Small Commercial EMS Scaled Field Placement - … Commercial EMS Scaled Field Placement ET Project Number: ET12PGE3461 ... Alameda County Retail HVAC Energy vs Outside …

PG&E’s Emerging Technologies Program ET12PGE3461

Small Commercial EMS Scaled Field Placement

ET Project Number: ET12PGE3461

Project Managers: Leo Carrillo and Mananya Chansanchai Pacific Gas and Electric Company Prepared By: Lisa Gartland, PhD, Peter Pollard, P.E., Magdalena Brum kW Engineering Inc. 287 17th Street, Suite 300 Oakland, CA 94612

Issued: September 30, 2015

Copyright, 2015, Pacific Gas and Electric Company. All rights reserved.

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ACKNOWLEDGEMENTS

Pacific Gas and Electric Company’s Emerging Technologies Program is responsible for this project. It was developed as part of Pacific Gas and Electric Company’s Emerging Technology –Technology Assessment program under internal project number ET12PGE3461. kW Engineering conducted this technology evaluation for Pacific Gas and Electric Company with overall guidance and Leo Carrillo and Mananya Chansanchai. PG&E would like to thank Siemens Building Technologies for their participation and support of this project.

For more information on this project, contact Leo Carrillo ([email protected]).

LEGAL NOTICE

This report was prepared for Pacific Gas and Electric Company for use by its employees and agents. Neither Pacific Gas and Electric Company nor any of its employees and agents:

(1) makes any written or oral warranty, expressed or implied, including, but not limited to those concerning merchantability or fitness for a particular purpose;

(2) assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, process, method, or policy contained herein; or

(3) represents that its use would not infringe any privately owned rights, including, but not limited to, patents, trademarks, or copyrights.

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ABBREVIATIONS AND ACRONYMS

CT Current transducer

EMS Energy management systems

HVAC Heating, ventilating and air conditioning

NF New Functionality

PCT Programmable Communicating Thermostats

ST Supporting Technology

TMY3 Typical Meteorological Year. The TMY3 data set contains data for 1020 locations for years 1991-2005.

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FIGURES

Figure 1A. Example HVAC Energy vs Outside Air Temperature –

Occupied Hours .......................................................... 18

Figure 1B. Example HVAC Energy vs Outside Air Temperature –

Staff Hours ................................................................ 19

Figure 1C. Example HVAC Energy vs Outside Air Temperature –

Unoccupied Hours ...................................................... 19

Figure 2. Daily Average Monitored HVAC Use at Placer County Fast

Food Restaurant Facility, Pre & Post EMS ...................... 20

Figure 3. Daily Average Monitored HVAC Use at Stanislaus County

Assembly/Restaurant Facility, Pre & Post EMS ................ 21

Figure 4. Daily Average Monitored HVAC Use at Kern County Retail

Clinic Facility, Pre & Post EMS Hours ............................. 21

Figure 5A. Daily Average Monitored Lighting Use at Kern County

Retail Clinic Facility, Pre & Post EMS ............................. 28

Figure 5B. Daily Average Monitored Lighting Use at Alameda

County Retail Facility, Pre & Post EMS ........................... 28

Figure 5C. Daily Average Monitored Lighting Use at Nevada County

Assembly Facility, Pre & Post EMS ................................ 28

Figure 5D. Daily Average Monitored Lighting Use at Lake County


Figure 5E. Daily Average Monitored Lighting Use at Stanislaus

County Assembly/Restaurant Facility, Pre & Post EMS ..... 29

Figure 5F. Average Monitored Daily Lighting Use at Santa Clara


Figure 5G. Daily Average Monitored Lighting Use at South Santa

Clara County Sit Down Restaurant Facility, Pre & Post

EMS.......................................................................... 29

Figure 5H. Daily Average Monitored Lighting Use at San Joaquin

County Sit Down Restaurant Facility, Pre & Post EMS ...... 29

Figure 5I. Daily Average Monitored Lighting Use at Alameda County

Fast Food Restaurant Facility, Pre & Post EMS ................ 30

Figure 5J. Daily Average Monitored Lighting Use at Placer County


Figure 5K. Daily Average Monitored Lighting Use at Merced County


Figure 6A. Daily Average Monitored HVAC Use at Kern County

Retail Clinic Facility, Pre & Post EMS ............................. 34

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Figure 6B. Daily Average Monitored HVAC Use at Alameda County

