Energy Renovation Explorer helps users explore, optimize, and match retrofit scenarios with market-available product combinations. It focuses on the selection of passive energy solutions and their combinations (namely envelope solutions for walls, windows, roofs and external shading devices) to minimize heating and cooling loads.
The tool is built upon several algorithmic techniques including machine learning (ML) for performance prediction, multi-objective genetic optimization to find the non-dominated, optimal solutions and classification algorithms (k-nearest neighborhood) to associate the selected component properties with existing market-available products (only in Luxembourg).
The tool also help users explore the solution space by means of expressive data visualizations and also supports the comparative analysis between multiple selected options. The selected optimal passive solutions are passed over to the Retrofit Solutions Impact Dashboard for the calculation of KPIs for both active and passive systems.