Privacy-Friendly Load Scheduling of Deferrable and Interruptible Domestic Appliances in Smart Grids

The massive integration of renewable energy sources in the power grid ecosystem with the aim of reducing carbon emissions must cope with their intrinsically intermittent and unpredictable nature. Therefore, the grid must improve its capability of controlling the energy demand by adapting the power consumption curve to match the trend of green energy generation. This could be done by scheduling the activities of deferrable and/or interruptible electrical appliances. However, communicating the users' needs about the usage of their appliances also leaks sensitive information about their habits and lifestyles, thus arising privacy concerns. This paper proposes a framework to allow the coordination of energy consumption without compromising the privacy of the users: the service requests generated by the domestic appliances are divided into crypto-shares using Shamir Secret Sharing scheme and collected through an anonymous routing protocol by a set of schedulers, which schedule the requests by directly operating on the shares. We discuss the security guarantees provided by our proposed infrastructure and evaluate its performance, comparing it with the optimal scheduling obtained by means of an Integer Linear Programming formulation

Privacy-friendly appliance load scheduling in smart grids

Abstract—The massive integration of renewable energy sources into the power grid ecosystem with the aim of reducing carbon emissions must cope with their intrinsically intermittent and unpredictable nature. Therefore, the grid must improve its capability of controlling the energy demand by adapting the power consumption curve to match the trend of green energy generation. This could be done by scheduling the activities of deferrable electrical appliances. However, communicating the users ’ needs about the usage of the electrical appliances leaks sensitive information about habits and lifestyles of the customers, thus arising privacy concerns. This paper proposes a privacy-preserving framework to allow the coordination of energy con-sumption without compromising the privacy of the users: the ser-vice requests generated by the domestic appliances are diveded in crypto-shares using Shamir Secret Sharing scheme and collected through an anonymous routing protocol based on Crowds by a set of schedulers, which schedule the requests operating directly on the shares. We discuss the security guarantees provided by our proposed infrastructure and evaluate its performance, comparing it with the optimal scheduling obtained through an Integer Linear Programming formulation. I

Evaluation of the Precision-Privacy Tradeoff of Data Perturbation for Smart Metering

Abstract: Smart grid users and standardization committees require that utilities and third parties collecting metering data employ techniques for limiting the level of precision of the gathered household measurements to a granularity no finer than what is required for providing the expected service. Data aggregation and data perturbation are two such techniques. This paper provides quantitative means to identify a tradeoff between the aggregation set size, the precision on the aggregated measurements, and the privacy level. This is achieved by formally defining an attack to the privacy of an individual user and calculating how much its success probability is reduced by applying data perturbation. Under the assumption of time-correlation of the measurements, colored noise can be used to even further reduce the success probability. The tightness of the analytical results is evaluated by comparing them to experimental data

From a Barrier to a Bridge: Data-Privacy in Deregulated Smart Grids

The introduction of so-called smart meters involves detailed consumption data. While this data plays a key role in integrating volatile renewable energy sources, a side effect is that it can reveal sensitive personal information. Concerns and protests led to a stopped smart meter rollout yet. In deregulated electricity markets, data-privacy is even more at risk: The UK, Texas and Ontario decided for a nation-wide communication intermediary in order to facilitate the exchange of the vast amount of smart meter data. However, this operational efficiency is achieved by the fact that an intermediary is a single point of failure. We present an approach based on encryption to secure the intermediary against privacy invasions and we can show that our prototypical implementation meets even restrictive requirements for large-scale data handling and processing. By aiming at customers’ confidence in smart metering, our solution might lay the ground for an ecosystem of energy services

On security and privacy of consensus-based protocols in blockchain and smart grid

In recent times, distributed consensus protocols have received widespread attention in the area of blockchain and smart grid. Consensus algorithms aim to solve an agreement problem among a set of nodes in a distributed environment. Participants in a blockchain use consensus algorithms to agree on data blocks containing an ordered set of transactions. Similarly, agents in the smart grid employ consensus to agree on specific values (e.g., energy output, market-clearing price, control parameters) in distributed energy management protocols. This thesis focuses on the security and privacy aspects of a few popular consensus-based protocols in blockchain and smart grid. In the blockchain area, we analyze the consensus protocol of one of the most popular payment systems: Ripple. We show how the parameters chosen by the Ripple designers do not prevent the occurrence of forks in the system. Furthermore, we provide the conditions to prevent any fork in the Ripple network. In the smart grid area, we discuss the privacy issues in the Economic Dispatch (ED) optimization problem and some of its recent solutions using distributed consensus-based approaches. We analyze two state of the art consensus-based ED protocols from Yang et al. (2013) and Binetti et al. (2014). We show how these protocols leak private information about the participants. We propose privacy-preserving versions of these consensus-based ED protocols. In some cases, we also improve upon the communication cost