'Institute of Electrical and Electronics Engineers (IEEE)'
Doi
Abstract
open3Game-theoretic Demand Side Management (DSM)
systems have been investigated as a decentralized approach for
the collaborative scheduling of the usage of domestic electrical
appliances within a set of households. Such systems allow for the
shifting of the starting time of deferrable devices according to
the current energy price or power grid condition, in order to
reduce the individual monthly bill or to adjust the power load
experienced by the grid while meeting the users’ preferences
about the time of use. The drawback of DSM distributed
protocols is that they require each user to communicate his/her
own energy consumption patterns to the other users, which may
leak sensitive information regarding private habits.
This paper proposes a distributed Privacy-Friendly DSM
system which preserves users’ privacy by integrating data aggregation
and perturbation techniques: users decide their schedule
according to aggregated consumption measurements perturbed
by means of Additive White Gaussian Noise (AWGN). We
evaluate the noise power and the size of the set of users required
to achieve a given privacy level, quantified by means of the
Kullback-Leibler divergence. The performance of our proposed
DSM system are compared to the ones obtained by a benchmark
system which does not support privacy preservation in terms of
social cost, peak demand and convergence time. Results show
that privacy can be preserved at the cost of increasing the peak
demand and the number of game iterations, whereas social cost
is only marginally incremented.C Rottondi; A Barbato; G VerticaleRottondi, CRISTINA EMMA MARGHERITA; Barbato, Antimo; Verticale, Giacom