Update Model

The next step is an update of the initial model to include detailed information about the building, its systems and operation. Each iterative improvement should be committed to the version control repository with a comment, identifying the modification to the initial model and the source of evidence associated with this modification. By linking modifications to clearly defined sources within the evidence hierarchy, it will be possible to later quantify the inherent model uncertainty and perform a more robust sensitivity analysis to identify the most influential parameters which merit further investigation.

3.5.2.1 Geometry

If using an existing model (architectural or engineering BIM), it is essential to check that the model conforms to the actual building, as layout or function may have changed since the original model was developed. If a site survey has been carried out as per section 3.4.1.2, check that the building measurements match with those in the as-built layout or design model. Where there are inconsistencies, update the BES model geometry to reflect these discrepancies, referencing the source survey or documentation.

3.5.2.1 Environment

As discussed in section 3.4.1.3, accurate weather data is essential to simulating building

performance, particularly for highly weather-dependent building types (e.g. offices, schools etc.). These building are generally more susceptible to outside weather conditions due to the nature of their design and operation, compared to factories or other industrial-type facilities which may tend to be dominated more by internal loads. Ideally, the model should use weather data

collected locally, if available. Otherwise, data from the closest available weather station should be used instead.

3.5.2.2 Constructions and Materials

External and internal surface constructions and materials are added according to as-built construction drawings, if available. Again, survey information is useful here as the building may have been retrofitted or upgraded in the past.

Material information is also required for each construction type. This can be obtained from product specification sheets, if supplied. However, this information is not typically available for older buildings. Therefore, guides and standards may be used to acquire this data (CIBSE 2007; ASHRAE 2009). Alternatively, there are a number of useful software packages which may be used to obtain manufacturer-supplied material information for their products. Tools such as BuildDesk U (BuildDesk Ltd 2013) provide information relating to typical building constructions and material properties for the UK and Republic of Ireland.

Figure 3-13: Screenshot from BuildDesk U (BuildDesk Ltd 2013)

It should be noted that not all properties are supplied by the manufacturer. Some values are taken from building regulations or standards, or defined manually by BuildDesk sta ff. However, the tool provides a ‘source rating’ system similar to the source hierarchy defined in the proposed methodology. Table 3-4 highlights the categories of source information quality defined by BuildDesk U.

Table 3-4: Source quality categories defined by BuildDesk U (BuildDesk Ltd 2013)

Class Description

A Data is entered and validated by the manufacturer or supplier. Data is

continuously tested by 3rd party.

B Data is entered and validated by the manufacturer or supplier. Data is certified

by 3rd party.

C Data is entered and validated by the manufacturer or supplier.

D Information is entered by BuildDesk without special agreement with the

manufacturer, supplier or others.

E Information is entered by the user of the BuildDesk software without special

agreement with the manufacturer, supplier or others.

3.5.2.3 Zone Typing

In order to maintain reasonable computational time, certain model simplifications are required. Since models depend on the definition of distinct zones in order to perform heat-balance calculations, a simplified representation of the real building is likely to be required here. Depending on the building under study, the analyst will need to decide on a suitable zoning strategy. A zoning strategy helps to simplify the model by aggregating similar thermal zones within the model. Numerous strategies have been proposed to handle this task (Souza and Alsaadani 2012):

 Zoning based on different spatial activities, spatial performance or building usage;  Zoning based on different HVAC requirements and/or controls;

 Zoning based on different solar gains;  Zoning based on temperature stratification;

 Zoning based on a combination of the above (Raftery, Keane, O’Donnell, et al. 2011). Many of these strategies are described in considerable detail in relevant simulation reference documentation (CIBSE 1998; iSBEM 2006; DesignBuilder Software Ltd 2011; US Department of Energy 2011b). The determination of the best practice for defining a zoning strategy for typical buildings is outside the scope of this study. Furthermore, the most suitable zoning strategy is highly dependent on the requirements on (1) the function and size of the building, (2) the requirement of the BES model (benchmarking, ECM analysis, fault detection, etc.) and (3) the computational and time resources available.

3.5.2.4 HVAC and Plant Information

The next step is to update the plant and heating, ventilation and air-conditioning (HVAC) equipment in the model. This element of the process deserves careful consideration as it is likely to have a significant impact on the performance of the model. Information collected from as- built drawings, mechanical layouts and site visits should be collated and assessed for accuracy. Systems will need to be defined for each zone served. Information pertaining to the system components will also be required, including (Raftery 2009):

 Fans: Type, maximum airflow, pressure, operating efficiency, part load curve;

 Coils: Type, heating/cooling capacity, air/water on/off design temperatures, maximum air/water flow-rates, operating set-point(s);

 Motors: Type, maximum power, operating efficiency;

 Pumps: Type, maximum flow rate and head, part load curve, operating set-point(s);  Boilers: Type, capacity, thermal efficiency, water flow rate and temperature, parasitic

electrical consumption, part load curve, operating set-point(s);

 Chillers: Type, capacity, nominal coefficient of performance, design fluid temperature and flow rate conditions, capacity ratio curve, part load curve, operating set-point(s);  Cooling towers: Type, capacity, fan power, design fluid temperature and flow rate

conditions, part load curve (for variable speed cooling towers), operating set-point(s);

3.5.2.5 Internal Loads

The final step in this phase of model preparation is the addition of internal loads to the model. This will include the following:

 Lighting Loads – the lighting intensity level for the building (defined in Watts or Watts/area) and associated operation schedule. If lighting the lighting circuit is not sub- metered, this data can be obtained from design documents or verified by a lighting audit as part of the site visit. Base-loads may also be attained by sampling the electrical energy consumption for the lighting circuit at different times of the day/week/year.

 Electrical/Plug Loads – this incorporates all of the equipment loads (defined in Watts or Watts/area) for the building (computers, displays, printers, etc.) as well their operating schedule. As with the lighting schedule, if the electrical circuit is not sub-metered, an ‘equipment audit’ will be necessary (see section 4.4.1.2 (b)). Base-loads values may also be

attained by sampling the electrical energy consumption for the plug/equipment circuit at different times of the day/week/year.

 Occupancy – this is the occupancy level (defined as number of people, or people/area) for the building. This is frequently the most difficult parameter to accurately assess. However, valuable information may be obtained from other aggregated data sources (temperature profiles, CO2 profiles, security/access information, RFID trackers, PIR sensors, PC usage, Wi-Fi network traffic etc.).