CITIS devised a ML-based methodology and built a custom software solution for the state-owned energy group Eesti Energia that identifies customers\u2019 energy consumption profiles automatically and detects when those profiles change. The core of the work was machine learning: clustering customers by how they actually use energy, rather than by the categories a utility usually has to hand, and flagging when someone\u2019s pattern shifts. We also developed the user interface for reading the results, and did preliminary work on forecasting consumption time series.<\/p>\n\n\n\n
The collaboration also produced public policy analysis. In June 2023 Andres V\u00f5rk<\/strong> and Helen Poltim\u00e4e published a study (in Estonian) in Riigikogu Toimetised<\/a>, the Estonian parliament\u2019s journal, on how introducing the fixed-price universal service in October 2022 changed household electricity consumption, finding that capping the peak price shifted use back into peak hours.<\/p>\n\n\n\n The project ran from January to December 2022 at the Center of IT Impact Studies, commissioned through procurement, and was carried out by Mihkel Solvak<\/strong>, Peeter Leets<\/strong>, Andres V\u00f5rk<\/strong>, and Taavi Unt<\/strong>.<\/p>\n\n\n\n