West Village Student Housing

Phase I: Apartment Monitoring 

and Evaluation 

A. German, C. Bell, B. Dakin, and M. Hoeschele

Alliance for Residential Building Innovation

June 2014
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iii

West Village Student Housing Phase I: 

Apartment Monitoring and Evaluation

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: 

A. German, C. Bell, B. Dakin, and M. Hoeschele

Alliance for Residential Building Innovation (ARBI)

Davis Energy Group, Team Lead 

NREL Technical Monitor: Michael Gestwick

Prepared under Subcontract No. KNDJ-0-40340-03 

June 2014 
iv

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v 

Contents

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

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

Acknowledgments .................................................................................................................................... vii

Definitions................................................................................................................................................. viii

Executive Summary................................................................................................................................... ix

1 Introduction........................................................................................................................................... 1

1.1 Background and Motivation ................................................................................................1

1.2 Research Questions ..............................................................................................................1

2 Project Description............................................................................................................................... 3

2.1 Measure Details ...................................................................................................................5

3 Methodology ......................................................................................................................................... 8

3.1 General Technical Approach ...............................................................................................8

3.2 Data Collection ....................................................................................................................8

3.3 Data Evaluation ....................................................................................................................9

Apartment Energy Usage Disaggregation .........................................................................11

3.4 Cost Effectiveness ..............................................................................................................11

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

4.1 Occupant Behavior.............................................................................................................12

4.2 Apartment Building Energy Use ........................................................................................13

Apartment Unit Energy Use ...............................................................................................13

Domestic Hot Water and Common Meter Energy .............................................................16

4.3 Phase I Zero Net Energy Evaluation ..................................................................................18

4.4 Cost Effectiveness ..............................................................................................................20

5 Conclusions and Discussion ............................................................................................................ 22

References................................................................................................................................................. 25

Appendix: Supplementary Evaluation Graphs....................................................................................... 26
vi 

List of Figures

Figure 1. West Village project site plan .................................................................................................... 3

Figure 2. Photograph of the completed village square surrounded by mixed use and student 

housing buildings................................................................................................................................. 4

Figure 3. Ramble A style apartment building showing exterior window sunshades, rooftop solar 

PV, and high efficiency heat pumps................................................................................................... 4

Figure 4. Modeled and actual average monthly consumption values for each apartment type (by 

number of bedrooms) ........................................................................................................................ 14

Figure 5. Histogram showing individual apartment energy consumption variation.......................... 15

Figure 6. Average disaggregated energy use over 12 months (March 2012 to February 2013) for the 

four-bedroom apartments.................................................................................................................. 16

Figure 7. Monthly average common meter use compared to modeled (15 buildings) ...................... 17

Figure 8. Actual common meter energy consumption for 14 buildings over 12 months (March 2012 

to February 2013)................................................................................................................................ 18

Figure 9. Comparison of annual Phase I consumption and production ............................................. 19

Figure 10. Total consumption, production, and net values for all Phase I buildings ........................ 20

Figure 11. Histogram showing variation in energy consumption over 12 months (March 2012 to 

February 2012) for all two-bedroom apartments............................................................................. 26

Figure 12. Histogram showing variation in energy consumption over 12 months (March 2012 to 

February 2012) for all three-bedroom apartments .......................................................................... 26

Figure 13. Histogram showing variation in energy consumption over 12 months (March 2012 to 

February 2012) for all 4-bedroom apartments................................................................................. 27

Figure 14. Average disaggregated energy use over 12 months (March 2012 to February 2012) for 

the two-bedroom apartments............................................................................................................ 27

Figure 15. Average disaggregated energy use over 12 months (March 2012 to February 2012) for 

the three-bedroom apartments ......................................................................................................... 28

Figure 16. Average disaggregated energy use over 12 months (March 2012 to February 2012) for 

the four-bedroom apartments ........................................................................................................... 28

Unless otherwise noted, all figures were created by the ARBI team.

List of Tables

Table 1. Breakdown of Apartment Units for Phase I of the Student Apartment Ramble Buildings ... 5

Table 2. Student Housing Energy Efficiency Measure Package ............................................................ 6

Table 3. Valid Date Ranges for Collected Data. ....................................................................................... 9

Table 4. Evaluation Terms for Life Cycle Costing. ................................................................................ 11

Table 5. Projected and Actual Production, Consumption, and Net Energy Values ........................... 19

Table 6. Life Cycle Cost Evaluation Key Input Metrics ......................................................................... 21

Table 7. Life Cycle Cost Comparison of a Single Ramble A Building Compared to California Title24 Standard ......................................................................................................................................... 21

Unless otherwise noted, all tables were created by the ARBI team.
vii 

Acknowledgments

Davis Energy Group would like to acknowledge the U.S. Department of Energy Building 

America program and their funding and support of development of this technical report as well 

as research that informed it. We would like to extend gratitude to the University of California, 

Davis and the developer West Village Community Partners for their ongoing cooperation 

throughout the design, construction, and monitoring stages of this project and their commitment 

to this project. In addition, we would like to acknowledge SunPower, Pacific Gas & Electric 

Company, Architectural Energy Corporation, and the Western Cooling Efficiency Center, for 

providing the team with data that was indispensable for this evaluation. 
viii

Definitions

ACH50 Air changes per hour at 50 Pascals

ARBI Alliance for Residential Building Innovation

DEG Davis Energy Group

EEM Energy efficiency measure

EER Energy efficiency ratio

HERS Home Energy Rating System

HPWH Heat pump water heater

HSPF Heating seasonal performance factor

HVAC Heating, ventilation, and air conditioning

LCC Life cycle cost

MEL Miscellaneous electric load

PG&E Pacific Gas & Electric

PV Photovoltaic

RASS Residential Appliance Saturation Study

SEER Seasonal energy efficiency ratio

WVCP West Village Community Partnership

VNM Virtual net metering

ZNE Zero net energy
ix

Executive Summary

West Village, the largest planned zero net energy (ZNE) community in the United States, is a 

new neighborhood currently under construction on the University of California at Davis campus. 

The multiuse project combines energy efficiency measures (EEMs) and on-site renewable 

generation to target a community-level ZNE goal. The focus of this research conducted by the 

Alliance for Residential Building Innovation (ARBI) is on the 192 student apartments (16 

buildings) that were completed in 2011 as part of the Phase I West Village multiyear build-out. 

The EEMs that are incorporated into these apartments, including increased wall and attic 

insulation, high performance windows, high efficiency heat pumps for heating and cooling, 

central heat pump water heaters (HPWHs), 100% high efficacy lighting, and ENERGY STAR®

major appliances, contribute significantly to source energy reductions with an estimated 37% 

savings over the Building America Benchmark (Hendron et al. 2010) in hot-dry climates and 

31%–39% Title-24 compliance savings. The implemented EEMs, and specifically the EEM 

package, have the potential to lead to market-ready solutions that cost-effectively provide 

comfort in multifamily buildings with efficient, safe, and durable operation. 

The primary objective of this project is to evaluate the ability of the project to meet the Building 

America Project Management Milestone goals and the project’s stated energy goals. This project 

presents an important opportunity to validate the cost effectiveness and performance of 

multifamily deep EEMs on a community scale. Utility billing data were used to compare 

measured versus modeled electricity use and to verify the accuracy of the modeling assumptions. 

This work seeks to address the following research questions: 

1. How does measured energy use compare to modeled and were the expected energy 

savings achieved?