Retail Facility, Pre & Post EMS ...................................... 34

Figure 6C. Daily Average Monitored HVAC Use at Nevada County

Assembly Restaurant Facility, Pre & Post EMS ................ 34

Figure 6D. Daily Average Monitored HVAC Use at Lake County


Figure 6E. Daily Average Monitored HVAC Use at Stanislaus County

Assembly/Restaurant Facility, Pre & Post EMS ................ 35

Figure 6F. Daily Average Monitored HVAC Use at Santa Clara


Figure 6G. Daily Average Monitored HVAC Use at South Santa Clara


Figure 6H. Daily Average Monitored HVAC Use at San Joaquin


Figure 6I. Daily Average Monitored HVAC Use at Alameda County


Figure 6J. Daily Average Monitored HVAC Use at Placer County Fast

Food Restaurant Facility, Pre & Post EMS ...................... 36

Figure 6K. Daily Average Monitored HVAC Use at Merced County


Figure 7. Cooling and Heating Setpoints During Occupied and

Unoccupied Periods Pre- and Post- EMS Installation ........ 39

Figure D - 1A. Kern County Retail HVAC Energy vs Outside Air

Temperature – Occupied Hours .................................... 70

Figure D – 1B. Kern County Retail HVAC Energy vs Outside Air

Temperature – Unoccupied Hours ................................. 70

Figure D - 2A. Alameda County Retail HVAC Energy vs Outside Air


Figure D – 2B. Alameda County Retail HVAC Energy vs Outside Air


Figure D – 3A. Nevada County Assembly HVAC Energy vs Outside

Air Temperature – Occupied Hours ............................... 71

Figure D – 3B. Nevada County Assembly HVAC Energy vs Outside

Air Temperature – Unoccupied Hours ............................ 71

Figure D – 4A. Lake County Assembly HVAC Energy vs Outside Air


Figure D – 4B. Lake County Assembly HVAC Energy vs Outside Air


Figure D – 5A. Stanislaus County Assembly/Restaurant HVAC

Energy vs Outside Air Temperature – Occupied Hours ..... 72

Figure D – 5B. Stanislaus County Assembly/Restaurant HVAC

Energy vs Outside Air Temperature – Unoccupied Hours . 72

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Figure D – 6A. Santa Clara County Assembly/Restaurant HVAC


