Energy Simulation of High-Rise Residential Buildings: Lessons Learned

Lessons Learned from Meter Calibrated Energy Simulations of Multi-Unit Residential Buildings

!   Graham Finch, MASc & Brittany Hanam, MASc – RDH Building Engineering

!   Curt Hepting, P.Eng Enersys Analytics

May 12, 2011 – NBEC 13 - Winnipeg

Overview

!   Energy Study Project background

!   Collection and weather normalization of utility data

!   Energy Model Calibration Process

!   Energy Simulation Results and Assessment of Energy Efficiency Measures

Energy Study Project Background

!   Energy study of over 60 architecturally representative mid- to high-rise Multi-Unit Residential Buildings (MURBs) in BC !   Constructed between 1974 and 2002

!   Half of study buildings underwent a full-scale building enclosure rehabilitation !  Allow for the assessment of actual energy use and

savings from enclosure improvements

!   Pre- and post-rehabilitation R-values, air-tightness characteristics determined, mechanical audits performed

!   Several energy models created and calibrated using over a decade of metered data !  DOE 2.1 based FAST and eQUEST used

CMHC SCHL

!   12 years of data from 1998-2009 provided for each building !   Intent to get at least 3 years pre-

and post-rehabilitation

!   Electrical Data !   Suites – Individually metered, but

combined into one monthly amount for confidentiality

!   Common areas - one meter

!   Natural Gas Data !   One meter per building for all uses

!   Includes domestic hot water & make-up air units

!   Also includes all suite fireplaces and pools/hot-tubs, where present

MURB Energy Study – Metered Energy Data

Monthly Energy Consumption – Typical Building

Total Building Energy Usage per Gross Floor Area - Sorted from Low to High

-

50

100

150

200

250

300

350

8 11 44 9 52 42 61 63 18 7 62 12 26 19 33 32 20 45 29 17 43 60 31 28 6 14 3 39 2 57 30 41 24 1 40 59 21 36 58

Building ID - Sorted from Least to Greatest Energy Intensity

Ener

gy C

onsu

mpt

ion

- kW

h/m

2 /yr

Common Electricity

Suite Electricity

Gas

Average = 213 kWh/m2/yr

Median = 217 kWh/m2/yr

Std Dev = 42 kWh/m2/yr

Range = 144 to 299 kWh/m2/yr

Total Annual Energy Consumption Intensity Space Heat Energy Usage vs Year Built

-

50

100

150

200

250

300

350

1972

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

Year of Construction

Ener

gy C

onsu

mpt

ion

- kW

h/m

2 /yr

Total Energy

Space Heat Energy

Understanding Energy Use & Airflow within MURBs

Parking GarageExhaust Fans

Parking Garage

Common Areas

PoolGas Boiler toheat pool &

hot-tubs

Suites

Elev

ator

Sha

ft

Com

mon

H

allw

ay

Cor

rido

rs

Sta

irw

ell

Sha

ft

Electric BaseboardHeaters in all

Suites

Gas fireplaces insome Suites

Air exhausted usingbathroom/kitchen fans

& windows

Air leakage of heatedventilation air through

elevator and stairwell shafts Ventilation air is heatedusing gas-fired make-up

air unit (MUA)

Hea

ted

vent

ilati

on a

ir s

uppl

ied

to e

ach

floor

com

mon

cor

rido

r (pr

essu

rize

d)

HeatedVentilation airfrom corridor

Domestic HotWater is heated

using Gas

Some Gas & ElectricHeat at Common Areas

Typically Unheated

Leak

age

of h

eate

dve

ntila

tion

air

into

sha

fts

Rec. Areas

Building Energy Distribution

Gas- To heat ventilation air for make-up air supply- To heat domestic hot water- To heat pool/hot-tubs- Suite fireplaces (if equipped)- Pilot lights for above

ElectricityCommon Areas- Interior lighting- Elevators- Ventilation fans and motors- Parking garage exhaust fans- Water distribution pumps- Baseboard heaters- Recreation areas/pool pumps- Exterior lighting- Communication- ControlsSuites- Baseboard heaters- Lighting- Appliances- Miscellaneous Electric Loads- Plug loads- Exhaust fans

Enclosure air-leakage

Air flow throughopen windows

Elevator pumping

Space Heating:

All study buildings have electric resistance heat suites

Gas fireplaces also fairly common (common gas meter)

Ventilation air heated (68-72F) using gas fired make-up air units.

