Benchmarking Industrial Building Energy Performance

Seminar on EAEF Project 64 & 68Seminar on EAEF Project 64 & 68Energy Performance Contracting & benchmarkingEnergy Performance Contracting & benchmarking

13 January 200613 January 2006School of Design & Environment, NUSSchool of Design & Environment, NUS

Energy SustainabilityUnit

Benchmarking Industrial Building Energy Performance

Chia Yen LingEnergy Sustainability UnitDepartment of BuildingSchool of Design and EnvironmentNational University of Singapore

http://www.jtc.gov.sg/

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This project has been supported by Jurong Town Corporation

Benchmarking Industrial Building Energy Performance

ObjectivesIntroductionMethodologyKey Energy Performance IndicatorsEnergy BenchmarkBenefitsPotential Cost SavingsConclusionOngoing work

Presentation OutlinePresentation Outline

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Objectives

• To identify and rank performance indicators affecting energy performance of industrial buildings.

• To develop a benchmarking curve or a set of curves for evaluating and benchmarking energy performance of industrial buildings.

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Introduction

Flatted Factories (77 blocks - 1.4mil m2)

Stack-up Factories (90 units - 2.4mil m2)

Standard Factories (1579 units - 0.2mil m2)

Workshops (796 units - 0.17mil m2)

Types of Industrial Buildings Types of Industrial Buildings

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Introduction

What is a What is a ‘‘flatted factoryflatted factory’’??

• High-rise industrial buildings ready-built multi-tenanted factories developed by industrial landlord

• Tenanted to various small to medium size enterprises for light industries

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Introduction

What is a What is a ‘‘flatted factoryflatted factory’’??

• Typically 5 to 7 storeys high

• Common spaces, shared amenities and services are maintained and operated by landlord

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Introduction

Typical floor planTypical floor plan

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Methodology

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Methodology

Select industrial property typeFlatted factory, Standard factory, Stack-up factories, Workshops

Determine population size of existing stock77 flatted factories

Determine sampling methodRandom sampling was employed. 59 responses out of a total of 77, resulting in a 77% response rate.

Determine information requirementsBuilding physical characteristics, operating schedules, management info

Definition of terms e.g. Gross Floor Area, Common Area

Step 1: Scope and definition Step 1: Scope and definition

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Methodology

Energy consumption data Extracted directly from original monthly electricity bills for each flatted factory, so a high level of accuracy was achieved.

Determine time period for which bills are collectedElectrical bills collected for a 12-month period for the year 2003

Formulation of data acquisition templateBuilding characteristics data were collected from industrial landlord & facility personnel

Verify energy and building dataSite visits were conducted to verify the information

Step 2: Data CollectionStep 2: Data Collection

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Methodology

Test for data reliabilityAverage design efficiency (gross lettable area to gross floor area) is 71% with a 95% confidence interval of +/- 2.1%.

Identify energy performance indicators

1. Simple linear regression

2. Stepwise least-squares multivariate linear regression

Establish energy benchmarks for flatted factories industrial buildings

Approach 1: Using the average performance of a group as an energy benchmark

Approach 2: Cumulative distributional energy benchmarking

Step 3: Data AnalysesStep 3: Data Analyses

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Key Energy Performance Indicators

Simple Linear RegressionSimple Linear RegressionPotential Energy Performance

Indicators R2 values

Gross floor area (m2) 0.684

Rentable area (m2) 0.481

Landlord common area (m2) 0.807

Number of lifts (nos.) 0.606

Floor-to-floor height (m) 0.463

Volume of flatted factory (m2) 0.798

Volume of landlord common area (m3) 0.855

Age (years) 0.339

Occupancy rate (%) 0.011

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Key Energy Performance Indicators

Stepwise leastStepwise least--squares multivariate linear squares multivariate linear regressionregression

Model Equation R2 Adjusted R2 P-Value VIF

1 Ê = 3136.47 + 0.868 (Volume of landlord common area) 0.854 0.852 < 0.0005 < 5

2Ê = 4306.386 + 0.708 (Volume of landlord common area) + 1930.804 (Number of Lifts)

