Integrating activity-based transport and building occupancy models for campus-scale energy management

Arrivals and departures lie at the intersection of travel and building occupancy behaviours which dominate the landscape of energy demand in urban areas. Although transport and building systems are clearly linked, existing studies rarely consider the interactions between these systems in their modelling frameworks, thus restricting the policy-relevant scenarios that can be tested. This paper contributes to the field of data-driven energy modelling by proposing a flexible framework to integrate the modelling of travel and building occupancy behaviours, in which a travel simulator is coupled with a building occupancy model through a proposed mesoscopic link. The framework is operationalised in the context of the South Kensington Campus, Imperial College London, using the UK Time Use Survey data and Wi-Fi traceable logs. Implementing the framework for a hypothetical transport incident (i.e. sudden closure of the nearest underground station) generates people’s occupancy and circulation patterns across buildings, thus providing actionable insights for district-level smart grid planning and management. From a district planning perspective, occupancy schedules and dynamics in closed buildings are sensitive to incidents, whereas open and shared buildings are relatively stable. This finding indicates the need for flexible energy controls and smart grids with energy storage. From a building management perspective, occupancy durations generally reduce when affected by incidents, suggesting shortening the schedules of heating, ventilation and air-conditioning systems. From a facility management perspective, big changes in occupancy of closed buildings indicate unstable demands for the surrounding equipment (e.g. e-scooters, chargers), and efficiencies may be gained by allocating spaces/schedules to meet the dynamic demand.