Privacy-preserving and secure schemes for energy storage unit communication in the future smart gri

The future smart grid will enable plug-in electric vehicles (PEVs) and homes to have energy storage units (ESU) that can store the excess power generated from renewable energy sources and sell it to the grid during the peak hours. This process, however, requires the utility company to be able to communicate with the ESUs.;One of the major challenges of PEV deployment is their large-scale simultaneous charging which may stress the power grid and lead to blackout in severe cases. To prevent such situations, optimal charging coordination should be employed. However, optimization schemes require the PEVs to report private information such as the vehicle's location, the parking duration, the battery state-of-charge, etc. To tackle the privacy concerns in power injection and power charging, we propose two schemes in this thesis; 1) A secure and privacy-preserving power injection querying scheme by exploiting the already available Advanced Metering Infrastructure (AMI) and Long-Term Evolution (LTE) cellular networks and 2) A privacy-aware communication scheme for charging coordination for PEVs.;The main idea of the rst scheme is based on collecting power injection bids from storage units and sending their aggregated value to the utility, rather than the individual bids, in order to preserve user privacy. We also develop a bilinear pairing based technique to enable the utility company to ensure the integrity and authenticity of the aggregated bids without accessing the individual bids. We implemented the proposed scheme in an integrated AMI/LTE network using the ns-3 network simulator. Our evaluations have demonstrated that the proposed scheme is secure and can protect user privacy with acceptable communication and computation overhead.;In the second scheme, anonymization and permutation techniques are used to preserve vehicles' anonymity. A temporal charging coordination scheme is then proposed based on a modied knapsack problem formulation in order to maximize the amount of power delivered to the PEVs before they leave the system without exceeding the available maximum charging capacity. Our results demonstrate that both the optimal charging coordination scheme based on the modied knapsack formulation and the privacy-aware charging coordination scheme exhibit an improved performance compared to a rst- come-rst-serve charging coordination benchmark.