Ventilation Distribution and Air Flow within MURBs

Pressurized Corridor:

Design flow rate varies <30 cfm/suite in older buildings to >130 cfm/suite post 2000s.

Actual flow rate making it into the suites less, often as low as 1/3 of design.

Ventilation/IAQ problems are common in MURBs

!   Top Down Analysis (Metered Energy Analysis) !   Total electricity & gas consumption known based on bills

!  Can approximate space-heating using baselines

!  Can approximate some end use energy but not refined

!   Bottom Up Analysis (Energy Model Simulation) !   Total electricity & gas consumption estimated based on

building type, occupancy, use and design •  Input mechanical equipment, schedules, building enclosure

characteristics

!  Can approximate end use energy distribution for all components

!  Needs metered data calibration for accuracy and to evaluate energy efficiency measures

Energy Consumption Analysis Methods

Top Down Assessment vs Energy Simulation – End Use Estimates Bldg #33

Top Down Meter Analysis – No Energy Simulation

Bottom Up Analysis using Calibrated Energy Model Simulation

Calibration of Energy Simulation using Metered Data

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

500,000

Aug

-98

Dec

-98

Apr

-99

Aug

-99

Dec

-99

Apr

-00

Aug

-00

Dec

-00

Apr

-01

Aug

-01

Dec

-01

Apr

-02

Aug

-02

Dec

-02

Apr

-03

Aug

-03

Dec

-03

Apr

-04

Aug

-04

Dec

-04

Apr

-05

Aug

-05

Dec

-05

Apr

-06

Aug

-06

Dec

-06

Apr

-07

Ener

gy C

onsu

mpt

ion

- kw

hr/m

onth Gas

Electricity - SuitesElectricity - Common

Top Down Metered Energy Analysis

Parking GarageExhaust Fans

Parking Garage

Common Areas

PoolGas Boiler toheat pool &

hot-tubs

Suites

Elev

ator

Sha

ft

Com

mon

H

allw

ay

Cor

rido

rs

Sta

irw

ell

Sha

ft

Electric BaseboardHeaters in all

Suites

Gas fireplaces insome Suites

Air exhausted usingbathroom/kitchen fans

& windows

Air leakage of heatedventilation air through

elevator and stairwell shafts Ventilation air is heatedusing gas-fired make-up

air unit (MUA)

Hea

ted

vent

ilati

on a

ir s

uppl

ied

to e

ach

floor

com

mon

cor

rido

r (pr

essu

rize

d)

HeatedVentilation airfrom corridor

Domestic HotWater is heated

using Gas

Some Gas & ElectricHeat at Common Areas

Typically Unheated

Leak

age

of h

eate

dve

ntila

tion

air

into

sha

fts

Rec. Areas

Building Energy Distribution

Gas- To heat ventilation air for make-up air supply- To heat domestic hot water- To heat pool/hot-tubs- Suite fireplaces (if equipped)- Pilot lights for above

ElectricityCommon Areas- Interior lighting- Elevators- Ventilation fans and motors- Parking garage exhaust fans- Water distribution pumps- Baseboard heaters- Recreation areas/pool pumps- Exterior lighting- Communication- ControlsSuites- Baseboard heaters- Lighting- Appliances- Miscellaneous Electric Loads- Plug loads- Exhaust fans

Enclosure air-leakage

Air flow throughopen windows

Elevator pumping

Bottom-Up Energy Model Simulation

200

Model Inputs

Actual Energy Use

240 220 260 180

kWh/m2/yr

Simulated Energy Use

The Importance of Meter Calibrations – Electricity

The Importance of Meter Calibrations – Natural Gas

!   Calendarization !  Conversion of metered data (any recording period) into

individual calendar months (ie Jan 1st to 31st)

!  Weather Normalization !  Process to combine and average > 1 year of monthly energy

data and develop typical year of data for analysis purposes

!  Process is performed pre- and post- building enclosure rehabilitation and mechanical upgrades (if performed)

