Long-Term Results from Evaluation 

of Advanced New Construction 

Packages in Test Homes: 

Martha’s Vineyard, Massachusetts

Dave Stecher, Katherine Allison, and 

Duncan Prahl 

IBACOS, Inc.

October 2012
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iii

Long-Term Results from Evaluation of Advanced New Construction 

Packages in Test Homes: Martha’s Vineyard, Massachusetts

Prepared for:

The National Renewable Energy Laboratory 

On behalf of the U.S. Department of Energy’s Building America Program

Office of Energy Efficiency and Renewable Energy

15013 Denver West Parkway 

Golden, CO 80401 

NREL Contract No. DE-AC36-08GO28308 

 

Prepared by: 

Dave Stecher, Katherine Allison, and Duncan Prahl 

IBACOS, Inc.

2214 Liberty Avenue

Pittsburgh, PA 15222 

NREL Technical Monitor: Michael Gestwick

Prepared under Subcontract No. KNDJ-0-40341-00 

October 2012 
iv

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v 

Contents

List of Figures ............................................................................................................................................ vi

List of Tables .............................................................................................................................................. vi

Definitions.................................................................................................................................................. vii

Executive Summary................................................................................................................................. viii

Acknowledgments ................................................................................................................................... viii

1 Introduction and Background ............................................................................................................. 1

1.1 Purpose and Research Questions .........................................................................................2

2 Mathematical and Modeling Methods................................................................................................. 4

3 Experimental Methods ......................................................................................................................... 8

4 Results................................................................................................................................................. 12

5 Discussion........................................................................................................................................... 23

6 Conclusions ........................................................................................................................................ 26

7 References .......................................................................................................................................... 27
vi 

List of Figures

Figure 1. Site plan ....................................................................................................................................... 1

Figure 2. BEopt annual energy calculations for the house without PV ................................................ 5

Figure 3. Outdoor data logger ................................................................................................................... 8

Figure 4. Indoor data logger....................................................................................................................... 8

Figure 5. First-floor plan with data logger locations ............................................................................... 9

Figure 6. Second-floor plan with data logger locations.......................................................................... 9

Figure 7. Basement plan with data logger location............................................................................... 10

Figure 8. Nighttime temperature differences in House 1 ...................................................................... 12

Figure 9. Daytime temperature differences in House 1......................................................................... 13

Figure 10. Nighttime temperature differences in House 2 .................................................................... 13

Figure 11. Daytime temperature differences in House 2....................................................................... 14

Figure 12. Nighttime temperature differences in House 3 .................................................................... 14

Figure 13. Daytime temperature differences in House 3....................................................................... 15

Figure 14. Nighttime temperature differences in House 4 .................................................................... 15

Figure 15. Daytime temperature differences in House 4....................................................................... 16

Figure 16. Comparison of temperature to electric energy used for heating....................................... 17

Figure 17. Hourly temperatures in the living rooms of the four houses ............................................. 18

Figure 18. Temperatures in the living rooms of houses 3 and 4.......................................................... 19

Figure 19. Absolute temperatures in the living room and bedrooms in House 3 .............................. 20

Figure 20. Temperature differences between the living room and bedrooms in House 3 ................ 20

Figure 21. Absolute temperatures in the living room and bedrooms in House 4 .............................. 21

Figure 22. Temperature differences between the living room and bedrooms in House 4 ................ 21

Unless otherwise noted, all figures and photos were created by IBACOS. 

List of Tables

Table 1. Technical Specifications for the Four Houses .......................................................................... 2

Table 2. Submetered Systems ................................................................................................................. 10

Table 3. House Occupancy ...................................................................................................................... 10

Table 4. Electricity Used from November 2010 to January 2011 (from Meter Readings) .................. 16

Table 5. Average Temperatures in Living Rooms and Bedrooms ....................................................... 17

Table 6. Measured Energy Consumptions Compared to the Calculated Energy Consumption from 

BEopt Modeling .................................................................................................................................. 22

Table 7. Peak Heating and Cooling Loads for the Three Bedrooms.................................................... 22

Unless otherwise noted, all tables were created by IBACOS. 
vii 

Definitions

ANSI American National Standards Institute

ASHRAE American Society of Heating, Refrigerating and AirConditioning Engineers 

benchmark Benchmark house as defined in the Building America House 

Simulation Protocols (Hendron and Engebrecht 2010) 

BEopt Building Energy Optimization (software)

