To achieve this, the SCI-BEMS infers user preferences on indoor temperature -which they may even be unable to describe- from their control actions and create personalised user profiles that quantify personal thermal preferences vs. comfort trade-offs. Based on these profiles it automatically adjusts HVAC and water heating according to ambient conditions in the indoor environment.
Heat4Cool aims to deal with the temporal and intra-person heterogeneity of personal preferences in multi-tenant/family households. User comfort preferences are seldom very precise, humans feel comfortable within ranges of temperatures or other ambient characteristics. This enables control strategies ranging from maximum user comfort, maximum energy efficiency with controlled comfort degradation or intermediate combinations energy savings and user comfort levels.
Finally, the SCI-BEMS will not focus at the local household scope, but will have a global view at the level of apartment building and/or district. This enables coordinated inter-household control strategies that can effectively a) reuse energy available anywhere within the building/district that is reusable by another house in order to become as zero-energy as possible toward the grid, and b) shape the reduced building/ district level energy consumption patterns according to the requests of the grid operator