Impact of appliance efficiency and fuel substitution on residential end-use energy consumption in Canada

Energy

and Buildings

24 ( 1996)

137-146

Impact of appliance efficiency and fuel substitution on residential end-use energy consumption in Canada V. Ismet Ugursal, Alan S. Fung Department

qf Mechanical

Engineering, Received

Technical

University

15 June 1995; accepted

ofNova

12 January

Scotia, Hulifax,

NS, Canudu

1996

Abstract In this paper, the effect of appliance efficiency and fuel substitution on residential end-use energy consumption in Canada is studied based studies conducted on the Expanded STAR database, which consists of detailed descriptions of 937 houses from differentregions of Canada, using an hour-by-hour building energy simulation program. The findings of this study clearly indicate that improving appliance efficiency reduces the overall end-use energy consumption in the residential sector. However, the magnitude of savings as a result of improving only appliance efficiencies is quite small. For example, by replacing appliances in 10% of residences by highly efficient appliances (reflecting the technology of the next decade), the savings in end-use energy consumption would be about 1%. Significantly larger savings, in the order of 5-lo%, can be obtained by improving house envelopes and heating/cooling systems in addition to improving appliance efficiencies (also assuming a 10% market penetration of energy efficiency improvement measures). Fuel substitution for space and domestic hot water heating can also have a significant potential for reducing residential energy consumption depending on the fuel substitution scenario adopted. on simulation

Keywords:

Residential

buildings;

Equipment;

Energy

consumption;

Canada; Simulation

1. Introduction In 1994, the total energy consumptionin Canadawasabout 7000 Petajoules [ 11, About 20% of this total was for residential use. Energy use by appliancesin homesrepresentsa significant portion of the national end-useenergy consumption in Canada ‘. As such, improving the energy utilization efficiency of householdappliancesneedsto be consideredas

a potential in realizing the necessaryreduction in national energy consumptionto meet the requirementsof the United Nations Framework Convention on Climate Change [ 21. In the pastseveraldecades,energy efficiency of appliances sold in Canadashowed substantialgains. For example from 1978 to 1983, the efficiency increasewas 43% for freezers, 27% for dishwashersandclothes washers,and 17%for refrigerators [ 31. This increasein efficiency is expectedto continue with regulations and adoption of incentive mechanismssuch as energy taxation, energy efficiency grants and subsidies, ’ In this paper, the values cited for energy consumption and savings are for ‘end-use’ energy rather than ‘source’ energy. This distinction is especially important in interpreting the results for electrical energy consumption and savings. ‘End-use’ electricity consumption and savings values are to be interpl-eted as electricity consumption and savings at the end-user level; as such, the efficiencies of electricity generation and transmission are not reflected in these values. 0378-7788/96/$15.00 PUSO378-7788(96)00970-l

0 1996 Elsevier

Science S.A. All rights reserved

both in Canadaandthe US. SinceCanadaimports about20% of its refrigerators and clotheswashersfrom the US, someof the effect of US legislation spills over into Canada through competition [ 31. Energy consumption and efficiency of household applianceshave complex effects on the overall energy consumption of houses.This complexity is due to the interaction of a large number of parametersincluding the time of the year (heating or cooling season); type of heating/cooling system and type of fuel used; efficiencies of the heating/cooling system, house envelope and appliances;time schedules of applianceusage;hot water consumption of appliance,occupancy and thermostatsetting; and type of ventilation system. Becauseof the interrelated effects of all of theseparameters, evaluating the effect of applianceefficiency on overall energy consumptionof housesrequires detailed computer modeling studies using building energy simulation models that are capable of simulating the effect of these parameterswith sensitivity and accuracy. In this paper, the effect of appliance efficiency and fuel substitution for spaceand domestichot water heating on the residentialend-useenergy consumptionin Canadais studied to identify the magnitudeof potential savingsin national enduse energy consumption that can be realized by improving efficiency and fuel substitution. The study is basedon simu-

138

V.I. Ugursnl,

AS. Fung /Energy

lation studies conducted on the Expanded STAR database, which consists of detailed descriptions of 937 houses from different regions of Canada, using an hour-by-hour building energy simulation program. A more detailed description of the study and its findings is published in a report [ 41. It should be clear to the reader that the values cited in this paper for energy consumption and savings are for ‘end-use’ energy rather than ‘source’ energy. This distinction is especially important in interpreting the results for electrical energy consumption and savings. ‘End-use’ electricity consumption and savings values are to be interpreted as electricity consumption and savings at the end-user level; as such, the efficiencies of electricity generation and transmission are not reflected in these values.

