District-scale energy demand models can be powerful tools for understanding interactions in complex urban areas and optimising energy systems in new developments. The process of coupling characteristics of urban environments with simulation software to achieve accurate results is nascent. This research developed a digital twin through a web map application for Singapore. The impact on the built environment is simulated with pandemic (COVID-19) and climate change scenarios. The former can be observed through varying occupancy rates and average cooling loads in the buildings during the lockdown period. The digital twin dashboard was built with visualisations of the 3D city, real-time data from sensors for some buildings, energy demand simulation results from the City Energy Analyst (CEA) tool, and occupancy rates from WiFi data for some buildings. The ongoing work focuses on formulating a resilience assessment metric to measure the robustness of buildings to these disruptions. The results show that the digital twin approach can support decarbonising initiatives for cities.