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Strategies for Decentralised Balancing Power

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Biologically-Inspired Optimisation Methods

Part of the book series: Studies in Computational Intelligence ((SCI,volume 210))

Abstract

There are many different approaches to central load management in power supply systems, such as direct load control or price signals to control production and consumption. Despite these measures there will always be an imbalance between production and consumption, i.e. due to fluctuating resource availabilities and unforeseen changes in consumption. As CO 2 emissions and sustainable electricity production have entered the focus of attention in politics and industries, ecologically advantageous concepts avoiding inefficiencies in power supply are strongly promoted. In this article, a self-organising approach to small devices such as freezers or washing machines as well as Combined Heat and Power plants (CHP) is presented, which aims at avoiding imbalances in the power network. While each device has its own constraints and specific task (e.g. provide heat or wash clothes), most of them have a limited degree of freedom in their schedules. A P2P approach with an Evolutionary Algorithm in combination with a local search is used to identify suitable partners to cover their production or consumption and thus to adjust the load in a way to minimise network imbalances.

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Author information

Authors and Affiliations

  1. Institute AIFB, Karlsruher Institute of Technology, 76128, Karlsruhe, Germany

    Andreas Kamper

  2. Institute IIP, Karlsruher Institute of Technology, 76128, Karlsruhe, Germany

    Anke Eßer

Authors
  1. Andreas Kamper
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  2. Anke Eßer
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Editor information

Editors and Affiliations

  1. Institute for Integrated and Intelligent Systems, Griffith University, Nathan Campus, 4111, Brisbane, Queensland, Australia

    Andrew Lewis

  2. Institut für Angewandte Informatik und Formale Beschreibungsverfahren - AIFB, Universität Karlsruhe, 76128, Karlsruhe, Germany

    Sanaz Mostaghim

  3. Faculty of Business, Technology and Sustainable Development, Bond University, 4229, Gold Coast, Queensland, Australia

    Marcus Randall

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© 2009 Springer-Verlag Berlin Heidelberg

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Kamper, A., Eßer, A. (2009). Strategies for Decentralised Balancing Power. In: Lewis, A., Mostaghim, S., Randall, M. (eds) Biologically-Inspired Optimisation Methods. Studies in Computational Intelligence, vol 210. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01262-4_10

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  • DOI: https://doi.org/10.1007/978-3-642-01262-4_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01261-7

  • Online ISBN: 978-3-642-01262-4

  • eBook Packages: EngineeringEngineering (R0)

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