Btu British thermal unit

cfm Cubic feet per minute

DHU Ductless heat pump unit

DHW Domestic hot water

EF Energy factor

ft2 Square foot

HSP Building America House Simulation Protocols (Hendron and 

Engebrecht 2010) 

HSPF Heating seasonal performance factor

IGF Internal gains factor

IHG Internal heat gains

in. Inch

kW Kilowatt

kWh Kilowatt-hour

LAMELs Lighting, appliances, and miscellaneous electric loads

LEED for Homes Leadership in Energy and Environmental Design for Homes

polyiso Polyisocyanurate

PV Photovoltaics

SEER Seasonal energy efficiency ratio

SHGC Solar heat gain coefficient

W Watt

XPS Extruded polystyrene
viii

Executive Summary

This report presents a cold climate project that examines the relationships among very energy 

efficient single-family residential thermal enclosures, room-to-room temperature variations, and 

simplified space conditioning systems. The project was developed, designed, and built by South 

Mountain Company and is located in West Tisbury, Massachusetts, on the island of Martha’s 

Vineyard. This project allowed investigators to compare room-to-room temperatures in four 

virtually identical houses that were all built to the same construction standard. Each of the four 

all-electric homes has a single ductless heat pump unit (DHU) located in the main living space 

with a single programmable thermostatic control built into the unit. Each bedroom and the main 

bathroom have radiant electric resistance panels with individual nonprogrammable thermostatic 

controls that occupants can turn on and off for their comfort. Results indicate that temperature 

fluctuations in the living room resulting from aggressive setup and setback of the DHU may 

contribute to fewer hours when the bedroom temperatures are within +2°F of the living room 

temperatures, compared to houses without setback. Solar gains in the living room, along with 

opening and closing doors, appear to have a significant impact on room-to-room temperature 

differences, as would be expected. Setback strategies do not appear to save energy but do 

contribute to significant temperature variations.

Acknowledgments

The authors thank the South Mountain Company for developing, designing, and constructing this 

innovative project (including the energy systems); for coordinating access to the houses; and for 

supporting data collection activities. The authors also thank the residents of the houses, who 

allowed the authors to record the data and endured the inconvenience of monthly meter readings, 

and Matt Coffey for diligently collecting the data. Finally, the authors thank the U.S. Department 

of Energy’s Building America Program for funding this research. 
1 

1 Introduction and Background

In 2010 IBACOS identified a project designed and built by South Mountain Company in West 

Tisbury, Massachusetts, on the island of Martha’s Vineyard that was nearing completion and was 

aligned with ongoing research into the application of simplified space conditioning systems in 

highly insulated houses. The community consists of eight all-electric two- and three-bedroom 

(1,251 and 1,447 ft2, respectively) Cape Cod style houses built in a cluster development as 

shown in Figure 1. Houses 1, 2, 3, and 4 in Figure 1 all have identical three-bedroom floor plans. 

Each of these four all-electric homes has a single ductless heat pump unit (DHU) located in the 

main living space with a single programmable thermostatic control built into the unit. Each 

bedroom and the main bathroom have radiant electric resistance panels with individual 

nonprogrammable thermostatic controls that the occupants can turn on and off for their comfort. 

Figure 1. Site plan 

Courtesy of South Mountain Company, used with permission

All houses are highly insulated and very airtight. Each has earned a platinum rating from the 

U.S. Green Building Council’s Leadership in Energy and Environmental Design for Homes 

(LEED for Homes) program. IBACOS was not involved in the design or specifications of the 

houses. South Mountain Company has been designing and building energy efficient houses for 

more than 30 years. Abrams (2011) contains a comprehensive description of the project and its 

technical features, which also is available on the South Mountain Company website. Table 1

gives the general specifications for the all-electric houses.
2 

Table 1. Technical Specifications for the Four Houses

Building System Specification

Below Slab R-20 XPS foam

Foundation Walls R-20 polyiso foam

Framed Wall R-31 cellulose in 91⁄2-in. double stud wall

Windows U-value = 0.19, south windows SHGC = 

0.62, all others SHGC = 0.48 

Air Leakage for Houses 1, 3, and 4 117 to 184 cfm 50

Air Leakage for House 2 236 cfm 50

Roof R-50 unvented attic in 14-in. deep 

engineered I joist roof rafter

HVAC—Main Living Space 

2-ton minisplit with single head in living 

room, 10 HSPF, 18 SEER, programmable 

thermostat

Supplemental Heating— 

Second-Floor Bedrooms

400-W radiant electric resistance panels, 

individual nonprogrammable thermostat in 

each bedroom controlling the panel in that 

room 

Supplemental Heating—First-Floor 

Master Bedroom

600-W radiant electric resistance panel, 

individual nonprogrammable thermostat in 

bedroom controlling that panel 

Ventilation 70-cfm continuous ~55% sensible heat 

recovery, 35-W fan

Water Heating 50-gal electric tank type, 0.94 EF

PV 5.04-kW grid connected

Notes: XPS, extruded polystyrene; polyiso, polyisocyanurate; SHGC, solar heat gain coefficient; HSPF, heating 

