Design of Optimal Energy Flow Control with Privacy-Cost Trade-Off in Smart Grids
Abstract: As a promising field, the development of smart grid has drawn more and more attention from many countries. A smart meter plays a significant role in a smart grid. It replaces the traditional electricity meter with the ability to frequently transmit instantaneous energy consumptions of the consumer to theenergy provider of the smart grid. From the view of electricity suppliers, it isbeneficial for planning, controlling and billing. However, from consumers’ perspective, the high-resolution energy record may lead to privacy problem, which means the consumers’ behaviour can be revealed by analysing the smart meter readings. In this thesis project, we will focus on the privacy leakage problem of the smart meter. We study the problem of optimal privacy-cost trade-off in a smart grid equipped with an energy provider, an alternative energy source, a smart meter,and an energy control unit. The privacy leakage is modelled as unauthorized detections of the consumer’s behaviours based on the smart meter readings of energy supplies from the energy provider. The control strategy is designed to manage the energy inflows to satisfy the instantaneous energy demands of the consumer and also to optimally trade off the privacy risk and energy cost. To evaluate the privacy risk, we use a Bayesian detection-operational privacy metric. Different scenarios are considered for which we show that their optimization problems can be reduced to linear programmings. Therefore, based on this observation, we propose optimal control strategy design algorithms to solve the optimization problems efficiently.
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