Supervised classification with interdependent variables to support targeted energy efficiency measures in the residential sector

Background Reducing energy consumption is the best sustainable long-term answer to the challenges associated with increasing demand for energy, fluctuating oil prices, uncertain energy supplies, and fears of global warming (European commission 2008; Wenig et al. 2015). Since the household sector represents around 30 % of the final global energy consumption (International Energy Agency 2014), customized energy efficiency measures can contribute significantly to the reduction of air pollution, carbon emissions, and economic growth. There is a wide range of potential courses of action that can encourage energy efficiency in dwellings, including flexible pricing schemes, load shifting, and direct feedback mechanisms (Sodenkamp et al. 2015). The major challenge is however to decide upon the appropriate energy efficiency measures in the circumstances when household profiles are unknown. Abstract