AI-driven optimal heating of apartment buildings

HeatCheck aims to develop a scalable, commercial-grade, open-source, AI-driven toolchain that merges meter data with ubiquitous wireless heat cost allocator data to optimize heating systems in apartment buildings. District heating operators have focused on supply temperatures and flows to satisfy various demand profiles. However, they typically overlook end-users and substations as beyond their control. Thus, buildings are bottlenecks in the transition to low-temperature district heating.
The HeatCheck toolchain empowers building owners to operate apartment buildings with unprecedented efficiency, in turn, paving the path for low-risk, near-term investments in renewable energy sources and large-scale investments in heat pumps in district heating networks. Ista, Brunata and Techem controls almost the entire Danish market for allocating heat costs in apartments, and combined provide heat metering in 25 million apartments globally.
HeatCheck seeks to leverage that massive data to detect and diagnose faulty heating systems automatically, optimize central controls to constrain heat losses and minimize harm from misuse, improve service offerings using digital-twin-based analytics and actively shift peak loads. The HeatCheck project provides a unique opportunity for heat cost allocation companies, district heating companies, building operators and research institutions to develop new services generating novel revenue streams and ensuring a cost-effective green transition.