seasonal performance factor; SEER, seasonal energy efficiency ratio; EF, energy factor; PV, photovoltaics. 

1.1 Purpose and Research Questions

The purpose of this study was to assess the comfort implications of the DHU and radiant electric 

resistance panel HVAC strategy and to evaluate the relative contribution of electrical energy 

usage for space heating from early November 2010 through the end of January 2011. The study 

team’s general approach was to evaluate the temperature differentials between the bedrooms and 

the main living space of each house. Rittelmann (2006) found conflicting standards related to 

evaluating whole-house comfort. As defined by the American National Standards Institute 

(ANSI) and ASHRAE (2004), thermal comfort is “that condition of mind which expresses 

satisfaction with the thermal environment and is assessed by subjective evaluation.” 

Rutkowski (2006) offers guidance for dry-bulb temperature variances from the thermostat setting 

during the heating season, as measured at the thermostat to be +2°F. Similarly, the temperature 

during the heating season in any room should be +2°F of the thermostat set temperature. Room-
3 

to-room temperature differences or floor-to-floor temperature differences should be no greater 

than 4°F in the heating season. Air temperature is only one factor in measuring overall thermal 

comfort (ASHRAE 2004), but Rittelmann (2006) found that, in well-insulated houses with lowemissivity windows, air temperature and mean radiant temperature track fairly closely, except 

when the windows are experiencing direct solar gain. 

In this project, the study team sought to answer several key research questions related to thermal 

comfort in very energy efficient houses. Because of the stage at which the project was identified 

(roughly 4 months after occupancy), detailed instrumentation was not possible. Using some lowcost data collection strategies in conjunction with the electromechanical submetering that South 

Mountain Company installed as part of the project’s construction, however, the study team felt 

that reasonable insight into these questions could be gained. The primary questions were as 

follows: 

1. What is the room-to-room temperature difference between the main space with the DHU 

and the individual bedrooms with radiant electric resistance panels?

2. What is the impact of thermostat setback/setup of the DHU on bedroom temperatures? 

3. What are the correlations among the temperature at the main DHU; the gross overall 

energy consumption for heating; and the breakdowns among the DHU, the radiant 

electric resistance panels, and internal gains from all other electricity used during the 

study period? 

The purpose of this investigation was not to compare modeled to actual energy consumption but 

to better understand the dynamics of multizone heating strategies and associated energy 

consumption. 
4 

2 Mathematical and Modeling Methods

The three-bedroom house (1,447 ft2 above grade, 784 ft2 below grade conditioned floor area) was 

modeled in BEopt (Building Energy Optimization) software (Version 1.1).1 The study team 

conducted the modeling to evaluate projected energy efficiency compared to the Building 

America benchmark using the House Simulation Protocols (HSPs) of Hendron and Engebrecht 

(2010). This was done primarily to validate that the strategy chosen by South Mountain 

Company met key source energy savings criteria for the Building America Program, not to try to 

predict actual energy consumption for end uses. BEopt 1.1 does not have DHUs or radiant 

electric resistance panels as options in the equipment libraries, nor does it have the capability to 

model zoned or hybrid heating systems. The study investigators evaluated two different 

scenarios to demonstrate the range of predicted energy consumption for heating. The first was a 

ducted forced air system with an electric furnace and an 18 SEER air-conditioning unit, 

completely within the conditioned space. The other was the same ducted forced air system with a 

9.2 HSPF/18 SEER air source heat pump, also completely within the conditioned space. 

Figure 2 shows the modeling calculations for the annual energy consumption of the house 

without PV. BEopt calculated 27% source energy savings with the electric resistance furnace and 

39% savings with the heat pump. No modeling was performed to evaluate the projected room-toroom temperature differences between the main living space with the heat pump and the 

bedrooms when the radiant electric resistance panels were not being used. BEopt modeling 

assumed that the whole house was heated and cooled using the DHU or the electric resistance 

furnace. Modeling also assumed a uniform space temperature throughout the house. 

