Stage-oe-small.jpg

Inproceedings3620

Aus Aifbportal
(Weitergeleitet von Inproceedings3620/en)
Wechseln zu:Navigation, Suche


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

Projekt

ENSURE



Forschungsgruppe

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“.


Forschungsgebiet

Energieinformatik