IDEAS home Printed from
   My bibliography  Save this article

A multi-layer agent-based model for the analysis of energy distribution networks in urban areas


  • Fichera, Alberto
  • Pluchino, Alessandro
  • Volpe, Rosaria


Significant research contributions and Directives approach the issue of the insertion of renewable-based energy systems on urban territory in order to face with the growing energy needs of citizens. The introduction of such systems gives raise to installers to both satisfy their energy demands and distribute eventual energy excesses to close neighbours. This paper presents a multi-layer agent-based computational model that simulates multiple events of the energy distribution occurring within urban areas. The model runs on the NetLogo platform and aims at elaborating the most suitable strategy when dealing with the design of a network of energy distribution. Experimental data are discussed based on two main scenarios within an operating period of 24 h. Scenarios consider both the variation of the percentages of installers of renewable-based energy systems and the distance along which energy exchanges occur.

Suggested Citation

  • Fichera, Alberto & Pluchino, Alessandro & Volpe, Rosaria, 2018. "A multi-layer agent-based model for the analysis of energy distribution networks in urban areas," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 710-725.
  • Handle: RePEc:eee:phsmap:v:508:y:2018:i:c:p:710-725
    DOI: 10.1016/j.physa.2018.05.124

    Download full text from publisher

    File URL:
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    1. Bracco, Stefano & Dentici, Gabriele & Siri, Silvia, 2016. "DESOD: a mathematical programming tool to optimally design a distributed energy system," Energy, Elsevier, vol. 100(C), pages 298-309.
    2. Lopez-Rodriguez, I. & Hernandez-Tejera, M., 2015. "Infrastructure based on supernodes and software agents for the implementation of energy markets in demand-response programs," Applied Energy, Elsevier, vol. 158(C), pages 1-11.
    3. Weber, C. & Shah, N., 2011. "Optimisation based design of a district energy system for an eco-town in the United Kingdom," Energy, Elsevier, vol. 36(2), pages 1292-1308.
    4. Mehleri, Eugenia D. & Sarimveis, Haralambos & Markatos, Nikolaos C. & Papageorgiou, Lazaros G., 2012. "A mathematical programming approach for optimal design of distributed energy systems at the neighbourhood level," Energy, Elsevier, vol. 44(1), pages 96-104.
    5. Mbodji, Abdoul K. & Ndiaye, Mamadou L. & Ndiaye, Papa A., 2016. "Decentralized control of the hybrid electrical system consumption: A multi-agent approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 972-978.
    6. Cedillos Alvarado, Dagoberto & Acha, Salvador & Shah, Nilay & Markides, Christos N., 2016. "A Technology Selection and Operation (TSO) optimisation model for distributed energy systems: Mathematical formulation and case study," Applied Energy, Elsevier, vol. 180(C), pages 491-503.
    7. Fichera, Alberto & Frasca, Mattia & Volpe, Rosaria, 2017. "Complex networks for the integration of distributed energy systems in urban areas," Applied Energy, Elsevier, vol. 193(C), pages 336-345.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Yang, Dong-xiao & Chen, Zi-yue & Yang, Yong-cong & Nie, Pu-yan, 2019. "Green financial policies and capital flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 135-146.
    2. Alberto Fichera & Elisa Marrasso & Maurizio Sasso & Rosaria Volpe, 2020. "Energy, Environmental and Economic Performance of an Urban Community Hybrid Distributed Energy System," Energies, MDPI, Open Access Journal, vol. 13(10), pages 1-19, May.
    3. Nikolaos Koutsoukis & Pavlos Georgilakis, 2019. "A Chance-Constrained Multistage Planning Method for Active Distribution Networks," Energies, MDPI, Open Access Journal, vol. 12(21), pages 1-19, October.
    4. Amtul Samie Maqbool & Jens Baetens & Sara Lotfi & Lieven Vandevelde & Greet Van Eetvelde, 2019. "Assessing Financial and Flexibility Incentives for Integrating Wind Energy in the Grid Via Agent-Based Modeling," Energies, MDPI, Open Access Journal, vol. 12(22), pages 1-32, November.
    5. Chen, Peipei & Wu, Yi & Zou, Lele, 2019. "Distributive PV trading market in China: A design of multi-agent-based model and its forecast analysis," Energy, Elsevier, vol. 185(C), pages 423-436.
    6. Sara Lumbreras & Sonja Wogrin & Guillermo Navarro & Ilaria Bertazzi & Maria Pereda, 2019. "A Decentralized Solution for Transmission Expansion Planning: Getting Inspiration from Nature," Energies, MDPI, Open Access Journal, vol. 12(23), pages 1-17, November.


    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:phsmap:v:508:y:2018:i:c:p:710-725. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Haili He). General contact details of provider: .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.