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Strategies for Decentralised Balancing Power

  • Andreas Kamper
  • Anke Eßer
Chapter
Part of the Studies in Computational Intelligence book series (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.

Keywords

Local Search Evolutionary Algorithm Knapsack Problem Energy Usage Power Supply System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Andreas Kamper
    • 1
  • Anke Eßer
    • 2
  1. 1.Institute AIFBKarlsruher Institute of TechnologyKarlsruheGermany
  2. 2.Institute IIPKarlsruher Institute of TechnologyKarlsruheGermany

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