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Assessing heating and cooling demands in buildings using the AUDITAC Customer Advising Tool (CAT)

Assessing heating and cooling demands in buildings using the AUDITAC Customer Advising Tool (CAT). Dr Ian Knight Cardiff University UK. CAT Basic philosophy. The CAT is based on a mixture of computer modelling and real building Case Studies.

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Assessing heating and cooling demands in buildings using the AUDITAC Customer Advising Tool (CAT)

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  1. Assessing heating and cooling demands in buildings using the AUDITAC Customer Advising Tool (CAT) Dr Ian Knight Cardiff University UK

  2. CAT Basic philosophy • The CAT is based on a mixture of computer modelling and real building Case Studies. • The aim is to assess the variation in the heating and cooling demands that arise from altering various building related parameters. • To obtain some confidence in the findings, the results from this modelling are compared with existing Case Studies to check overall magnitudes and variations of predicted cooling loads. • The CAT references potential Energy Conservation Opportunities (ECO’s)

  3. UK Case Studies used to produce the CAT tool 8 Case Study buildings suitable for inclusion in this work.

  4. Case Studies – UK load breakdowns • An analysis template was used for the Case Studies. Using this template we compared simulated data with measured data to identify and quantify the potential savings through control and operation. • The comparisons allowed us to identify which components contribute most to the cooling demand in each building. • From these studies we were able to identify some common trends to the building loads in these real buildings in the UK. • The main driver for cooling energy loads in the UK buildings studied is the internal gains from activities. The use of external air to provide free cooling is one of the main opportunities to reduce the cooling load.

  5. Comparison of Case Studies with Cell Modelling Results • The detailed modelled UK Case Study Buildings were compared to the nearest generic modelled cell to see how well the ‘cell’ cooling load predictions agreed with real building cooling loads. This provided confidence in the simple cell modelling approach. • The findings from these comparisons were that the modelling gave heating and cooling demand values that were comparable to the Case Study measured values in terms of kWh/m2. There were inevitably some differences due to system efficiencies, operational issues, etc – but overall the comparison provided the sorts of figures anticipated. • We were not able to undertake a similar comparison for other climate types, but have assumed that the modelling is valid for them too.

  6. Analysis of the ‘Cells’ • The ‘cells’ are the basic building blocks of the CAT and describe the main elements of a building that should affect the cooling loads. • Each cell modelled for the CAT is made from multiples of a square plan form of 10m x 10m x 2.4m.

  7. Criteria Plan layout – square, other forms, orientations and overshadowing Plan depth – shallow (10mx10m) medium (20mx20m) deep (30mx30m) Layout – open/cellular mix (10m x 10m cells) Number of storeys – single, top/mid/bottom Glazing ratio – 10, 25, 50, 75, 90% Thermal mass – light/medium/heavy Weather locations – Vienna (Austria), Berlin (Germany), Madrid (Spain), Paris (France), London (UK), Athens (Greece), Rome (Italy), Lisbon (Portugal) and Stockholm (Sweden). Other locations Parameters U-values (fabric) – 0.1, 0.25, 0.5, 1, 2, 4 U-values (window) 0.5, 1, 2, 3, 6 Solar Heat Gain Coefficient (SHGC) – 0.1, 0.3, 0.5, 0.7, 0.9 Air change rate (infiltration only) – 0.1,0.25, 0.5, 1, 2, 4 Internal Gains (W/m2) – 10, 20, 40, 80, 120, 160 Hours of use of the heating and cooling systems – continuous, occupancy hours only, optimum start/stop Variation in heating and cooling setpoints – 21°C (Heat) and 24°C (Cool). 19 to 25° cooling setpoint in 1°C intervals Variation in occupancy, equipment and lighting schedules – 08:00 to 18:00, continuous, 08:00 to 21:00 Spatial distribution of cooling loads Matrix of combinations modelled for Simplified Cube Building

  8. Cells – details of runs • 3 plan depths – all runs • 3 thermal mass – all runs • 6 window:wall glazing ratios – all runs • 9 weather files/locations – all runs (Data obtained from Energy+ v1.4 weather files) This gives us an initial number of runs (486) in which all combinations are covered. For each of these runs a further series of modelling tests are undertaken where the cell values for the parameters below are kept at their average value while one parameter is altered over its range. • 6 fabric U-values – average value 0.5 W/m2K • 5 window U-values - average value 3.0 W/m2K • 5 Solar Heat Gain Coefficients - average value 0.5 • 6 air changes - average value 0.5 airchanges per hour (ac/h) • 6 internal gains - average value 40 W/m2

  9. CAT database data entry page • The database front end is shown alongside. The CAT first requires the user to choose the criteria which best describe the building or part of the building to be audited.

  10. CAT database data entry page (2) • This page further allows entry of information about some building parameters as well. These values are used to set the graphs shown in the results page – default values are preset for convenience. • The page also allows estimates of the heating and cooling systems overall efficiencies to be entered, along with the carbon intensity of the energy consumed in these systems. This allows an estimation of the effect of any changes in the overall carbon emissions to be displayed in the results page as well. • The overall carbon emissions are important to ensure that effects on other building energy demands are not neglected when attempting to reduce cooling use.

  11. CAT database results page • Part of the CAT database results page is shown alongside. • The database values are displayed as a series of graphs showing how the heating and cooling demands for the building are predicted to vary as a percentage change from the initial parameter value entered, if the various building parameters are altered over the likely ranges to be found in practice. • The database does not allow the calculation of the combined effect of variations in more than one parameter, as we have insufficient runs with the required combinations to do this at present

  12. UK Greece Fabric Window Infiltration Int. Gains CAT Database • The database is populated only with data from the modelling runs. • In total there are 11,178 combinations of building variables in the database, covering 9 countries. • The database is available online at www.cardiff.ac.uk/archi/research/auditac/index.htmlor standalone on the CD-ROM from the project • The standalone database uses a standalone server which does not require any installation and can be run directly from the CD.

  13. Effect of variations in A/C system parameters • The CAT does not show the effect of A/C system variations. • Currently these have to be assessed using a separate tool also available from AUDITAC

  14. Generation of Inspection and Audit advice using the CAT • Using the CAT the Inspector or Auditor can quickly decide which aspects of the building and occupancy he should assess on his visit, and the potential magnitude of the reduction in A/C cooling demand to be obtained from certain actions such as reducing the solar heat gains or internal gains. • The CAT provides a visual warning of potential adverse effects on overall Carbon Emissions from focussing only on the cooling effects. • The CAT provides a direct link to the descriptions of the generic Energy Conservation Opportunities potentially applicable in the building being inspected or audited.

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