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|Title=Generation of Time-of-Use Tariffs for Demand Side Management using Artificial Neural Networks | |Title=Generation of Time-of-Use Tariffs for Demand Side Management using Artificial Neural Networks | ||
|Year=2018 | |Year=2018 | ||
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|DOI Name=10.1145/3208903.3212037 | |DOI Name=10.1145/3208903.3212037 | ||
|Projekt=ENSURE | |Projekt=ENSURE | ||
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Aktuelle Version vom 24. August 2021, 19:56 Uhr
Generation of Time-of-Use Tariffs for Demand Side Management using Artificial Neural Networks
Generation of Time-of-Use Tariffs for Demand Side Management using Artificial Neural Networks
Published: 2018
Juni
Herausgeber: ACM
Buchtitel: Proceedings of the Ninth International Conference on Future Energy Systems (e-Energy '18)
Seiten: 396-398
Verlag: ACM
Erscheinungsort: New York, NY, USA
Organisation: Ninth International Conference on Future Energy Systems (e-Energy '18), ACM
Referierte Veröffentlichung
BibTeX
Kurzfassung
This poster proposes a new method to generate individual time-of-use electricity tariffs to exploit the flexibility of energy prosumers while preserving privacy and minimizing communication effort as well as computational cost. Since an employed tariff structure may be impossible to derive analytically from a particular behavior of a prosumer, artificial neural networks may be used to learn the underlying mechanisms implicitly based on simulated household data. Using the acquired knowledge, such a network could be able to generate suitable tariffs to achieve a desired behavior.
ISBN: 978-1-4503-5767-8
DOI Link: 10.1145/3208903.3212037
Effiziente Algorithmen/en„Effiziente Algorithmen/en“ befindet sich nicht in der Liste (Effiziente Algorithmen, Komplexitätsmanagement, Betriebliche Informationssysteme, Wissensmanagement, Angewandte Technisch-Kognitive Systeme, Information Service Engineering, Critical Information Infrastructures, Web Science und Wissensmanagement, Web Science, Ökonomie und Technologie der eOrganisation, ...) zulässiger Werte für das Attribut „Forschungsgruppe“.