Figure D – 6B. Santa Clara County Assembly/Restaurant HVAC


Figure D – 7A. Santa Clara County Sit Down Restaurant HVAC


Figure D – 7B. Santa Clara County Sit Down Restaurant HVAC

Energy vs Outside Air Temperature – Staff Hours ........... 73

Figure D – 7C. Santa Clara County Sit Down Restaurant HVAC


Figure D – 8A. San Joaquin County Sit Down Restaurant HVAC


Figure D – 8B. San Joaquin County Sit Down Restaurant HVAC

Energy vs Outside Air Temperature – Staff Hours ........... 74

Figure D – 8C. San Joaquin County Sit Down Restaurant HVAC


Figure D – 9A. Alameda County Fast Food Restaurant HVAC Energy

vs Outside Air Temperature – Occupied Hours ............... 75

Figure D – 9B. Alameda County Fast Food Restaurant HVAC Energy

vs Outside Air Temperature – Unoccupied Hours ............ 75

Figure D – 10A. Placer County Fast Food Restaurant HVAC Energy


Figure D – 10B. Placer County Fast Food Restaurant HVAC Energy


Figure D – 11A. Merced County Fast Food Restaurant HVAC Energy


Figure D – 11B. Merced County Fast Food Restaurant HVAC Energy


TABLES

Table 1. Electricity Savings from EMS Installation in Eleven Small

Commercial Facilities .................................................... 2

Table 2. Business Type and Square Footage Data for PG&E Service

Territory as of 1999 ...................................................... 6

Table 3. Installation Dates & Monitoring Periods for Eleven Projects .. 11

Table 4. Local Weather Data, Annual Weather Data, and Building

Energy Use Reference Data Used to Annualize and

Normalize Monitoring Results ....................................... 14

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Table 6. CEUS Electricity Use per Floor Area Used to Normalize

Savings in the Facilities ............................................... 22

Table 7. Annual Lighting and HVAC Electricity Savings Due to EMS

Installation, in Percent ................................................ 24

Table 8. Lighting Electricity Savings From EMS Installation during

Occupied, Staff & Unoccupied Periods ........................... 25

Table 9. HVAC Electricity Savings From EMS Installation during

Occupied, Staff & Unoccupied Periods ........................... 32

Table 10. Extreme Outdoor Low and High Temperatures During

Each Facility’s Monitoring Period ................................... 33

Table 11. Weekly Operating Hour Comparison ............................... 38

Table 12. Comparison of Temperature Setpoints, Reported Pre-

Install and EMS Post-Install ......................................... 40

Table 13: Potential Information to Collect to Determine the

Eligibility and Verify Effective Operation of Supporting

Technologies ............................................................. 49

Table 14: Potential Information Needed to Determine the Eligibility

and Verify Effective Operation of New Functionalities ...... 50

Table E - A. CEUS Electricity Use per Floor Area Used to Normalize

Savings in the Facilities ............................................... 76

Table E - B. Total Building Electricity Savings Estimates Based on

Typical CEUS Data ...................................................... 77

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CONTENTS

ABBREVIATIONS AND ACRONYMS _____________________________________________ II

FIGURES _______________________________________________________________ III

TABLES ________________________________________________________________ V

CONTENTS _____________________________________________________________VII

EXECUTIVE SUMMARY _____________________________________________________ 1

INTRODUCTION __________________________________________________________ 4

BACKGROUND __________________________________________________________ 5

ASSESSMENT OBJECTIVES __________________________________________________ 7

EMERGING TECHNOLOGY/PRODUCT _________________________________________ 7

DATA COLLECTION APPROACH _____________________________________________ 8

“Before” and “After” Surveys .................................................... 8

Data Loggers ........................................................................ 10

EMS Online Data ................................................................... 12

ENERGY SAVINGS ANALYSIS AND RESULTS ____________________________________ 13

Lighting Analysis ................................................................... 15

HVAC Analysis ...................................................................... 15

Lighting Monitoring Savings Results ......................................... 24

HVAC Monitoring Savings Results ............................................ 31

Qualifications of Evaluation Findings ........................................ 37

Pre and Post Occupant Behavior .............................................. 37

Survey Highlights .................................................................. 41

Pre-Installation Surveys .................................................... 41 Post-Installation Surveys................................................... 41

EVALUATIONS __________________________________________________________ 42

POTENTIAL FOR EFFICIENCY PROGRAM INCENTIVES ______________________________ 43

Introduction ......................................................................... 43

Definitions ............................................................................ 43

Custom Incentive Measures .................................................... 44

Deemed Incentive Measures ................................................... 45

Hybrid-Deemed incentive Measures ......................................... 46

Screening Projects for Eligibility and Verification ....................... 49

Supporting Technologies ................................................... 49

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New Functionalities........................................................... 50

EMS Controls: Fixed Incentive and Functionality Incentives ....... 51

RECOMMENDATIONS ____________________________________________________ 52

Potential Next Steps .............................................................. 52

Comparison of Savings with Existing Modeling Results .......... 52 Expand and Develop Incentive Approach and Tools .............. 53

