Metadata only
Datum
2021Typ
- Conference Paper
ETH Bibliographie
yes
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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. Mehr anzeigen
Publikationsstatus
publishedExterne Links
Buchtitel
2021 IEEE Madrid PowerTechSeiten / Artikelnummer
Verlag
IEEEKonferenz
Thema
Ancillary services; Consumer privacy; Mutual information; Online gradient descent; Smart meterOrganisationseinheit
09481 - Hug, Gabriela / Hug, Gabriela
Anmerkungen
Conference lecture held on June 29, 2021ETH Bibliographie
yes
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