!  Energy data is correlated with monthly heating degree days (at different baselines) to develop a HDD relationship

•  Benefit of this study to correlate assumptions with daily data

•  Normalization easy to do in a spreadsheet – need to see & understand trends with the data

•  Pre-packaged software can do this – but may not accurately represent some energy use behavior

Metered Energy Collection and Weather Normalization

Meter Assessment and Weather Normalization of Data

Gas Consumption Pre and Post Rehab

y = 0.2430x + 77.3001

R2 = 0.8666

y = 0.2122x + 71.974

R2 = 0.9109

0

20

40

60

80

100

120

140

160

180

200

0 100 200 300 400 500 600

Monthly HDD

Gas

Con

sum

ptio

n - G

J/m

onth

Gas - Pre RehabGas - Post RehabGas - Pre RehabGas - Post Rehab

Natural Gas – Pre-Post Rehabilitation Building 11 Make-up Air Heating Only – Fixed Thermostat

Gas Consumption Pre and Post Rehab

y = 0.0007148x2 + 0.0649066x

R2 = 0.7000204

y = 0.0004614x2 + 0.1990927x

R2 = 0.5650406

0

50

100

150

200

250

300

0 100 200 300 400 500 600

Monthly HDD

Gas

Co

nsu

mp

tio

n -

GJ/

mo

nth

Gas - Pre RehabGas - Post RehabGas - Post RehabGas - Pre Rehab

Natural Gas – Pre-Post Rehabilitation Building 17 Fireplaces Only (No MAU) – Occupant Controlled Thermostat

Suite Electricity Consumption Pre and Post Rehab

y = -0.000432x3 + 0.557175x2 - 14.989006x + 41332.105085

R2 = 0.976696

y = -0.00027x3 + 0.60575x2 + 11.18491x + 42011.83422

R2 = 0.93838

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

0 100 200 300 400 500 600

Monthly HDD

Su

ite

Elec

tric

ity

Co

nsu

mp

tio

n -

kWh

/mo

nth

Suite Elec - Pre RehabSuite Elec - Post RehabSuite Elec - Post RehabSuite Elec - Pre Rehab

Suite Electricity – Pre-Post Rehabilitation Building 33 Electric Baseboard Heat - Occupant Controlled Thermostat Suite Electricity – Pre-Post Rehabilitation Building 17 Electric Baseboard Heat - Occupant Controlled Thermostat

Suite Electricity Consumption Pre and Post Rehab

y = -0.000333x3 + 0.297434x2 + 10.057163x + 37032.022306

R2 = 0.918362

y = -0.000513x3 + 0.464302x2 - 23.867279x + 44178.404540

R2 = 0.875213

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000

0 50 100 150 200 250 300 350 400 450 500

Monthly HDD

Sui

te E

lect

rici

ty C

onsu

mpt

ion

- kW

h/m

onth

Suite Elec - Pre RehabSuite Elec - Post RehabSuite Elec - Post RehabSuite Elec - Pre Rehab

Common Electricity Consumption Pre and Post Rehab

y = 7.1879x + 40594

R2 = 0.1849

y = 3.2597x + 38957

R2 = 0.0875

20,000

25,000

30,000

35,000

40,000

45,000

50,000

55,000

0 100 200 300 400 500 600

Monthly HDD

Com

mon

Ele

ctri

city

con

sum

ptio

n -

kWh/

mon

th

Common Elec - Pre Rehab

Common Elec - Post RehabCommon Elec - Pre Rehab

Common Elec - Post Rehab

Common Electricity – Pre-Post Rehabilitation Building 11 Common Electricity – Non-Adjusted Thermostats

Odd Occupant Behavior and Seasonal Influence Trends Buildings 34/35 - Heating Degree Days Versus Energy Consumption - Monthly

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

800,000

900,000

0 50 100 150 200 250 300 350 400 450 500

Monthly Heating Degree Days

Ener

gy C

onsu

mpt

ion

(kw

hr/m

onth

)

Total Gas

Total Electricity

September

June

!   Very detailed Pre- & Post-Rehabilitation U/R-values calculated for input into energy model !   Calculated U-values for every detail of each wall, roof, window assembly

