Evaluating intelligent buildings according to level of service systems integration

The intelligent building is supposed to provide the environment and means for an optimal utilization of the building, according to its designation. This extended function of a building can be achieved only by means of an extensive use of building service systems, such as HVAC, electric power, communication, safety and security, transportation, sanitation, etc. Building intelligence is not related to the sophistication of service systems in a building, but rather to the integration among the various service systems, and between the systems and the building structure. Systems'integration can be accomplished through teamwork planning of the building, starting at the initial design stages of the building. This paper examines some existing buildings claimed to be “intelligenti, according to their level of systems'integration.

Service life prediction of exterior cladding components under standard conditions

An empirical method was developed for the prediction of the service life of building components, based on an evaluation of their actual performance and on the identification of failure mechanisms affecting their durability. The service life of exterior components subjected to normal service conditions is predicted. Four types of exterior claddings are exemplified: cementitious mortar, synthetic rendering, ceramic mosaic, and wet-fixing stone cladding. The proposed prediction models yield high degrees of fit to the data ( R -super-2 in the range of 0.86 to 0.93 at a 0.0001 level of significance). Life cycle costs (LCC) analysis - following service-life prediction results - leads to the conclusion that maintenance and replacements costs account for 10-80% of initial capital costs. Synthetic rendering exhibited the highest LCC effectiveness, reflecting durability and low capital costs. The method can be used for planning preventive maintenance, evaluating economic implications of failures, and planning service life.

Window signalling systems: control strategies and occupant behaviour

Signalling systems that tell building occupants when to open and close windows have become a popular strategy for balancing the comfort benefits of manual windows with the efficiency benefits of automation in mixed-mode buildings. Data from surveys, interviews and site observations in 16 US buildings reveal a diversity of design objectives, control sequences and circumstances to anticipate when designing buildings with window signalling systems. The signals had the strongest influence on occupants’ use of windows when they were visible, the logic behind the controls algorithms was clearly understood, and they were seen as an informational device linked to an explicit internal policy that has to do with efficient and comfortable building operation. Lower levels of participation occurred when occupants tend not to pay attention to their windows, or the signals, unless they are uncomfortable, at which point it matters little what the signals indicate. However, occupants who do discover value in the signals are more likely to be more satisfied with their personal control. Occupants’ reasons for opening windows may include the desire for fresh air or air movement, which is as important to them as temperature adjustment, but admittedly difficult to program into the controls’ algorithms.&nbsp

Smart building management vs. intuitive human control—Lessons learnt from an office building in Hungary

Smart building management and control are adopted nowadays to achieve zero-net energy use in buildings. However, without considering the human dimension, technologies alone do not necessarily guarantee high performance in buildings. An office building was designed and built according to state-of-the-art design and energy management principles in 2008. Despite the expectations of high performance, the owner was facing high utility bills and low user comfort in the building located in Budapest, Hungary. The objective of the project was to evaluate the energy performance and comfort indices of the building, to identify the causes of malfunction and to elaborate a comprehensive energy concept. Firstly, current building conditions and operation parameters were evaluated. Our investigation found that the state-of-the-art building management system was in good conditions but it was operated by building operators and occupants who are not aware of the building management practice. The energy consumption patterns of the building were simulated with energy modelling software. The baseline model was calibrated to annual measured energy consumption, using actual occupant behaviour and presence, based on results of self-reported surveys, occupancy sensors and fan-coil usage data. Realistic occupant behaviour models can capture diversity of occupant behaviour and better represent the real energy use of the building. This way our findings and the effect of our proposed improvements could be more reliable. As part of our final comprehensive energy concept, we proposed intervention measures that would increase indoor thermal comfort and decrease energy consumption of the building. A parametric study was carried out to evaluate and quantify energy, comfort and return on investment of each measure. It was found that in the best case the building could save 23% of annual energy use. Future work includes the follow-up of: occupant reactions to intervention measures, the realized energy savings, the measurement of occupant satisfaction and behavioural changes