Modelling home electricity management for sustainability: The impact of response levels, technological deployment & occupancy

• Smart and sustainable households minimize energy consumption and CO2 emissions.
• Our simulation tool evaluated the influence of technology level deployment.
• Real-time pricing is most economical but inefficient to reduce net CO2 emissions.
• A fully deployed HEMS did not reduce CO2 emissions for small households.
• To reach climate targets, highly energy efficient sensors will be needed.

The evolution of electricity grids into a smart grid requires the inclusion of control systems to control load, flatten peaks and ensure the distribution of electricity. In parallel, the building sector will also be incorporating more control technology and put emphasis on sustainability issues such as reducing CO2 emissions associated with the buildings’ electricity consumption. This article aims at modelling the residential sector and assesses the different levels of technology deployment to control the electricity consumption of household appliances. The number of inhabitants and their habits are also considered, and the response levels of users towards control systems are simulated. For this matter, a Markov-chain algorithm was developed for synthesising the electric load and introducing Home Energy Management System (HEMS). The emission levels from electricity consumption were assessed based on hourly CO2 emission data from electricity production in Finland. Numerous electricity pricing models were also included, to assess the economic impacts of HEMS. The article suggests that a fully deployed HEMS may not be profitable for households with a low number of inhabitants. This is because the power consumption of appliances in stand-by mode offsets the positive impacts of HEMS on the electricity consumption profile.