Enhancing the Accuracy of Building Performance Simulation through Post-Occupancy Calibration

The performance gap between predicted and actual energy consumption in buildings remains a significant challenge in sustainable construction. This study investigates the role of post-occupancy evaluation (PoE) in refining Building Performance Simulation (BPS) models to enhance accuracy and reliability. A case study approach was employed to analyse a five-storey office building in Sri Lanka, where discrepancies between simulated and actual energy performance were assessed. The study identified HVAC inefficiencies, lighting usage variations, and unpredictable occupant schedules as key contributors to the energy performance gap. A structured calibration process was implemented using empirical PoE data to iteratively refine the simulation model. A Sensitivity analysis was conducted to determine the most influential parameters affecting performance discrepancies. Under this, HVAC inefficiencies were identified as the dominant factor, followed by lighting and daily occupant patterns. The calibration process reduced the energy performance gap from an initial 22.11% to 8.88%, demonstrating a significant improvement in predictive accuracy. Findings underscore the need for a paradigm shift from static, assumption-driven modelling to dynamic, data-informed simulation practices. The study proposes a replicable methodological framework for integrating PoE into BPS workflows, emphasizing real-time monitoring and adaptive controls as essential for performance-driven design. The implications reach design professionals, facility managers, and policymakers who aim to enhance building energy performance and meet long-term sustainability goals.