Digital Twin-Based Simulation of Smart Building Energy Performance: BIM-Integrated MATLAB/Simulink Framework for BACS and SRI Evaluation

The increasing complexity of smart buildings and the tightening requirements of European regulations have amplified the need for integrated modeling environments capable of assessing automation and control strategies in early design stages. This paper presents a digital-twin-based simulation framework that links building information modeling (BIM) data with MATLAB/Simulink models of heating, ventilation, and air conditioning (HVAC), lighting, and shading systems to support the standardized evaluation of Building Automation and Control Systems (BACS) according to EN ISO 52120 and the Smart Readiness Indicator (SRI). The proposed framework enables rapid scenario development, systematic comparison of automation classes, and assessment of predictive control concepts within a unified, regulation-aligned environment. A representative academic building is used to demonstrate how the toolchain supports consistent simulation of operational states, subsystem interactions, and energy-related behaviors across varying control strategies. The results highlight the ability of the framework to capture performance trends, support compliance-driven decision-making, and provide a basis for the gradual introduction of predictive and artificial intelligence (AI)-enabled methods. The approach offers a structured path to more advanced digital-twin-driven building design, verification, and optimization.