The Energy Performance of Buildings Directive (EPBD) has set a target to achieve carbon-neutral building stock and generate 80% of its electricity from renewable sources by 2050. While Model Predictive Control (MPC) can contribute significantly to energy flexibility in buildings, its remote implementation remains relatively unexplored, especially in the residential sector. The purpose of this research is to demonstrate the reliability, robustness, and computational efficiency of a cloud-based application of an MPC called Smart Energy Management (SEM) on a multi-family residential building. The SEM was tested on a virtual building model in TRNSYS using an open-source distributed event streaming platform for data exchange and synchronization. Simplified models for thermal behavior prediction, including an R3C3 model of the building, were developed in C++. The SEM was evaluated in eight scenarios with varying weather conditions, optimization criteria, and runtime periods. The results demonstrate that the SEM maintains stability and robustness over a 2-week period with a 15-minute planning resolution while ensuring thermal comfort. The C++ implementation of the optimization algorithm enables SEM deployment on low-spec servers, supporting cost-effective applications in real buildings with minimal intervention.

The Retabit platform is a data-driven tool designed to bridge the gap between building rehabilitation and urban regeneration by integrating energy, economic, and social dimensions into a single framework. Leveraging multiple public data sources, the platform provides actionable insights to local and national authorities, public housing agencies, urban planners, energy service providers, and research institutions, helping to align renovation initiatives with broader urban transformation goals and climate action objectives. The platform consists of two main components: Analyse, for examining building conditions through multidimensional indicators, and Plan, for designing and simulating renovation projects. Retabit contributes to more transparent and informed decision-making, encourages collaboration across sectors, and addresses long-term sustainability by incorporating participatory planning and impact evaluation. Its scalable structure makes it applicable across diverse geographic areas, policy contexts, and domains linked to sustainable urban development.