摘要

This paper analyzes how different heating systems affect hourly electricity consumption in detached houses in Norway. Hourly electricity meter data, weather data, and response data from a household survey are merged into a large panel data set, and multiple regression models are applied to isolate the impacts of different heating systems for each hour of the day during the heating period. The results show that compared to direct electric heating, the additional use of air-to-air heat pumps, wood burning stoves, and oil stoves leads to relatively constant reductions in hourly electricity consumption over the course of the day while largest reductions - especially during hours of morning peak consumption - are achieved by using non-electric central heating systems. The presented method can be applied to other energy carriers, metering intervals and consumer groups and - depending on the data available - be used to model individual and aggregate regional energy demand with a high temporal resolution as well as to analyze how area-wide changes in climatic factors and important consumer characteristics will affect consumption of different energy carriers in smart energy systems.

  • 出版日期2015-12-15