 

1 See http://beopt.nrel.gov/ for more information.
5 

Figure 2. BEopt annual energy calculations for the house without PV

The study team calculated the whole-house heating contribution for the study period to attempt 

to account for all the direct space heating energy (DHU and electric resistance panels) and 

internal heat gains (IHGs) from the other lighting, appliances, and miscellaneous electric loads 

(LAMELs) and domestic hot water (DHW) subsystems. Measurements of the subsystems are 

described in Section 4. The team used Equation 1 to calculate the heating energy usage for the 

entire study period: 

HP Pan LAMEL DHW Heating kWh in Energy kWH kWH ++= IHG + IHG (1)

where

kWhHP = measured kilowatt-hours used by the heat pump during the study period 

kWhPan = measured kilowatt-hours used by the radiant panels in the bedrooms during the study 

period 

27% Savings 

with Respect to

Benchmark 39% Savings 

with Respect to

Benchmark
6 

IHGLAMEL = calculated internal gains in kilowatt-hours from measured LAMELs during the study 

period 

IHGDHW = calculated internal gains in kilowatt-hours from measured DHW in gallons during the 

study period. 

The additional whole-house contribution of the sensible internal gains from ventilation fan and 

LAMEL electric usage was estimated for each house using an internal gains factor (IGF). The 

IGF in Equation 2 is the percentage of sensible load considered to be contributing to satisfying 

the heating loads, using the equations found in the HSPs (Hendron and Engebrecht 2010): 

∑ = ∑

LAMEL

Sens fract LAMEL

B

B

IGF 

 (2)

where

∑BSens fract LAMEL = sum of the sensible load fractions of benchmark LAMELs from the equations 

in the HSPs 

∑BLAMEL = sum of site kilowatt-hours for benchmark LAMELs. 

For the house size (2,231 ft2

 conditioned floor area) and the number of bedrooms, the IGF was 

calculated as

%.66

 7104 kWh

 4657 kWh =

The IGF was then applied to each house to estimate the internal gains using Equation 3: 

IHG = ∑ kWhLAMEL × IGF Nov

LAMEL Jan (3)

where kWhLAMEL is the calculated LAMEL use per month for the study period in kilowatt-hours. 

The kWhLAMEL was calculated by subtracting the electric readings of each of the submeters from 

the whole-house utility meter reading.

Using Equation 4, the study team also estimated the whole-house contribution of the sensible 

internal gains from the DHW system:

Btu 3413

 1 kWh

day

gal NCTH

day

Btu NCTH

×

























= ∑ × Act

Nov

DHW Jan gpMo

DHW

IHG

IHG (4)

where
7 

IHGDHW = internal heat gain from the DHW system losses for the entire study period in site 

kilowatt-hours 

NCTHIHGBtu/day = new construction test home daily internal DHW heat gain from the HSPs 

(Hendron and Engebrecht 2010) in British thermal units 

NCTHDHWgal/day = new construction test home daily DHW usage from the HSPs (Hendron and 

Engebrecht 2010) in gallons 

gpMoAct = measured DHW gallons in the study houses over the course of the study period. 
8 

3 Experimental Methods

The study team used the data collected for comparisons of variations in temperature between the 

main living space and rooms not actively conditioned by the DHU. The impact of independently 

controlled electric resistance heaters in each room was also evaluated. Validation of whole-house 

energy savings was outside the scope of this study. 

Temperatures in each bedroom, at the thermostat location in the main living space, in the 

basement, and outdoors were measured and recorded hourly using miniature data loggers. The 

data loggers recorded the room temperature each hour on the hour. Because of limitations in the 

data logger storage capabilities, the fluctuations in temperature between hours (i.e., 5-minute 

average) were not measured. Figure 3 and Figure 4 are representative images of the outdoor and 

indoor sensors installed in the house. 

Figure 3. Outdoor data logger

Courtesy of South Mountain Company, 

used with permission

Figure 4. Indoor data logger

Courtesy of South Mountain Company, 

used with permission
9 

Sensor locations throughout the house are shown in Figure 5, Figure 6, and Figure 7. 

Figure 5. First-floor plan with data logger locations

Courtesy of South Mountain Company, 

used with permission

Figure 6. Second-floor plan with data logger locations

Courtesy of South Mountain Company, 

used with permission
10 

Figure 7. Basement plan with data logger location

Courtesy of South Mountain Company, 

used with permission

Data were collected from early November 2010 through the end of January 2011. Before 

IBACOS became involved in the project, South Mountain Company had installed submetering in 

each house on the subsystems shown in Table 2. 