2. Was the the project able to achieve the stated energy goals?

3. How cost effective is this package of EEMs in a multifamly application?

4. What role do occupants have in high performance buildings and how well do tenants 

respond to energy education efforts by the developer? 

Build-out of the community is ongoing, yet thus far the project has been a success, as

demonstrated by the design and construction of buildings that incorporate cost-effective

measures that reduce heating and cooling energy use significantly. Results have provided 

valuable insights and lessons learned into the largest planned ZNE community in the United 

States, which will be useful for builders, developers, researchers, and consultants alike.

Actual apartment energy consumption for the 16 Phase 1 buildings exceeds original model 

predictions by 18% over a 12-month period (March 2012 to February 2013). Average monthly 

apartment energy consumption profiles suggest that non-heating, ventilation and air conditioning 

(HVAC) use is likely the primary cause of the discrepancy. Electrical energy disaggregation 

indicated that for the predominant four-bedroom apartment type, modeled HVAC energy use 

over the 10-month period was overpredicted by 56%, while non-HVAC energy was 

underpredicted by 54%. This may be attributed to the “multiple household” effect, whereby 

student occupancy may tend to have more duplication of certain electronic devices (computers, 
x 

gaming stations, TVs, etc.) that would skew consumption away from what might be expected 

from more typical multifamily household assumptions. 

As heating and cooling loads are driven down significantly with high performance homes, 

occupants may be the most influential variable in total home energy consumption, especially in 

milder climates. Measured non-HVAC base load at West Village averaged 85% of total 

apartment electricity over the 10-month period. As technology drives efficiency further, the 

impact of the occupant becomes increasingly important.

Annual energy use of the common area meters (serving the HPWH and building exterior 

lighting) was found to be 55% higher than projected. Half of the HPWHs were found to have 

ongoing issues resulting in excessive resistance heat operation, and it is theorized that improper 

initial commissioning due to lack of experience with the technology is the key issue. It is 

recommended that the installing contractor, either mechanical or plumbing with appropriate 

training, has sufficient experience with refrigerant systems.

It is clear that more in-depth and regular engagement with the tenants is necessary to ensure buyin and participation from tenants on achieving the ZNE goals. Tenant education on basic energy 

efficiency strategies, creating a community energy and sustainability vision, and implementing 

and enforcing rules on excessive consumption (e.g., use of individual room refrigerators) are 

needed. Considering that this report summarizes the first full year of operation, we anticipate that 

West Village Community Partners and UC Davis will use the results of this initial evaluation to 

improve processes and quality control procedures to optimize community-wide performance. 

This may involve the addition of EEMs or photovoltaics where necessary, improved tracking and 

maintenance of energy-consuming components, and increased efforts to encourage and 

incentivize student participation in reducing energy use.
1 

1 Introduction

1.1 Background and Motivation

West Village, the largest planned zero net energy (ZNE) community in the United States, is a 

new neighborhood currently under construction on the University of California at Davis campus. 

It’s a multiuse project incorporating energy efficiency measures (EEMs) and on-site renewable 

generation to achieve community-level ZNE goals. It is designed to enable faculty, staff, and 

students to live near campus, take advantage of environmentally friendly transportation options, 

and participate fully in campus life. Sited on more than 200 acres, when complete the community 

will provide housing for almost 2,000 students, 343 homes for faculty and staff, a 10-acre 

recreation complex, and the first community college center on a university campus. 

West Village began as a public-private partnership to develop much-needed housing for UC 

Davis students, faculty, and staff. Along the way, UC Davis and its development partner, West 

Village Community Partnership, LLC (WVCP), embraced the aspirational goal of making West 

Village a ZNE community. This decision was in part due to California’s Energy Efficiency 

Strategic Plan (CPUC 2008) that all residential construction be ZNE by 2020 as well as the 

University’s greenhouse gas reduction goals. Grants from the U.S. Department of Energy, 

California Energy Commission, and the California Public Utilities Commission supported design 

and development of this innovative ZNE community at West Village.

The focus of this research conducted by the Alliance for Residential Building Innovation (ARBI) 

is on the 192 student apartments that were completed in 2011 under Phase I of the West Village 

multiyear project. The EEMs that are incorporated into these apartments (see Table 2), including 

increased wall and attic insulation, high performance windows, high efficiency heat pumps for 

heating and cooling, central heat pump water heaters (HPWHs), 100% high efficacy lighting, and 

ENERGY STAR® major appliances, contribute significantly to source energy reductions with an 

estimated 37% savings (BEoptTM v1.1) over the Building America Benchmark in hot-dry 

climates. Title-24 compliance savings were 31%–39% depending on building and orientation. 

These EEMs, and specifically the EEM package, have the potential to lead to market-ready 

solutions that cost-effectively provide comfort in multifamily buildings with efficient, safe, and 

durable operation. These apartment buildings have also been certified Platinum under the 

Leadership in Energy and Environmental Design for Homes certification program. 

The primary objective of this project is to evaluate the ability of the project to meet the Building 

America Project Management Milestone goals and the project’s stated energy goals. This project 

presents an important opportunity to validate the cost effectiveness and performance of 

multifamily deep EEMs on a large scale, which has never before been done. Utility data are used 

to compare measured versus modeled electricity use and to verify the accuracy of the 

assumptions employed in the model. Incremental construction costs from the builder are used to 

evaluate cost effectiveness. 

1.2 Research Questions

The primary research questions are the following: 

1. How does measured energy use compare to modeled and were the expected energy 

savings achieved?
2 

2. Was the the project able to achieve the stated energy goals?

3. How cost effective is this package of EEMs in a multifamly application?

Secondary research questions include the following: 

4. What role do occupants have in high performance buildings and how well do tenants 

respond to energy education efforts by the developer? 
3 

2 Project Description

UC Davis’ goal for West Village is to minimize the community’s energy use and greenhouse gas 

production by reducing building energy use, providing on-site energy generation from a mix of 

renewable sources, and encouraging bicycle use and public transportation. Project goals were set 

by UC Davis in order to meet future campus and state greenhouse gas reduction and 

sustainability goals. Figure 1 shows the overall site plan for West Village with Phase 1 student 

housing outlined by the red line. Figure 2 and Figure 3 show the completed village square. 

Nearly 10 years ago, Davis Energy Group (DEG) began coordinating with UC Davis to develop 

strategies for a highly efficient residential community to be built on UC Davis land. Results of 

previous work are summarized in the CARB’s 2009 and 2010 Building America annual reports 

(CARB 2009, 2010), a report prepared for Chevron Energy Solutions (DEG 2010), an American 

Council for an Energy Efficient Economy paper (Dakin et al. 2010), and a 2012 ARBI Building 

America technical report focused on initial performance of the central HPWH as well as the 

overall construction quality assurance and quality control processes (Dakin et al. 2012). 

Figure 1. West Village project site plan
4 

Figure 2. Photograph of the completed village square surrounded by

mixed-use and student housing buildings

(courtesy of University of California, Davis)1

Figure 3. Ramble A style apartment building showing exterior window sunshades,

rooftop solar photovoltaics (PV), and high efficiency heat pumps

 

1 West Village UC Davis (2011). Apartment Living: The new Viridian apartments overlooking the Village Square at 

UC Davis West Village. (Photo by Greg Urquiaga/UC Davis) [Web Photo]. Retrieved from 

http://westvillage.ucdavis.edu/image-gallery/20110914_west_village_7493.jpg/view on October 28th, 2011. 
5 

Construction of the first phase of student apartments began in 2010 and was completed in 

September 2011, in time for student arrival for fall quarter occupancy. This first phase consists 

of 16 three-story buildings, each with 12 units for a total of 192 units (see Table 1), and two 

similar building styles, Ramble A and Ramble B. In January 2011, the developer started taking 

reservations for leases on the student apartment buildings. By April, 80% of the units had leases 

reserved and by September when occupancy opened up nearly 100% of units were leased. Phase 

II consists of an additional 16 buildings of similar design that were completed for occupancy in 

September 2012. The final student housing phase, Phase III, was recently completed in time for 

fall 2013 occupancy. The scope of this report covers the performance of the 16 Phase I 

apartments only.