!   Calculated area-weighted U-values using detailed area calculations

Detailed Enclosure R-value Calculations

PRE R-2.92 POST R-4.26

Typical Enclosure R-values – Study MURBs

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

7 11 17 18 19 20 21 28 32 33 62 39 41 Typ Avg

Ove

rall

Encl

osur

e R

-Val

ue, h

r-ft

2 -F/

Btu

Building Number

Pre Post

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

1980 1985 1990 1995 2000 2005

Ove

rall

Encl

osur

e R

-Val

ue, h

r-ft

2 -F/

Btu

Year of Construction

!   Assuming nominal R-values (i.e. neglecting thermal bridging) has significant impact on modeled consumption !  Use of nominal values results in underestimations of space-

heat by 7% to 29% for study buildings (if only we built this well)

Impact of Incorrect Nominal R-Value Assumptions

Accuracy of weather normalization becomes apparent here

Calibration Process – Suite Electricity

-20%

-15%

-10%

-5%

0%

5%

10%

15%

20%

0

50,000

100,000

150,000

200,000

250,000

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

DifferenceEnergy in kWh

Billed

Simulated

Difference

Avg. Monthly Error: 35.4% 9.7%

Ann. Error: 46.2%

Un-Calibrated Suite Electricity – Bldg 33

-20%

-15%

-10%

-5%

0%

5%

10%

15%

20%

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000



Billed

Simulated

Difference

Avg. Monthly Error: .0% 2.7%

Ann. Error: .1%

Calibrated Suite Electricity – Bldg 33

Adjustments to Electric Space Heat Output & Lighting Baseboard heat constrained within DOE model – to represent occupant behaviour, zoning – Uniform across ALL buildings studied

Calibration Process – Common Electricity

Un-Calibrated Common Electricity – Bldg 33

-20%

-15%

-10%

-5%

0%

5%

10%

15%

20%

0

10,000

20,000

30,000

40,000

50,000

60,000



Billed

Simulated

Difference

Avg. Monthly Error: -42.7% .2%

Ann. Error: -42.7%

-20%

-15%

-10%

-5%

0%

5%

10%

15%

20%

0

10,000

20,000

30,000

40,000

50,000

60,000



Billed

Simulated

Difference

Avg. Monthly Error: 1.7% .6%

Ann. Error: 1.6%

Calibrated Common Electricity – Bldg 33

Adjustments to Elevators & Lighting Adjustments to account for equipment & heating

Calibration Process – Natural Gas

-20%

-15%

-10%

-5%

0%

5%

10%

15%

20%

0

100

200

300

400

500

600

700

800


DifferenceNatural Gas in GJ

Billed

Simulated

Difference

Avg. Monthly Error: 31.5% 3.5%

Ann. Error: 27.1%

Un-Calibrated Natural Gas – Bldg 33 Calibrated Natural Gas – Bldg 33

-20%

-15%

-10%

-5%

0%

5%

10%

15%

20%

0

100

200

300

400

500

600

700


DifferenceNatural Gas in GJ

Billed

Simulated

Difference

Avg. Monthly Error: .6% .6%

Ann. Error: .7%

Avg. Monthly Error: .6% .6%

Ann. Error: .7%

Adjustments to Make-up Air Flow-rate (ie from nameplate to actual installed), MAU Temperature & DHW systems

Distribution of Energy Consumption – Typical MURB

Average of 13 Buildings = Total 206.3 kWh/m2/yr

Units of kWh/m2/yr, % total

Electric Baseboard

Heating, 25.1, 12%

Fireplaces, 37.7, 18%

Ventilation Heating, 39.7,

19%DHW, 32.9,

16%

Lights -Common, 3.7,

2%

Lights - Suite, 15.9, 8%

Plug and Appliances

(Suites), 18.7, 9%

Equipment and Ammenity (Common), 28.3, 14%

Elevators, 4.2, 2%

!   Fireplace use simulated in model and calibrated with data from buildings with only gas fireplaces on meter

!   Average 17.6 GJ/year/suite average fireplace use (13.3 to 24.1 GJ depending on manual pilot light shut-offs

Impact of Fireplace Energy Consumption

2.8

1.9 2.0

1.3

0.8

0.30.1 0.1

0.5

1.2

2.1

2.6

0.0

0.5

1.0

1.5

2.0

2.5

3.0


Natural Gas, GJ/suite

Billed Simulated

39.9 39.9

25.1 29.1

37.5

0

20

40

60

80

100

120

Suites with Fireplaces Suites without Fireplaces

Ann

ual S

pac

e H

eat C

onsu

mpt

ion,

kW

h/m

2 Fireplace Gas

Suite Electric Space Heat

MAU Gas

-37.5 for fireplace +4 for electric heat 10:1 ratio?

