English

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.

As the climate warms, the frequency and scale of extremely hot events are likely to increase. This study predicts overheating risk for the city of Sheffield, UK at a spatial resolution of 5km when the diurnal Urban Heat Island effect is included. Local Hot Summer Years for current and future years are introduced based on the outputs from the UK Climate Projections weather generator. It is found that overheating risk in the urban sites is higher than the adjacent sites and the discrepancy increases with changing climate.

Among passive strategies to reduce energy consumption in buildings, we focus on natural ventilation, which can bring an important decrease in temperature during summer depending on climate. Despite its simplicity, it needs particular attention to be efficient and can be improved with building control. In this paper, we focus on a simplified thermal model based on an electrical analogy (6R2C), coupled with a statistical airflow model and calibrated for a residential building in Mediterranean climate.