  Frequent metering of electricity consumption is crucial for demand side
management in smart grids. However, metered data can be processed fairly easily
by employing well-established nonintrusive appliance load monitoring techniques
to infer appliance usage, which reveals information about consumers' private
lives. Existing load shaping techniques for privacy primarily focus only on
altering metered real power, whereas smart meters collect reactive power
consumption data as well for various purposes. This study addresses consumer
privacy preservation via load shaping in a demand response scheme, considering
both real and reactive power. We build a multi-objective optimization framework
that enables us to characterize the interplay between privacy maximization,
user cost minimization, and user discomfort minimization objectives. Our
results reveal that minimizing information leakage due to a single component,
e.g., real power, would suffer from overlooking information leakage due to the
other component, e.g., reactive power, causing sub-optimal decisions. In fact,
joint shaping of real and reactive power components results in the best
possible privacy preservation performance, which leads to more than a twofold
increase in privacy in terms of mutual information.
