Currie Community High School Energy audit report

David Jenkins1, Gillian Menzies

1, Richard Kilpatrick

1, and Tessa Parnell

2

1 Urban Energy Research Group, School of Built Environment, Heriot-Watt University, Edinburgh

2 Mott-MacDonald Fulcrum, London

1. Introduction

This report is an overview of the energy consumption and behaviour of Currie Community High

School (CCHS), as part of a UK Energy Research Centre/NESTA funded study “Measuring Climate

Change Good Practice in Schools”. This overview is intended to inform the wider study, which

investigates the effect of an exemplary low energy school within a local community.

CCHS was built in the mid-1960s with a series of refurbishments carried out in the 1990s. The

school have recently invested in a small-scale wind turbine and solar thermal installation, the

latter used to heat the swimming pool (though these post-date the energy data used in this

report). The primary form of space and water heating is mains gas and other services (IT, cooking

etc) are typical of a modern secondary school. Low energy lighting, such as compact and tubular

fluorescent, is prevalent throughout the building, though there are aspects to the construction

of the building that are less efficient – and this is typical of the building construction age.

The school also has a well-established sustainability ethic, which influences their teaching and

public outreach programmes. Like many schools in built-up areas, the building is also used for

evening classes and other extra-curricular activities.

The work described in this report is being led by University of Leeds, with Heriot-Watt University

managing the energy consumption data analysis overviewed in this report. Canterbury Christ

Church University and Mott MacDonald are also involved as project partners. This energy report

will aim to analyse the available energy data and draw comparisons with other schools and

industry benchmarks.

2. Annual and monthly energy consumption patterns

Energy consumption data was provided by the school at different intervals. Electrical demand

data was available in the form of half-hourly measurements, while monthly gas bill data (for

heating and hot water) was also provided. While the temporal detail in the electrical demand

data will be explored in later sections, to highlight year-on-year changes to the energy patterns

of the school the monthly data for both electrical and gas consumption will now be examined.

2.1 Boiler consumption data

Data for heating and boiler usage can be collected in two ways. A more hi-tech approach, and

only relevant for long-term studies, would be to use monitoring equipment that directly records,

in this case, the gas usage. One way of doing this is to measure the temperature of the incoming

and outgoing water in the central heating system, while simultaneously measuring the flow rate

of this water (through, for example, an ultrasonic flow detector). The result of these

measurements is enough to calculate the energy being consumed to heat this flow of water,

which is essentially the energy being consumed by the boiler.

A more straightforward approach is simply to use gas bill data as a record of energy

consumption. An example of such data is given in Figure 1. The weakness of using this data for

an energy analysis is immediately clear. As bill data will usually be a result of paying an account

with the energy supplier, which can be in debit or credit at any given time, it is often a poor

indicator of real energy consumption over a given month.

Further to this, the tariff used year-on-year is subject to fluctuations. Therefore, from Figure 1

alone, it is not possible to ascertain whether, for example, 2006 was a particularly cold year or

the energy tariff just happened to be substantially more. From the provided data, the tariffs in

use (averaged over each year) are 1.31, 1.86 and 2.63p/kWh for 2004, 2005 and 2006

respectively. Assuming these are reasonably consistent over each year, and ignoring standing

charges, the corresponding estimated gas consumption values are given in Figure 2.

Figure 1 – Monthly gas bill data (£) of CCHS for 2004-2006

£0

£2,000

£4,000

£6,000

£8,000

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Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

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bill

(£

)

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2005

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Figure 2 – Monthly gas consumption estimates (MWh) of CCHS for 2004-2006

After applying the different tariffs, there is less year-on-year variation. The annual gas

consumption using these estimates is 3,159, 2,368 and 2,768 MWh respectively for 2004, 2005

and 2006. However, it is also clear from both Figures 1 and 2 that, for example, a high December

bill is followed by a low January bill and vice versa (a low December bill followed by a high

January bill). This is likely to be a result of the debit/credit problem of using gas bill data to

estimate consumption.

A useful compromise between measuring this data and reading gas bills would be for a member

of staff to record the actual meter reading once a month. This will provide the school with real

energy data and identify when energy is being used and how it might relate to changes occurring

in the school over time. This would enable firmer conclusions to be made from such data.

2.2 Electrical consumption data

Figure 3 presents the monthly electrical consumption for CCHS, for 2006, 2007 and 2008 – note

that these are different years to those used for the gas consumption analysis due to the data

available at time of writing. A similar month-on-month trend is seen for all three years, with

reduced electrical consumption during the warmer months, though variations in these trends

are subject to similar issue as discussed in section 2.1 (such as the effect of term times).

