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Design Framework fo...
Design Framework for Privacy-Aware Demand-Side Management with Realistic Energy Storage Model
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- Avula, Ramana R., 1993- (författare)
- KTH,Teknisk informationsvetenskap
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- Chin, Jun-Xing (författare)
- Power Systems Laboratory, ETH Zurich, Switzerland
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- Oechtering, Tobias J., 1975- (författare)
- KTH,Teknisk informationsvetenskap
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- Hug, Gabriela (författare)
- Power Systems Laboratory, ETH Zurich, Switzerland
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- 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.
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Ingår i: IEEE Transactions on Smart Grid. - : Institute of Electrical and Electronics Engineers (IEEE). - 1949-3053 .- 1949-3061. ; 12:4, s. 3503-3513
- Relaterad länk:
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https://kth.diva-por... (primary) (Raw object)
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https://urn.kb.se/re...
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https://doi.org/10.1...
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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
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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