PeHEMS: Privacy enabled HEMS and load balancing prototype

Abstract

Smart grid efficient load balancing and the need for privacy are, in principle, contradictory. While richer information obtained from frequent energy readings help improve both the prediction and the control of the demand, and, effectively, improve the efficiency of the energy equilibrium production problem, it also gives rise to consumer privacy concerns. This is possible by analysing energy signatures to detect appliance usage and home living patterns of behaviour, which in effect cascades to a range of privacy invasion risks. This paper argues that the objective of energy efficiency might not necessarily be contradictory to protecting user privacy. In particular, we introduce a new notion of smart meter privacy which we call reconciled privacy and we connect it with a simple energy management algorithm that caps the energy a home may consume in 30 minute intervals by using a rechargeable battery system. System benchmarking is underpinned by formulating a methodology to assess a) utility cost savings, b) wholesale energy savings, and c) privacy protection. Our results suggest that the proposed algorithm will protect customer privacy and will improve energy production efficiency as compared with other energy management schemes. This is due to the algorithm's principle of promoting a universal consumption pattern that is close to its average, which in retrospect allows individual usage differences to be absorbed. To support this work, we use data from trials in Bristol city, which forms part of the 3eHouses EU FP7 project, and we present a prototype implementation showcasing the visualisation of privacy and energy control.