When assessing energy demand at the design stage of a building, a building physics bottom up approach is the most commonly used. It is important that the model has the capacity to calculate energy demands and carbon emissions, whilst also taking into account the effect of different building designs and installed technologies on the quality of the indoor environment (Kavgic et al., 2010). Figure 2-8 shows the strengths and weaknesses of this type of model.
Figure 2-8 - Strengths & Weaknesses of Building Physics Approach Based on Source Data: (Kavgic et al., 2010)
In the UK, most energy models are based on the Building Research Establishment Domestic Energy Model (BREDEM), which complies with EU requirements for domestic energy models (Building Standards Institute (BSI), 2008b). Whilst BREDEM has been updated a number of times, including as recently as 2012, (Building Research Establishment (BRE), 2013), the Standard Assessment Procedure 2009 (SAP 2009) is based on an older version (BREDEM 12). This model is currently embedded in UK Building Regulations as a compliance evaluation tool, but is due to be updated in 2014. After this date, SAP 2012 will be integrated into policy, and will utilise the most recent BREDEM model (BREDEM 2012). The development of BREDEM and SAP is shown in Figure 2-9 (Kelly, S. et al., 2012, p. 18).
Strengths
Detailed evaluation of technology Empirical and physical data used Scenario analysis of fabric and technology
combinations possible
Ability to focus on fabric performance before the addition of technological solutions
Weaknesses
Requirement for large amounts of data Impact of occupants evaluated via
assumptions
Fixed inputs can be unsuitable for some dwellings
Based on assumptions and standardised algorithms
Figure 2-9 - Development of SAP and BREDEM in the UK Source: (Kelly, S. et al., 2012, p. 18)
BREDEM requires extensive input data relating to the dwelling construction and installed systems, and this is used, via a series of algorithms, to calculate the energy demands associated with space and water heating, lighting and cooking.
When good quality data is inputted correctly it can provide an accurate prediction of dwelling energy demands (Natarajan et al., 2011). Essentially, the inputs and underlying calculation methods and algorithms for both BREDEM and SAP are largely identical. However, SAP includes more assumptions and fixed values for certain parameters to ensure standardisation in use, whilst BREDEM allows more flexibility in input data. RdSAP is a further simplified version of the model that is used to evaluate existing buildings (Kelly, S. et al., 2011).
A summary of the parameters utilised in the SAP 2009 methodology is given in Figure 2-10, with an example of a blank example worksheet provided in Appendix 1 (Department of Energy & Climate Change (DECC), 2011).
It has been suggested that other methods of assessment, such as the PassivHaus Planning (Design) Package (PHPP), may be more rigorous and detailed in their approach and thus produce more reliable predictions of household energy demand than that derived from SAP (Association for Environmentally Conscious Building (AECB), 2008).
Figure 2-10 - Summary of SAP Structure and Key Parameters Produced by Author
The development of the PassivHaus Standard began in 1991, but it was not formalised until 1995 (Feist et al., 2007). It is essentially a steady state energy modelling tool, with assessments carried out using the standardised PHPP software and methodology (McLeod, R. S. et al., 2012).
The key criteria for compliance with PHPP, defined within the current version of the standard, are (Passivhaus Institute, 2009, p. 1):
S H D W 2/yr
S C D W 2/yr
S H L W 2
S P E D W 2/yr
A C P H 3/(h.m2) @
50Pa)
Limiting performance levels are also applied to element u-values, thermal bridging and air change rates, with recommendations made for specification of white goods and integrated systems (PassivHaus Trust, 2014a). When the requirements and principles of the PHPP framework are applied correctly, the primary aim of the concept can be achieved, which is to design and construct
‘a building, for which thermal comfort can be achieved solely by post-heating or post-cooling of the fresh air mass, which is required to achieve sufficient indoor air quality conditions – without the need for additional recirculation of air’ (PassivHaus Trust, 2014b Web)
Several studies have been undertaken to assess the fundamental differences between SAP and PHPP and the way in which they calculate outputs (Association for Environmentally Conscious Building (AECB), 2008;
Moutzouri, 2011; Passivhaus Trust, 2011; Scottish Building Standards Division (SBSA), 2009). The main areas of divergence include:
• SAP is a compliance tool whilst PHPP is a design tool – this affects the philosophy that is used in the calculation methodology for energy and carbon demands. PHPP includes a fixed target energy usage of 15kWh per m2of useful floor area, per year, while SAP incorporates the use of a notional Part L compliant building for comparison with the proposed design.
• SAP uses internal measurements (including stairwells) in calculations while PHPP uses external measurements (excluding stairwells), which results in the SAP model being more prone to underestimations of heat loss. PHPP is able to inherently incorporate thermal bridges into the calculations, and enables them to be resolved within the physical design.
SAP has the functionality to either include detailed definition of individual junctions between elements or to insert default values, which may increase the likelihood of error in the assessment process.
• Within SAP, there is potential to trade-off occupant comfort against use of renewable technologies and other ‘credits’. PHPP is more focused on the end user and the ability of the property to meet their needs.
• The treated floor area defined in PHPP does not include consideration of flights of stairs with in excess of three steps, while SAP takes account of all stairways (Feist et al., 2007).
• Both models take into account orientation and shading, but weather data is standardised within the SAP model (generally using degree data for the East Pennines). PHPP uses monthly degree data, and more localised weather datasets are utilised.
• PHPP assesses individual window units and excludes evaluation of window effect on lighting requirements, whilst SAP uses a total area of glazing for each facade and considers daylight effects.
• SAP does not specifically account for the effect of passive solar gains in terms of effect on heating/cooling requirements, whilst PHPP facilitates dynamic modelling.
There are numerous other subtle differences between the two techniques, although they are both basically steady state heat loss models that utilise a degree day climate approach, and then deduct internal/solar gains. However, the AECB (2008) and The University of Strathclyde/Scottish Building Standards Division (2009) found that if an identically designed house is modelled using both PHPP and SAP methodology, it will produce different results in terms of heating demands and carbon emissions.
SAP generally underestimates both of these values, and McLeod (2012) raises concerns that the use of SAP rather than PHPP may be concealing the true extent of carbon saving that could be achieved in the UK. Thermal performance as a contributing factor to this will be further investigated within the scope of