Decentralized Intelligence in Energy Efficient Power Systems
- Power systems are increasingly built from distributed generation units and smart consumers that are able to react to grid conditions. Managing this large number of decentralized electricity sources and flexible loads represent a very huge optimization problem. Both from the regulatory and the computational perspective, no one central coordinator can optimize this overall system. DecentralizedPower systems are increasingly built from distributed generation units and smart consumers that are able to react to grid conditions. Managing this large number of decentralized electricity sources and flexible loads represent a very huge optimization problem. Both from the regulatory and the computational perspective, no one central coordinator can optimize this overall system. Decentralized control mechanisms can, however, distribute the optimization task through price signals or market-based mechanisms. This chapter presents the concepts that enable a decentralized control of demand and supply while enhancing overall efficiency of the electricity system. It highlights both technological and business challenges that result from the realization of these concepts, and presents the state-of-the-art in the respective domains.…
Document Type: | Part of a Book |
---|---|
Zitierlink: | https://opus.hs-offenburg.de/4259 | Bibliografische Angaben |
Title (English): | Decentralized Intelligence in Energy Efficient Power Systems |
Author: | Anke WeidlichORCiDGND, Harald Vogt, Wolfgang Krauss, Patrik Spiess, Marek Jawurek, Martin JohnsStaff Member, Stamatis Karnouskos |
Year of Publication: | 2012 |
Place of publication: | Berlin, Heidelberg |
Publisher: | Springer |
First Page: | 467 |
Last Page: | 486 |
Parent Title (English): | Handbook of Networks in Power Systems |
Editor: | Alexey Sorokin, Steffen Rebennack, Panos M. Pardalos, Niko A. Iliadis, Mario V. F. Pereira |
ISBN: | 978-3-642-23192-6 |
DOI: | https://doi.org/10.1007/978-3-642-23193-3 |
Language: | English | Inhaltliche Informationen |
Institutes: | Forschung / INES - Institut für nachhaltige Energiesysteme |
Fakultät Maschinenbau und Verfahrenstechnik (M+V) | |
Institutes: | Bibliografie |
DDC classes: | 600 Technik, Medizin, angewandte Wissenschaften |
Tag: | Electric power production | Formale Angaben |
Open Access: | Closed Access |
Licence (German): | Urheberrechtlich geschützt |