Using smart meter data for grid load visualization

Local energy is frequently used to generate sustainable energy. This makes maintaining the balance between energy consumption and energy production far more challenging for grid operators. Grid operators and other players in the energy sector are therefore eager to gain a better understanding of the load on their networks.

For example, grid operator Stedin is looking into ways to use data on energy consumption and generation to create load profiles for capacity calculations and congestion forecasting. However, grid operators cannot simply monitor capacity per consumer because the data involved contains personal information about the consumer and is thus subject to privacy laws.

Using Multi-Party Computation, the grid operators are able to virtually combine and analyze smart meter data while keeping the underlying information confidential.  We are working with Technolution Spark to develop methods that Stedin could use to use smart meter data without breaching consumer privacy. 

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How does Multi-Party Computation work?

Secure Multi-Party Computation (commonly known as MPC) is a cryptographic technique that allows multiple parties to collaborate on sensitive data without the need to reveal their data source. It enables calculations on a joint data set, without parties exchanging or combining datasets.

The data input from an individual party remains hidden from other parties and the result of the analysis is only known to pre-specified parties. With MPC, one can run computations on multiple data sources as if the data were centralized, without the data ever being brought to a central place.

This makes it possible, for example, to combine data from multiple sources in an analysis, without the need to entrust this data to a “third party”, which can be highly beneficial from a data privacy/confidentiality and data security point of view. 

Click here to learn more about Multi-Party Computation

Photo Credit: Matthew Henry on Unsplash

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