Building Energy & Operational Carbon

BIPV retrofit workflow: Rhino/BIM building model, weather data, sun path and urban shading analysis feeding a PVsyst energy-loss flow from effective irradiation to inverter output

Assess the electricity generation and life-cycle carbon reduction potential of BIPV in existing building retrofits. Integrate urban-scale solar modelling with LCA to evaluate and optimize retrofit strategies in high-density urban environments.

Exploded view of an instrumented office: weather station, occupancy, temperature and humidity, CO2 and window-contact sensors, HVAC monitoring, electricity and plug-load meters linked through an IoT gateway

Investigate building energy performance and operational carbon emissions through intelligent monitoring and data-driven approaches to improve assessment accuracy and support low-carbon building operation and retrofit strategies.

Four-stage framework: Shanghai sample selection in ArcGIS, a morphology–energy dataset from Rhino simulation, clustering and SHAP-explained regression models, and meso-scale design guidelines with a parameter candidate pool

Extract interpretable morphology parameter ranges for sustainable mesoscale design through a hybrid framework combining prototype-based and explainable machine learning. Identify representative design tasks and practical constraints using structured indicators and empirical Shanghai samples. Investigate morphology–energy interactions across cooling, heating, lighting, and solar potential using explainable surrogate models. Develop evidence-based design guidelines and a parameter candidate pool for real-world optimization.

Workflow from a multi-source urban building database through archetype-based energy modelling and building-level carbon emission maps to mitigation potential, carbon credits and economic benefits

Develop an urban building database to assess building operational carbon emissions. Unlock the potential for emissions mitigation and economic benefits through carbon crediting mechanisms.