Leveraging Smart Meter Data to Optimize Grid Investments

The purpose of this project is to develop a software-based toolset that enables distribution system operators
to improve the maintenance and asset management of their grid through prescriptive maintenance and
predictive asset management. Prescriptive maintenance uses digital twins to predict problems and to prescribe
solutions for them. To allow for predictive asset management, the toolset combines available geospatial
datasets with grid operation data to predict fault vulnerability of electrical assets. This way, the toolset
extends asset lifetime, reduces maintenance costs, and maintains the security of power supply. As a
result, the project facilitates the transition towards green energy sources in Denmark by enabling distribution
system operators to minimize costs while simultaneously allowing them to maximize the use of grid
assets, ultimately helping them to meet the demands of increased electrification. Pilot tests and demonstration
of the toolset will happen in collaboration with two Danish DSOs, Dinel A/S and Energi Ikast A/S,
while commercialization of the toolset will be driven by Kamstrup A/S, a global player in the use of energy
data.