Table 1. Breakdown of Apartment Units for Phase I of the Student Apartment Ramble Buildings

Conditioned 

Floor 

Area/Building

(ft2)

Bedroom 

Number 

of 

Buildings

Total Number 

of Units

Ramble A 16,011 (6) 4-bedroom

(6) 3-bedroom

13 156 

Ramble B 14,202 (6) 4-bedroom

(6) 2-bedroom

3 36 

Total – – 16 192 

2.1 Measure Details

Table 2 summarizes the EEMs incorporated in this project and their associated incremental costs. 

DEG and WVCP coordinated to develop incremental cost projections in 2009. These costs along 

with the projected energy savings were used to conduct economic evaluations and develop and 

optimize the EEM packages. The cost data provided were based on contractor bids and closely 

reflect actual costs. 

Incremental costs for the EEMs for a Ramble A building (not including PV) were estimated at

about $46,000 more than a building built to the regional builder standard (California’s Title-24 

energy efficiency standards, from here on referred to as Title-24) (CEC 2008). After factoring in 

Pacific Gas & Electric (PG&E) utility incentives for energy efficiency the incremental cost drops 

to just under $41,000. This equates to a net incremental cost of $3,380 per apartment or about 

$2.50/ft2

, not including PV systems.
6 

Table 2. Student Housing EEM Package

Measure Builder Standard (Title-24) 

Specification West Village Specification

Incremental Cost 

Over Title24/Building

Basic Building Characteristics

Building Type/Stories Multi Family, 3 stories

# of Buildings and Units 16 buildings, 192 units

Envelope

Exterior Wall Construction and

Insulation

2 × 6 16 in. o.c. R-19 Batt, 

Grade 3

2 × 6 16 in. o.c. R-21 batt w/1/2 in. R-3 exterior 

sheathing, grade 1 $5,418 

Foundation Type and Insulation Slab – Uninsulated

Roofing Material and Color 

Asphalt shingles

Reflectivity = 0.20,

Emissivity = 0.85

Cool Roof Rating Council-certified roofing 

product 

reflectivity = 0.25, emissivity = 0.85

$0 

Ceiling Insulation R-38 r-49 blown cellulose $791

Radiant Barrier Yes

House Infiltration – Blower Door 

Test No, 7.0 ACH50 Yes, 5.0 ACH50 $0 

Thermal Mass None 1⁄2-in. Gypcrete on floors 2 and 3 $2,031

Envelope HERS Verifications None Quality insulation installation + 

blower door test $4,2002

Glass Properties: U-Value/SHGC

All Windows Dual vinyl – 0.40/0.40 Gilwin Dual Vinyl – 0.32/0.23 $2,949

Heating, Ventilation, and Air Conditioning (HVAC) Equipment

Heating Type and Efficiency Heat pump/7.7 HSPF Heat pump/8.5 HSPF

$9,763 AC Type and Efficiency Heat pump/SEER 13/EER 10 Heat pump/SEER 15/EER 12.5

Distribution Type and Details Ductwork, R-6 in attic Ducted, R-6 in conditioned space on floors 1

and 2, attic on floor 3

Verify Duct Leakage Tested, <6% $1,200

 

2 $2,400 for QII and $1,800 for blower door.
7 

Measure Builder Standard (Title-24) 

Specification West Village Specification

Incremental Cost 

Over Title24/Building

HERS Verifications Tight ducts <6%

Tight ducts <6%, refrigerant charge, high EER 

(12.5), Cooling coil airflow ≥350cfm/ton, fan 

Watt draw ≤0.58 W/cfm, Cooling right sizing 

(per Manual J and S)

Water Heating Equipment

Water Heater Type and

Efficiency

Individual gas storage water 

heater,

Energy factor = 0.57

Central A. O. Smith Heat Pump, coefficient of 

performance 2.9 @ 65oF. $6003

HW Distribution Recirculation, Timer + Temperature

Appliances and Lighting

ENERGY STAR Appliances

None, standard efficiency 

dishwasher, fridge, and clothes 

Washer

Dishwasher/fridge/washer $6,000 

Dryer Fuel Electric

Oven/Range Fuel Electric

Miscellaneous Load Control None

Fluorescent Lighting Package ~30% 100% w/vacancy controls $12,840

Total Incremental Cost $45,792

Utility Incentives $5,229

Net Incremental Cost $40,563

 

3 Cost savings include elimination of gas lines and venting
8 

3 Methodology

The scope of this technical report focuses on the evaluation of total apartment energy use, total 

Phase I community energy use, and the ability to meet the project’s stated energy goals. 

3.1 General Technical Approach

ARBI worked with WVCP, SunPower and PG&E to obtain monthly utility data and generation 

data from the PV monitoring systems for each of the apartments. Measured energy consumption 

and PV generation are compared to energy estimates from modeling. Additionally, DEG is 

reporting on lessons learned from WVCP’s perspective and future improvements to encourage 

engagement and further reduce energy use from West Village occupants. 

3.2 Data Collection

To evaluate energy use and generation, DEG worked with WVCP and SunPower to obtain and 

evaluate monthly utility data and PV generation data from each of the apartments and common 

area meters. Measured energy consumption and PV generation were compared to energy 

estimates from modeling. 

Energy data was collected from two sources: PG&E utility meter data4 and SunPower’s 

monitoring website.

5 SunPower monitors both total PV system production and total building 

energy consumption on a 5-minute interval basis. Originally, the analytical approach was to 

compare the consumption and production values, from SunPower’s monitoring website, on an 

hourly basis to assess Phase I performance. Unfortunately, due to errors in the SunPower 

equipment, the reported consumption values from SunPower were inaccurate and therefore had 

to be eliminated from the datasets. The errors in the SunPower consumption data were 

discovered when comparing the monthly PG&E net consumption values to the difference of the 

SunPower consumption and generation values. 

In place of the SunPower consumption data, a combination of SunPower production and PG&E 

net energy use was used to evaluate energy production, energy consumption and net energy on a 

monthly basis for each individual meter (192 apartments and 16 common area meters). PG&E 

utility data were provided as monthly net energy values. Daily SunPower production data was 

aggregated into monthly values corresponding to the PG&E billing periods for direct 

comparison. Energy consumption was then calculated as the difference between these two values 

according to the following equation. 

Net Energy = Energy Consumption - Energy Production (1)

In this relationship, net energy is positive if the apartment unit or common meter consumed more 

than it produced and negative if it produced more than it consumed. 

 

4 The uncertainty of the net energy measurement is minimal provided the high accuracy of revenue-grade electricity 

meters. The meters used at West Village are General Electric’s kV2c meter with a reported accuracy of ±0.2% for 

energy and demand.