Table 2. Submetered Systems

Subsystem Meter Measurement

DHU Watt-hour kilowatt-hour (electric)

Radiant Panels (Bundled) Watt-hour kilowatt-hour (electric)

DHW Watt-hour kilowatt-hour (electric)

PV Inverter Output Watt-hour kilowatt-hour (electric)

Cold Water to DHW Tank flow gallons

Table 3 gives the number of occupants in each house. 

Table 3. House Occupancy

Occupant House 1 House 2 House 3 House 4

Adults 2 2 3 2

Children 1 2 1 2
11 

One of the residents in the community collected the watt-hour and flow meter readings each 

month. The data loggers for temperature measurements were launched at the beginning of the 

study period and downloaded once at the end of the study period. The data loggers collected the 

room temperature once each hour. No attempt was made to record the door open/closed state of 

the bedroom doors in the houses. Two temperature data loggers failed in two of the houses: an 

east second-floor bedroom data logger in House 1 and a west second-floor bedroom data logger 

in House 2. 

Before IBACOS became involved, South Mountain Company offered a prize to any resident who 

could achieve net zero annual energy use. As reported by Rosenbaum (2011), two of the eight 

houses reached net zero annual consumption. One of the houses that achieved net zero was also 

one of the houses in this study group. The other three houses in this study group had the highest 

total site energy consumption of all eight houses. 
12 

4 Results

The study team analyzed temperature data to compare the temperature at the thermostat location 

to the temperature in each of the bedrooms. Rutkowski (2009) recommends that the temperatures 

in rooms other than where the thermostat is located should be no more than +2°F of the 

temperature at the thermostat. For the study period, temperatures in the bedrooms were sorted 

into hourly bins in 2°F increments above or below the thermostat temperature. The temperature 

data were further disaggregated into day (8:00 a.m. to 7:00 p.m.) and night (8:00 p.m. to 

7:00 a.m.), which represented the 12 hourly temperature readings taken by the data loggers. 

These were used to analyze differences in temperatures when the bedrooms were presumed to be 

normally unoccupied (day) and occupied (night), respectively. Investigators also analyzed the 

electric consumption for the study period for heat pump use, radiant electric resistance panel use, 

and sensible internal gains.

Results for House 1 from 8:00 p.m. to 7:00 a.m. and 8:00 a.m. to 7:00 p.m. are shown in Figure 8

and Figure 9, respectively.

Figure 8. Nighttime temperature differences in House 1
13 

Figure 9. Daytime temperature differences in House 1

Results for House 2 from 8:00 p.m. to 7:00 a.m. and 8:00 a.m. to 7:00 p.m. are shown in Figure 

10 and Figure 11, respectively.

Figure 10. Nighttime temperature differences in House 2
14 

Figure 11. Daytime temperature differences in House 2

Results for House 3 from 8:00 p.m. to 7:00 a.m. and 8:00 a.m. to 7:00 p.m. are shown in Figure 

12 and Figure 13, respectively.

Figure 12. Nighttime temperature differences in House 3
15 

Figure 13. Daytime temperature differences in House 3

Results for House 4 from 8:00 p.m. to 7:00 a.m. and 8:00 a.m. to 7:00 p.m. are shown in Figure 

14 and Figure 15, respectively.

Figure 14. Nighttime temperature differences in House 4
16 

Figure 15. Daytime temperature differences in House 4

Table 4 gives the electric and DHW consumption for the houses during the study period 

(November 2010 through January 2011). 

Table 4. Electricity Used from November 2010 to January 2011 (from Meter Readings)

End Use House 1 House 2 House 3 House 4

kWhHP 813 kWh 582 kWh 737 kWh 391 kWh

kWhPan 379 kWh 906 kWh 311 kWh 514 kWh

kWhLAMEL 711 kWh 1,395 kWh 1,013 kWh 1,745 kWh

kWhDHW 480 kWh 1,171 kWh 989 kWh 1,067 kWh

GalDHW 1,770 gal 5,860 gal 4,280 gal 5,050 gal

The study team aggregated the data to evaluate the percentage of time during which the 

bedrooms were no more than +2°F of the temperature at the thermostat and the percentage of 

time the bedrooms were in each of the other incremental 2°F bins above or below the thermostat 

temperature (i.e., the –4°F to –2°F bin combined with the +2°F to +4°F bin). Figure 16 shows the 

comparison of these percentages to the electric energy used for heating during the study period, 

which is a combination of direct meter readings and calculated contributions as described in 

Section 4. 
17 

Figure 16. Comparison of temperature to electric energy used for heating

Table 5 shows the average temperatures in the living rooms and bedrooms of the four houses 

from November 2010 through January 2011. 