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Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

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Figure 3 – Monthly electrical consumption estimates (MWh) of CCHS for 2004-2006

The total annual electrical energy consumption from this data is 612, 625 and 584MWh for 2006,

2007 and 2008 respectively. This year-on-year variation is relatively modest, though the total

electrical energy consumption in 2008 is 7% less than that of 2007. With local, historical weather

information (not available for this report) it would be possible to further investigate if the

variations observed can be explained from climate effects alone, or whether additional changes

to the building or user behaviour are affecting the energy consumption. Section 3 further

explores this electrical demand data at a higher temporal resolution.

3. Electrical demand profiles

When attempting to investigate energy patterns in a building, annual or monthly energy

consumption data does not usually provide sufficient detail. With the hourly data supplied by

CCHS, the pattern of energy consumption throughout a day, and how this might change by

season, can be displayed and the reasons for variations postulated.

Figure 4 shows average daily profiles for the three years where electrical consumption data was

available (2006, 2007 and 2008). The very similar patterns seen year-on-year are a result of the

averaging process – if every weekday is averaged together across an entire year then the effect

is to smooth out the profile shape into something that could be describe as generic. While 2006

and 2007 are very similar in magnitude, 2008 shows a noticeable reduction in energy use,

particularly during peak times (that will correspond to times of highest occupancy). It is

suggested that this could be due to lighting upgrades over this time, though reductions in space

heating (due to draughtproofing, insulation measures or simply a warmer winter) can also have

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Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

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2008

a noticeable effect – with the gas boiler used less, the electrical consumption associated with the

delivery of this heat will be reduced.

Figure 4 – Average weekday electrical consumption profiles for 2006, 2007 and 2008 in CCHS

Figure 5 – Comparison of daily electrical consumption profiles for CCHS during 2008

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To encapsulate variations in electrical usage throughout a day and throughout the year

simultaneously, Figure 5 shows 365 daily electrical profiles for 2008. Term times can be clearly

seen (e.g. during the summer) but also the gradual change in profile shape during the year.

There is a very strong correlation with climate – January is typically the coldest month and this

period is where the highest electrical usage (over 200kW peak power recorded) is observed. This

implies that the electrical consumption of the pumps and fans associated with the gas boiler,

along with lighting usage during times of poor daylight, are having an influence on this electrical

consumption.

4. Comparisons with other schools

When attempting to assess the real energy performance of a school there are two particularly

useful comparisons to carry out, namely: (i) the energy consumption of the school when

compared to benchmark data and (ii) the energy consumption of the school when compared to

other schools. The sections below carry out these comparisons, where data exists.

4.1 Benchmark data

The electrical energy consumption data for 2008 for CCHS is 584MWh/yr, equating to

49kWh/m2. The gas consumption data for 2006 (most recent available at time of writing) has

been estimated (from section 2.1) at 2768MWh or 232kWh/m2.

Table 1 is a list of currently available benchmarks that are sometimes referred to in the building

design industry. At first glance, CCHS appears to be slightly higher than “typical” in both gas and

electricity usage; however, there are several caveats that should be borne in mind before

making conclusions from this table. Firstly, CCHS is in Scotland, whereas the benchmarks are UK-

wide – a Scottish school would be expected to have a significantly higher energy consumption

than those in southern UK.

Table 1 – School gas and electricity consumption benchmarks used in industry

Gas consumption

(kWh/m²/yr)

Electricity consumption

(kWh/m²/yr)

Source

Benchmark Typical practice

Good practice

Typical practice

Good practice

Secondary Schools 174 136 30 24 ECG 731

Secondary Schools (no pool)

157 110 34 25 GPG 3432

Secondary Schools (with pool)

187 142 36 29 GPG 343

Secondary Schools – 50th percentile

155 n/a 39 n/a E&WBE3

Secondary Schools – 25th percentile

n/a 112 n/a 31 E&WBE

Secondary schools, NI

120 101 22 16 EBPSBNI4

CCHS 232 49

Just as importantly, the energy benchmarks of Table 1 are not based on recent assessments of

school energy consumption – and even some of the provided references disagree as to what is

“typical” and “good practice” energy use in the schools sector. In addition to this, the PPP and

PFI schools projects that have been underway over recent years (though now largely finished),

along with a rapid increase in IT energy consumption, has changed school energy patterns.

