Modelling Privacy of Smart Meter Data

Smart meter data form the backbone of various data driven distribution system applications ranging from demand response, outage management, power theft detection, capacitor bank switching to distribution network planning and asset management. However, a consumer's concern for privacy often limits the usage of smart meter data. Privacy preserving algorithms have been proposed to address privacy concern of the consumers. However, lack of a privacy model inhibits estimation of privacy preserved by these algorithms. Privacy pricing can be an alternate approach to encourage smart meter data sharing by incentivizing consumers. However, price estimation of privacy is a challenging task due to the lack of a mathematical privacy model. Unavailability of a privacy model makes it difficult to quantify the privacy of smart meter data. This paper proposes a mathematical model for objective assessment of privacy of smart meter energy data. At first, the possible applications of privacy model of smart meter data are presented. Then, the notion of smart meter data privacy is discussed. Based on this notion, a mathematical model is proposed to quantify the privacy of a time series of energy data. Privacy of practical smart meter data is evaluated using proposed model. The model is also used to study the impact of metering interval and time series length on privacy. The results demonstrate the efficacy of the proposed model.