2. Methodology To study the impact of appliance efficiency and fuel substitution for space and domestic hot water consumption on residential energy consumption in Canada, batch simulations were conducted on a housing database representing the housing stock in Canada using an hour-by-hour building energy simulation program that was extensively validated against field data and benchmark simulation programs [ 51. The Expanded STAR housing database was used in the simulations. Expanded STAR consists of detailed descriptions of 937 houses from different regions of Canada. It was formed using 698 house files from the Canada Mortgage and Housing Corporation (CMHC) STAR-HOUSING database [ 61 and 239 houses from the Hot-2000 database of Natural Resources Canada [7]. The Expanded STAR database is representative of the housing stock at the national level; however, the distribution of houses, fuels used and fuel consumption at provincial level requires improvement [ 41. The file for each house in the Expanded STAR database includes architectural and construction details of the house, the type and efficiency of the space and domestic hot water heating systems, and the thermostat and occupancy schedules. However, there is no information on the type and number of appliances in the houses, or the appliance annual electricity consumption and usage pattern. Therefore, an exhaustive literature review was conducted to develop representative estimates for the annual electricity consumption, usage patterns (i.e. load curves), and saturation of appliances in Canada. Data compiled from numerous studies conducted in Canada and the US were reviewed, and electricity consumption, load curves and saturation values for household appliances were estimated from the data [4,8]. The various appliances were distributed randomly amongst the houses in the database according to the saturation data. For example, Statistics Canada data indicate that 44% of households in Canada have dishwashers [9]. Thus, 44% of the houses in the database were randomly assigned a dishwasher. Using similar saturation data, all of the appliances found in Canadian houses were assigned randomly to the

and Buildings

24 (1996)

137-146

houses in the database. At the end of this process, each house in the database was assigned a set of appliances reflecting the saturation of appliances in Canada. Based on the results of an exhaustive literature review, representative load curves for a number of major appliances were identified [4]. These load curves are largely based on the data published by Lawrence Berkeley Laboratory [ lo], Bonneville Power Authority [ 111, Electric Power Research Institute [ 121 and Ontario Hydro [ 131, and are given in Table 1. Since load curves for minor, or miscellaneous, appliances are not reported, a ‘reasonable’ load curve for all remaining appliances given in Table 1 was used. Using the annual electricity consumption data and load curves for the appliances in each house in the database, the baseline appliance electrical load (representing the present level of appliance energy efficiency) and composite appliance load curve for each house were determined. The house data in the Expanded STAR database, the baseline appliance electrical load and composite appliance load curve for each house were integrated and converted into the input data file format required by the building energy simulation program. Thus, complete input data files for 937 houses representing the Canadian housing stock were developed to be used in the batch simulations. Batch simulations were conducted on the whole database to study different scenarios including three levels of appliance and furnace/boiler efficiencies, and improvements in the building envelope. Thus, a baseline simulation was conducted using the baseline appliance electrical loads that reflect the present level of residential energy consumption in Canada. Then, the appliance electrical loads were modified to represent three levels of improvement in appliance efficiencies, and more batch simulations were conducted. Similarly, batch simulations were conducted for other energy improvement scenarios. From the comparison of baseline and subsequent batch simulation results, the impact of improving appliance and boiler/furnace efficiencies, building envelope improvements, and fuel substitution on space and domestic hot water heating on the residential energy consumption in Canada was determined for various market penetration levels of these energy efficiency measures.

3. Description

of simulation

studies conducted

Using the building energy simulation program and the Expanded STAR database, simulations were conducted to estimate the total household energy consumption with different scenarios for appliance efficiency, furnace efficiency, higher insulation level, and heat recovery ventilator options. 3.1. Appliance ejjkiency levels used in simulations The energy consumption values for the various appliances used in the baseline simulations are those given by Ugursal

V.I. Ugursul. Table 1 Baseline appliance

load curves

A.S. Fung /Energy

and Buildings

24 (1996)

139

137-146

(% of daily load in each hour)

Hour

Refrigerator

Freezer

Cooking

Dishwasher

Clothes washer

Clothes dryer

DHW

Lighting

TV

Miscellaneous

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

3.94 3.71 3.58 3.63 3.50 3.60 3.78 3.87 3.94 4.02 4.00 4.16 4.21 4.21 4.31 4.50 4.60 4.78 4.84 4.78 4.73 4.72 4.43 4.16

3.97 3.88 3.89 3.89 3.72 3.67 3.70 3.80 4.04 4.10 4.25 4.37 4.41 4.61 4.68 4.75 4.66 4.52 4.41 4.26 4.23 4.08 4.07 3.97

0.23 0.17 0.15 0.32 0.80 2.25 3.54 4.34 4.64 4.31 4.25 5.27 4.58 3.69 4.03 5.93 11.10 16.53 11.34 6.04 3.48 1.79 0.83 0.37

1.04 0.50 0.26 0.26 0.26 0.78 1.82 3.39 6.17 6.79 5.75 4.71 4.17 4.43 3.65 3.65 3.65 4.95 9.17 11.46 9.27 6.51 4.17 3.13

0.45 0.23 0.19 0.17 0.19 0.61 1.46 4.49 6.55 7.74 8.37 8.28 7.75 6.59 6.25 5.76 6.13 6.35 5.51 4.96 4.57 3.89 2.54 0.96

0.45 0.27 0.15 0.11 0.19 0.97 2.64 4.22 6.26 7.72 8.30 8.05 7.14 6.27 5.85 5.82 5.73 5.73 5.48 5.37 5.36 4.28 2.52 1.12

1.81 1.54 1.17 1.04 1.04 1.95 4.17 7.02 7.54 7.13 6.50 5.71 4.92 4.42 3.90 3.50 4.08 4.79 5.58 5.71 5.46 5.06 4.08 2.83