0.881 0.877 < 0.0005 < 5

3

Ê = 4306.386 + 1.150 (Volume of landlord common area) + 2251.767 (Number of lifts) –2.423 (Landlord common area)

0.890 0.884 < 0.0005 > 5

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Landlord's normalized energy-use intensities (EUI) (kWh/m3/yr)

Freq

uenc

yNormalized Energy-Use Intensities (EUI) BenchmarkApproach 1: Using the average performance of a group as Approach 1: Using the average performance of a group as an energy benchmarkan energy benchmark

Frequency distribution of landlord's normalized energy-use intensities (EUI) of flatted factories

• Mean value is 11.71 kWh/m3/year• Skewness value of 0.68• Approximately 50% of the buildings studied have energy efficiencies below the

mean value of 11.71 kWh/m3/year

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Normalized Energy-Use Intensities (EUI) Benchmark

Approach 2: Cumulative distributional energy benchmarkingApproach 2: Cumulative distributional energy benchmarking

0

20

40

60

80

100

0 5 10 15 20 25 30 35

Landlord Energy Efficiency (kWh/m3/year)

Cum

ulat

ive

Perc

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ge (%

)

Cumulative Percentile Distribution Curve of Flatted Factories Normalized Energy-Use Intensities (EUI)

•70% of the buildings studied have EUI of between 10 and 15 kWh/m3/year

•Benchmarking metrics established by Royal Institution of Chartered Surveyors (RICS) in 1993 ranges from 29 to 38 kWh/m3/year

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Normalized Energy-Use Intensities (EUI) BenchmarkApproach 2: Cumulative distributional energy benchmarking Approach 2: Cumulative distributional energy benchmarking (Application)(Application)


•For existing buildings, building owners may determine his/her building performance ranking & set energy efficiency target for its management.

•For a proposed new building, a developer can set target for his design team.

Your Bdg 18kWh/m3/yrTARGET13kWh/m3/yr

5 kWh/m3/yr

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Reliability of Benchmark Curve

1. Variance

2. Coefficient of Variation

This applies to linear functions which involves one variable.

( )1

2

1

−

−=∑=

n

XXVar

n

ii

%100⎟⎠⎞

⎜⎝⎛=

XSCV

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The cumulative benchmark curve is

• Non-linear function

• EUI is a composite measure of Energy Consumption (kWh) / Volume of landlord common area

Thus,

TAYLOR SERIES LINEARIZATION METHOD is used.

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TAYLOR SERIES LINEARIZATION METHOD (Wolter, 1985)

If the function is a ratio of two random variables i.e. , then the

simple expression for the Taylor linearized estimated variance isYXR ˆˆˆ =

( ) ( ) ( )⎥⎦

⎤⎢⎣

⎡++=

XYXYCov

XXVar

YYVarRRVar ˆˆ

ˆ,ˆ2ˆˆ

ˆˆˆ)ˆ(

222

xNXyNYwhere == ˆ&ˆ (in the case of simple random sampling)

And the corresponding estimated coefficient of variation (CV) is

( ) RRvRcv ˆ/ˆ)ˆ( =

),,( volumeofvaluemeanxnconsumptioenergyofvaluemeanysizesampleN ===

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In applying TAYLOR SERIES LINEARIZATION METHOD,

The Taylor linearized estimated variance

0051.0)ˆ( =RVar

And the corresponding estimated coefficient of variation (CV) is

( )%6219.0006219.0)ˆ( =Rcv

Low variance and CV value indicates high reliability of the benchmarking curve developed!

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Benefits

• With the accurate benchmarking developed, industrial landlords can set new energy targets for efficiency.

• Improved design and specifications for new or retrofitting projects.

• Identify buildings for retrofit.

