Cost-Friendly Differential Privacy of Smart Meters Using Energy Storage and Harvesting Devices

Cost-friendly differential privacy (CDP) of smart meters can be preserved by an appropriate charging and discharging mechanism that uses rechargeable batteries (RBs) to generate Laplace distributed random noise. However, the existing CDP methods have several issues. First, the maximum discharge rate of an RB requires to vary with the maximal consumption of houses. Second, the probability of an RB to charge/discharge depends on the demand, regardless of the state-of-charge (SoC) of an RB. Third, in extreme SoC (near-empty or almost fully charged) of an RB, no noise added to the demand. To overcome these, we propose a mechanism in which a novel probability density function is designed to generate near Laplace distributed random noise. We also utilize a renewable energy source with small storage in cascade with an RB to enhance performance. Both theoretical analysis and simulations are performed to demonstrate the effectiveness of our proposed method.

Automated summary

This study proposes a cost-friendly differential privacy (CDP) mechanism for smart meters using rechargeable batteries to generate Laplace distributed random noise. The existing CDP methods face issues such as varying maximal discharge rate, dependence on demand regardless of the state-of-charge (SoC), and no added noise in extreme SoC. To overcome these issues, a new probability density function is designed to generate near Laplace distributed random noise, and a renewable energy source is utilized to enhance performance.