1.23 1.23 I .23 1.23 2.63 4.94 7.41 4.94 2.63 0.62 0.62 0.62 0.62 0.62 0.62 0.62 2.63 8.64 12.34 12.34 12.34 12.34 4.94 2.63

1.42 0.71 0.71 0.71 0.71 0.71 3.51 3.57 I .42 1.42 1.42 1.42 2.84 2.84 2.84 2.84 7.14 7.14 11.43 11.43 11.43 11.43 7.14 3.51

1.39 1.39 1.39 1.39 1.39 1.39 1.39 1.39 6.94 6.94 6.94 6.94 6.94 6.94 6.94 6.94 6.94 6.94 6.94 6.94 1.39 1.39 1.39 1.39

Sum

100.00

99.99

99.98

99.91

99.99

100.00

100.95

100.01

99.86

99.96

and Fung [ 81. These values were developed from an exhaustive literature review and reflect the energy consumption of appliances currently in use. The effects of three levels of appliance energy efficiency improvements are assessed in comparison to the baseline appliance energy consumption. The three levels of appliance efficiency improvements represent the technologies available at present, to be available in the near future (2-3 years) and to be available within the next decade. The energy consumption values used for appliances reflecting these three levels of appliance efficiencies were obtained largely from Koomey et al. [ 141 and Nadel et al. [ 1.51and are described in detail elsewhere [4]. The appliance energy consumption values used in the simulations are Table 2 Appliance

energy

Appliance

consumption

values used in simulations Annual electricity Baseline

Refrigerator Freezer Dishwasher (excl. hot water) Clothes washer Clothes dryer TV Hot water heater Lights and conv. All other appliances

given in Table 2. In addition to improvements in appliance efficiencies, the efficiencies of heating and cooling equipment were also improved over the baseline efficiencies in some scenarios evaluated. For heating equipment, efficiency improvements were assumed to be 5%, 10% and 15%, and for cooling equipment, the improvements were assumed to be 5%, 25% and 33%, respectively, reflecting the higher potential for improvement, Reduction in domestic hot water heating energy consumption as a result of improvements in clothes washers (automatic controls for type of fabric, dirtiness, etc., bubble action, horizontal axis machines), dishwashers (low energy dishwashers, cold water detergents), insulation of hot water tanks and piping, and reduced hot

1440 1530 280 90 1050 410 4490 4700

consumption

(kWh) Efficiency 890 570

Level

1

Efficiency

Level 2

700 470

230 230 same; savings in hot water consumption included below 830 620 165 135 3090 2080 4075 3535 5 % improvement 10% improvement

Efficiency

Level 3

420 285 230 520 135 1850 3100 15% improvement

140

V.I. Ugursal,

Table 3 Average annual heating system efficiencies

in Expanded

AS. Fung /Energy

STAR database

Fuel

No. of systems in Expanded STAR

Average annual efficiency (%)

Oil Natural gas Electric Propane Wood

229 406 296 4 2

10.3 68.8 99.9 11 45

water consumption due to use of faucet aerators and low-flow shower heads were also considered. 3.2. Simulations conducted The different scenarios that were simulated are described below. 3.2. I. Baseline simulations Baseline simulations were conducted to establish a baseline energy consumption level to which all other scenarios can be compared. For the baseline simulations, the following input data were used. (i) House thermal characteristics (such as thermal conductance, infiltration, etc.) from Expanded STAR database. (ii) Baseline energy consumption data for appliances. (iii) Heating system efficiency data of the houses given in the Expanded STAR database. The averages of heating system efficiencies in Expanded STAR are given in Table 3. 3.2.2. Series 1 simulations The objective of this series of simulations is to investigate the combined effect of improved appliance and lighting efficiency as well as improved boiler/furnace efficiency on the total residential energy consumption. Thus, house thermal characteristics from Expanded STAR database were used unchanged, whereas three different scenarios on appliance efficiency levels, along with three levels of furnace efficiency improvements were used in the simulations. The following simulations were conducted: Series l.A: Level 1 Appliance, Lighting and Furnace/ Boiler Efficiency Series l.B: Level 2 Appliance, Lighting and Furnace/ Boiler Efficiency Series 1.C: Level 3 Appliance, Lighting and Furnace/ Boiler Efficiency 3.2.3. Series 2 simulations The objective in this series of simulations is to investigate the effect of improved appliance and lighting efficiency on the total residential energy consumption. Thus, in these simulation runs, the furnace and/boiler efficiency values as well as house thermal characteristics are kept at the same value as indicated in the house data files, and only the appliance efficiency levels are changed.

and Buildings

24 (1996)