Table 5. Average Temperatures in Living Rooms and Bedrooms

Room House 1 House 2 House 3 House 4

Living Room 69.4°F 71.8°F 70.0°F 68.8°F

First-Floor Bedroom 62.0°F 68.7°F 65.2°F 63.6°F

Second-Floor East Bedroom Failed sensor 68.5°F 64.6°F 67.0°F

Second-Floor West Bedroom 65.5°F Failed sensor 65.1°F 67.2°F
18 

Figure 17 shows the hourly temperatures in the living room of each of the houses for the entire 

study period. 

Figure 17. Hourly temperatures in the living rooms of the four houses
19 

Figure 18 shows the temperatures in the living rooms of houses 3 and 4 from January 14, 2011, 

to January 21, 2011. 

Figure 18. Temperatures in the living rooms of houses 3 and 4
20 

Figure 19 shows the absolute temperatures in the living room and bedrooms in House 3, and 

Figure 20 shows the temperature differences between the living room and the bedrooms in 

House 3 from January 14, 2011, to January 21, 2011. 

Figure 19. Absolute temperatures in the living room and bedrooms in House 3

Figure 20. Temperature differences between the living room and bedrooms in House 3
21 

Figure 21 shows the absolute temperatures in the living room and bedrooms in House 4, and 

Figure 22 shows the temperature differences between the living room and the bedrooms in 

House 4 from January 14, 2011, to January 21, 2011. 

Figure 21. Absolute temperatures in the living room and bedrooms in House 4

Figure 22. Temperature differences between the living room and bedrooms in House 4
22 

Table 6 shows the measured energy consumptions compared to the calculated energy 

consumption from BEopt modeling. 

Table 6. Measured Energy Consumptions Compared to the 

Calculated Energy Consumption from BEopt Modeling

House 1 House 2 House 3 House 4

Annual measured wholehouse electric heat use 

(heat pump plus radiant 

electric resistance panels)

6,167 kWh 11,636 kWh 9,106 kWh 10,212 kWh 

BEopt calculated use 

(electric resistance) 14,151 kWh 14,151 kWh 14,151 kWh 14,151 kWh 

BEopt calculated use 

(heat pump) 11,764 kWh 11,764 kWh 11,764 kWh 11,764 kWh 

Table 7 shows the calculated peak heating and cooling loads for the three bedrooms. 

Table 7. Peak Heating and Cooling Loads for the Three Bedrooms

Heating, 

Btu/h

Cooling, 

Btu/h

Master Bedroom 1,934 1,904

Bedroom 2 877 902

Bedroom 3 1,008 1,273
23 

5 Discussion

Although the data from houses 1 and 3 and houses 2 and 4 have similar characteristics, houses 1 

and 2 are not included in the detailed temperature analysis because they are each missing 

temperature data from one upstairs bedroom as discussed in Section 2. House 1 achieved an 

annual net zero energy consumption (Rosenbaum 2011). 

Houses 3 and 4 had similar absolute total heating electricity consumption despite very different 

heat pump and resistance heat amounts. House 3 used 1,048 kWh of total electricity during the 

study period, 737 kWh at the heat pump and 311 kWh at the resistance heaters, accounting for 

59% of the heat contribution per Equation 1. House 4 used 980 kWh of total electricity during 

the study period, 466 kWh at the heat pump and 514 kWh at the resistance heaters, accounting 

for 43% of the heat contribution per Equation 1. Per Equation 2, houses 3 and 4 used the 

equivalent of 668 kWh (38% of total heat kilowatt-hours) and 1,152 kWh (54% of total heat 

kilowatt-hours) of electric resistance from the internal gains associated with the electricity used 

for LAMELs, respectively. As shown in Figure 16, houses 1 and 3 and houses 2 and 4 showed 

similar trends with respect to the distribution of electricity use for the heat pump, radiant electric 

resistance panels, and the electricity attributable to the LAMEL internal gains.