These uncertainties highlight the importance of real energy data, and also comparing like with

like. With this in mind, section 4.2 takes some real energy data of a selection of Edinburgh

schools and investigates the performance of CCHS in this context.

4.2 Data from other schools

As part of a PhD project at Heriot-Watt, the electrical consumption of several Edinburgh schools

are currently being collated. The results are shown in Table 2 and Figure 6, with CCHS

highlighted (all other schools are anonymous). It should be noted that electrical consumption

alone is not sufficient for a complete comparison of energy consumption between schools, but

gas consumption data was not available for these other schools (and is generally more difficult

to obtain). However, total electrical consumption can be a useful indicator of overall energy

management in the school as low figures will generally only be possible if a concerted effort is

made with regards to, for example, switching off lighting and IT equipment.

1 Energy Consumption Guide 73: Saving Energy in Schools, Energy Efficiency Best Practice Programme, 1996

2 Good Practice Guide 343: Saving Energy – a Whole School Approach, Carbon Trust, 2005

3 Energy and Water Benchmarks for Maintained Schools in England: 2002-03, DfES

4 Energy Benchmarks for Public Sector Buildings in Northern Ireland, Jones, Turner, Browne, Illingworth,

Proceedings of CIBSE National Conference Dublin, 2000

Table 2 – Edinburgh schools data from Heriot-Watt University project (originally supplied by City of

Edinburgh Council)

*CCHS

+Recently undergone refurbishments

Figure 6 – Electrical consumption per unit floor area for selected Edinburgh schools (CCHS in red)

School AgePrimary/

Secondary

Floor

Area (m²)

No. of

Pupils

Annual

Electricity

use (MWh)

Swimming

Pool

Energy Per

floor area

(kWh/m²)

Energy Per

Pupil

(kWh/pup)

A 1983 S 8042 782 667 P 83.0 853

B 1978 P 4082 389 225 - 55.1 579

C 2009 S 16852 933 966 P 57.3 1035

D 1960 P 2535 174 195 - 77.0 1122

E 1980 S 9382 275 343 - 36.5 1245

F 1989 S 11430 1102 513 P 44.9 465

G 2008 S 1120 59 240 - 214.0 4061

H 1968 P 4001 395 134 - 33.5 340

I 1975 P 4111 367 219 - 53.2 596

J 1966 S 2316 101 147 - 63.6 1459

K 1991 S 12349 923 863 - 69.9 935

L 1954 P 13145 712 441 P 33.6 619

M 1895 P 6162 240 389 - 63.1 1621

N 1961 P 2515 290 487 193.5 1678

O 1960 S 15368 1423 695 P 45.2 489

P 1970 S 11535 806 644 - 55.8 799

Q 1964 S 1405 55 299 212.8 5437

R 2002 S 9168 744 598 P 65.2 804

S 1893+ S 11742 913 565 P 48.1 619

T 1978 S 11436 401 1433 P 125.3 3574

U 1970 S 2304 78 71 30.7 907

V* 1965 S 11918 902 584 P 49.0 648

W 2007 P 2700 260 162 - 59.9 622

X 1937 P 2800 399 176 - 62.8 440

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Figure 6 shows that the electrical consumption of CCHS, at 49kWh/m2, is towards the lower end

of the school energy data used in this comparison. This level of energy consumption appears

consistent with a low energy school. Furthermore, the other secondary schools built in the 1960s

and 1970s (labelled J, O, P, Q, T and U) are quite diverse in terms of electrical energy use, though

only O and U have lower consumption figures than CCHS, with U not having a swimming pool.

Therefore by most real comparisons CCHS performs well, particularly for the type of building

that the school operates from. The comparison with energy benchmarks is less clear, though

such benchmarks are often poor indicators of real energy use and should be used with caution.

5. Improving the energy efficiency of the school

Schools account for 2% of UK carbon emissions, equivalent to 15% of UK public sector

emissions.5 The government’s carbon management strategy for the schools sector, published in

April 2010, sets an ambitious target to cut emissions from energy use in schools by 53% by 2020.

This needs to be tackled through a number of complimentary strategies: investment in

upgrading the fabric of school buildings, and investment in technological interventions, together

with conscious user behaviour changes. Schools are the ideal teaching grounds for energy

efficiency and investment projects. Energy efficiency has been introduced into the curriculum

with the aim that educating young people in sustainable practices, from an early age, will help

embed behaviour change and lead to a more sustainable society.