137-146

The following simulations were conducted: Series 2.A: Level 1 Appliance and Lighting Efficiency Series 2.B: Level 2 Appliance and Lighting Efficiency Series 2.C: Level 3 Appliance and Lighting Efficiency 3.2.4. Series 3 simulations In these simulation runs, the objective is to investigate the combined effect of improved building envelope, improved appliance/lighting efficiencies, and improved furnace/boiler efficiencies on the residential energy consumption. Thus, the thermal resistance values for walls, roof and windows are increased from their actual values to ‘medium insulation level’ (see Table 4) in all houses that have insulation levels lower than the ‘medium insulation level’. It is assumed that when a home owner improves the insulation level, air-tightness level is also improved as a result of direct (such as caulking, weather-stripping, etc.) and indirect (reduced leakage through joints, window-wall interfaces, etc.) improvemerits. Consequently, in these simulations, the infiltration rate is reduced by 15% reflecting the improvements in building envelope. Simulations were conducted to study the effect of improving appliance efficiency in conjunction with building envelope improvements (both insulation and air tightness) and furnace efficiency. Thus, three levels of appliance, lighting and boiler/furnace efficiency are used in simulations with building envelopes improved to ‘medium insulation level’: Series 3.A: Level 1 Appliance, Lighting and Furnace/ Boiler Efficiency Series 3.B: Level 2 Appliance, Lighting and Furnace/ Boiler Efficiency Series 3.C: Level 3 Appliance, Lighting and Furnace/ BoiIer Efficiency 3.25 Series 4 simulations These simulation runs are similar to Series 3 simulations described above, except in these simulation runs, the thermal resistance values for walls, roof, and windows are increased from their actual values to ‘high insulation level’ (see Table 4) rather than ‘medium insulation level’ in all houses that have insulation levels lower than the ‘high insulation level’. It is similarly assumed that when a home owner improves the insulation level, air-tightness level is also improved as a result of direct and indirect improvements. Consequently, in these simulations the infiltration rate is reduced by 30% reflecting the improvements in building envelope. Table 4 Description

of ‘medium’

and ‘high’

Roof RSI Wall RSI Window RSI RSI: thermal

resistance,

m* K/W.

insulation

levels

Medium

High

4.39 2.52 0.31

6.49 3.80 0.48

Wall RSI increase in exposed walls only.

V.I. Ugur.wd.

AS. Fung / Energy

Simulations are conducted to study the effect of improving appliance efficiency in conjunction with building envelope improvements (both insulation and air tightness) and furnace efficiency. Thus, three levels of appliance, lighting and boiler/furnace efficiencies are used in simulations with building envelopes improved to ‘high insulation level’: Series 4.A: Level 1 Appliance, Lighting and Furnace/ Boiler Efficiency Series 4.B: Level 2 Appliance, Lighting and Furnace/ Boiler Efficiency Series 4.C: Level 3 Appliance, Lighting and Furnace/ Boiler Efficiency In addition to the above scenarios, several others were evaluated to determine the effect of installing heat recovery ventilators in the houses that have ventilation systems, using night temperature setback, and various combinations of energy efficiency improvement measures. The results of these analyses are presented elsewhere [ 41.

4. Results of simulation

and Buildings

24 (1996)

137-146

141

Series

1 Slmulatlons

- Eleddc

Space

Heat

3 120.00 eI2100.00 8

eo.00

ils

:::,"I

2

20.00 -"""

0.00 2

Serbs

5 1

1 Simulations

- Natural

Gas Space

‘

Heat

100.00 eo.00

% 3

80.00

i

20.00 40.00 0.00 =

S.srles 1 StmulaUotw

- 011 Space

Heat

studies

The results presented here focus on the totals of primary space heating fuels, namely natural gas, electricity and oil, for all of Canada. Results for other fuels (propane and wood) are not reported in detail since they are of insignificant magnitude. Also, no analyses of the results are conducted at provincial level because the distribution of housing stock, fuel usage and fuel consumption in Expanded STAR is not well representative of the Canadian housing stock at provincial level. However, detailed results presented elsewhere [ 41 can be analyzed in numerous different levels and from different perspectives. It is also possible to simulate and study any scenario regarding changes in efficiencies of equipment and appliances, building envelope, temperature control scheme, etc. using the methodology presented here.

Series

1 Simulations

ImBSLN

Fig.

O1.A

- Total for All Fuels

El1.e

m1.c

1

1.Series1 simulation results.

4.1. Results of Series 1 simulations As can be seenfrom Fig. 1,residentialenergy consumption decreases as appliance and heating system efficiencies increase.A switch to the highest level of efficiency in all houseswould result in a reduction of 21% in overall residential energy consumption, all of which is in the form of electricity. In houseswhere the primary spaceheating fuel is electricity, spaceheating energy requirement increasessignificantly asappliance efficiency improves. There are two reasonsfor this: (i) as appliance efficiency increases,heat gain from appliances decreases, thus space heating requirement increases;(ii) sincethe efficiency of spaceheating with electricity cannot increase(already 100%)) there is no reduction in spaceheating energy requirement. On the other hand, the electricity consumption for DHW heating and appliances decreasessignificantly asapplianceefficiency increases.This is as a result of the reduced DHW consumption for dish

washing, clothes washing and general washing, as well as reducedheat lossesfrom the system.It can also be seenthat the reduction in applianceenergy consumptionis greaterthan the increasein electricity consumption for space heating, indicating that it is not beneficial to ‘heat’ a housewith appliances.There are severalreasonsfor this. (i) A large part of the energy used in inefficient heating and use of DHW (such as iri a clothes washer) is lost down the drain without any heat gain to the house, (ii) A large part of the energy used in clothes dryers is exhausteddirectly to outdoors. (iii) The heatgain from inefficient appliancesis not always ‘useful’ heat gain. When little or no heating is necessary during the warmer periods of shoulder seasons(spring and fall), the heatgain iswastedsinceit doesnot offset the heating requirement from the furnace or boiler. On the other hand, during the cooling season,the heat gain is a nuisancein nonair-conditioned housesand a source of additional energy

142

V.I. Ugur.wl.

