The growing demand for sustainable living solutions has intensified the need for energy-efficient designs in residential buildings. This paper examines the impact of specific measures of energy efficiency in single-family homes by analyzing the trade-offs between energy performance and cost. A recently constructed house in Croatia, representative of the current real estate market, is used as a case study. The study focuses on the role of insulation thickness in exterior walls and roof, evaluating its effects on reducing heat loss and minimizing heating and cooling demand. In addition, an economic analysis is conducted to identify cost-effective energy efficiency improvements. The findings, with payback periods ranging from 2 to over 100 years, underscore the importance of balancing energy savings with financial feasibility, providing valuable insights to homeowners, contractors, and policymakers involved in sustainable residential construction.

The article is focused on buildings with legacy one-pipe heating systems that have inherent problems with high losses and maintaining comfort when classical zone hysteresis and constant forward medium temperature control are applied to them. We show a great potential of predictive control to improve both comfort and energy efficiency in these systems by exploiting the possibilities existing in synchronized operation between rooms and the central heating station of the building. Optimal day-ahead scheduling based on predictive control is applied to assess the efficient operation mode of such a system which is then compared with classical reactive controls. The case study of primary school in Strem, Austria is considered and significant comfort improvement and savings possibilities are revealed.

Predictive control and optimization in buildings proved to be a promising approach in increasing energy efficiency of the sector as one of the largest energy consumer. Zone digitalization is still one of the ongoing issues in older buildings, and has only recently started to be interesting in the residential sector due to high prices of required expert knowledge and automation equipment. However, buildings systems digitalization and networking also brought to fore the system security issues. Distributed approach to zone digitalization and predictive control, enabled by recent advances in embedded technology, implies both hardware topology and control algorithm structure. The paper focuses on a case where each zone holds a separate controller with tailored temperature setpoint prediction and model predictive control algorithm, which independently calculate the optimal heating control laws of the corresponding zones. Furthermore, the controllers are mutually and iteratively bidding toward the joint energy efficiency goal of the whole building. Such control structure enables fast digitalization and optimal joint operation of the building while keeping the independency of the users and retaining the data privacy. Only essential data is transmitted to the central coordinator in form of a summed information, which cannot extrapolate particular user data. Additionally, single zone controller security breach does not inflict damage to the whole system. System resiliency to security issues is therefore strongly increased.