5 SunPower uses Continental Control System’s Wattnode WNC-3Y-208-MB for PV energy production 

measurements with a reported accuracy of ±0.5% for energy. 
9 

The majority of data presented in this report represent the 10-month period between March 2012 

and December 2012, over which the two data sources coincide (see Table 3). Unfortunately, the 

useful data ranges of available data for the two data streams did not seamlessly align. The PV 

systems were installed, permitted, and operational by November 2011, at which point PG&E 

switched over to a net energy meter. However, the SunPower monitoring meters came online 

sometime between February and June 2012. The majority of the meters were operational and 

accurately reporting PV production by March 1, 2012. For those SunPower meters that were not 

operational by this date,

6 the PV systems themselves were assumed to be operational. This 

assumption appeared to be valid after reviewing the net meter data for those units. For the 

systems without operational production meters, the generation data were extrapolated back to 

March 1, 2012, using production from PV systems with similar capacity and orientation and 

which had later PV production that aligned well. Once a SunPower meter was determined to be 

operating properly, any subsequent days with zero or missing production data were assumed to 

be instances where the PV system was actually nonoperational.7 

Table 3. Valid Date Ranges for Collected Data

PG&E – Net SunPower – Production 

Start Date November 2011 March 2012

End Date December 2012 January 2013

Annual consumption and production were estimated by further extrapolating PV production back

through January 2012. Annual PV production was estimated by using the 11-month PV 

production data, as listed in Table 3, and the monthly fractions of annual production provided by 

NREL’s PVWatts calculator,

8 which projects monthly system performance based on nominal 

size, location, orientation, etc. (February 2012 production was estimated to be 5% of annual 

production based on PVWatts). January 2013 production was used as a proxy for January 2012 

production. Annual consumption was subsequently calculated for the January through December

2012 period using actual PG&E net data and the estimated annual production according to 

equation 1. 

3.3 Data Evaluation

Data evaluation was conducted to compare energy consumption, energy production, and net 

energy for the following groups: 

• Individual apartments

• Building common meter (central HPWH and building exterior lighting)

• By apartment type (two-, three-, and four-bedroom) 

 

6 74 SunPower monitoring meters were not operational as of March 1, 2012. By May 1, 2012 all but five meters 

were operational.

7 One exception to this assumption is when the reporting connection to the PV system is lost but the PV system is 

still generating; in this case, once the connection is regained, the PV system reports the aggregate generation across 

all of the days when the connection was lost. In these instances, the total generation value is accurate but needs to be 

dispensed across the previously lost days.

8 http://www.nrel.gov/rredc/pvwatts/
10 

• By building type (Ramble A and Ramble B)

• Phase I student housing community in its entirety. 

Comparisons were also made to original eQUEST modeling estimates for each apartment type. 

Due to the limitations of BEopt with multifamily buildings, the BEopt software9 was not 

appropriate to use for this evaluation. However, assumptions used in the eQUEST model largely 

followed the Building America Research Benchmark Definition (Hendron 2008) with the 

following differences. 

• Cooling thermostat set point of 78°F 

• Heating thermostat set point of 70°F 

• A multiplier of 0.58 (42% reduction)10 applied to miscellaneous electric load (MEL)

usage to better align annual consumption with multifamily MEL usage presented in the 

2009 Residential Appliance Saturation Study (RASS) (KEMA 2009) 

• Altered vacation schedules as follows:

o Winter break – 2-week holiday break in January 

 Assumes no occupancy

 20% lighting levels

 67% MELs

 Weighted average heating thermostat setback temperature of 65°F 

o Spring break – 1 week in early April 

 Assumes 50% occupancy 

 50% lighting levels

 78% MELs

 Weighted average thermostat setback of 82°F cooling and 65oF Heating

o Summer break – 2 months in summer (July/August) 

 Assumes 50% occupancy

 50% lighting levels

 78% MELs

 Weighted average cooling thermostat setback temperature of 82°F. 

The eQUEST energy model was re-evaluated using and Actual Meteorological Year (AMY) 

weather file from the Sacramento Metropolitan Airport (KSMF) National Oceanic and 

 

9 BEopt v1.1 was used to evaluate a single four-bedroom apartment unit to provide estimated Benchmark savings of 

37% as stated previously.

10 During the original design Building America used state specific multipliers, which for California was 0.77. The 

additional reduction corresponds to a 25% decrease beyond the 23% attributed by the state multiplier. 
11 

Atmospheric Administration weather station. These results were used for comparison to actual 

energy consumption. 

Apartment Energy Usage Disaggregation

Initially, DEG planned on disaggregating heating and cooling energy use from the base loads 

using SunPower hourly energy consumption. Since these data were unavailable, ARBI was left 

with only monthly energy consumption to use as a basis for disaggregation. 

Monthly electricity usage for each apartment was disaggregated into two main categories: base

load and space conditioning. The Ramble student apartments are all-electric and use heat pumps 

for both space heating and cooling; therefore, the process was simplified to evaluating a single 

fuel only. The HPWHs are centrally metered and not considered in this disaggregation. The base

loads for a given residence were estimated from the “shoulder” seasons, which are times during 

spring and fall that have little or no space conditioning. These seasons are necessary to 

disaggregate the base load end uses from the temperature or seasonally dependent HVAC end 

uses. Average energy use during the spring shoulder season (March–May) was used as the 

monthly base load for each unit. Monthly multipliers for lighting energy from the Building 

America House Simulation Protocols (Hendron et al. 2010) were applied to this base load to 

estimate the seasonality of the use of interior lights. The difference between the monthly adjusted 

base load and the average total apartment energy use was then taken as heat pump energy 

consumption. The cooling season was assumed to be April through September with the 

remaining months in the heating season. Averages across the Phase I population were taken to 

estimate average disaggregated energy use for each of the three unit types (two-bedroom, threebedroom, four-bedroom apartment) and are presented in the results.

3.4 Cost Effectiveness

An economic analysis of the EEM package was completed to evaluate and compare the life cycle 

costs (LCCs) for the Title-24 builder standard base case and the proposed ZNE package using 

various financing scenarios. The evaluation terms are presented in Table 4. First year utility costs 

were estimated using current year (2013) PG&E’s rates for the Davis region. Replacement costs 

were assigned for lighting, the heat pump, and the HPWH. Any scenario was considered to be 

cost effectiveness given the evaluation terms if its LCC was less than that of the base case. PV 

cost effectiveness was not evaluated in this report.

Table 4. Evaluation Terms for Life Cycle Costing

Evaluation 

Period

Real 

Discount 

Rate11

Fuel 

Escalation 

Rate

Financing 

Interest 

Rate

20 Years 3%12 3%13 5%

 

11 A real discount rate is the discount rate which factors in the effects of inflation. 12 3% is taken from the DOE 2010 real discount rate (U.S. Department of Commerce 2010). 

13 Fuel escalation rates are very uncertain, 3% is an estimate only.
12 

4 Results 

4.1 Occupant Behavior

General feedback from WVCP after this first year of occupancy is positive. Student housing 

retention from year 1 to year 2 has been relatively high at around 40%. While WVCP has 

continued to market the energy and sustainability components and occupants generally appear 

excited about these features, there is no evidence that they factor into the renters’ decision 

process. This appearance of excitement does not necessarily translate into engaged occupants, 

especially since they do not pay for their energy use and do not have access to information about 

how much energy they use. Residents do have the ability to access an online SunPower account 

that provides hourly electricity consumption and PV production, but the SunPower consumption 

data are not valid and is of little value to occupants. SunPower and WVCP held three training 

sessions throughout the past year on how to access and interpret the data available from the 

website. Around 75–100 residents attended these sessions. Instructions for creating an account 

were left in every apartment at the beginning of each lease. As of December 2012, only 27 

residents have established accounts (this includes students from both Phase I and Phase II). 

