Decarbonization-as-a-service: A mixed-integer linear programming model for optimal retrofit planning in buildings

The decarbonization of the building sector remains a critical component of climate action, as buildings are responsible for a significant share of global CO 2 emissions and energy consumption. Despite numerous efforts, existing approaches often fall short in addressing the complexity of building systems, user-specific characteristics, budgetary constraints and real-world decision-making processes. This study introduces a Mixed-Integer Linear Programming (MILP) methodology embedded within a Decarbonization-as-a-Service (DaaS) framework that supports stakeholders in identifying optimal retrofit strategies tailored to each building’s profile. The framework integrates detailed user, provided inputs—covering passive and active systems, energy usage patterns and renovation budgets, with a structured optimization model that selects among predefined decarbonization actions. These include energy-efficient envelope upgrades, replacements for HVAC and electrical appliances, and installations of photovoltaic (PV) and battery storage systems. The model aims to minimize annual CO 2 emissions while adhering to cost and technical feasibility constraints. The approach is validated through two case studies: one of a single-family residential prototype building model and one of a multi-residential building complex located in Vienna, Austria. Results are compared against the high-fidelity simulators EnergyPlus and SIM-VICUS confirming the accuracy of the proposed energy assessment models. Representative renovation scenarios are then evaluated across different budget levels, showcasing the framework’s ability to achieve up to near-complete decarbonization (97.44% for the Austrian case). These results demonstrate the methodology’s ability to deliver effective, scalable decarbonization pathways aligned with EU climate targets and renovation wave objectives.