The hourly sampled temperature differences between each of the bedrooms and the living room 

in each house were categorized into 2°F temperature bins as shown in Figure 16. House 3 had 

greater total electricity use and greater heat pump operation, and the temperatures in the 

bedrooms were within +2°F of the temperature in the living room 20% of the time and within 

+4°F 41% of the time. In House 4, with lower total electricity use but more resistance heat use 

and a significantly higher LAMEL contribution, bedrooms were within +2°F of the temperature 

in the living room 30% of the time and within +4°F 60% of the time. 

To better understand these percentages, look at the differences in the apparent heating system 

setup/setback strategy employed in houses 3 and 4, as shown in Figure 17. House 3 appears to be 

operated with a “set it and forget it” mentality for the DHU and setback/setup for the radiant 

electric resistance panels, although the east bedroom and the master bedroom were observed to 

frequently fall below the set-point temperature, indicating that the panels had been completely 

turned off. 

House 4 appears to have been operated in a completely different manner. The DHU unit was 

operated with daily setback and setup, frequently with the setback temperature apparently turned 

off. This caused dramatic temperature swings in the living room. The radiant electric resistance 

panels were operated in the same way, with the temperature apparently set anywhere from 

approximately 66°F to 70°F when needed and set to off when not needed. Figure 20 and Figure 

22 show the impact of this strategy on the +2°F comfort band. The temperature difference is not 

attributable to the DHU equalizing temperatures in the upstairs bedrooms; instead, it is the 

downward temperature drift in the living room that brings the temperatures closer together.

Also note that houses 1 and 3 had similar average living room temperatures and similar total 

heating energy consumption, but the aggressive setback strategy yielded significant fluctuations 

in temperatures in House 1. This may result from occupant comfort desires, but the data from 
24 

Table 4 and Table 5 do not indicate that a setback strategy will save energy in houses with these 

thermal enclosure characteristics and space conditioning systems. 

All four houses showed a trend toward cooler bedrooms during the day compared to the night, 

which can be expected based on typical occupancy patterns (i.e., bedrooms are generally not 

used during the day). 

Another factor that drives the temperature differences is the sun-tempered design of these 

houses. The living room is the dominant area that receives solar gain, and, as such, the 

temperature in that space was seen to rise by more than 7°F over the course of a sunny day. This 

response was not as dramatic in the bedrooms, and, in some cases, the rooms with doors that 

were apparently closed dropped in temperature while the living room was rising in temperature. 

The frequency of door operation was not explicitly measured, but it appears that the impact of 

door closure can be observed from the data. January 17 appears to be a sunny day, based on the 

rise in the living room temperatures in houses 3 and 4, as shown in Figure 18. Figure 21 shows 

that the second-floor east and west bedrooms in House 4 have a similar rise in temperature as the 

living room, but the first-floor bedroom temperature drops dramatically during the day. 

Conversely, Figure 19 shows that, in House 3, all bedroom temperatures rise as the living room 

temperature rises. This indicates that the first-floor bedroom in House 4 was either intentionally 

cooled by opening windows or, more likely, was isolated from the main body of the house by 

closing the door. The first-floor bedroom is on the north side of the house; therefore, even on a 

sunny day, it would not be expected to receive any appreciable solar gain. This pattern appears 

repeatedly in the data set.

With the heating strategy of a single DHU located in the main living space and radiant electric 

resistance panels in each bedroom controlled by individual thermostatic controls, the occupants’ 

behavior of leaving bedroom doors open or closed has a significant impact on room-to-room 

temperatures. The study team suspects that the houses with greater electric resistance heat use 

had the bedroom doors closed for longer periods of time, but these houses also appear to be 

operated with aggressive setup and setback schedules. Based on work by Prahl (2006), keeping 

the first floor at a steady temperature in an energy efficient house with a point source fuel fired 

heater helps to maintain more consistent temperatures in the upstairs bedrooms when the doors 

are open. Further study to evaluate the temperature differences relative to door-open versus doorclosed status would be valuable in removing the impact of occupant behavior on the temperature 

data.

The role of the LAMELs in these houses is impossible to accurately evaluate; however, even 

with the assumptions used, LAMELs appear to be a large contributing factor. The distribution of 

these loads throughout the house and their relative use are unclear. In houses this small and this 

well insulated, the contribution of these “mini space heaters” can have significant localized 

impacts, such as waste heat from cooking and entertainment devices, among others. A more 

detailed inventory of actual devices and usage patterns would be needed for deeper analysis to 

identify specific drivers of the relative temperature differences from room to room in these 

houses. 
25 

Based on the bedroom load calculations, fan-assisted air transfer from the main living space to 

the bedrooms could be an alternative strategy. Assuming that the temperature at the ceiling is 5°F 

higher than the thermostat set point because of stratification in the room, approximately 350 cfm 

of air from the main living space would meet the peak heating load for the master bedroom or 

bedrooms 2 and 3 combined (350 cfm × 5°F × 1.085 = 1,899 Btu/h). The three bedrooms could 

be “heated” with two low sone inline fans (one for the master bedroom, one for the other two 

bedrooms) that draw approximately 95 W each. House 3 used between 42 and 152 kWh per 

month for electric resistance heat. This translates to equivalent run times of approximately 7 to 