WVCP continues development of a methodology for holding residents responsible for exceeding 

monthly utility usage targets, since excess use has direct cost implications for WVCP. Energy 

modeling conducted by DEG was revised to evaluate the expected monthly apartment electricity 

consumption by apartment type (number of bedrooms) using the worst orientation and after 

removing any vacation schedules. Originally, WVCP’s plan was to monitor and notify residents 

after any month they had surpassed the consumption allotments. After the second notification, a 

fee would be assessed to the apartment occupants. Due to difficulty in processing monthly 

apartment consumption data, they have not yet begun sending these notifications. Each 

apartment unit is metered individually, resulting in 13 bills per building (12 apartments plus the 

common meter). This situation creates the laborious task for WVCP of reviewing and analyzing 

each utility bill singularly. Additionally, current utility regulations limit the ability of property 

managers to charge fees to tenants for utilities. In California, the only utility they are allowed to 

charge for is cold water consumption. However, the amount they can charge for cold water use is 

potentially very minimal and it costs WVCP to read each cold water meter. On other properties 

where they have implemented a similar methodology and charged for cold water usage, the cost 

to read and assess the charges was greater than the income from the charges. Currently at West 

Village there is a cold water meter at each apartment, but they are not reading any of them. 

While this strategy involves penalizing occupants for excess use, WVCP is alternatively

considering adoption of a program that incentivizes residents for achieving low energy use below 

the predefined threshold. Further evaluation of which strategies will be most successful, from a 

cost-effective, motivational, and legal standpoint, is ongoing. 

The apartments were initially designed to include a central energy consumption display and 

smart power strips in each bedroom that could be programmed and controlled remotely. The 

devices, developed by GreenWave,

14 were to be installed in each of the apartments to provide a 

means of reducing plug load energy use. Due to conflicts with the wireless communication 

between this device and the installed Internet infrastructure, these products were removed from 

 

14 http://www.greenwavereality.com/solutions/ 
13 

the apartments before they were fully functional early in 2011 and will likely not be reinstalled. 

This feature was an advertised component to students for the 2011–2012 leasing year and 

residents were excited about it since it may have resonated with how they typically access and 

control information in a digital manner. While WVCP is not actively researching other products, 

WVCP is still interested in incorporating such a service in current or future phases of the project. 

Since build-out of the West Village community continues, the WVCP team has been focused on 

leasing activities and ensuring all buildings and systems are operational, and has not had the 

opportunity to focus as much as it would like on tenant engagement. However, the current 

WVCP team is enthusiastic about expanding educational activities and increasing resident 

engagement in order to explain the occupant’s role in a high performance building and better 

translate the community vision. 

Several proposed ideas include a monthly educational series and community-level competitions 

for energy use reductions. In late 2012, there was a pilot competition underway in which WVCP 

and Architectural Energy Corporation are monitoring electricity by major end-use in 24 

apartments scattered throughout the Phase I and II community (Risko 2012) . Twelve of the units 

were part of a control and the other 12 were given feedback on their energy use, in the hopes of 

educating residents and encouraging behavioral changes that will reduce their energy use. These 

residents were provided with a list of tips and sent regular updates on their current usage, how 

they were performing in relation to others in the competition, and personalized advice for how to 

quickly bring their consumption down. WVCP reports that participants appeared to be very 

receptive to feedback. Architectural Energy Corporation is expanding this monitoring effort to 

120 additional apartments that will continue through the end of 2014. Another behavioral 

evaluation underway is with the UC Davis Western Cooling Efficiency Center and Toyota. They 

recruited 50 individual occupants in 50 separate apartments to participate and have provided all 

of them with three specific energy-saving behaviors including hang drying clothes, turn off 

computers at night, and reduce showering time. Half of these participants are provided with an 

in-house “button,” which they are instructed to push each time they perform one of these energysaving acts. The device provides verbal positive feedback to the participants and records the 

activity. This evaluation continued for 2 months. 

4.2 Apartment Building Energy Use

The Phase I Ramble buildings consist of 12 apartments each, composed of two-, three-, and fourbedroom units. Aside from the apartment units, each building has a single common meter on 

which the central HPWH and exterior lighting are connected. 

Apartment Unit Energy Use

Average apartment consumption (no domestic hot water use) by unit type (number of bedrooms) 

is compared to eQUEST modeling estimates (using Annual Meteorological Year weather data) in 

Figure 4. Average actual consumption over a 12-month period exceeded projected use by 23% 

for both the three-and four-bedroom units, while the two-bedroom units indicated 4% lower than 

projected usage. 

The monitored monthly use profiles follow a similar trend seasonally with the exception of the 

two-bedroom apartments that demonstrate a pronounced dip in energy use from May through 

September 2012, which would seem to indicate lower average summer occupancy. With two 
14 

occupants there is a greater chance that both occupants will be gone over the summer compared 

to apartments with three or four occupants. On average, the three-bedroom and four-bedroom 

apartments appear to be fully or partially occupied during the summer. The load reductions that 

were predicted in the model based on expected vacancy during the summer months are not 

observed in the data. 

Figure 4. Modeled and actual average monthly consumption values for each apartment type

(by number of bedrooms)

Figure 5 presents a histogram comparing the ratio of “actual-to-modeled” 10-month energy 

consumption for each of the 192 apartments (modeled use shown as black bar at 100%). There is 

a wide variation in annual consumption with roughly a 4:1 ratio between high and low usage 

apartments. Roughly half of the apartment units have consumption values within 25% of 

modeled predictions and about 85% of the three- and four-bedroom apartments consume more 

energy than what was predicted. Only 39% of the two-bedroom apartments consume more 

energy than predicted. Figure 11 through Figure 13, in the Appendix, are additional graphs that 

show this comparison by apartment type. 

0

100

200

300

400

500

600

700

800

900

Consumption [kWh]

Month/Year

2-Bed - Actual

2-Bed - Model

3-Bed - Actual

3-Bed - Model

4-Bed - Actual

4-Bed - Model
15 

Figure 5. Histogram showing individual apartment energy consumption variation

Heating and cooling energy use was disaggregated from all other energy (lighting, appliances, 

and plug loads). This is shown in Figure 6 for the average four-bedroom apartment (see the 

Appendix for the results for all apartment types). The 12-month heating and cooling energy use 

is 54% lower than projected values, but the base load energy use is 54% higher than projected 

values (green dotted lines) and total energy use for the average four-bedroom apartment is 23% 

higher than projected values. Space conditioning may be lower due to some combination of 

occupants using less aggressive thermostat set points than assumed (78°F in cooling and 70°F in 

heating), occupants relying on the ceiling fans during the summer, and the apartments 

performing better than expected thermally. One hypothesis for the high base load consumption is 

the “multiple household” effect, whereby student occupancy tends to have more duplication of 

certain electronic devices (computers, gaming stations, TVs, etc.) that would skew consumption 

away from what might be expected from the more typical multifamily household usage 

represented in the California RASS data. Entertainment and computing devices may likely be 

located in each bedroom instead of shared in the living area. While lighting may also be a 

contributing factor, it is theorized that it is less so than plug loads because of vacancy sensors 

installed throughout the apartments.

