Real and Reactive Power Based Optimal Privacy Protection in Smart Grid Demand Response

Cihan Emre Kement, Marija Ilic

Frequent metering of consumption data is crucial for demand side management in smart grids. However, the metered data can easily be processed with nonintrusive appliance load monitoring techniques to infer appliance usage, which provides insight about the private lives of consumers. Existing load shaping techniques for privacy focus only on hiding or altering metered real power, whereas smart meters also collect reactive power data for various purposes. In this work, we present optimizing the consumer privacy in a demand response scheme considering both real and reactive power data. Also, we consider the user cost and comfort as objectives, and build the optimization problem in such a way that the effects of optimizing sub-objectives on the others can be observed. Results show that hiding only real or only reactive power is not sufficient for ensuring privacy and they need to be altered simultaneously. Shaping real and reactive demand at the same time results in more than twofold increase in privacy in terms of mutual information.

Knowledge Graph

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