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.
|Project Period||September 1., 2022 to August 1., 2025|
|Total Budget||DKK 7.6 million|
|Organization Managing the Project||SDU CEI|
|SDU Project Manager||Hamid Reza Shaker|
|Additional Partners||Energi Ikast A/S