Multi-Party Computation protects privacy-sensitive capacity data
Sustainable energy is often generated locally. This makes it a lot more complicated for grid operators to maintain the balance between energy consumption and energy production. Grid operators and other players in the energy sector are keen, therefore, to have greater insight into the load on their networks. Grid operator Stedin, for example, is looking for possibilities to use data on energy consumption and generation to create load profiles for capacity calculations and congestion forecasts. But grid operators can’t simply monitor capacity per user, as the data involved conveys information about the consumer and is therefore subject to privacy legislation. Technolution Spark and ICT privacy specialist Roseman Labs are studying methods that Stedin could deploy to use smart meter data without breaching consumer privacy.
Fully respecting consumer privacy
Roseman Labs in Breda is specialized in Secure Multi-Party Computation (MPC). This method makes it possible to aggregate data from several smart meters, while ensuring that data from individual meters remains invisible and never leaves the domain of the consumer. The grid operator cannot make the data of individual households visible, but can use encrypted data for calculations. Technolution Spark and Roseman Labs are carrying out a proof of concept for Stedin to demonstrate the applicability and privacy compliance of the MPC method.
Visualizing grid load
For this proof of concept, the partners visualized the aggregated grid load of 6 smart meters on a dashboard in Stedin’s Innovation Lab. Technolution Spark equipped the P1 or data ports of the smart meters with a so-called Edge computer. The Edge computers are all linked to a central computer, the concentrator, running on software from Roseman Labs, which aggregates the data of the meters. Thanks to Roseman Labs’ MPC algorithm, the data of the individual meters remains unknown; only the aggregated data is transmitted to the dashboard, which runs in a cloud environment.
“This project shows how challenges in society, like preventing grid overload, can be met without infringing the privacy of consumers. By using privacy technology, data can be used that is inaccessible to traditional technologies.”
A basis for future adjustments
Visualizing the local grid load is only one of the possible use cases for the data of smart meters. If this proof of concept demonstrates that the privacy of consumers can be fully protected using the MPC method, MPC will be able to play an important role in managing the grid infrastructure.