In order to compare actual non-HVAC energy use with current Building America assumptions, 

the original model was revised to use the MEL assumptions in the current House Simulation 

Protocols (Hendron et al. 2010). In addition to ARBI’s 25% reduction to better align total MEL 

energy use with California RASS data, the California state multiplier of 0.77 was also removed, 

since this has been eliminated in the most current version of the House Simulation Protocols to 

0

2

4

6

8

10

12

40%45%50%55%60%65%70%75%80%

85%

90%95%

100%105%110%115%120%125%130%135%140%145%150%155%160%165%170%175%180%185%190%195%200%

Frequency

Percent of Modeled

2-Bed

3-Bed

4-Bed
16 

keep assumptions consistent nationwide.15 The four-bedroom apartments were selected for this 

comparison because they exhibited the most pronounced difference in base load consumption, 

and based off the conclusions of the “multiple household” effect, they would most likely have 

the greatest duplication of MELs. With this change, actual base load energy consumption is 

within 24% of modeled values, as shown in Figure 6 (gray dotted line). Although not shown in 

the graphic, if the vacation assumptions are also removed from the modeling estimates, actual 

base load energy consumption becomes only 17% greater than this revised modeling estimate.

Figure 6. Average disaggregated energy use over 12 months 

(March 2012 to February 2013) for the four-bedroom apartments16

Domestic Hot Water and Common Meter Energy

Figure 7 compares modeling estimates for common meter energy consumption with actual

consumption. Values for 14 common meters are averaged in the solid red line.

17 Actual 

consumption is much higher than original predictions. Seasonal variations in the water heating 

load are also more pronounced than estimated. 

The water heaters are set up to operate primarily in heat pump mode and use minimal electric 

resistance heating for backup during times of high load or low outdoor air temperatures. There 

 

15 Note that this was a post-process alteration and therefore the change in MEL load did not affect space 

conditioning energy use. 

16 Disaggregation results are estimates only and are not based on submetering. Preliminary results from a parallel 

monitoring project that includes end-use submetering indicate that total HVAC may be higher than is estimated here 

and is primarily a result of system fans being operated continuously. Fan energy use not associated with heating and 

cooling operation will show up as base load energy in this disaggregation process, not heating and cooling energy.

17 One building meter is not shown here because it supports a large site lighting load that cannot be separated from 

the common meter energy use. Another had unreliable or missing data for a portion of the year.

0

100

200

300

400

500

600

700

800

1 2 3 4 5 6 7 8 9 10 11 12

Energy Usage [kWh]

Month

Ltg+App+MEL - Actual

Ltg+App+MEL - Model

(RASS)

Ltg+App+MEL - Model

(Align with Current HSP)

Heating - Actual

Heating - Model

Cooling - Actual

Cooling - Model
17 

have been ongoing issues with heat pump operation, resulting in excessive resistance heat 

operation and consequently high electricity use. It is hypothesized that this is the primary result 

of the high energy consumption; however, it is possible that there are higher than estimated 

recovery loads. Further investigation is needed to better qualify the high energy use. 

ARBI has installed detailed monitoring on one of the HPWH systems (ARBI 2013), which has 

provided performance data and helped identify potential operating problems. Monitoring has 

shown that when commissioned correctly system efficiencies track relatively well with 

manufacturer engineering performance data. Without proper feedback it has proved difficult to 

identify operational problems, which has led to systems running in electric resistance mode for 

long periods before the issue is recognized.

The Phase I heat pumps were installed by plumbers with no previous experience with HPWHs. 

After ARBI completed the installation of monitoring equipment in September 2011, it was 

quickly identified that the systems were not properly commissioned or operating correctly and 

were operating exclusively in electric resistance mode. Over the first year of operation, there 

have been several instances of heat pump operational issues, and several of the systems appear to 

be having more problems than others, resulting in high energy use. The water heaters installed in 

later phases have been installed and commissioned by mechanical contractors who may be more 

suited to install such systems given their experience with heat pumps. These systems do not 

appear to have the operational problems evident in Phase I and the installation/commissioning 

issues have not been present now that the installers are more familiar with the heat pumps. 

Figure 7. Monthly average common meter use compared to modeled (15 buildings)

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

Consumption [kWh]

Month/Year

Avg. Actual Common Meter

Model - Common Meter
18 

Figure 8 shows the variation in common meter energy consumption across the 14 buildings. 

Only four of the buildings are operating within a reasonable range from the expected value 

(within 25%), with 10 buildings 34%–216% higher than modeling estimates predicted. 

Figure 8. Actual common meter energy consumption for 14 buildings over 12 months

(March 2012 to February 2013)

4.3 Phase I Zero Net Energy Evaluation

The first year’s performance in regards to achieving project ZNE goals for the Phase I 

community was completed using monthly utility net meter and SunPower PV production data. 

This is a preliminary evaluation because the ZNE goals have been set for the entire community, 

which is still being built out. Because of the operational and installation issues with the HPWHs

resulting in high energy use, energy usage for the common meters was separated out from the 

apartment meters.

Table 5 and Figure 9 show overall PV production is 4% greater than projected, suggesting good 

alignment with the SunPower model.18 On the consumption side, apartment usage is 18% higher 

than projected, while common area usage is 55% higher than the original estimates. Overall, 

combined consumption is 28% higher than projected. 

 

18 In comparing monthly measured PV generation to theoretical generation estimated by NREL PVWatts, the two 

values correlated well for most of the months. However, in the period of July through October there is a fairly strong 

divergence as the actual generation data falls much more rapidly than the projected data. It is hypothesized that this 

is due to dust accumulation and hotter PV operating temperatures, which would be removed after the first significant 

rain of the season. Increased production might be realized if regular panel array cleaning is conducted during the 

summer. SunPower includes an assumption for reduced performance due to dirt accumulation in its annual 

projections.

0

10

20

30

40

50

60

70

80

Consumption [MWh]

Common Meter

Ramble A Ramble B

Model - Ramble A Model - Ramble B
19 

Table 5. Projected and Actual Production, Consumption, and Net Energy Values

Production

(MWh)

Consumption

(MWh)

Net Energy

(MWh)

Projected Actual % Diff Projected Actual % Diff Actual

Apartments 1,024 1,110 8% 1,163 1,377 18% 267.3

Common 

Meter 471 451 -4% 390 602 55% 151.1 

Total 1,495 1,561 4% 1,552 1,979 28% 418.4

Figure 9. Comparison of annual Phase I consumption and production

Figure 10 presents monthly net, production, and consumption values over the entire Phase I 

community for the 12-month evaluation period. The net values are negative when production 

surpasses consumption and positive when consumption is greater than production. The 

community is a net producer for 3 months out of the year (May through July) with three months 

in the shoulder season (April, August, and September) when consumption roughly equals 

production. The magnitude of the summer net production is not large enough to offset the winter 

effect when consumption rises and PV production falls. 

0

500

1,000

1,500

2,000

2,500

Projected

Production

Projected

Consumption

Actual

Production

Actual

Consumption

Energy [MWh]

Common Areas

Apartments
20 

Figure 10. Total consumption, production, and net values for all Phase I buildings

4.4 Cost Effectiveness

An economic analysis of the package of EEMs was completed to evaluate cost effectiveness. 

There are no split incentives in this project since the developer investing the dollars in energy 

efficiency is also the utility bill owner. However, projects where tenants pay utility bills are 

presented with a unique set of challenges in justifying the investment to the developer. 

Based on the results of energy data disaggregation, actual HVAC energy consumption appears to 

be lower than original estimates. It is also expected that once the operational issues are resolved 

on the HPWHs that system performance should be consistent with expectations. Actual domestic 

hot water recovery loads may be higher than estimated; however, higher draws would impact

both the base case and improved cases. Provided that the majority of EEMs affect space 

conditioning and domestic hot water energy use, it was concluded that original model results can 

be used with some confidence to conduct a cost effectiveness evaluation. While high efficacy 

lighting and ENERGY STAR appliances were components of the EEM package, there are not 

sufficient data to separate these end uses from the total base load. The presence of vacancy 

sensors in each major space in the apartments reduces the impact of occupant behavior on total 

lighting hours and increases likelihood that lighting savings will be realized. The assumption 

upon which this cost evaluation is contingent is that the high base load seen in the above graphs 

is primarily due to increased plug loads. 

