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Strategies for decentralised balancing power


Andreas Kamper, Anke Esser



Veröffentlicht: Juni 2009
Herausgeber: A. Lewis, S. Mostaghim, M. Randall
Buchtitel: Biologically-inspired Optimisation Methods: Parallel Algorithms, Systems and Applications
Nummer: 210
Seiten: 261-289
Reihe: Studies in Computational Intelligence
Verlag: Springer
Erscheinungsort / Ort: Berlin, Heidelberg
BibTex-ID: kaes09
BibTeX

Kurzfassung
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.

ISBN: 978-3-642-01261-7
DOI Link: 10.1007/978-3-642-01262-4



Forschungsgruppe

Effiziente Algorithmen


Forschungsgebiet
Energieinformatik


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