Who Produces the Peaks? Household Variation in Peak Energy Demand for Space Heating and Domestic Hot Water

Abstract

Extensive research demonstrates the importance of user practices in understanding variations in residential heating demand. Whereas previous studies have investigated variations in aggregated data, e.g., yearly heating consumption, the recent deployment of smart heat meters enables the analysis of households’ energy use with a higher temporal resolution. Such analysis might provide knowledge crucial for managing peak demand in district heating systems with decentralized production units and increased shares of intermittent energy sources, such as wind and solar. This study exploits smart meter heating consumption data from a district heating network combined with socio-economic information for 803 Danish households. To perform this study, a multiple regression analysis was employed to understand the correlations between heat consumption and socio-economical characteristics. Furthermore, this study analyzed the various households’ daily profiles to quantify the differences between the groups. During an average day, the higher-income households consume more energy, especially during the evening peak (17:00–20:00). Blue-collar and unemployed households use less during the morning peak (5:00–9:00). Despite minor differences, household groups have similar temporal patterns that follow institutional rhythms, like working hours. We therefore suggest that attempts to control the timing of heating demand do not rely on individual households’ ability to time-shift energy practices, but instead address the embeddedness in stable socio-temporal structures.

Over- and underconsumption of residential heating: Analyzing occupant impacts on performance gaps between calculated and actual heating demand

“…The years 2019 to 2021, which data for this analysis is based on, was characterized by several lockdowns following Covid-19 pandemic, and the average temperature was slightly lower with 2,887 degree days on average compared to 2,955 degree days for a 10-year period (2012 to 2021) (www.dmi.dk). Finally, the difference between practices related to DHW and space heating might influence the performance gap across energy labels, for example as DHW use seems to constitute larger shares in newer buildings compared to older buildings [23] and as DHW use patterns seem to differ across household types [24].…”

In Control or Being Controlled? Investigating the Control of Space Heating in Smart Homes

“…This is especially relevant in the case of Denmark, where the district heating system holds great potential for enabling energy demand flexibility by including residential buildings in the energy system. A Danish study on time-based district heating consumption data for space and water heating shows that different groups of residents have slightly different patterns of consumption [43]. It is seen how pensioners tend to have less peaking consumption, whereas high-income households and households with children show slightly higher morning peaks compared to others.…”