According to IMserv6 and their report on Energy Savvy Schools there are five challenges to

energy saving in schools:

• Complete and accurate energy-related data

Smart metering enables remote, automated and accurate half hourly reading of energy

usage on a building(s) basis. To understand where, when and how energy is being used

requires consumption to be identified from specific sources such as heating, lighting and ICT.

This can be achieved by installing sub-meters for different locations, even specific rooms and

devices if necessary. Sub-metering may help identify energy usage for community or after

hours activities; use of zoned controls would allow only the areas required to be supplied

rather than heating the whole school for a single event. CCHS already has access to half-

hourly electrical consumption data, but as shown above, data pertaining to gas consumption

is often estimated, on a per-school basis, and links only roughly to weather data and

occupation. More frequently sampled and zoned data would help identify specific heating

and hot water energy consumption, and encourage behavioural changes to reduce

consumption.

Energy, environmental and financial benefits derived through efficiency

improvements are immediate. Solar panels, in contrast, typically take three

5 Climate Change and Schools: a carbon management strategy for the school sector, Department for Children,

Schools and Families, DCSF-00366-2010. 6 Creating the Energy Savvy Schools of Tomorrow, IMSERV White paper, available at

www.imserv.com/energy-savvy-schools

years before they ‘pay back’ the carbon emissions embedded in their

manufacture, and 10 years before they yield a true financial return – even

with generous government subsidies.7

• Limited or no specialist experience in interpreting energy and related data

Energy conservation requires specialist expertise to transform raw energy data into

actionable ‘energy intelligence.’ CCHS is somewhat fortunate to have a Business Manager in

place, whereas other schools may rely on teaching staff to ‘champion’ energy management

on top of their academic duties. Effective and ongoing energy saving is achieved through

monitoring of day-to-day energy consumption. Analysis of real energy consumption and

patterns can identify sources of waste, leading to behavioural and operational changes

which deliver carbon and monetary savings. Having complete and reliable energy data

means that schools can be in a better position to negotiate more attractive tariffs with

suppliers.

• Problems in making energy insight and savings visible to all

Feedback is important in reducing energy consumption. CCHS already provide a large display

screen in the school reception area visually showing in real-time, staff, pupils and visitors the

positive contribution which the 11kW wind turbine and 30kW solar thermal installations

make. Solar panels and wind turbines may not enjoy the same financial or environmental

benefits as energy efficiency but do have the advantage of being visible and engaging,

especially for young people.

• Difficulty embedding change and accurately monitoring progress

The need to continually monitor energy consumption and behaviour is emphasised: changes

to the working environment, fluctuations in energy prices, building use changes, new targets

and new technologies all affect the decision making process in reducing energy

consumption.

• Not taking a ‘whole school’ holistic approach

Having an ‘Energy Champion’ or business manager will reap benefits more effectively and

quickly. Sustained change will result from involving the whole school in a cross-curriculum

manner, and allowing pupils to understand how energy efficiency and supply affects, and is

affected by, economics, technology, media, and natural resources. The analysis of data can

be considered from a scientific and mathematical stance, and critiqued through use of

language and interpretation. CCHS is making good educational use of the data throughout a

number of its core curriculums and at various levels throughout the school.

CCHS are using the resources they have to good effect with good visibility of installed

technologies and embedded curriculum use of data and sustainable development issues. The

school building itself would benefit from a number of technological improvements which would

impact significantly on gas consumption for space heating and electrical loads for lighting and

equipment. Technological improvements include:

7 Creating the Energy Savvy Schools of Tomorrow, IMSERV White paper, Page 2.

Lighting

Lights left on in one room during break, lunch and after school for one academic year costs an

additional £117 in electricity8. Behavioural campaigns to remind occupants to switch lights off can

be effective, but need constant reminders and feedback to provide lasting benefits.

Lighting controlled by occupancy sensors, photocell sensors, daylight-linked dimmers and time

controls can have relatively short payback periods, ranging from 2-10 years9. This period of

payback is dependent upon a baseline which is determined by the existing technology efficiency,

the hours of use, and the controls which are employed. Areas which can take advantage of

natural daylighting should be separately controlled.

LED lighting offers the potential to significantly reduced energy consumption. Some designs of

LED luminaries offer very directional light quality, rather than diffusing light over a large space.

