BEST FAÇADE Energy Benchmarking of Double-Skin Façade Buildings

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ISQ, R.Prof.Dr. Cavaco Silva, 33, Taguspark – Oeiras 2740-120 Porto Salvo; PORTUGAL

Rogério Duarte

Mário de Matos

BEST FAÇADE

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ISQ: Instituto de Soldadura & Qualidade – 22.11.2006: 2

Energy Benchmarking of DSF Buildings

INTRODUCTION

Double-skin façade (DSF) is a building related technology of high-rise glazed office buildings, which has gained significant acceptance among architects and promoters.

Actual energy performance of DSF buildings is still lacking a more accurate evaluation. Main objective of this work is:

To assess the circumstances for which the DSF technology has energetic advantages Based on existent DSF buildings to discover the best energy practices of this technology For this purpose a benchmarking analysis tool was considered to examine DSF buildings:

Work developed at ISQ deals specifically with analysis and interpretation of energy performance data –

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Energy Benchmarking of DSF Buildings

THE BENCHMARKING DATA

Sample quality 24 11 9 2 0 5 10 15 20 25 30 Initial sample Returned questionnaires Climat consumption data Climat+Elect consumption

data Detailed main consumptions

Number of DSF Buildings

'stand-by' estimated measured data

Target group directly adressed by BestFaçade (27+3 DSF buildings)

0 1 2 3 4 5 Num be r of buildings

Sw eden Austria Belgium France Germany Greece Portugal

forecast

11 Buildings Sample by main climatic region as classified in WP1 report 5; 46% 4; 36% 2; 18% nordic moderate mediterranean

Despite of the data collection effort....

Data collection tools: • Questionnaires • Interviews • Technical visits

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Energy Benchmarking of DSF Buildings

EXAMPLE OF ENERGY BENCHMARKS

Cooling supply energy system

5/11 5/11

1/11

district cooling electricity (Other)

Heating supply energy system

6/11 2/11

1/11 2/11

district heating electricity gas/fuel (Other)

Cooling space HVAC system

4/11

4/11 3/11

overhead radiation cooling hot air cooling (Other)

Statistical analysis of energy consumption related to one or more variables

AIM: allow a meaningful comparison between DSF buildings,

with different typologies, subject to different environments, management conditions, etc

Heating space HVAC system

5/11

2/11 4/11

radiator hot air heating (Other)

Solar shading

9/11 2/11

venetian blind canvas screens

Daylight control systems

8/11

1/11 1/11 1/11 3/11

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Energy Benchmarking of DSF Buildings

ENERGY PERFORMANCE INDICATORS

0 50 100 150 200 250 300 350 400 450 500 550 1 2 3 4 5 10 20 21 23 48 49 Buildings [kW h /m 2a] Heating Cooling

EEI: Energy Efficiency Indicator

0 50 100 150 200 250 V C A D B G Q E R T W DSF Building code [k W h /m 2. a]

Buildings energy needs are (“without difficulty”…) obtained from energy billing accounting procedures.

ANNUAL ENERGY DELIVERED PER m2 _{USEFUL PAVEMENT AREA [kWh/m}2_a]

normalizes energy consumption by building size

and is usually called Energy Efficiency Indicator

0 100 200 300 400 500 600 1 2 3 4 5 10 20 21 23 48 49 Buildings [k W h /m 2 a ]

Energy consumption – total climatization

Good and

poor

performers

are easily

identified!

Statistical parameters Average EEI = 123 kWh/m2_.a Mode = 112 kWh/m2_.a Median (percentile 50) = 112 kWh/m2_.a Percentile 95 = 221 kWh/m2_.a Percentile 5 = 51 kWh/m2_.a

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Energy Benchmarking of DSF Buildings

CLIMATE NORMALIZATION – METHOD

Because buildings in different cities around Europe are to be compared, it is imperative to normalize energy performance by the severity of the climate.

Normalization procedure was based in the heating and cooling degree-day method,

by making use of TAPM generated climatic data for each city in which there was a DSF building Main advantage of the method chosen:

On a coherent basis is possible to compare buildings subjected to different climate Main disadvantage of the method chosen:

Solar radiation gains are not well thought-out in the degree-day method

It was used a 21ºC base indoor temperature in the calculations for heating and cooling seasons It was assumed that heating or cooling could occur during the entire year

Energy consumption data considered in this work was obtained for different years,

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Energy Benchmarking of DSF Buildings

CLIMATE NORMALIZATION – EEI RESULTS

EEI: Energy Efficiency Indicator

0 50 100 150 200 250 V C A D B G Q E R T W DSF Building code [k W h /m 2 .a ] From a previous slide EEI: Energy Efficiency Indicator

normalized 0 50 100 150 200 250 300 350 400 450 500 550 600 D C A B E V G Q R T W DSF Building code [k W h /m 2 .a ]

Good performers

are still

the good performers!

