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Virtual Organization Structure for Agent-Based Local Electricity Trading

Author

Listed:
  • Amin Shokri Gazafroudi

    (BISITE Research Group, University of Salamanca, Edificio I+D+i, 37008 Salamanca, Spain)

  • Javier Prieto

    (BISITE Research Group, University of Salamanca, Edificio I+D+i, 37008 Salamanca, Spain
    Air Institute, IoT Digital Innovation Hub (Spain), Carbajosa de la Sagrada, 37188 Salamanca, Spain)

  • Juan Manuel Corchado

    (BISITE Research Group, University of Salamanca, Edificio I+D+i, 37008 Salamanca, Spain
    Air Institute, IoT Digital Innovation Hub (Spain), Carbajosa de la Sagrada, 37188 Salamanca, Spain
    Department of Electronics, Information and Communication, Faculty of Engineering, Osaka Institute of Technology, Osaka 535-8585, Japan
    Pusat Komputeran dan Informatik, Universiti Malaysia Kelantan, Karung Berkunci 36, Pengkaan Chepa, Kota Bharu 16100, Kelantan, Malaysia)

Abstract

End-users are more active because of demand response programs and the penetration of distributed energy resources in the bottom-layer of the power systems. This paper presents a virtual organization of agents of the power distribution grid for local energy trade. An iterative algorithm is proposed; it enables interaction between end-users and the Distribution Company (DisCo). Then, the performance of the proposed algorithm is evaluated in a 33-bus distribution network; its effectiveness is measured in terms of its impact on the energy trading scenarios and, thus, of its contribution to the energy management problem. According to the simulation results, although aggregators do not play the role of decision makers in the proposed model, our iterative algorithm is profitable for them.

Suggested Citation

  • Amin Shokri Gazafroudi & Javier Prieto & Juan Manuel Corchado, 2019. "Virtual Organization Structure for Agent-Based Local Electricity Trading," Energies, MDPI, vol. 12(8), pages 1-11, April.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:8:p:1521-:d:224992
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    References listed on IDEAS

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    1. Francisco Prieto-Castrillo & Amin Shokri Gazafroudi & Javier Prieto & Juan Manuel Corchado, 2018. "An Ising Spin-Based Model to Explore Efficient Flexibility in Distributed Power Systems," Complexity, Hindawi, vol. 2018, pages 1-16, May.
    2. Zhang, Chunyu & Wang, Qi & Wang, Jianhui & Korpås, Magnus & Khodayar, Mohammad E., 2016. "Strategy-making for a proactive distribution company in the real-time market with demand response," Applied Energy, Elsevier, vol. 181(C), pages 540-548.
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    Cited by:

    1. Kühnbach, Matthias & Bekk, Anke & Weidlich, Anke, 2022. "Towards improved prosumer participation: Electricity trading in local markets," Energy, Elsevier, vol. 239(PE).
    2. Hosna Khajeh & Hannu Laaksonen & Amin Shokri Gazafroudi & Miadreza Shafie-khah, 2019. "Towards Flexibility Trading at TSO-DSO-Customer Levels: A Review," Energies, MDPI, vol. 13(1), pages 1-19, December.
    3. Libor Dražan & René Križan & Miroslav Popela, 2021. "Design and Testing of a Low-Tech DEW Generator for Determining Electromagnetic Immunity of Standard Electronic Circuits," Energies, MDPI, vol. 14(11), pages 1-15, May.
    4. Godwin C. Okwuibe & Amin Shokri Gazafroudi & Sarah Hambridge & Christopher Dietrich & Ana Trbovich & Miadreza Shafie-khah & Peter Tzscheutschler & Thomas Hamacher, 2022. "Evaluation of Hierarchical, Multi-Agent, Community-Based, Local Energy Markets Based on Key Performance Indicators," Energies, MDPI, vol. 15(10), pages 1-23, May.
    5. Jin, Xiaolong & Wu, Qiuwei & Jia, Hongjie, 2020. "Local flexibility markets: Literature review on concepts, models and clearing methods," Applied Energy, Elsevier, vol. 261(C).
    6. Pedro Faria & Zita Vale, 2019. "Distributed Energy Resources Management 2018," Energies, MDPI, vol. 13(1), pages 1-4, December.

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