This may mean that LED’s are still not ideal for large spaces requiring uniform light distribution

levels (e.g. a classroom), but are more suited to spotlight applications e.g. countertops and

display areas. However, both this problem and the high cost factor of LED lighting (a previous

barrier) are improving year-on-year, and this technology is likely to become a more common

lighting choice in buildings in the near future. More commonly used is low energy fluorescent

tube lighting, which can have payback periods as low as 2-3 years.9

Heating

The first rule in reducing energy consumption in buildings is to reduce demand, and then to

provide the required energy as efficiently as possible. To reduce demand in CCHS requires simple

and low-tech solutions like wall and roof insulation, draughtproofing, or window replacement,

with paybacks as listed below 9. [Note – upgrading well fitting single-glazing to double-glazing or

advanced passive glazing options can take over 13 years to pay back in financial terms, based on

electrical heat supply, and up to 50 years based on gas heat supplies. As energy prices rise, this

payback period will naturally fall, but will remain significant in the short to medium term10.]

Wall insulation payback 3-6 years

Roof insulation payback 2-4 years

Draughtproofing payback 1-3 years

Condensing energy efficient boilers have significantly higher efficiencies than standard non-

condensing boilers (>87% efficiency compared to 75% or less). Condensing boilers extract heat

from otherwise wasted flue gases. Instead of a single pass heat exchange system which expels

flue gases at 180°C, condensing boilers reroute these gases over a second heat exchanger and

8 Currie Community High School website, http://www.curriechs.co.uk/

9 Good Practice Guide 312, Pages 23-25 Invest to save?: financial appraisal of energy efficiency measures

across the government estate, available from www.carbontrust.co.uk 10

Menzies, G. 2010 Carbon, Energy and Monetary Investment Model for Low Carbon Building Design, International Renewable Energy Conference, Sousse, Tunisia, 5-7 November.

expel at around 55°C. Payback periods of around 2 years are quoted11. It is stressed that payback

periods are heavily subject to existing systems, patterns of use and replacement options.

Equipment changes

Use of ICT equipment in schools is consistently increasing with the use of smart boards and

increased use of PCs. These technologies not only consume large quantities of power, but they

also emit a significant amount of heat. This heat poses a significant threat to overheating in

schools12. Use of low energy (15W) laptops has a combined effect of lowering electricity

consumption and emitted heat.

Low and Zero Carbon Technologies (LZCTs)

The use of LZCTs should only usually be considered after demand-reduction measures have been

considered. Reducing demand is generally a more cost-effective approach, and can also change

the types of LZCTs that might be effective. Table 3 presents the capital and running costs,

payback periods and carbon reduction potential of selected carbon saving technologies – though

these are not building-specific carbon-savings, merely indicative savings from literature13.

Some of these measures, much like the LZCTs already installed in CCHS, are visible and therefore

can have additional value for a building such as a school – but this should not be used to over-

estimate their significance when compared to some of the previously suggested energy efficiency

improvements.

Table 3 –carbon savings and payback periods of chosen LZCTs

Capital cost per kW

Running costs Payback time Lifetime CO

2

reduction per £

Solar thermal systems Low-Medium Low Low-Medium High

Photovoltaics High Low High Medium

District Heating Medium-High Low Medium-High Medium-High

Combined Heat and Power

Medium Low-medium Medium High

Ground source heat pumps

Medium Low Low-Medium High

Wind power Medium-High Low Low-Medium High

Biomass Medium Low-Medium Medium Medium-High

11 CT021 Carbon Trust, How to implement condensing boilers, available from www.carbontrust.co.uk

12 Jenkins D.P., Peacock A.D. and Banfill P.F.G., Will future low-carbon schools in the UK have an overheating

problem?, Building and Environment, 44, 2009, 490-501 13

Shearer, D and Anderson, B, SBSA, 2005, Low and Zero Carbon Technologies in the Scottish Building Standards

6. Conclusions

Currie Community High School has a clear objective to teach and practice sustainability and

energy efficiency, and this is reflected in the recorded energy consumption. From the data

available, the school is near the lower end of school energy use when compared to a database of

Scottish schools. Due to the age of the building, it is likely that a considerable contribution to this

energy efficiency emanates from good energy behaviour – i.e. despite the construction of the

building not being exemplary, the energy practices carried out within the building appear to be

successful.

Comparing the school to energy benchmarks, much of which is based on outdated energy data,

places the school in a more average setting – but, as already discussed, it is suggested that this is

more about the veracity of the generic energy benchmarks, rather than the energy efficiency of

CCHS.

A list of typical energy improvements have been provided that CCHS might look at adopting in the

future. Before carrying out such measures, a more detailed investigation of the building itself

would need to be carried out, but this report could be used to aid such an objective.

19th May 2011