Pricing differentially private smart meter data in distribution networks

More electrification in the mobility and building sectors, as well as increased electricity generation from distributed renewable energy sources such as household photovoltaic systems, are two of the most promising paths toward a more environmentally sustainable energy system. Electric power distribution system operators (DSOs) must improve the network’s observability in this context to address a variety of technical and market-related concerns, including local network congestion, flexibility exchanges, and resource allocation. To achieve this goal, DSOs are installing smart meters at end-users’ locations, as well as measuring devices and monitoring systems on low and medium-voltage networks. Despite the fact that smart meters are an important part of this transformation, privacy laws prevent data from being used for anything other than normal operation and billing without the consent of end-users. We present a model for dealing with differentially private data from smart meters. After that, we present an optimization problem for pricing such differentially private smart meters data, taking into account the value generated for the DSO through state estimation. Using real-anonymous smart meter data from a DSO in Switzerland, we evaluate the effectiveness of our suggested mechanism for buying such differentially private data