Table 6 demonstrates the key inputs to the LCC evaluation that was conducted over a 20-year 

period. First-time costs and savings were calculated for a single Ramble A 12-unit building. 

-50

-25

0

25

50

75

100

125

150

175

200

225

Energy [MWh]

Month/Year

Cons.

Prod.

Net
21 

Results of the analysis are presented in Table 7. Four financing scenarios were evaluated. If the 

builder has sufficient equity on hand such that financing of the incremental costs for the EEMs

isn’t necessary, then the cost savings over the 20-year period are $18,793. Additionally, three 

different loan periods are presented; at 10, 15, and 20 years, all with a 5% interest rate. With a 

20-year loan, the LCC savings are $15,316 or $578 per year. 

Table 6. LCC Evaluation Key Input Metrics

Capital 

Incremental 

Cost

1st Year 

Electricity 

Savings

1st Year 

Gas 

Savings

Evaluation 

Period

Real 

Discount 

Rate

$40,563 -$1,040 $5,605 20 yrs 3% 

Table 7. LCC Comparison of a Single Ramble A Building

Compared to California Title-24 Standard

Financing Scenario Total LCC LCC 

Savings

LCC 

Savings/yr

Title-24 Base Case $489,223 – –

No Financing $470,440 $18,793 $940

10yr Loan @ 5% Interest $473,917 $15,316 $766

15yr Loan @ 5% Interest $475,829 $13,404 $670

20yr Loan @ 5% Interest $477,669 $15,316 $578
22 

5 Conclusions and Discussion 

This report evaluated the first 10 months of energy consumption data available for Phase I of the 

student housing building at West Village. Build-out of the community is ongoing, yet thus far the 

project has been a success, demonstrated by the design and construction of buildings that 

incorporate cost-effective measures that reduce heating and cooling energy use significantly. 

Results have provided valuable insights and lessons learned into the first planned ZNE

community in the United States. Information gleaned thus far will be valuable for other 

developers and communities who may consider other community-level ZNE or high 

performance projects. Following are responses to the specific research questions.

1. How does measured energy use compare to modeled and were the expected energy 

savings achieved?

Total energy consumption for the 16 Phase 1 apartment buildings was found to exceed modeling 

projections by 28%. Apartment usage was found to be 18% higher than projections and the 

common area meter HPWH and building exterior lighting combined usage was found to be 55% 

higher than projected. 

There is a great degree of variability in usage among the individual apartments. The factor of 4 

ratio in usage from high to low use apartments (ranging from 45% to 200% of predicted 

10-month values) suggests significant behavioral and occupancy variability. Average monthly 

apartment energy consumption profiles suggest that non-HVAC use is the primary cause for the 

discrepancy. For the four-bedroom apartments, energy use disaggregation showed HVAC energy 

use was overpredicted by 56% and non-HVAC energy use was underpredicted by 54%. Relying 

on the 2009 RASS for estimates of multifamily plug load usage was not ideal, given the fact that 

the student apartments are composed of multiple “households,” while statewide multifamily 

estimates in RASS are more heavily biased toward single households, with less duplication of 

energy consuming appliances and electronic gadgets. When MEL estimates were increased to 

reflect assumptions in the current House Simulation Protocols (Hendron et al. 2010), actual base

load energy use still exceeds modeled by 24%. While it is accepted that MEL usage is affected 

by occupancy and unit floor area, an important conclusion from this study is that it is also highly 

dependent on occupancy type; e.g., student housing versus conventional multifamily, versus 

single-family housing. 

Roughly half of the HPWHs have experienced operational issues resulting in excessive 

resistance heat operation and consequently high electricity use. WVCP and ARBI are currently 

investigating the details of these problems, but it is theorized that improper initial commissioning 

combined with difficulty in readily diagnosing system operation may be the primary cause. All 

the Phase I HPWHs were installed by plumbers with no previous experience with HPWHs. The 

HPWHs in future phases have been or are to be installed and commissioned by mechanical 

contractors. It is recommended that the installing contractor has experience with refrigerant 

systems, either mechanical contractors or plumbers with appropriate training, as they may be 

more suited to install such systems. 
23 

2. Was the the project able to achieve the stated energy goals?

The answer to this is yet to be determined. The West Village ZNE goals are defined on a 

community level and construction is roughly 50% complete at this stage. Occupant-supplied plug 

load energy use is higher than the initial assumptions used for modeling due to the “multiple 

household” effect, resulting in annual consumption above projections. WVCP and UC Davis 

continue to be committed to this goal and will use the results of this initial Phase I evaluation to 

improve implementation efforts and optimize performance. This may involve the addition of 

EEMs or PV where necessary, increased encouragement of student participation in reducing 

energy use, or adjusting future modeling assumptions. 

3. How cost effective is this package of EEMs in a multifamly application?

Cost analysis demonstrates that the package of EEMs incorporated at West Village is cost 

effective compared to the Title-24 compliant construction under various common financing 

scenarios. During the design phase much attention was paid to selection of EEMs that were 

proven and cost effective. This is very compelling evidence to be presented to production 

builders in support of future similar projects.

There are several issues that make the cost effectiveness of NZE communities challenging: 

• Under California regulation that was in place when the first two phases of student 

housing were permitted, virtual net metering (VNM) of onsite generation was not 

allowed. VNM allows for generation and consumption to be traded across meters within 

the community and is an attractive model for multifamily property managers who are also 

utility account owners. The result of this was that each individual apartment meter was 

connected to a unique PV array and inverter with its own net-metering account. Utility 

account owners are charged for additional consumption at the end of the year for any 

apartment that consumes more than they produce, and are reimbursed at far less than the 

electricity retail rate for apartments that produce more than they consume19. From a cost 

perspective to WVCP, minimizing utility bills requires that each individual apartment 

achieve net zero. It is critical that creative models, such as VNM, be allowed under 

regulatory framework to encourage participation in ZNE construction by developers and 

property owners. A VNM program has now (starting in Phase III development) been 

established in California for multifamily projects, but VNM is allowed on a per building 

basis only, not across property lines. 

• Property managers that are also the utility bill owners are able to better justify the 

investment in energy efficiency in that they can reap the benefits of reduced utility bills. 

However, there are real challenges to controlling tenant energy consumption who are 

largely disconnected from their consumption. One option is to charge a premium for 

these features in monthly rent, which may increase awareness in some tenants but doesn’t 

provide any direct feedback on usage. Other possibilities include setting utility caps in the 

rental agreement and assessing fees for tenants that over-consume. However, utility 

regulations in California make this difficult or impossible, as they prohibit property 

managers from collecting income from tenants for utility fuel consumption. 

 

19 Under AB 920 this rate is close to $0.04/kWh as of September 2013.
24 

A project of this type highlights an encouraging point that a developer without previous 

experience with ZNE projects or installing EEMs could have such success, even given the 

regulatory difficulties and complexities present. With a constantly changing regulatory 

framework it is difficult to estimate what this model would look like for similar projects in other 

locations and with other developers 

4. What role do occupants have in high performance buildings and how well do tenants 

respond to energy education efforts by the developer? 

