Brightcon 2026, hackathon and courses

Highlights:

• Introduction of Lighthouse, a Python package integrating Brightway and premise
• Flexible building modelling framework
• Automated generation of the solution space of phased renovation scenarios
• Time-resolved life cycle assessment with dynamic life cycle inventory
• Advanced decision-support capabilities
• Open-source, scalable, and interoperable design

Abstract

The urgent need to decarbonise the European building stock, as highlighted by the EU Renovation Wave, requires robust and transparent tools to support large-scale renovation decision-making. A significant share of existing buildings must undergo deep energy renovation in the coming decades, raising complex questions about optimal renovation strategies. However, current building LCA practices largely represent renovation as a single event, failing to capture the evolutive nature of buildings, which is shaped by financial, technological and regulatory constraints.
This context led to the development of Lighthouse, a Python package designed to systematically generate and evaluate building renovation scenarios. Lighthouse allows users to model a building by selecting an archetype and specifying its dimensions, material composition, systems, and renovation history. Based on a flexible set of renovation measures and constraints, the tool automatically generates all compatible renovation scenarios.
For each scenario, Lighthouse performs a comprehensive, time-resolved life cycle assessment, including dynamic updates to the whole life cycle inventory through integration with premise and the Brightway ecosystem. The tool additionally provides multiple analytical tools to support decision-making, including scenario comparison, sensitivity analysis, and Pareto front exploration based on characteristics occurrences.
Lighthouse directly addresses key limitations in current LCA practices by providing a way to navigate the uncertainty related to the evolutive nature of buildings. The tool will soon be released as an open-source Python package. Developed with scalability and interoperability in mind, it supports applications from single buildings to urban-scale analyses and integration of external tools such as EnergyPlus. Its presentation in the “Open Tools and Development” session highlights its contribution to transparency, reproducibility, and community-driven development.