1,543 research outputs found
Differentially Private State Estimation in Distribution Networks with Smart Meters
State estimation is routinely being performed in high-voltage power
transmission grids in order to assist in operation and to detect faulty
equipment. In low- and medium-voltage power distribution grids, on the other
hand, few real-time measurements are traditionally available, and operation is
often conducted based on predicted and historical data. Today, in many parts of
the world, smart meters have been deployed at many customers, and their
measurements could in principle be shared with the operators in real time to
enable improved state estimation. However, customers may feel reluctance in
doing so due to privacy concerns. We therefore propose state estimation schemes
for a distribution grid model, which ensure differential privacy to the
customers. In particular, the state estimation schemes optimize different
performance criteria, and a trade-off between a lower bound on the estimation
performance versus the customers' differential privacy is derived. The proposed
framework is general enough to be applicable also to other distribution
networks, such as water and gas networks
Design of Privacy-Preserving Dynamic Controllers:Special Issue of "Security and Privacy of Distributed Algorithms and Network Systems"
As a quantitative criterion for privacy of “mechanisms” in the form of data-generating processes, the concept of differential privacy was first proposed in computer science and has later been applied to linear dynamical systems. However, differential privacy has not been studied in depth together with other properties of dynamical systems, and it has not been fully utilized for controller design. In this paper, first we clarify that a classical concept in systems and control, input observability (sometimes referred to as left invertibility) has a strong connection with differential privacy. In particular, we show that the Gaussian mechanism can be made highly differentially private by adding small noise if the corresponding system is less input observable. Next, enabled by our new insight into privacy, we develop a method to design dynamic controllers for the classic tracking control problem while addressing privacy concerns. We call the obtained controller through our design method the privacy-preserving controller. The usage of such controllers is further illustrated by an example of tracking the prescribed power supply in a DC microgrid installed with smart meters while keeping the electricity consumers' tracking errors private
Smart Meter Privacy with Renewable Energy and a Finite Capacity Battery
We address the smart meter (SM) privacy problem by considering the
availability of a renewable energy source (RES) and a battery which can be
exploited by a consumer to partially hide the consumption pattern from the
utility provider (UP). Privacy is measured by the mutual information rate
between the consumer's energy consumption and the renewable energy generation
process, and the energy received from the grid, where the latter is known by
the UP through the SM readings, and the former two are to be kept private. By
expressing the information leakage as an additive quantity, we cast the problem
as a stochastic control problem, and formulate the corresponding Bellman
equations.Comment: To appear in IEEE SPAWC 201
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