24 hours per day for the fans. This indicates a strategy that encourages a modest but acceptable 

level of stratification in the main space and adequately sized transfer fans with intakes located 

where air temperature is predicted to be the highest. This approach may be as (or more) effective 

than individual radiant panels at maintaining uniform temperatures in an energy efficient way. 

IBACOS is investigating this strategy as part of its ongoing research in laboratory homes through 

the Building America program. 

Finally, these data show that, above all, personal comfort is relative. Different people have 

different comfort and privacy needs and operate their heating systems and houses in different 

ways, whether for energy savings, comfort, or both. South Mountain Company has not received 

any comfort complaints from the occupants of these homes. 
26 

6 Conclusions

Four identical houses built in West Tisbury, Massachusetts, showed a wide range of energy use 

for space heating from early November 2010 through the end of January 2011. The DHU and the 

radiant electric resistance panels were estimated to have provided 43% to 71% of the electric 

energy needed for space heating, with almost all of the remainder being satisfied by internal 

gains attributed to LAMELs. Temperature measurements indicate that, with increased use of the 

radiant electric resistance panels in the bedrooms, temperatures were (not surprisingly) closer to 

the living room temperature where the DHU was located. Temperature excursions resulting from 

aggressive setup and setback of the DHU may contribute to higher percentages of time where the 

bedrooms were within +2°F of the living room because the living room temperature dropped 

closer to the temperatures of the bedrooms. In the two houses with complete temperature data 

sets, the bedrooms were within +2°F of the living room temperature no more than 30% of the 

time. Solar gains in the living room also appear to drive wider temperature swings. Opening and 

closing doors appears to have a significant impact on room-to-room temperature differences, as 

would be expected. Energy consumption between two houses with similar average living room 

temperatures but very different setback schedules had very similar heat pump and electric 

resistance energy consumption during the study period. 

After accounting for the electrical output of the 5.04-kW PV system, House 1 achieved an annual 

net zero energy consumption. This house also demonstrated significant temperature swings in the 

living space, where the DHU was located, and significant temperature variations between the 

bedrooms and the living room. 
27 

7 References

Abrams, J. (2011). “High-Performance Homes on a Budget.” Journal of Light Construction

(January); pp. 39–46. http://www.jlconline.com/building-envelope/high-performance-homes-ona-budget.aspx. Accessed August 2011. Also available at http://www.southmountain.com/pressand-media. Accessed October 2012. 

ASHRAE (2004). “ANSI/ASHRAE Standard 55-2004, Thermal Environmental Conditions for 

Human Occupancy.” Atlanta, GA: ASHRAE.

Hendron, R.; Engebrecht, C. (2010). Building America House Simulation Protocols. NREL/TP550-49426. Golden, CO: National Renewable Energy Laboratory. 

Prahl, D. (2007). “Small Homes, Excellent Enclosures, Almost No Heating System—Fact or 

Fiction?” Proceedings of the Thermal Enclosure of Buildings X Conference, Clearwater, FL, 

December 2–7, 2007. Atlanta, GA: ASHRAE. 

Rittelmann, W. (2006). “A Systemic Short-Term Field Test for Residential HVAC Thermal 

Comfort Performance.” Proceedings of the 2006 ACEEE Summer Study on Energy Efficiency in 

Buildings, August 13–18, 2006. Washington, D.C.: ACEEE. pp. 1-260 – 1-271 

Rosenbaum, M. (2011). Zero-Net Possible? Yes! Energy Performance of Eight Homes at 

Eliakim’s Way. West Tisbury, MA: South Mountain Company. 

Rutkowski, H. (2009). Manual D—Residential Duct Systems. 3rd edition, Version 1. Arlington, 

VA: Air Conditioning Contractors of America. 

Rutkowski, H. (2006). Manual J—Residential Load Calculation. 8th edition, Version 2. 

Arlington, VA: Air Conditioning Contractors of America. 
DOE/GO-102012-3494 ▪ October 2012

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