Simulation-Based Validation of Energy Performance Models Across Ghana’s Climatic Zones: Pathways to Sustainable Office Buildings

Energy efficiency in office buildings is pivotal to Africa’s sustainable development agenda. In Ghana, improving building performance aligns with AU Agenda 2063’s vision for resilient infrastructure and resource-efficient cities. This study evaluates the energy performance of three existing office buildings in Ghana (CSB 1, CSB 2, and CSB 3) strategically selected across Ghana’s distinct sub-climatic zones (coastal, forest, and savannah). Whole-building energy models were developed in eQUEST software and calibrated against 2022 monthly electricity utility records. The simulation models demonstrated strong predictive accuracy in accordance with ASHRAE Guideline 14 statistical criteria, achieving Coefficient of Determination (R2) values of 0.908, 0.752, and 0.948, and Coefficient of Variation of the Root Mean Square Error (CV(RMSE)) values of 12.24%, 14.84%, and 16.32% for CSB 1, CSB 2, and CSB 3 respectively. Each validated baseline model was subsequently assessed under five energy efficiency modification scenarios. Baseline Energy Performance Index (EPI) values were established at 131.84 kWh/m²/yr. (CSB 1), 114.31 kWh/m²/yr. (CSB 2), and 132.31 kWh/m²/yr. (CSB 3). Sensitivity analysis revealed that integrating combined active and passive efficiency strategies yielded the most substantial optimisations, reducing EPI values to 117.18 kWh/m²/yr., 103.52 kWh/m²/yr., and 114.18 kWh/m²/yr., respectively. These reductions represent individual annual operational energy savings of 11.12% for CSB 1, 9.45% for CSB 2, and 13.70% for CSB 3. By establishing calibrated empirical baselines across distinct microclimates, this research contributes to the growing discourse on sustainable building practices in sub- Saharan Africa by addressing the tropical building performance gap and providing an evidence-based framework for targeted retrofits. A Human-Centric Governance Framework for Responsible Human-AI Collaboration in The Built Environment Systems: Integrating Human and Machine Epistemologies Within Industry 5.0