Academic Project: Heriot Watt Post-Graduate Center - Edinburgh, UK

HERIOT WATT POST-GRADUATE CENTER – EDINBURGH, UK Heriot Watt University - Dubai

Table of Contents Introduction Description of Modeled Building Glazing External Shading IES-VE Model Results Annual Carbon Emissions of the Modeled Building Results Analysis Conclusion References Bibliography

4 5 6 7 9 12 13 15 16 17

Introduction This report deals with the performance of the HeriotWatt’s Postgraduate Centre with respect to the energy consumption and carbon emissions. The relatively modern building is in Edinburgh, with both heating and cooling systems present. Firstly, the incomplete IES-VE building model is completed, using the specifications provided. After running the simulations for the modeled building, its annual energy performance data is compared with that of the real building, for which the data already exists from monitoring study. Then the performance of the modeled building is compared to the available industry standards, known for similar nondomestic buildings in the UK. Further justification is provided for the variations that arise between the modeled and existing building energy values. Lastly the energy performance of the actual university campus is compared with that of other non-domestic UK buildings.

Real life building

Description of Modeled Building Incomplete IES-VE Model

The actual building is a mixed-use building, with a total of four floors. The overall area of the actual existing building has been approximately calculated from the floor plans provided; Rough area of real building = (23.8m x 31.1m) x 4 = 2960.7 m2

Missing Zones

Final Complete Model

The IES-VE model is examined for the missing inputs. The basic construction although is modeled but lacks certain essential features. The floors represent different zones. The required input as in the real building is replicated in the model by carrying out the following actions: Missing Zones: Two missing zones are added in the geometry of the building. A lecture room is made above the first-floor office, having height = 3m. Another zone for unheated space is made above the lecture room with height = 1.5m. The slope for this space is 21.3m and plane = 9m.

Glazing Curtain wall and windows are inserted into the walls for the provision of natural daylight. Appropriate glazing has been applied, although some approximations have been made, since exact detailing is not visible in the photos.

East Facade with glazing

South façade – The entire south building side is 100% glazed.

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East façade – 100% glazing is applied to half area of east face, while two windows of height: 1.5m and width: 1m, are added in lecture room 1.

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North façade – Glazing is added for the crush area, on the fourth floor. Two windows are added each in lecture room 1 and 2.

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West façade – Glazing and windows are added in the firstfloor office area and second floor lecture room.

North Facade with glazing

West Facade with glazing

External Shading External Shading in the Actual Building

Local Shade

External Mesh in IES-VE Model

Local shade, having depth 0.4m, is added over the glazed areas (south façade) to prevent the direct sun rays from penetrating in the interior. For the west and east facades, the local shade measures 3.7m in length and 0.2m in width.

There is an external shading mesh which can be seen in the real existing building’s east façade and was similarly built in the IES-VE software model too. This mesh was created having a height of 0.2m. However, due to technical difficulties when the simulation was run, an error was encountered, maybe due to the increased amount of data input. This mesh was later removed for the simulations to run smoothly.

Construction Materials: The default construction template was already set i.e. based on 2002 regulations and was not changed in the model.

Variation Profiles: Variation profiles, in the building template manager specify the present occupancy in the facility, and are applied in the case of lighting, internal heat gains and air exchanges, assuming that nothing is left on at night.

Thermal Templates: First two new thermal templates were created in IES-VE, which were missing from the already existing input; • Lecture rooms – This template resembles the lecture auditorium, but the variation profile is changed to ‘9-5 weekday working’.

• Crush areas – This template resembles the office template, but the internal gains from computer are changed to 5 W/m2.

All the zones are cross-checked in the assign room thermal template option, for their assigned thermal template. This is an important step since IES-VE sometimes assigns the templates automatically, and might have incorrect information put in.

• For offices/manager’s office, ‘office template’ has been assigned from the existing thermal templates.

• For the toilets, ‘toilet template’ is assigned from the list of thermal templates.

• The café is assigned with the ‘café template’.

• Miscellaneous areas, corridors, lobbies and other spaces are assigned the ‘circulation thermal template’.

• Stores, plant rooms, server rooms, lifts, stairs, unheated space and crush area roof have been assigned the ‘voids template’.

