IBPSA2015

This paper introduces a longitudinal study monitoring occupants’ window opening behaviour in a mixed-mode office building in Beijing, China, when natural ventilation is specifically used for controlling the building’s indoor thermal environment. Based on the field measured data, the influence of factors, including outdoor air temperature, outdoor PM2.5, indoor air temperature, time of day, occupancy and previous window state, on the observed state of windows is analysed.

This paper investigates how advanced HVAC systems and predictive control can influence the interaction between a house and the grid. The case study corresponds to a house in Toronto, Ontario, Canada, analysed during the heating season.

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 building performance, the owner was facing high utility bills and low user comfort in his building which is located in Budapest, Hungary. The objective of the project presented in this paper was to determine the optimal indoor environmental parameters and HVAC control scheme both from the energy use and the indoor thermal comfort point of view taking into consideration occupant behaviour patterns experienced in the building.

The increasing number of highly insulated and air tight buildings leads to the concern of indoor environment overheating. This research studies the possibility of applying natural ventilation as a way to avoid high temperatures indoors. A monitored passive house was modelled in ESP-r and the impact of natural ventilation on indoor temperatures was simulated. The multi-zonal energy model was coupled with an airflow network and several control strategies were tested for the openings of the dwelling. Thirteen control settings were simulated.

In Europe, the increasingly restricting environmental regulations push the residential building sector to replace pollutant fossil fuel boilers with more environmentally friendly technologies. Double service Air-to-Water-Heat-Pumps (AWHP) are suitable for this purpose as they can assure space heating (SH) and domestic hot water (DHW) generation while reducing CO2 emissions. However, AWHP performances are quite dependent of the commissioning and running processes.

This paper investigates the interaction between supermarket heating, ventilation and air conditioning and refrigeration systems through simulation in EnergyPlus. This interaction has been studied by modelling a generic UK supermarket. The impact on the sum of HVAC and refrigeration energy consumption due to changes in a range of operating conditions was studied. These include the effect of altering HVAC temperature set-points, supply air temperatures and refrigeration case operating temperatures on their overall energy use.

This paper is concerned with the development of data-driven predictive models capable of forecasting commercial building heating loads based on BEM (Building Energy Management) systems recorded variables, as well as weather data. To address the lack of available complete datasets from actual commercial building BEM systems, a detailed representation of a reference building using EnergyPlus was implemented as a benchmark. Data analysis of the simulated results is used to detect relationships between variables and select input variables for the predictive models.

Previous work by the authors has identified that the selection of supply air temperature control reset schedule has the potential to influence total HVAC energy use in Australian office buildings by up to 10%. This previous work has also identified a general but not uniform trend for lower supply air temperatures, which go hand-in-hand with lower airflows, to produce generally improved efficiency relative to high temperature high flow scenarios. However these results also indicated clear evidence that such a generalisation would not always produce the best outcomes.