Residential Demand Side Aggregation of Privacy-Conscious Consumers
dc.contributor.author
Chin, Jun Xing
dc.contributor.author
Hug, Gabriela
dc.contributor.author
Bernstein, Andrey
dc.date.accessioned
2021-08-23T14:13:30Z
dc.date.available
2021-08-20T05:48:41Z
dc.date.available
2021-08-23T14:13:30Z
dc.date.issued
2021
dc.identifier.isbn
978-1-6654-3597-0
en_US
dc.identifier.isbn
978-1-6654-1173-8
en_US
dc.identifier.other
10.1109/PowerTech46648.2021.9494989
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/501463
dc.description.abstract
The increasing adoption of smart meters has led to growing concerns regarding privacy risks stemming from the high resolution measurements. This has given rise to privacy protection techniques that physically alter the consumer's energy load profile, masking private information by using localised devices, e.g. batteries or flexible loads. Meanwhile, there has also been increasing interest in aggregating the distributed energy resources (DERs) of residential consumers to provide services to the grid. In this paper, we propose an online distributed algorithm to aggregate the DERs of privacy-conscious consumers to provide services to the grid, whilst preserving their privacy. Results show that the optimisation solution from the distributed method converges to one close to the optimum computed using an ideal centralised solution method, balancing between grid service provision, consumer preferences and privacy protection. More importantly, the distributed method preserves consumer privacy, and does not require high-bandwidth two-way communications infrastructure.
en_US
dc.language.iso
en
en_US
dc.publisher
IEEE
en_US
dc.subject
Ancillary services
en_US
dc.subject
Consumer privacy
en_US
dc.subject
Mutual information
en_US
dc.subject
Online gradient descent
en_US
dc.subject
Smart meter
en_US
dc.title
Residential Demand Side Aggregation of Privacy-Conscious Consumers
en_US
dc.type
Conference Paper
dc.date.published
2021-07-29
ethz.book.title
2021 IEEE Madrid PowerTech
en_US
ethz.pages.start
9494989
en_US
ethz.size
6 p.
en_US
ethz.event
14th IEEE PowerTech Conference (PowerTech 2021)
en_US
ethz.event.location
Online
en_US
ethz.event.date
June 28 – July 2, 2021
en_US
ethz.notes
Conference lecture held on June 29, 2021
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Piscataway, NJ
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02632 - Inst. f. El. Energieübertragung u. Hoch. / Power Systems and High Voltage Lab.::09481 - Hug, Gabriela / Hug, Gabriela
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02632 - Inst. f. El. Energieübertragung u. Hoch. / Power Systems and High Voltage Lab.::09481 - Hug, Gabriela / Hug, Gabriela
en_US
ethz.date.deposited
2021-07-08T08:18:26Z
ethz.source
FORM
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2021-08-23T14:13:36Z
ethz.rosetta.lastUpdated
2023-02-06T22:21:37Z
ethz.rosetta.versionExported
true
dc.identifier.olduri
http://hdl.handle.net/20.500.11850/493504
dc.identifier.olduri
http://hdl.handle.net/20.500.11850/501439
ethz.COinS
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