Date

IES-VE Model Results The first round of simulation was run when the glazing and missing zones were added to the IES-VE model. The variation profile was also corrected for the additional thermal templates, which were created as part of the requisite input. The total energy, total natural gas and total electricity values thus achieved are presented in the table:

Total Natural Gas (MWh)

Jan 01-31

Total Electricity (MWh) 10.0720

19.2344

Total Energy (MWh) 29.3065

Feb 01-28

8.7603

15.6625

24.4228

Mar 01-31

9.2062

11.1829

20.3891

Apr 01-30

9.6765

7.0291

16.7056

May 01-31

10.2477

2.6319

12.8796

Jun 01-30

9.0919

1.0682

10.1600

Jul 01-31

11.1865

0.8018

11.9882

Aug 01-31

10.9479

0.6615

11.6093

Sep 01-30

9.7247

1.6242

11.3489

Oct 01-31

10.1114

8.7244

18.8357

Nov 01-30

9.1961

14.2899

23.4860

Dec 01-31

9.6340

18.2501

27.8841

117.8549

101.1609

219.0158

Summed Total

DATE

TOTAL TOTAL TOTAL ELECTRICITY NATURAL ENERGY (MWH) GAS (MWH) (MWH)

Jan 01-31

13.5304

16.1555

29.6859

Feb 01-28

11.7706

13.0682

24.8388

Mar 01-31

12.3738

8.7929

21.1667

Apr 01-30

13.0092

5.1450

18.1542

May 01-31

13.8981

1.6124

15.5104

Jun 01-30

12.4029

0.5555

12.9585

Jul 01-31

15.2445

0.3678

15.6123

Aug 01-31

14.8621

0.2762

15.1383

Sep 01-30

13.2009

0.8683

14.0692

Oct 01-31

13.6171

6.4287

20.0458

Nov 01-30

12.3533

11.4862

23.8396

Dec 01-31

12.9413

15.2518

28.1931

159.2044

80.0085

239.2127

Summed Total

•A few more changes were entered in the model, like the internal heat gains for Miscellaneous - TV (10W/m 2) and Computers (5W/m 2). These equipments have been included since; a TV is installed in the café of the real existing building, and it has been assumed that the users might work on their laptops in the café. Subsequently a final simulation is run of the model in the IES-VE software and the values thus achieved are shown in table.

•The significant change in the total energy and total electricity values are since the energy released by the added electrical equipments has a profound effect on the indoor environment. When the internal heat gains are increased, the heating load in the winter is reduced, but more load is added in the electricity consumption and the heating load which is replaced is in a more efficient fuel i.e. gas. As a result the total natural gas value has declined. Moreover there will be an increase in the cooling load in the summer (Comfortable Low Energy Architecture , None)

The following graph shows that the energy consumption due to the total natural gas reduces during the months May – August, since the heating load is less and cooling system will be in use which works on electricity, resulting in a slight increase in the total electricity consumption.

Annual Carbon Emissions of the Modeled Building Date

Total Natural Gas Carbon Emission (kgCO2)

Total Electricity Carbon Emission (kgCO2)

Total Carbon Emission (kgCO2)

Total Carbon Emission Ex. Equip (kgCO2)

Jan 01-31

3199

6935

10194

8357

Feb 01-28

2587

6085

8673

7075

Mar 01-31

1741

6397

8138

6461

Apr 01-30

1019

6726

7744

5987

May 01-31

319

7185

7505

5667

Jun 01-30

110

6414

6522

4925

Jul 01-31

73

7881

7954

6117

Aug 01-31

55

7684

7738

5981

Sep 01-30

172

6825

6997

5319

Oct 01-31

1273

7040

8313

6476

Nov 01-30

2274

6387

8661

6983

Dec 01-31

3020

6691

9711

7953

15842

82308

98150

77301

Summed Total

Results Analysis  According to ECON 19, the annual energy consumption delivered by total gas of a standard air-conditioned office is 97kWh/m2 and that by total electricity is 128kWh/m2, as a good practice. These values have been selected since they are suitable for areas ranging between 2000m 2 to 8000m2. If the energy consumption of the actual Heriot Watt Postgraduate Centre building is calculated, using these industry benchmarks, the figures would be 287.1MWh for total gas consumption and 378.9MWh for total electricity usage. If the modeled building is further compared with these industry benchmarks, it can be found that the model has a better performance in terms of the total energy consumption than various other non-domestic buildings in the UK.

The electricity and gas consumption of the actual building is 294.3MWh and 40.59MWh respectively. These precalculated values have been provided for a period of one year. After comparing these real building values with the modeled building values, which are 159.2MWh for total electricity consumption and 80MWh for total natural gas consumption, it is found that the modeled building has a better performance than the actual building, in terms of energy efficiency. This has been proved by the data available at CarbonBuzz, showing that the measured electricity demands are approximately 85% higher than the predicted values, in university campuses (Morant, 2012). It is to be noted that this result may not be completely true, as energy modeling software do not predict precise actual energy use (Betz, 2013). But the main reason for the poor performance of the actual building could be due to the increased amount of internal heat gains from the neglectful user behavior, poor insulation and inefficient heating systems which were ignored while construction. Another factor which could be responsible for this kind of performance of the real building is ignorance to reliable sources of renewable energy, which are proven to enhance the energy efficiency of a built form. Â

The discrepancies in the modeled and measured energy consumption values might be due to the following aspects: 1. Design Assumptions – The input of data into the building model was significantly carried out based on assumptions. There might be certain inputs which were not taken into consideration like the occupancy patterns, management and control of building services, further internal heat gains.

