2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2016
DOI: 10.1109/icassp.2016.7472066
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Privacy-preserving energy flow control in smart grids

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Cited by 25 publications
(31 citation statements)
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“…in turn implies that (10) holds for B(b) = b T (q) Vb(q). Therefore, from Corollary 1, the solutions of the MDP belief update equation (12) are safe with respect to the privacy unsafe set (14). Hence, the privacy requirement is satisfied.…”
Section: A Privacy Verification For Mdps Via Sdpsmentioning
confidence: 89%
“…in turn implies that (10) holds for B(b) = b T (q) Vb(q). Therefore, from Corollary 1, the solutions of the MDP belief update equation (12) are safe with respect to the privacy unsafe set (14). Hence, the privacy requirement is satisfied.…”
Section: A Privacy Verification For Mdps Via Sdpsmentioning
confidence: 89%
“…Furthermore, the establishment of smart grids and demand management as well as the fluctuation of power generation due to an increasing percentage of renewable energies are enhancing the issue of increasing energy needs [5,6]. These changes in energy demand and generation are challenging for network operators and power generation facilities, since power needs are becoming less stable and unpredictable while rising at the same time [7,8]. To address those challenges, accurate and fine-grained monitoring of electrical energy consumption within residential environments is needed [2,9] as well as proper demand management [10].…”
Section: Introductionmentioning
confidence: 99%
“…With the sampling rate in the order of seconds, data handling for several months/years becomes feasible and hardware costs are relatively low. However, with the ability to provide realtime information through smart metering and determining detailed household energy consumption, consumer privacy concerns are arising and energy data protection becomes prominent [7,13]. To address these issues, energy monitoring must be carried out cost-effectively and under the consideration of privacy concerns.…”
Section: Introductionmentioning
confidence: 99%
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“…This privacy-by-design approach, also known as load signature moderation, uses ESSs to alter the consumers' energy consumption profile in order to hide the appliances' usage pattern. In [1], a best-effort privacy algorithm is used to hide the appliance usage information, whereas, in [5], a stochastic control model formulated as a partially observable Markov decision process (PO-MDP) is used. In [4], a differential privacy approach is proposed, where noise is added to the consumers' energy consumption using a rechargeable battery.…”
Section: Introductionmentioning
confidence: 99%