Statistical parameters Average EEI = 268 kWh/m2_.a Median (percentile 50) = 221 kWh/m2_.a Percentile 95 = 575 kWh/m2_.a Percentile 5 = 55 kWh/m2_.a

One of the three best performers (R,T and W) is a experimental test facility.

V,E and D changed their rate more than one position. These buildings are each located in the three different WP1 climatic regions.

BEST PRACTICES

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Energy Benchmarking of DSF Buildings

ENERGY NEEDS FOR HEATING AND COOLING

0 50 100 150 200 250 0 1 2 3 4 5 E n e rgy C o ns u m pt ion I nde x [k W h /m 2 a ] DSFbuildings SSF buildings

heating cooling cooling heating

0 100 200 300 400 500 600 0 1 2 3 E n e rgy C o ns um p ti on I nd e x C li m at e N o rm al iz ed [kWh /m 2a] DSFbuildings cooling heating

Due to lack of data and as reference sample could be considered small,

it was decided to include single skin façade (SSF) office buildings in the statistical analysis.

Forecast was then: data of 58 buildings!... however only 17 have supplied annual energy consumption heating and cooling, which is the minimum data for an energy performance benchmark related analysis

Tendencies are as shown:

•Actual buildings have both heating and cooling consumptions with minimum values between 25 and 50kWh/m2_.a

•For heating, maximum values are between 150 and 175kWh/m2_.a

•For cooling, maximum values are between 75 and 100kWh/m2_.a

•Europe consumes more heating in actual buildings than cooling energy,

but if taking in account the climate region, the scenario is different

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Energy Benchmarking of DSF Buildings

INTRODUCTION OF SSF SAMPLE WITH THE DSF SAMPLE

Heating consumption index

0 50 100 150 200 250 1 11 21 31 41 51 61

Sample with DSF (dark painted) and SSF together

[kW

h

/m

2.

a]

Cooling consumption index

0 50 100 150 200 250 1 11 21 31 41 51 61

[k W h /m 2 .a ]

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Energy Benchmarking of DSF Buildings

INTRODUCTION OF SSF SAMPLE WITH THE DSF SAMPLE

Ventilation consumption index

0 25 50 75 100 125 150 175 200 225 250 1 11 21 31 41 51 61

[kW

h

/m

2.

a]

Lighting consumption index

0 25 50 75 100 125 150 175 200 225 250 1 11 21 31 41 51 61

[k W h /m 2 .a ]

Electricity consumption inde x

0 25 50 75 100 125 150 175 200 225 250 1 11 21 31 41 51 61

[kW h /m 2. a] 480

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Energy Benchmarking of DSF Buildings

COMPARISON WITH EUROPEAN BENCHMARKS

CLUSTER ANALYSIS

CLIMATIZATION ENERGY CONSUMPTION INDEX [kWh/m2a]

DSF - Nordic DSF - Nordic DSF - Nordic DSF - Nordic DSF - Nordic DSF - Moderate DSF - Moderate DSF - Moderate DSF - Mediterranean DSF - Mediterranean DSF - Mediterranean DSF - Mediterranean DSF - Mediterranean

SSF AC Benchmark good UK-prestige DSF - Moderate

SSF AC Benchmark good Greece SSF AC Benchmark typ Greece

SSF AC Benchmark good UK

SSF AC Benchmark typ UK

SSF AC Benchmark typ UK-prestige

0 50 100 150 200 250 0 50 100 150 200 250 Heating [kWh/m2a] Co oling [k Wh /m2 a] DSF - Nordic DSF - Moderate DSF - Mediterranean total 100kWh/m2a (EPBD - SE) total 155kWhe/m2a

(EPBD - PT:new Banks)

total 121kWhe/m2a

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Energy Related Clustering Analysis of DSF Buildings

ENERGY CLUSTERS OF CLIMATIZATION CONSUMPTION

CLIMATIZATION ENERGY CONSUMPTION INDEX [kWh/m2a]

SSF AC Benchmar k good UK-pr esti ge SSF AC Benchmar k good Gr eece

SSF AC Benchmar k typ Gr eece

SSF AC Benchmar k good UK

SSF AC Benchmar k typ UK

SSF AC Benchmar k typ UK-pr esti ge

0 50 100 150 200 250 0 50 100 150 200 250 Heating [kWh/m2a] C oo lin g [ kW h/ m 2a ] DSF - Nordic DSF - Moderate DSF - Mediterranean total 1 0 0 k Wh/ m2 a (EPBD - SE) total 1 5 5 k Whe / m2 a

(EPBD - PT:new Banks)

total 1 2 1 k Whe / m2 a

(EPBD - PT:new Of f i ces)

V Q R T A C AD AB AE E G B W

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Energy Benchmarking of DSF Buildings

Conclusions & Future Work

It was very difficult to obtain sufficient data to perform a more detailed analysis, as we hoped and expected at beginning of our work

There are DSFs that perform better and DSFs that perform worse than SSF

With the existing data a statistical treatment was questionable so cluster analysis was used Cluster analysis identified regional trends