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Information Disclosure in VPP - Information Disclosure by Decentralized Coordination in Virtual Power Plants and District Energy Systems

Autor(en):
Bremer, Jörg [DBLP] ;
Lehnhoff, Sebastian [DBLP]
Zusammenfassung
Grouping small, hardly predictable, and volatile energy resources to jointly operating virtual power plants with sufficient flexibility for coordination is widely seen as a key aspect of integrating renewable energy into the grid. For several reasons, self-organizing, agent-based systems are probably the best technology for coordination. A major drawback of many currently existing solutions is the necessity to communicate plain information for negotiation and optimization. Such information contains e.g. possible energy generation schemes or aggregated costs. Previous works have already shown that identification of anonymously sent information is possible. In this paper, we demonstrate the possibility of disaggregating cost structure information as an example of possible leakage of business information in the case of participation in virtual power plants or district energysystems. From this perspective, we derive measures to ensure privacy preservation in decentralized coordination algorithms
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Bremer, J. & Lehnhoff, S., (2022). Information Disclosure in VPP - Information Disclosure by Decentralized Coordination in Virtual Power Plants and District Energy Systems. In: Wohlgemuth, V., Naumann, S., Arndt, H.-K., Behrens, G. & Höb, M. (Hrsg.), EnviroInfo 2022. Bonn: Gesellschaft für Informatik e.V.. (S. 133).
@inproceedings{mci/Bremer2022,
author = {Bremer, Jörg AND Lehnhoff, Sebastian},
title = {Information Disclosure in VPP - Information Disclosure by Decentralized Coordination in Virtual Power Plants and District Energy Systems},
booktitle = {EnviroInfo 2022},
year = {2022},
editor = {Wohlgemuth, Volker AND Naumann, Stefan AND Arndt, Hans-Knud AND Behrens, Grit AND Höb, Maximilian} ,
pages = { 133 },
publisher = {Gesellschaft für Informatik e.V.},
address = {Bonn}
}
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Mehr Information

ISBN: 978-3-88579-722-7
ISSN: 1617-5468
Datum: 2022
Sprache: en (en)
Typ: Text/Conference Paper

Keywords

  • Virtual Power plant
  • Distributed Optimization
  • Self-Organization
  • Data Privacy
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  • P328 - EnviroInfo 2022 [25]

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Gesellschaft für Informatik e.V. (GI), Kontakt: Geschäftsstelle der GI
Diese Digital Library basiert auf DSpace.