A.S. Fung /Energy

waste in air-conditioned houses since the air-conditioner has to work harder to extract this additional heat gain. A review of the detailed output files indicates that in houses with airconditioning the decrease in total energy consumption with increased appliance efficiency is even greater since the airconditioning system has to work less to remove the appliance heat gain during the cooling season. In houses where the primary heating fuel is other than electricity, space heating energy requirements increase in Series 1.A simulation because the increase in heating system efficiency cannot make up for the loss of heat gain from improved appliances. However, in Series l.B and l.C simulations, space heating energy decreases slightly to the level of baseline consumption as the improvement in heating system efficiency can make up for the reduced heat gain from appliances. As in electrically heated houses, energy consumption for DHW heating and appliances, as well as the total energy consumption decreases significantly.

and Buildings

24 (1996)

137-146

saies

2 simulatlcne

Series 2 Simulations

Seifea

- Eleulfc

- Natural

2 Slmulatlons

-oil

t3paca

Heat

Gas Space

Space

Heat

Heat

4.2. Results of Series2 simulations As seenin Fig. 2, the total energy consumptiondecreases with the use of more efficient appliances.By switching to more efficient appliances,electricity consumptionis replaced by a smaller amount of other fuel consumption. A switch to the highest level of applianceefficiency in all houseswould result in a reduction of 11% in overall residential energy consumption,all of which is in the form of electricity. Clearly, the total reduction in energy consumptionis lessthan that of Series 1 simulationssinceefficiencies of heating systemsare not increased. In houseswhere the primary spaceheating fuel is electricity, the results are identical to those in Series 1 simulations since the heating systemefficiency is constant at 100%. In houseswherethe primary heatingfuel is other than electricity, spaceheating energy requirementsincreasefor all fuels since the heat gain from appliancesdecreasesas appliance efficiency increases,and the heating systemshave to make up for this heat gain. Also, while the fuel consumptionfor space heatingincreases,the fuel consumptionfor DHW heatingand appliancesdecreasesas appliance efficiency increases.The net result of this is that the total energy consumption for space/DHW heating and appliancesdecreasesfor all houses regardlessof spaceheating fuel type. Using detailed results, the ratios of the increasein space heating energy consumption to the reduction in appliance energy consumption were calculated. These ratios clearly show the effect of heating system efficiency on the heating energy requirement and end-use energy savings. In those houseswhere electricity is usedfor spaceheating (which has a conversion efficiency of lOO%), the increasein spaceheating energy consumption is equivalent to 57% of the savings in appliance energy consumption, i.e. for each 100 units of electricity saved in appliances,the heating system has to provide 57 units of heat from electricity. Thus, it is clear that heat gain from appliancesis not a feasible source of space

Setfee 2 Slmulaticne

- Total for All Fuels

Fig. 2. Series 2 simulation

results.

heating. Similar conclusionscan be madefor natural gas,oil and propanespaceheatingsystems.However, for wood space heating, the conclusion is the opposite: the increasein space heating energy consumptionis actually more than the savings in applianceenergy consumption:for every 100units of electricity saved in appliances,wood equivalent of 123 units of energy hasto be burned in the furnace. The reasonfor this is the low (45%) energy conversion efficiency of wood space heatingsystems.However, when the savingsin DHW heating energy are also included in the comparisons,high efficiency applianceswould result in overall end-useenergy savings in wood heatedhousesaswell. 4.3. Resultsof Series3 and Series4 simulations The results are given in Fig. 3 and Fig. 4. When these resultsare comparedto the resultsfrom Series1 simulations, it can beseenthat improving the building envelopeto medium insulationlevel resultsin a further 10%reduction, andto high

V.I. Ugursul, Serbs

3 Simulations

- Electtfc

Space

AS. Fung /Energy

and Buildings

f-teat

Setfe8

loo.00

d

80.00

1

80.00

j

20.00 40.00

4 Slmulattons

- EtecMc

Space

Heat

loo.00 80.00

c $

143

24 (1996) 137-146

80.00

70.00 B 3

80.00

5x:

0.00 1 Sedss

3 Simulations

- Natural

Gas Space

Heat

Series

f

2

4 Stmulattons

Gas Space

Heat

100.00 80.00 6o.ao

10.00 0.00

Sertes

3 Slmulattons

- Ott Space

Heat Series

100.00

4 E

- Natural

4 Slmutattons

- Oil Space

Heat

100.00 90.00

90.00 80.00

80.00

i

70.00 80.00

2

ig 20:oo

f Setfes

100.00

3 Stmulations

-Total

10.00 0.00

for All Fuels Serbs

8paca Heat

UfN

3.A

q

3.B

q

- Total for Att Fuels

TOT&

Ap$lancr

spa00 b1

n l35lN q

4 Simulations

ctw

!&iance

TOTAL

3.c

Fig. 3. Series 3 simulation results.

n BSN o Fig. 4. Series 4

insulation level resultsin a 20% reduction in total residential energy consumption in Canada.

