Abstract
The collection of fine-grained consumptions of users in the smart grid enables energy suppliers and grid operators to propose new services (e.g., consumption forecasts and demand-response protocols) allowing to improve the efficiency and reliability of the grid. These services require the knowledge of aggregate consumption of users. However, an aggregate can be vulnerable to reidentification attacks which allow revealing the users’ individual consumption. Revealing an aggregate data is a key privacy concern. This paper focuses on publishing an aggregate of time-series data such as fine-grained consumptions, without indirectly disclosing individual consumptions. We propose novel algorithms which guarantee differential privacy, based on the discrete Fourier transform and the discrete wavelet transform. Experimental results using real data from the Irish Commission for Regulation of Utilities (CRU) demonstrate that our algorithms achieve better utility than previously proposed algorithms.
Highlights
A smart city is a designation given to a city that incorporates information and communication technologies to enhance the quality and performance of urban services such as energy, transportation, and utilities in order to reduce resource consumption, wastage, and overall costs. e overarching aim of a smart city is to enhance the quality of living for its citizens through smart technology [1,2,3].e smart grid is an important part of the smart city
E smart grid modernizes the traditional electricity grid by establishing a communication infrastructure in parallel to the energy delivery network. is infrastructure is used by the grid operators and suppliers to remotely collect finegrained consumptions from household smart meters and to provide new energy services such as consumption forecasts or demand-response. ese services are suitable for improving the efficiency and reliability of the grid, saving energy and, more generally, for optimizing energy usage
(ii) We propose the “clamping Fourier perturbation algorithm (CFPA)” using the clamping mechanism proposed in [18], for reducing the sensitivity, and the noise introduced in FPA. is new algorithm is an improvement of the Fourier perturbation algorithm (FPA)
Summary
A smart city is a designation given to a city that incorporates information and communication technologies to enhance the quality and performance of urban services such as energy, transportation, and utilities in order to reduce resource consumption, wastage, and overall costs. e overarching aim of a smart city is to enhance the quality of living for its citizens through smart technology [1,2,3]. Forecasting enables the supplier to predict future consumptions based on past aggregate data in order to improve the grid and retail operations and enhance energy trading [4], while demand-response (DR) aims to shift the users’ consumption from peak to off-peak periods in order to avoid consumption peaks in the smart city. In order t√o e nsure the desired budget of privacy ε, a factor 2T must be added to the noise, where T is the size of the time-series.
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