christophe, 2013. "Methodologies for supervision of Hybrid Energy Sources based on Storage Systems – A survey," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 91(C), pages 52-71.
    2. Breban, Stefan & Saudemont, Christophe & Vieillard, Sébastien & Robyns, Benoît, 2013. "Experimental design and genetic algorithm optimization of a fuzzy-logic supervisor for embedded electrical power systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 91(C), pages 91-107.
    3. Courtecuisse, Vincent & Sprooten, Jonathan & Robyns, Benoît & Petit, Marc & Francois, Bruno & Deuse, Jacques, 2010. "A methodology to design a fuzzy logic based supervision of Hybrid Renewable Energy Systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(2), pages 208-224.
    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. Heping Jia & Qianxin Ma & Yun Li & Mingguang Liu & Dunnan Liu, 2023. "Integrating Electric Vehicles to Power Grids: A Review on Modeling, Regulation, and Market Operation," Energies, MDPI, vol. 16(17), pages 1-18, August.

    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. Pankovits, Petronela & Abbes, Dhaker & Saudemont, Christophe & Brisset, Stephane & Pouget, Julien & Robyns, Benoit, 2016. "Multi-criteria fuzzy-logic optimized supervision for hybrid railway power substations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 130(C), pages 236-250.
    2. Aouad, Anthony & Almaksour, Khaled & Abbes, Dhaker, 2024. "Storage management optimization based on electrical consumption and production forecast in a photovoltaic system," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 224(PB), pages 128-147.
    3. Aparicio, Néstor & Añó-Villalba, Salvador & Belenguer, Enrique & Blasco-Gimenez, Ramon, 2018. "Automatic under-frequency load shedding mal-operation in power systems with high wind power penetration," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 146(C), pages 200-209.
    4. Robyns, Benoît & Davigny, Arnaud & Saudemont, Christophe, 2013. "Methodologies for supervision of Hybrid Energy Sources based on Storage Systems – A survey," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 91(C), pages 52-71.
    5. Abbes, Dhaker & Martinez, André & Champenois, Gérard, 2014. "Life cycle cost, embodied energy and loss of power supply probability for the optimal design of hybrid power systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 98(C), pages 46-62.
    6. Lesel, J. & Bourdon, D. & Claisse, G. & Debay, P. & Robyns, B., 2017. "Real time electrical power estimation for the energy management of automatic metro lines," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 131(C), pages 3-20.
    7. Bourbon, R. & Ngueveu, S.U. & Roboam, X. & Sareni, B. & Turpin, C. & Hernandez-Torres, D., 2019. "Energy management optimization of a smart wind power plant comparing heuristic and linear programming methods," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 158(C), pages 418-431.
    8. Djamila Rekioua & Khoudir Kakouche & Abdulrahman Babqi & Zahra Mokrani & Adel Oubelaid & Toufik Rekioua & Abdelghani Azil & Enas Ali & Ali H. Kasem Alaboudy & Saad A. Mohamed Abdelwahab, 2023. "Optimized Power Management Approach for Photovoltaic Systems with Hybrid Battery-Supercapacitor Storage," Sustainability, MDPI, vol. 15(19), pages 1-30, September.
    9. Hatti, M. & Meharrar, A. & Tioursi, M., 2011. "Power management strategy in the alternative energy photovoltaic/PEM Fuel Cell hybrid system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 5104-5110.
    10. Breban, Stefan & Saudemont, Christophe & Vieillard, Sébastien & Robyns, Benoît, 2013. "Experimental design and genetic algorithm optimization of a fuzzy-logic supervisor for embedded electrical power systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 91(C), pages 91-107.
    11. Olatomiwa, Lanre & Mekhilef, Saad & Ismail, M.S. & Moghavvemi, M., 2016. "Energy management strategies in hybrid renewable energy systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 821-835.
    12. Das, Barun K. & Hoque, Najmul & Mandal, Soumya & Pal, Tapas Kumar & Raihan, Md Abu, 2017. "A techno-economic feasibility of a stand-alone hybrid power generation for remote area application in Bangladesh," Energy, Elsevier, vol. 134(C), pages 775-788.
    13. Ziogou, Chrysovalantou & Ipsakis, Dimitris & Seferlis, Panos & Bezergianni, Stella & Papadopoulou, Simira & Voutetakis, Spyros, 2013. "Optimal production of renewable hydrogen based on an efficient energy management strategy," Energy, Elsevier, vol. 55(C), pages 58-67.
    14. Hegazy Rezk & N. Kanagaraj & Mujahed Al-Dhaifallah, 2020. "Design and Sensitivity Analysis of Hybrid Photovoltaic-Fuel-Cell-Battery System to Supply a Small Community at Saudi NEOM City," Sustainability, MDPI, vol. 12(8), pages 1-20, April.
    15. Jannet Jamii & Mohamed Trabelsi & Majdi Mansouri & Mohamed Fouazi Mimouni & Wasfi Shatanawi, 2022. "Non-Linear Programming-Based Energy Management for a Wind Farm Coupled with Pumped Hydro Storage System," Sustainability, MDPI, vol. 14(18), pages 1-17, September.
    16. Das, Barun K. & Al-Abdeli, Yasir M. & Kothapalli, Ganesh, 2017. "Optimisation of stand-alone hybrid energy systems supplemented by combustion-based prime movers," Applied Energy, Elsevier, vol. 196(C), pages 18-33.
    17. Blondin, M.J. & Sicard, P. & Pardalos, P.M., 2019. "Controller Tuning Approach with robustness, stability and dynamic criteria for the original AVR System," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 163(C), pages 168-182.
    18. Das, Barun K. & Al-Abdeli, Yasir M. & Woolridge, Matthew, 2019. "Effects of battery technology and load scalability on stand-alone PV/ICE hybrid micro-grid system performance," Energy, Elsevier, vol. 168(C), pages 57-69.
    19. Baños, R. & Manzano-Agugliaro, F. & Montoya, F.G. & Gil, C. & Alcayde, A. & Gómez, J., 2011. "Optimization methods applied to renewable and sustainable energy: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(4), pages 1753-1766, May.

    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:matcom:v:131:y:2017:i:c:p:172-189. 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.journals.elsevier.com/mathematics-and-computers-in-simulation/ .

    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.