Energy consumption in non-domestic buildings

The energy consumption associated with non-domestic buildings represents 11% of the UK’s total energy consumption, 11% of Europe and 18% of the USA’s. Annual non-domestic building energy consumption is often presented in the form of average benchmarks, such as 350kWh/m2 for a large air-conditioned building and 200kWh/m2 for a small naturally ventilated office. One problem with benchmark values is that they only highlight total annual energy use, hence giving very little insight into how and where a building is actually consuming energy. Some benchmarks provide a breakdown of energy use by energy category (lights, IT, cooling, heating) however, this data still fails to demonstrate how the energy associated with these categories varies throughout the year. To further understand building energy use, more detailed data and analysis is required. In conjunction with a local council, the electricity demand data for a variety of office, school and public buildings has been made available for analysis. This data consists of half hourly resolution data spanning two years, for 17 types of non-domestic buildings. By performing basic analysis on the data, key trends and patterns in energy use can be identified. These trends can include differences between annual profiles, differences between winter and summer months, and differences in weekday and weekend energy use. Additionally, other variables can be investigated including climate, user behaviour and general building data to determine how they influence a building, hence affect the buildings energy consumption. The paper will describe the creation of a database of half-hourly building energy demand data, along with the collation of corresponding building information (such as floor area and occupancy) and local climate data (from onsite weather stations). A methodology will be proposed to ascertain the degree to which the pattern recognition is possible in non-domestic energy usage, and the variables that should be used to calibrate this data, with the possibility of “standardised” energy profiles as a result.