This chapter outlines the contextual challenges that give rise to the need for high-resolution performance modelling and simulation. These challenges correspond to the various aspects underpinning government policy and regulations, the competing technical solutions that might be brought to bear, and the often conflicting requirements of stakeholders.

Whilst it has long been recognised that building performance is a multi-variate problem domain (Markus et al. 1972), it is only with the advent of performance simulation that the issue can be adequately addressed at the design stage.

This chapter describes some of the assessments and ratings that are used to evidence acceptable performance and demonstrate compliance with building regulations. In some cases, equations are given to enable BPS+ outputs to be mapped to indices that are not included in a specific program or to support a comparison with what might have been calculated otherwise.

This chapter makes the case for a computational approach to design based on high-resolution models that support holistic, multi-variate appraisals of performance over extended periods and under a range of conditions likely to be experienced in practice. Although such an approach is not routinely practiced at present, it could become widely accepted if it was demonstrated to be better, cheaper, and quicker than the present fragmented approach to design/upgrade stage options appraisal. The chapter that follows then summarises a wide range of applications, in some cases following judicious simplifications applied to an otherwise high-resolution input model.

This chapter considers the application of BPS+ in support of community energy schemes whereby technologies for energy generation are co-located with demands as a means to attain improved resource utilisation. Whether and where this approach is generally viable has yet to be proven.

This chapter addresses the concept of a smart grid (Kamran 2022) defined as an electricity supply network that uses digital communications technology to detect and react to local changes in demand and supply. The issues to be considered within a BPS+ simulation include demand management/response, supply asset dispatching, active network control, accommodating behaviour change, appliance selection, and design for operational resilience. BPS+ has evolved to a level that can address these issues and thereby enable a balance to be struck between the requirements of consumers and network operators.

There can be many reasons why BPS+ predictions do not match reality and consequently fail to deliver design stage expectations - the so-called performance gap (de Wilde 2014). This chapter considers some principal causal factors that can be accommodated within a high-resolution model as required in specific cases. These include design parameter uncertainty, occupant behaviour, operational events, and construction defects.

The world is not running out of energy resources although there are diminishing options that are deemed acceptable in many jurisdictions. From an energy planning perspective, the future need not be viewed in a negative manner as something that is too uncertain to enable informed action: it should be viewed as an opportunity. Simulation offers a practical way to improve upon what has gone before by planning for a more integrated energy system at all scales.

This chapter considers the possibility of establishing large-scale renewable energy assets in a manner that complements matched loads located nearby or remotely distributed but synchronised. To this end, BPS+ can be used to determine the load profiles of target communities (local, remote, existing, or planned) and size corresponding renewable energy technology (RET) installations. In the latter case, this might entail the use of a commercial package such as PVsyst or a free package such as RETScreen in cases where a BPS+ tool does not offer such a modelling feature. This chapter summarises the nature of supply-side models and indicates how they can be utilised to complement BPS+. The presented models, although rudimentary, are considered suitable for inclusion in BPS+ to provide first-order estimate of the available renewable resources. The models correspond to assessment methods as taught by Energy Systems Research Unit (ESRU) staff to students in the Renewable Energy Systems and the Environment MSc course at the University of Strathclyde. Three technologies are briefly covered corresponding to tidal stream, wind, and solar power capture.

ESP-r is a multi-physics modelling tool, which is primarily focused on modelling the performance of the built environment. The generic nature of the tool allows considerable latitude in application scale and detail - for example, to represent explicitly a thermostat, a computer monitor, a vehicle, or a portion of a ship as well as buildings at variable levels of detail. It holds a super-set data model supporting multiple domain solvers as well as acting as a repository for the descriptors needed by third-party tools.

The following scripts should be considered in conjunction with the description given in Section 4.5.

As the construction industry becomes more assertive in its demands of BPS+, it is likely that high on the agenda will be the harmonisation of user interfaces. This will help regularise training at all levels and ensure that users can switch between applications as required.