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Controlled Self-organization for Steering Local Multi-objective Optimization in Virtual Power Plants

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Highlights in Practical Applications of Agents, Multi-Agent Systems, and Trust-worthiness. The PAAMS Collection (PAAMS 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1233))

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Abstract

The future smart grid has to be operated by rather small and hardly flexible energy resources. Such duty comprises different planning tasks. Virtual power plants powered by multi-agent control are seen as a promising aggregation scheme for coping with problem size and for gaining flexibility for distributed load planning. If agents are allowed to freely include local preferences into decision making the overall solution quality deteriorates significantly if no control mechanism is installed. We scrutinized this deterioration and propose an approach based on controlled self-organization to achieve an overall maximization of integrated local preferences while at the same time preserving global solution quality for grid control as much as possible. Some first results prove the applicability of the general approach. Further research directions and questions for future work are derived from these first results.

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Authors and Affiliations

  1. University of Oldenburgȩ, 26129, Oldenburg, Germany

    Jörg Bremer & Sebastian Lehnhoff

Authors
  1. Jörg Bremer
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  2. Sebastian Lehnhoff
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Corresponding author

Correspondence to Jörg Bremer .

Editor information

Editors and Affiliations

  1. University of Salamanca, Salamanca, Spain

    Fernando De La Prieta

  2. University of Lille, Villeneuve d’Ascq, France

    Philippe Mathieu

  3. Polytechnic University of Valencia, Valencia, Spain

    Jaime Andrés Rincón Arango

  4. German University in Cairo, New Cairo City, Egypt

    Alia El Bolock

  5. Polytechnic University of Valencia, Valencia, Spain

    Elena Del Val

  6. University of Valencia, Valencia, Spain

    Jaume Jordán Prunera

  7. Instituto Superior de Engenharia do Port, Porto, Portugal

    João Carneiro

  8. Complutense University of Madrid, Madrid, Spain

    Rubén Fuentes

  9. National Laboratory for Energy and Geology, Amadora, Portugal

    Fernando Lopes

  10. Polytechnic University of Valencia, Valencia, Spain

    Vicente Julian

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Bremer, J., Lehnhoff, S. (2020). Controlled Self-organization for Steering Local Multi-objective Optimization in Virtual Power Plants. In: De La Prieta, F., et al. Highlights in Practical Applications of Agents, Multi-Agent Systems, and Trust-worthiness. The PAAMS Collection. PAAMS 2020. Communications in Computer and Information Science, vol 1233. Springer, Cham. https://doi.org/10.1007/978-3-030-51999-5_26

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  • DOI: https://doi.org/10.1007/978-3-030-51999-5_26

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