5. Impact of appliance efficiency on residential end-use energy consumption in Canada The savingsin the residentialconsumptionof eachfuel for different scenariosif the energy savingmeasureswere applied in all residencesin Canada (i.e. 100% penetration of energy saving measures)were calculated. Since it is not realistic to assumethat thesemeasureswould be adoptedin 100% of the housing stock, these savings are higher than what can be reasonablyexpected.To obtain amore realistic representation of the impact of appliance efficiency on residential energy consumption in Canada, two levels of market penetration levels, 10% and 20%, are assumedfor adoption of energy saving measures.The resultsfor market penetrationlevel of 10% are presentedin Table 5. The resultsof 20% penetration level can be calculated by multiplying the values in Table 5

4.A

simulation

q

4.B

q

4.C

results.

by two. It should be noted that in all calculations market penetration is assumedto be instantaneous,i.e. a gradual adoption of measuresis not considered.Although the results are self-explanatory, it may be worthwhile to point out the following observations. (i) Regardlessof the scenarioadopted,the residentialconsumptionof electricity decreases.The magnitudeof electricity savingsvaries betweennegligibly small (results of Series 2.A simulation), and 4.6% with 10% penetration and 9.2% with 20% penetration (results of Series 4.C simulation). However, the samecannotbe saidfor all other fuels. Depending on the scenarioevaluated, increasesin the consumption of other fuels (which are usedfor spaceand DHW heating) are seenfor certain scenarios,most notably for Series2 simulations which involved improvement of appliance efficiencies only. As discussedearlier, when only the appliance efficiencies are improved, the heat gain that comesfrom the applianceshas to be replaced by the heating fuel, and this causesthe increasein the consumptionof that fuel.

144

V.I. Ugursal,

Table 5 Savings in residential

Canada Series 1.A l.B 1.C 2.A 2.B 2.c 3.A 3.B 3.c 4.A 4.B 4.c

1992

fuel consumption

in Canada with different

Electricity (GWh)

Natural (GL)

131000

14600

Savings 2870 3920 4620 2870 3920 4620 3410 4460 5160 4260 5330 6040

AS. Fung/Energy

7 112 16.5 - 84 -63 - 89 187 282 326 416 498 530

gas

scenarios

and Buildings

24 (1996)

137-146

(10% penetration

of energy

saving measures; negative

values indicate

increases)

Oil (ML)

Wood (Cord)

Propane (ML)

Total

3570

5820000

558

1270000

100

-14

- 11900 31500 58900 - 72200 - 82500 - 103900 40000 79000 103000 135000 167000 184000

-5 -4 -3 -9 -11 - 14 7 8 9 16 16 17

9720 18900 24400 4210 8360 9040 22500 31100 36000 38400 46300 50600

0.8 1.5 1.9 0.3 0.7 0.7 1.8 2.4 2.8 3.0 3.6 4.0

4 15 -39 -44 -55 60 74 81 122 132 137

(ii) Regardless of the scenario evaluated, there is a decrease in total residential energy consumption. The overall savings in energy consumption vary between 0.33% and 3.97% of the total for 10% penetration of energy saving measures, and between 0.66% and 7.94% for 20% penetration. The savings associated with the improvement of only appliance efficiencies vary between 0.33% and 0.71% for 10% penetration, and 0.66% and 1.42% for 20% penetration. These results clearly indicate that although improving appliance efficiency would result in about l-2% reduction in the overall residential energy consumption, for amore significant impact, energy saving measures such as improved building envelope and control of mechanical systems should be applied along with improving appliance efficiency. (iii) The magnitude of energy savings increases linearly with market penetration level of energy saving measures.

6. Impact of appliance efficiency and fuel substitution on fuel consumption in Canada There is an opportunity to reduce end-use fuel consumption in Canada by switching from oil and propane to natural gas and electricity for space and DHW heating. To study the impact of fuel switching and improving appliance efficiency on residential energy consumption, two fuel switching scenarios are evaluated: Fuel Switching Scenario 1: switch 20% of oil and 20% of propane consumption to natural gas Fuel Switching Scenario 2: switch 20% of oil and 20% of propane consumption to electricity For Fuel Switching Scenario 1, it is assumed, in keeping with the current practice, that the new furnaces that are installed in place of existing oil and propane furnaces would be high or medium efficiency furnaces, with an average efficiency of 80%.