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Potential Cost Savings

Scenario 1: All flatted factories meet the average performanceScenario 1: All flatted factories meet the average performance

• Average performance is 11.71 kWh/m3/year

• Large cost savings that can be accrued:

Possible Energy Saving (kWh/year) = 1.9 million kWhCost Savings (kWh/year) = $323,000

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Landlord's normalized energy-use intensities (EUI) (kWh/m3/yr)

Freq

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y

Frequency distribution of landlord's normalized energy-use intensities (EUI) of flatted factories

Class I15 flatted factories0 to 9.75 kWh/m3/yearMean: 8.8 kWh/m3/yearTotal: 509,656 m3

Class III15 flatted factories> 12.8 kWh/m3/yearMean: 16.2 kWh/m3/yearTotal: 360,936 m3

Class II32 flatted factories9.76 to 12.79 kWh/m3/yearMean: 11.2 kWh/m3/yearTotal: 931,062 m3

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Potential Cost Savings

Scenario 2: All Class III flatted factories are benchmarked Scenario 2: All Class III flatted factories are benchmarked against Class II flatted factoriesagainst Class II flatted factories


Large cost savings that can be accrued:

Possible Energy Saving (kWh/year) = 1.4 million kWhCost Savings (kWh/year) = $243,000

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Ongoing Work

Detailed Energy Audit Study

Studies include site measurement, energy datalogging and building assessment.

Aim:

Diagnostics work

To gain a profiling of energy performance with respect to systems’performance for the three classes.

To develop systems’ energy benchmark

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EF P

roje

ct 6

4 &

68

Ener

gy P

erfo

rman

ce C

ontr

actin

g &

ben

chm

arki

ngEn

ergy

Per

form

ance

Con

trac

ting

& b

ench

mar

king

13 J

anua

ry 2

006

13 J

anua

ry 2

006

Scho

ol o

f Des

ign

& E

nviro

nmen

t, N

US

Scho

ol o

f Des

ign

& E

nviro

nmen

t, N

US



Ongoing Work

Class I Flatted Factory

Sem

inar

on

EAEF

Pro

ject

64

& 6

8Se

min

ar o

n EA

EF P

roje

ct 6

4 &

68

Ener

gy P

erfo

rman

ce C

ontr

actin

g &

ben

chm

arki

ngEn

ergy

Per

form

ance

Con

trac

ting

& b

ench

mar

king

13 J

anua

ry 2

006

13 J

anua

ry 2

006

Scho

ol o

f Des

ign

& E

nviro

nmen

t, N

US

Scho

ol o

f Des

ign

& E

nviro

nmen

t, N

US



Ongoing Work

How is landlordHow is landlord’’s energy consumed in s energy consumed in common spaces?common spaces?

•Corridor•Toilet•Lift lobbies•Stairways•Carpark

Mechanical ventilation for toilets

•Toilet Flushing System

•Booster Pump

Sem

inar

on

EAEF

Pro

ject

64

& 6

8Se

min

ar o

n EA

EF P

roje

ct 6

4 &

68

Ener

gy P

erfo

rman

ce C

ontr

actin

g &

ben

chm

arki

ngEn

ergy

Per

form

ance

Con

trac

ting

& b

ench

mar

king

13 J

anua

ry 2

006

13 J

anua

ry 2

006

Scho

ol o

f Des

ign

& E

nviro

nmen

t, N

US

Scho

ol o

f Des

ign

& E

nviro

nmen

t, N

US



Conclusion

• Volume of landlord common area is one of the key energy indicators of industrial buildings.

• Cumulative distributional energy benchmarking is a more effective benchmarking tool.

• Industrial landlords can use the energy benchmark curve to compare his own energy performance with that of others.

Sem

inar

on

EAEF

Pro

ject

64

& 6

8Se

min

ar o

n EA

EF P

roje

ct 6

4 &

68

Ener

gy P

erfo

rman

ce C

ontr

actin

g &

ben

chm

arki

ngEn

ergy

Per

form

ance

Con

trac

ting

& b

ench

mar

king

13 J

anua

ry 2

006

13 J

anua

ry 2

006

Scho

ol o

f Des

ign

& E

nviro

nmen

t, N

US

Scho

ol o

f Des

ign

& E

nviro

nmen

t, N

US



THANK YOUTHANK YOU

The financial sponsorship and contributions of The financial sponsorship and contributions of JurongJurong Town Town Corporation are hereby gratefully acknowledged.Corporation are hereby gratefully acknowledged.

Benchmarking Industrial Building Energy Performance

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