Calibration Results – Total Energy Consumption

0

50

100

150

200

250

300

Bldg07 Bldg11 Bldg17 Bldg18 Bldg19 Bldg20 Bldg21 Bldg28 Bldg32 Bldg33 Bldg62

Tota

l Ene

rgy

Con

sum

ptio

n, k

Wh/

m2

Meter Pre-Rehab

Model Pre-Rehab

Meter Post-Rehab

Model Post-Rehab

-15%

-10%

-5%

0%

5%

10%

15%

20%

25%

Bldg07 Bldg11 Bldg17 Bldg18 Bldg19 Bldg20 Bldg21 Bldg28 Bldg32 Bldg33 Bldg62

Tota

l Ene

rgy

Cons

umpt

ion,

kW

h/m

2

Metered Savings

Modeled Savings

Average Metered (Actual Savings) = 7.5% (-11% up to 19%) Average Modeled Savings = 3% (0% to 7%) In all cases* actual savings exceeded modeled

!   Improve glazing

Applying Calibrated Model to Assess Energy Efficiency Measures

!   Improve ventilation & heat recovery

!   Reduced thermal bridging

Scenario Simulation Inputs Baseline Pre •  Walls effective R-3.6

•  Windows single glazed U = 0.7, SC = 0.67

•  Air tightness “Tight – High Average”, 0.15 cfm/ft2

•  Make-up air temperature set-point 68°F

•  No heat recovery Good •  Walls effective R-10

•  Windows double glazed, argon fill, low-e, low conductive frame; U = 0.27, SC = 0.35

•  Air tightness “Tight – Low Average”, 0.05 cfm/ft2


•  No heat recovery

•  No Fireplaces Best •  Walls effective R-18.2

•  Windows triple glazed, argon fill, low-e, low conductive frame; U = 0.17, SC = 0.23

•  Air tightness “Very Tight”, 0.02 cfm/ft2


•  80% Heat Recovery

•  No Fireplaces

Combination of Energy Efficiency Measures Simulated

102.4

38.2

9.7

0.0

20.0

40.0

60.0

80.0

100.0

120.0

Baseline Good Best

An

nual

Spa

ce H

eat C

onsu

mpt

ion,

kW

h/m

2

Potential for MURB Space Heat Consumption in Vancouver

91% Space Heat Savings

63% Space Heat Savings

110.3

60.839.4

96.0

81.3

74.2

0

50

100

150

200

250

Baseline Good Best

An

nu

al E

nerg

y Co

nsu

mp

tion,

kW

h/m

2

Electricity

Gas

Impact of Space Heat Energy on Total Energy Consumption

!   Can reduce energy by almost half with ventilation and enclosure upgrades only !   Further improvements from DHW, Lighting, Appliances, Controls etc.

Current Levels ~ 200 kWh/m2/yr We can get to ~100 kWh/m2/yr

!   2-3 years of monthly utility data usually sufficient for energy assessments of existing MURBs !   Careful with HVAC/enclosure changes, may need more data

!   Careful with weather normalization – usually non-linear relationship when occupants have control of thermostat

!   Need accurate R-values and mechanical inventories (detailed audits necessary), basic understanding of air-tightness/airflows

!   Energy models need to be calibrated with actual data – apply findings, tweaks & knowledge to new building models

!   Calibrated models can predict approximate space-heat energy savings for enclosure rehabilitations !   Some difficulty with gas fireplaces and make-up air consumption & influence

!   Mechanical system changes (ie balancing of make-up air, set-point temperature increases, dead controls) can throw of estimates (and real savings)

!   Occupant behaviour and airflow within tall buildings have significant influence on actual energy consumption and savings potentials

Conclusions – MURB Energy Simulations

Questions? [email protected]