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Evaluation of Hierarchical, Multi-Agent, Community-Based, Local Energy Markets Based on Key Performance Indicators

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  • Godwin C. Okwuibe

    (School of Engineering and Design, Technical University of Munich, Arcisstrasse 21, 80333 Munich, Germany
    OLI Systems GmbH, Speyerer Strasse 90, 67376 Harthausen, Germany)

  • Amin Shokri Gazafroudi

    (OLI Systems GmbH, Speyerer Strasse 90, 67376 Harthausen, Germany)

  • Sarah Hambridge

    (Grid Singularity, Am Weinhang 9, 10965 Berlin, Germany
    Grid Singularity, Unipessoal, Lda., Av. José Gomes Ferreira, 11-63 (Edificio Atlas II), Algés, 1495-39 Lisbon, Portugal)

  • Christopher Dietrich

    (Grid Singularity, Am Weinhang 9, 10965 Berlin, Germany
    Grid Singularity, Unipessoal, Lda., Av. José Gomes Ferreira, 11-63 (Edificio Atlas II), Algés, 1495-39 Lisbon, Portugal)

  • Ana Trbovich

    (Grid Singularity, Am Weinhang 9, 10965 Berlin, Germany
    Grid Singularity, Unipessoal, Lda., Av. José Gomes Ferreira, 11-63 (Edificio Atlas II), Algés, 1495-39 Lisbon, Portugal)

  • Miadreza Shafie-khah

    (School of Technology and Innovations, University of Vaasa, 65200 Vaasa, Finland)

  • Peter Tzscheutschler

    (School of Engineering and Design, Technical University of Munich, Arcisstrasse 21, 80333 Munich, Germany)

  • Thomas Hamacher

    (School of Engineering and Design, Technical University of Munich, Arcisstrasse 21, 80333 Munich, Germany)

Abstract

In recent years, local energy markets (LEMs) have been introduced to empower end-customers within energy communities at the distribution level of the power system, in order to be able to trade their energy locally in a competitive and fair environment. However, there is still some challenge with regard to the most efficient approach in organising the LEMs for the electricity exchange between consumers and prosumers while ensuring that they are responsible for their electricity-related choices, and concerning which LEM model is suitable for which prosumer or consumer type. This paper presents a hierarchical model for the organisation of agent-based local energy markets. According to the proposed model, prosumers and consumers are enabled to transact electricity within the local energy community and with the grid in a coordinated manner to ensure technical and economic benefits for the LEM’s agents. The model is implemented in a software tool called Grid Singularity Exchange (GSyE) , and it is verified in a real German energy community case study. The simulation results demonstrate that trading electricity within the LEM offers economic and technical benefits compared to transacting with the up-stream grid. This can further lead to the decarbonization of the power system sector. Furthermore, we propose two models for LEMs consisting of multi-layer and single-layer hierarchical agent-based structures. According to our study, the multi-layer hierarchical model is more profitable for household prosumers as compared to trading within the single-layer hierarchical LEM. However, the single-layer LEM is more be beneficial for industrial prosumers.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:10:p:3575-:d:814893
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    References listed on IDEAS

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    1. Gazafroudi, Amin Shokri & Khorasany, Mohsen & Razzaghi, Reza & Laaksonen, Hannu & Shafie-khah, Miadreza, 2021. "Hierarchical approach for coordinating energy and flexibility trading in local energy markets," Applied Energy, Elsevier, vol. 302(C).
    2. Naval, Natalia & Yusta, Jose M., 2021. "Virtual power plant models and electricity markets - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    3. Thomas Morstyn & Niall Farrell & Sarah J. Darby & Malcolm D. McCulloch, 2018. "Using peer-to-peer energy-trading platforms to incentivize prosumers to form federated power plants," Nature Energy, Nature, vol. 3(2), pages 94-101, February.
    4. Zhou, Yue & Wu, Jianzhong & Long, Chao, 2018. "Evaluation of peer-to-peer energy sharing mechanisms based on a multiagent simulation framework," Applied Energy, Elsevier, vol. 222(C), pages 993-1022.
    5. 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.
    6. Pfenninger, Stefan & Staffell, Iain, 2016. "Long-term patterns of European PV output using 30 years of validated hourly reanalysis and satellite data," Energy, Elsevier, vol. 114(C), pages 1251-1265.
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    2. Wolfram Rozas & Rafael Pastor-Vargas & Angel Miguel García-Vico & José Carpio, 2023. "Consumption–Production Profile Categorization in Energy Communities," Energies, MDPI, vol. 16(19), pages 1-27, October.

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