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Sökning: id:"swepub:oai:DiVA.org:kth-293101" > Design Framework fo...

Design Framework for Privacy-Aware Demand-Side Management with Realistic Energy Storage Model

Avula, Ramana R., 1993- (författare)
KTH,Teknisk informationsvetenskap
Chin, Jun-Xing (författare)
Power Systems Laboratory, ETH Zurich, Switzerland
Oechtering, Tobias J., 1975- (författare)
KTH,Teknisk informationsvetenskap
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Hug, Gabriela (författare)
Power Systems Laboratory, ETH Zurich, Switzerland
Månsson, Daniel (författare)
KTH,Elektroteknisk teori och konstruktion
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 (creator_code:org_t)
Institute of Electrical and Electronics Engineers (IEEE), 2021
2021
Engelska.
Ingår i: IEEE Transactions on Smart Grid. - : Institute of Electrical and Electronics Engineers (IEEE). - 1949-3053 .- 1949-3061. ; 12:4, s. 3503-3513
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • Demand-side management (DSM) is a process by which the user demand patterns are modified to meet certain desired objectives. Traditionally, DSM was utility-driven, but with an increase in the integration of renewable sources and privacy-conscious consumers, it also becomes a “consumer-driven" process. Promising theoretical studies have shown that privacy can be achieved by shaping the user demand using an energy storage system (ESS). In this paper, we present a framework for utility-driven DSM while considering the user privacy and the ESS operational cost due to its energy losses and capacity degradation. We propose an ESS model using a circuit-based and data-driven approach that can be used to capture the ESS characteristics in control strategy designs. We measure privacy leakage using the Bayesian risk of a hypothesis testing adversary and present a novel recursive algorithm to compute the optimal privacy control strategy. Further, we design an energy-flow control strategy that achieves the Pareto-optimal trade-off between privacy leakage, deviation of demand from a DSM target profile, and the ESS cost. With numerical experiments using real household data and an emulated lithium-ion battery, we show that the desired level of privacy and demand shaping performance can be achieved while reducing the ESS degradation.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)

Nyckelord

Demand-side management
smart meter privacy
energy storage model
Bayesian hypothesis testing
lithium-ion battery degradation
Privacy
Integrated circuit modeling
Hidden Markov models
Data privacy
Energy loss
Degradation
Bayes methods

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