As heating and cooling loads in milder climates are continually driven down in high performance 

homes, occupants increasingly are becoming the most influential variable in impacting total 

home energy consumption. Measured non-HVAC base load at West Village averaged 85% of 

total apartment electricity (excluding water heating). Additionally, there is a great degree of 

variability due to occupancy and behavior across individual apartments with a factor of 4 ratio in 

usage from high to low use apartments. Some of this may be tempered during the design process 

through the installation of efficient hardwired lighting and appliances. However, as technology 

drives efficiency further, the impact of the occupant becomes increasingly important, primarily 

as reflected in their use of electronic devices. This is an important consideration given that 

modeling is relied upon heavily to size PV systems to meet project ZNE goals. Without feed-in 

tariffs or central distributed generation, achieving ZNE on a unit-by-unit basis becomes very 

complicated.

While occupants generally indicate interest in the efficiency of the West Village community, it is 

clear that more in-depth and regular engagement is necessary to increase the likelihood of 

achieving the community ZNE goals. Tenant education on basic energy efficiency strategies, 

creating a community energy and sustainability vision, and implementing and enforcing rules on 

excessive consumption (e.g., use of individual room refrigerators) are needed. Limited energy 

education efforts have been implemented as of publication of this report. However, WVCP is 

currently pursuing other strategies to help improve overall performance. Several proposed ideas 

include a monthly educational series and community level competitions for energy use 

reductions. WVCP is considering adoption of a program that incentivizes residents for achieving 

low energy use below a predefined threshold. Further evaluation of what strategies will be most 

successful, from a cost-effective, motivational, and legal standpoint, is still necessary. 
25 

References 

ARBI (2013). “Multi-Family Heat Pump Water Heater Evaluation”. Prepared for Building 

America by the Alliance for Residential Building Innovation. To be published in 2013. 

CARB (2009). 2009 Annual Progress Report Budget Period 2 (BP2). Attachment YY: West 

Village Zero Energy Community Report. Prepared for the U.S. Department of Energy by the 

Consortium for Advanced Residential Buildings. December. 

CARB (2010). 2010 Annual Progress Report Budget Period 3 (BP3). Attachment Y: Technical 

Paper – Zero Energy Communities: UC Davis’ West Village Community. Prepared for the U.S. 

Department of Energy by the Consortium for Advanced Residential Buildings. December, 2010. 

CEC (2008). “2008 Building Energy Efficiency Standards for Residential and Nonresidential 

Buildings.” California Energy Commission. CEC-400-2008-001-CMF. December. 

CPUC (2008). California Long Term Energy Efficiency Strategic Plan. California Public 

Utilities Commission. September.

Dakin, B.; Backman, C.; Hoeschele, M.; German, A. (2012). West Village Community: Quality 

Management Processes and Preliminary Heat Pump Water Heater Performance. Prepared for 

Building America by the Alliance for Residential Building Innovation. Accessed June 2014. 

http://apps1.eere.energy.gov/buildings/publications/pdfs/building_america/west_village_hpwh.p

df. 

Dakin, B.; Hoeschele, M.; Idrees, O. (2010). “Zero Energy Communities: UC Davis’ West 

Village Community.” ACEEE Summer Study on Energy Efficiency in Buildings. Washington, 

DC: American Council for an Energy Efficiency Economy, August. 

DEG (2010). “UC Davis West Village Community Energy Study”. Prepared for Chevron Energy 

Solutions by Davis Energy Group. May, 2010. 

Hendron, R. (2008). Building America Research Benchmark Definition. Golden, CO: National 

Renewable Energy Laboratory, NREL/TP-550-44816. Accessed June 

2014. http://apps1.eere.energy.gov/buildings/publications/pdfs/building_america/44816.pdf.

Hendron, R.; Engebrecht, C. (2010). Building America House Simulation Protocols. Golden, 

CO: National Renewable Energy Laboratory, NREL/TP-550-

49246. www.nrel.gov/docs/fy11osti/49246.pdf.

KEMA (2009). 2009 California Residential Appliance Saturation Study. Prepared for the 

California Energy Commission. CEC-200-2010-004-ES. October. 

Risko, G. (2012). “Preliminary Results: ZNE Related Verification & Assessment for the West 

Village Apartments Development”. Prepared for Pacific, Gas, and Electric Company by 

Architectural Energy Corporation. February, 2013. 

U.S. Department of Commerce (2010). “Energy Price Indices and Discount Factors for Life 

Cycle Cost Analysis – 2010”. Prepared for the United States Department of Energy (DOE) 

Federal Energy Management Program by the U.S. Department of Commerce. 
26 

Appendix: Supplementary Evaluation Graphs

Figure 11 through Figure 13 show the observed range in energy consumption compared to model 

predictions for all apartments by apartment type. 

Figure 11. Histogram showing variation in energy consumption over 12 months 

(March 2012 to February 2013) for all two-bedroom apartments

Figure 12. Histogram showing variation in energy consumption over 12 months 

(March 2012 to February 2013) for all three-bedroom apartments 

0

1

2

3

4

40%45%50%55%60%65%70%75%80%85%90%95%

100%105%110%115%120%125%130%

135%140%145%150%

155%160%165%170%175%180%185%190%195%200%

Frequency

Percent of Modeled

Actual

Model

Modeled [kWh]

4,987

0

1

2

3

4

5

6

7

8

40%45%50%55%60%65%70%75%80%85%90%95%

100%105%110%115%120%125%130%135%140%145%150%155%160%165%170%175%180%185%190%195%200%

Frequency

Percent of Modeled

Actual

Model

Modeled [kWh]

5,590
27 

Figure 13. Histogram showing variation in energy consumption over 12 months 

(March 2012 to February 2013) for all four-bedroom apartments

Figure 14 through Figure 16 demonstrate the results of data disaggregation for the three-bedroom 

and two-bedroom apartments, respectively. 

Figure 14. Average disaggregated energy use over 12 months 

(March 2012 to February 2013) for the two-bedroom apartments

0

1

2

3

4

5

6

7

8

9

10

40%45%50%55%60%65%70%75%80%85%

90%95%

100%105%110%115%120%125%130%135%140%145%150%155%160%165%170%175%180%185%190%195%200%

Frequency

Percent of Modeled

Actual

Model

Modeled [kWh]

6,394

0

100

200

300

400

500

600

1 2 3 4 5 6 7 8 9 10 11 12

Energy Usage [kWh]

Month

Ltg+App+MEL - Actual

Ltg+App+MEL - Model

Heating - Actual

Heating - Model

Cooling - Actual

Cooling - Model
28 

Figure 15. Average disaggregated energy use over 12 months 

(March 2012 to February 2013) for the three-bedroom apartments

Figure 16. Average disaggregated energy use over 12 months 

(March 2012 to February 2013) for the four-bedroom apartments

0

100

200

300

400

500

600

700

1 2 3 4 5 6 7 8 9 10 11 12

Energy Usage [kWh]

Month

Ltg+App+MEL - Actual

Ltg+App+MEL - Model

Heating - Actual

Heating - Model

Cooling - Actual

Cooling - Model

0

100

200

300

400

500

600

700

800

1 2 3 4 5 6 7 8 9 10 11 12

Energy Usage [kWh]

Month

Ltg+App+MEL - Actual

Ltg+App+MEL - Model

Heating - Actual

Heating - Model

Cooling - Actual

Cooling - Model
DOE/GO-102014-4442 ▪ June 2014

Printed with a renewable-source ink on paper containing at 

least 50% wastepaper, including 10% post-consumer waste.

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