Flux Research Group / School of Computing

Privacy-Aware Peak Load Reduction in Smart Homes

Aarushi Sarbhai, Jacobus (Kobus) Van der Merwe, and Sneha Kumar Kasera

International Conference on COMmunication Systems & NETworkS (COMSNETS) 2019.



Smart meters record power consumption data at every minute or even every second. This fine-grained data on electricity usage exposes private information about the residents of the house like the number of occupants, times of occupancy, appliance information, and much more. A solution to obscure this data is to add a battery to each home and use it strategically to manipulate the readings observed at the smart meter. Deploying such a solution at a large scale can result in sudden peaks in the energy usage. This is an alarming concern for the electric utility companies as this may cause outages, making the grid unstable. This paper is the first to expose this shortcoming and propose algorithms to mitigate the problem while maintaining the privacy of the residents. Furthermore, this paper shows that the proposed algorithms are more effective in preserving privacy than existing ones while reducing the peak load.