Effects of COVID-19 confinement on the simulation of energy needs and uses of residential buildings in Milan

This paper examines the impact of COVID-19 confinement on the simulation of energy needs and uses of residential buildings in Milan. Data-driven schedules for electricity use before and during lockdown, derived from smart metering data, are applied to an urban building energy model to analyze their effects on energy needs for heating and cooling and the energy use for lighting and for other services. Electricity uses, heating and cooling needs, and total primary energy (TOE) are compared for pre-COVID and during-COVID cases. Electricity increases by 8%, while heating decreases by 10%, and cooling increases by 26%. The 5% decrease in TOE is mainly due to the decrease in heating. The study uses heat maps to display the coefficient of variation of root mean square error (CVRMSE) at different temporal and spatial aggregations, indicating significant differences between pre- and during-COVID cases. The CVRMSE for electricity consumption is highest at the hourly level for single buildings, reaching a maximum of 44, and decreases at higher levels of aggregation. The CVRMSE for TOE is highest at the hourly level for single buildings, reaching a maximum of 230. A scenario is created by combining during-COVID and pre-COVID schedules for a hybrid work model, called post-COVID. The post-COVID scenario results indicate a significant impact of remote work on energy consumption patterns.