2. Modeling Software – There could be some errors in the equations used by the IES-VE tool, leading to inaccuracies in the predicted values.

3. Management and Controls – The facilities supervisor has control over the central plant equipment, affecting the energy consumption of the building significantly. Efficient control system leads to a better energy performance, whereas if any inappropriate strategy is employed in the actual building, it can be responsible for the weak performance.

4. User Actions – Although users don’t have a direct control over the control of building services like heating or cooling, but they can still affect the energy consumption by influencing the internal conditions i.e. by opening windows. Moreover, the users might be using various energy consuming equipments such as plug loads, external lighting, which cannot be controlled by the building regulations.

5. Built Quality – The energy performance of a building is highly affected by the quality of its construction. The actual building could be having some of these issues, like gaps in insulation, thermal bridging, which have not been considered in the modeled building. (A.C., 2011) After reviewing the energy consumption values of the non-domestic UK buildings, the modeled building and the real building, it can be concluded that the actual building is not a very high energy building. It has average energy consumption in terms of electricity and quite low energy consumption of natural gas. The electricity consumption could be higher in the actual building since students might be making more use of electronic devices which increases the internal heat gains, reducing the heating load which is covered by the consumption of natural gas.

Another reason for the differences in the industry benchmarks and the actual university postgraduate center energy consumption values could be due to the variation profile, which is weekday 9am to 7pm or weekday 9am to 5pm, but might be exceeded in reality if special programs are held or the students, staff members or the ancillary staff stay on campus to complete their work.

Conclusion

After carrying out this task and from research, it is clear that energy models don’t do a very good job at predicting a building’s actual energy consumption. The simplest explanation for this argument is that these modeling tools are not intended to provide any higher degree of predictive certainty of actual energy use. The energy performance of any building cannot be completely estimated until it is employed by the users. For a better assessment on building energy consumption, collecting data on building systems and post occupancy evaluation plays an important role. Since there was no access to gather information by visiting the premises of the postgraduate center, accurate predictions regarding the built form were not possible to be included in the modeling software, which is a major setback for the discrepancies.

Recommendations for further work: This study highlights the significance of ensuring that the built quality is maintained throughout the construction procedure, so that the real building can be delivered as predicted. To bridge the energy performance gap, the actual consumption must be reduced by regular monitoring and surveys, better control of services and conscious use of equipments by the users, and assumptions should be increased by having a better understanding of the occupant behavior and including accurate loads in the model.

References Material on Internet A.C., M. (2011) Loughborough University Institutional Repository. [online] Available at: <https://dspace.lboro.ac.uk/dspace-jspui/bitstream/2134/9429/7/AnnaCarolinaMenezesPredictedvsActualEnergyPerformanceofNonDomesticBuildings.pdf> [Accessed 8/12/2014].

Betz, F. (2013) Research Gate. [online] Available at: <http://www.researchgate.net/post/What_are_the_driving_factors_behind_the_discrepancies_of_energy_use_in_ buildings_between_simulated_and_measured> [Accessed 9/12/2014].

CampusUK, n.d. Partner Universities. [Online] Available at: http://www.campusuk.com/countries/uk/partners/heriot.php [Accessed 13 November 2019].

Comfortable Low Energy Architecture. (None) CLEAR: Comfortable Low Energy Architecture. [online] Available at: <http://new-learn.info/packages/clear/thermal/buildings/active_systems/internal_gain.html> [Accessed 9/12/2014].

Morant, M. (2012) Constructing Excellence Wales. [online] Available at: <http://www.cewales.org.uk/cew/wpcontent/uploads/Presentation42.pdf> [Accessed 10/12/2014].

Bibliography Material on Internet Menezes, A.C. (2012) Predicted VS. Actual Energy Consumption of Non-domestic Buildings. [online] Available at: < http://www.cibse.org/getmedia/d800431a-1834-48b5-9d9f-e71d19cff52a/04-Menezes-PREDICTED-VS-A CTUAL-ENERGY-CONSUMPTION-OF-NON-DOMESTIC-(1).pdf.aspx > [Accessed 10/12/2014] None. (2013) Improving the energy performance of community buildings. [online] Available at: <https://www.bedford.gov.uk/environment_and_planning_sustainabilitydoc> [Accessed 10/12/2014] Worthen, W. (None) Sustainable AIA: 2031–Why Energy Models Don’t Predict Actual Energy Use. [online] Available at: < http://www.aia.org/practicing/AIAB088189> [Accessed 10/12/2014]

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