Society depends on a secure electricity supply which is increasingly important as various sectors are being electrified to substitute fossil fuels. The sustainability targets for the future cannot be met unless the necessary transformation of the power system is addressed. The future power system should be renewable, flexible, intelligent, secure, and resilient. This transformation should be made at acceptable costs, without jeopardising the security of electricity supply. The electricity grid is a crucial enabler for the energy transition. Intensified electrification and digitalisation imposes new challenges and requirements for the grid.  At the same time, the power system will be more exposed to natural disasters in the future due to climate change and increased weather-related stress. It is important to understand the new risk picture and find the right strategies for dealing with the security of electricity supply in the future power system.

This article describes a reference data set for a representative Norwegian radial, medium voltage (MV) electric power distribution system operated at 22 kV. The data set is developed in the Norwegian research centre CINELDI and will in brief be referred to as the CINELDI MV reference system. Data for a real Norwegian distribution system were provided by a distribution grid company. The data have been anonymized and processed to obtain a simplified but still realistic grid model with 124 nodes. The data set consists of the following three parts: 1. Grid data files: describe the base version of the reference system that represents the present-day state of the grid, including information about topology, electrical parameters, and existing load points. 2. Load data files: comprise load demand time series for a year with hourly resolution and scenarios for the possible long-term development of peak load. These data describe an extended version of the reference system with information about possible new load points being added to the system in the future. 3. Reliability data files: contain data necessary for carrying out reliability of supply analyses for the system.