% of Total

(GJ)

To evaluate the impact of adopting these two scenarios, first the energy requirement from each fuel was calculated from equivalent fuel consumption using the following equation: Energy requirement from fuel (I) in TJ equivalent = (consumption of fuel (I) in TJ equivalent) X (utilization efficiency for fuel (I) ) In evaluating these equations, the equivalent fuel consumption values can be obtained from Tables 5-7 using the heating value of fuels: 1 GL of natural gas = 37.9 TJ; 1 ML of NGL (assumed propane) = 25.5 TJ; 1 GWh of electricity = 3.6 TJ; 1 ML of oil = 38.7 TJ; 1 cord of wood = 16.6 GJ. The utilization efficiencies for the fuels used are given in Table 3. The end-use fuel consumption values from each fuel with Fuel Switching Scenario 1 were calculated as follows: (i) reduce the oil and propane energy by 20% and add these amounts on to natural gas energy; (ii) calculate the new equivalent fuel consumption values for natural gas using the equation above and 80% fuel utilization efficiency for new natural gas furnaces; (iii) calculate the new fuel consumption values using the heating value of the fuels; (iv) calculate the savings for each fuel with respect to the actual fuel consumption in Canada. The same procedure was used to calculate the end-use fuel consumption values for each fuel with Fuel Switching Scenario 2. It is also assumed that fuel switching occurs at the beginning of the year, i.e. a gradual switching scenario is not considered. The end-use fuel savings that can be obtained by fuel switching with 20% penetration of energy saving measures for the two fuel switching scenarios studied here are presented

V.I. Ugutxzl, Table 6 Fuel savings with Fuel Switching Natural (GL) Canada

1992

Simulation l.A 1.B l.C 2.A 2.B 2.c 3.A 3.B 3.c 4.A 4.B 4.c

gas

A.S. Fung/

Scenario No. 1 over no fuel switching

Energy and Buildings

(20% penetration

Oil (ML)

Propane (ML)

Natural (So)

14600

3570

558

Savings -719 -712 -708 - 729 -732 - 736 -689 - 684 -681 - 665 -661 -659

719 712 708 729 731 736 690 684 681 665 661 659

1 I4 113 113 115 116 117 109 108 108 105 105 105

in Table 6 and Table 7. More detailed results can be found in Ref. [4]. The following observations can be made from the results presented in Tables 6 and 7. (i) By switching to natural gas from oil and propane (Fuel Switching Scenario No. 1) obviously the natural gas consumption increases while oil and propane consumption decreases. It should also be noted that there is a slight decrease in total fuel energy consumption (see last two columns of Table 6). This decrease is as a result of the higher average efficiency of replacement natural gas fired furnaces (assumed to be 80%) compared to that of oil and propane fired furnaces (70.3% and 77%, respectively). (ii) By switching to electricity from oil and propane (Fuel Switching Scenario No. 2), oil and propane consumption decreases while electricity consumption increases. Since the end-use energy conversion efficiency of electric resistance heating is nearly lOO%, there is a reduction in the total enduse energy consumption as seen in the last two columns of Table 7. It should however be noted that the efficiencies of electricity generation and transmission are not considered in these calculations. Thus, the values cited for reduction in electricity consumption are at the end-use level, which is different than the ‘primary’ or ‘source’ energy consumption used in the generation of electricity. (iii) Depending on the fuel switching scenario selected and the assumptions for market penetration of energy efficiency measures, the reductions and shift in fuel consumption can be significant. Thus, promotional or incentive programs can be utilized to modify the fuel mix in the residential market. The impact of any fuel switching scenario can be evaluated using the approach presented here. 7. Conclusions In this paper, the effect of appliance efficiency on the overall residential end-use energy consumption in Canada is

24 (1996)

of energy

137-146

saving measures)

145

(negative

values indicate

increases)

Oil (%)

Propane (%I

Energy

Energy

(TJ)

(%)

100

100

100

706000

100

-4.9 - 4.9 -4.8 -5.0 -5.0 - 5.0 -4.7 -4.7 -4.7 -4.6 -4.5 -4.5

20.2 20.0 19.8 20.4 20.5 20.6 19.3 19.2 19.1 18.6 18.5 18.5

20.4 20.3 20.2 20.7 20.8 21.0 19.5 19.4 19.4 18.8 18.8 18.8

3480 3450 3430 3530 3540 3560 3340 3310 3300 3220 3200 3190

0.49 0.49 0.49 0.50 0.50 0.50 0.47 0.41 0.47 0.46 0.45 0.45

gas

investigated based on simulation studies conducted on the Expanded STAR database using an hour-by-hour building energy simulation program. In addition, the effect of fuel substitution for space and domestic hot water heating on residential end-use energy consumption is evaluated. A range of scenarios on the impact of appliance efficiency improvements, as well as house envelope and mechanical system improvements on residential end-use energy consumption were evaluated by conducting simulations on the Expanded STAR database. In addition, the consequences of fuel switching on fuel consumption were studied using the same approach. In all simulations, it is assumed that energy saving and fuel substitution measures are carried out at the beginning of the year, i.e. a gradual adoption of measures is not considered. The findings clearly indicate that to reduce the residential end-use energy consumption improving only appliance efficiencies is not an effective approach in itself. For more significant reductions in energy consumption, improvement in house envelope and mechanical systems should also be considered. Since the energy savings associated with improving appliance efficiencies is not high (less than 1% for a 10% market penetration), it is very important that detailed costbenefit analyses are carried out in making decisions. Depending on how the energy consumption is shifted from certain fuels to others, there can be significant reductions in total end-use energy consumption in Canada. In this study, two possible scenarios were evaluated, and the associated findings are therefore applicable to these scenarios only. The important conclusion that can be drawn from this study is that the magnitude of the reductions should be calculated specifically for the scenario in question as there are no general conclusions that can be drawn. Using an approach similar to that used here, the economic and technological feasibility of numerous strategies to meet regional or national residential energy reduction objectives

