Space heating demand profiles of districts considering temporal dispersion of thermostat settings in individual buildings

Abstract

Future energy infrastructures are expected to be smart, with the application of energy storage and demand-side management strategies. To size the energy storage and assess the flexibility of the heat demand in a district, insight into its heat demand profile is a prerequisite.A tool was developed to generate the hourly space heating demand of a district. A crucial element in the calculation is the behaviour of occupants, particularly the temporal dispersion of thermostat settings in individual buildings. This dispersion smooths out the morning (and evening) peaks in the space heating demand of a district when occupants turn up their thermostats.Hourly gas consumption data were obtained of 8077 buildings with gas fired boilers in 2020. A dynamic resistance capacitance (RC) building model of a single aggregated building representing the 8077 dwellings was used to calculate their space heating demand profile in 2020. A comparison with the actual gas consumption data (corrected for domestic hot water use and cooking) allowed the estimation of the temporal thermostat settings, the dispersion thereof and the thermostat temperature levels of buildings in the district. The combined space heating demand profile of the individual buildings calculated using the same RC building model (each with its own thermostat settings) reproduced the actual space heating demand profile relatively well.