User behaviour plays a key role in the energy demand of residential buildings, and its importance will only increase when moving towards nearly-zero-homes. However, little information is available on how users interact with their homes. Due to the lack of informa-tion, user behaviour is often included in building per-formance simulations through one standard user pro-file. To obtain more accurate building simulations, we need user profiles that capture the wide variations in behaviour without making simulations overly compli-cated.

In this study, the feasibility of using thermal buffering enhanced with phase change material (PCM) to enable heat pump load shifting for a typical UK dwelling was investigated by comparing the performance of a buffered, load-shifted heat pump against a reference case. The impact of load shifting on a larger population of heat pumps was also explored.  The results indicate that with adequate buffering the operation of a domestic heat pump can be wholly moved to off-peak periods without adversely affecting space or hot water temperatures.

A valuable skillset for building industry professionals is proficiency in high-level, scripting languages that can automate and perform many common repetitive or technically intensive tasks. This application-focused paper emphasizes the use of the Python program-ming language in various workflows common to the building performance modeling and simulation pro-cess. Python is an open, powerful, and easy-to-learn scripting language with an emphasis on programmer productivity.

The purpose of this study is to assess the capabilities of a thermal model to represent actual building energy consumption when trying to best fit the input data of the model to the actual data of the building in operation. The approach has been applied to a building for which many factors affecting energy use have been monitored for a whole year. Beyond detailed inspection and advanced investigation have been carried on to assess some uncertain parameters.

The discovery of a novel non-rod, non-cone photore-ceptor in the human eye that mediates a number of effects on the brain has sparked a growing interest in incorporating these non-visual effects of light into the design process of buildings. Appropriately–timed light exposure has the potential to stabilize and im-prove circadian rhythms, including sleep, and has di-rect stimulating effects on alertness and performance.

A bottom-up approach is developed for the specification of operational data with a high space-time resolution, to be used as inputs in multi-zone residential building models. These archetype models will be used to analyse demand modulation of total domestic electricity consumption, thus requiring a detailed knowledge of domestic loads. The approach is based on national Time-Use Survey (TUS) resident activity data. To illustrate the approach, the EnergyPlus simulation platform is used to model a multi-zone case study building.

In this paper, two different forms of the non-linear PDE-system for heat and mass transfer in porous materials and their implementation with COMSOL Multiphysics are considered. The φ-based form presents the relative humidity as system variable and leads in general to non-conservative solutions.

Being highly insulated, low energy buildings are very sensitive to variable solar and internal gains. In this context, thermal mass is useful in storing surplus energy, reducing temperature variations and improving thermal comfort. Thus, conduction modelling is fundamental, but not sufficient: appropriate superficial heat transfer modelling is also needed. Therefore, several common simplifying assumptions have been investigated and adapted to the case of high performance buildings.

This study reports the application of a stochastic simulation model that estimates community-scale residential electricity demand and photovoltaic (PV) generation to simulate the voltage of medium- and low-voltage distribution networks. This model enables the evaluation of the impact of PV diffusion and energy management technologies using, for example, battery and electric vehicles, on voltage management.