146

V.I. Ugursal,

Table 7 Fuel savings with Fuel Switching

Canada

1992

Simulation l.A I.B 1.c 2.A 2.B 2.c 3.A 3.B 3.c 4.A 4.8 4.c

Scenario

A.S. Fung/Energy

No. 2 over no fuel switching

and Buildings

(20% penetration

24 (1996)

of energy

137-146

saving measures)

(negative

values indicate

increases)

Electricity (GWh)

Oil (ML)

Propane (ML)

Electricity (%)

Oil (So)

Propane (%I

Energy

Energy

VJ)

(%o)

131000

3570

558

100

100

100

624000

100

Savings -6050 - 6000 - 5960 -6140 -6160 - 6200 -5800 -5760 - 5740 -5600 -5570 -5550

719 712 708 729 731 736 690 684 681 665 661 659

114 113 113 115 116 117 109 108 108 105 105 10.5

-4.6 -4.6 -4.5 -4.7 -4.7 -4.7 -4.4 -4.4 -4.4 -4.3 -4.2 -4.2

20.2 20.0 19.8 20.4 20.5 20.6 19.3 19.2 19.1 18.6 18.5 18.5

20.4 20.3 20.2 20.7 20.8 21.0 19.5 19.4 19.4 18.8 18.8 18.8

8930 8846 8790 9054 9085 9139 8561 8497 8460 8257 8209 8187

1.3 1.3 1.2 1.3 1.3 1.3 1.2 1.2 1.2 1.2 1.2 1.2

can be evaluated, and optimal residential energy efficiency and fuel substitution strategies can be developed. Acknowledgements The authors gratefully acknowledge the financial support from Canada Mortgage and Housing Corporation for this project. They also acknowledge the contributions of Duncan Hill of Canada Mortgage and Housing Corporation and Tom Hamlin of Natural Resources Canada. References [ I] Statistics Canada, Energy Statistics Handbook, Catalogue 57.601, Ottawa, Ont., 1995. [2] UN Frumework Convention on C/imafe Change, UNEP/WMO Information Unit on Climate Change, Geneva, Switzerland, 1992. [ 3 I National Energy Board, Canadian Energy Supply and Demand 19&72005, Ministry of Supplies and Services, Canada, Sept. 1988. [4] V.I. Ugursal and A.S. Fung, Energy Eficiency Technology Impact Appliances. Final Rep., Canada Mortgage and Housing Corporation, Ottawa, Ont., 1995. [5] Enermodal Engineering, Enerpuss, Version 3.0, Enermodal Engineering Ltd., Waterloo, Ont., July 1990. [6] Scanada Consultants Ltd., Environmental Impact Study: Phase I Development of a Database on Housing Characteristics Representative of the Cunadian Housing Stock, Final Rep,, Canadian Mortgage and Housing Corporation, Ottawa, Ont., 1992.

Ltd., Hot-2000 Housing Dntu Base, Bumaby, BC, [71 SAR Engineering 1993. [81 V.I. Ugursal and A.S. Fung, Household appliances: electricity consumption, saturation and classification, Energy Build., (1995). [91 Statistics Canada, Household Facilitiesand Equipment, Catalogue No. 64-202, Ottawa, Ont., 1992. [ 101H. Ruderman, J.H. Eto, K. Heinemeier, A. Golan and D.J. Wood, Residential end-use load shape data analysis: final report, Rep. No. LBL-27114 (DOE Contract No. DE-AC03-76SFOO098), Lawrence Berkeley Laboratory, CA, Apr. 1989. [Ill R. Pratt, C. Conner, E. Richman, K. Ritland, W. Sandusky and M. Taylor, Description of electric energy use in single-family residences in Pacific Northwest, DOE Rep. No. DOE/BP-1379522, Bonneville Power Administration, 1989. 1121P.B. Usoro, I.C. Schick and M.F. Ruane, Residential end-use loadshape estimation, Vol. 1: Methodology and results of statistical disaggregation from whole-house metered loads, EPRI Rep. EM-4525, May 1986. [I31 ewave Engineering, Final Rep.: Development of OH-RES, the Ontario Hydro Residential DSM Analysis Too/, Ontario Hydro, Toronto, Ont., Dec. 1992. S. Boghosian, [ 141 J.G. Koomey, C. Atkinson, A. Meier, J.E. McMahon, B. Atkinson, I. Turiel. M.D. Levine, B. Nordman and P. Chan, The potential for electricity efficiency improvements in the U.S. residential sector, Rep. No. LBL-30477 (DOE Contracr No. DE-AC0376SFOOO98), Lawrence Berkeley Laboratory, July 199 1. [ 151 S. Nadel, D. Boume, M. Shephard, L. Rainer and L. Smith, Emerging technologies to improve energy efficiency in the residential and commercial sectors, Rep. No. A931, American Council for an Energy Efficient Economy, Feb. 1993.