Considerations for Future Field Studies .................................... 53

APPENDICES ___________________________________________________________ 55

Appendix A: Pre-Installation Survey ........................................ 55

Appendix B: Post-Installation Survey ....................................... 62

Appendix C: Post-Installation Survey Responses ....................... 67

Appendix D: Graphs of HVAC Energy vs Outside Air Temperature 69

Appendix E: Estimates of Whole Building Savings Using CEUS Benchmark Data

........................................................................................... 76

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EXECUTIVE SUMMARY This Emerging Technology report describes the data collection and analysis done to evaluate

the energy savings potential of an energy management system (EMS) with integrated HVAC

and lighting control functionality that is specially designed for small commercial facilities. As

part of the project, kW Engineering performed a retrofit isolation analysis of the EMS

installation in eleven facilities representing a variety of building types and climate zones in

PG&E’s service territory. The installation of an EMS provided an opportunity for customers to

re-examine, improve and enforce operating schedules and settings.

For a limited period of time prior to and immediately following system installation, energy

use of HVAC and some lighting systems was monitored at each site. Information from

participant surveys and online EMS control systems was also used to inform the energy

savings analysis. HVAC energy data was extrapolated to estimate annualized savings based

on typical weather where appropriate. However for most sites, the range of weather during

the monitoring periods (in winter) was quite limited. This likely resulted in lower measured

HVAC savings than had the monitoring periods occurred during the summer months, when

HVAC usage is typically higher across California climate zones.

As shown in Table 1 on the following page, the greatest savings came from reductions in

HVAC energy use, averaging 18% in nine buildings with confirmed savings. HVAC data for

two sites was excluded due to anomalies; further detail is provided in the report. Savings

from reduced lighting use occurred in six of eleven buildings, with average lighting savings

of 6% for all sites.

Using benchmark data from the California Commercial End Use Study, kW estimated that

the lighting and HVAC savings from the eleven buildings translated into an average building

savings of approximately 5%, or 20 kWh per square foot. Note, these building-level savings

are estimates only, not using whole building data. See Appendix E.

While savings on average were significant, there were large variations from building to

building, as is typical for controls measures. Lighting energy savings varied from a low of -

6% to a high of 36%. Annualized HVAC savings ranged from a low of 6% to a high of 31%.

Savings depended primarily on how well the HVAC and lighting was controlled before the

EMS installation. For these small commercial sites, lighting was already fairly well-controlled

in most sites, with staff shutting off lights at the end of the day. In this sample, there was

no discernible pattern of lighting savings by building type.

For HVAC, the EMS controls provided savings through tighter scheduling, more overnight

setbacks, and daytime setpoint enforcement. A clear example is two restaurant sites with

“staff-only” hours, which achieved annualized savings of 60% on average during those

hours through temperature setbacks implemented using the EMS. Of course HVAC savings

are also impacted by climate, with more extreme climates using more energy for HVAC, and

thus providing more opportunity for savings through better HVAC controls. However,

climate factors were outweighed by the baseline scheduling in determining HVAC savings

achieved.

Table 1 on the following page summarizes the monitored percent savings for lighting and

HVAC after installation of small commercial EMS at 11 facilities.

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TABLE 1. ELECTRICITY SAVINGS FROM EMS INSTALLATION IN ELEVEN SMALL COMMERCIAL FACILITIES

The ability to make broad conclusions from this study were impacted by the small number

of sites monitored (a common challenge with technology assessments), the limited range of

weather conditions monitored (with installation occurring in winter at many sites), and some

site anomalies and logger issues. Future studies could address these limitations, thereby

increasing the size of the study population and range of monitored weather conditions, and

hopefully minimizing the relative impact of site anomalies and logger issues on study

results.

Notwithstanding these limitations, our study of the eleven participating facilities suggests

that the implementation of the EMS is an effective measure for saving energy in small

commercial buildings, and overall, the EMS functioned mostly as expected during the

assessment period.

LocationCalifornia

Climate ZoneBuilding Type Lighting %

Savings

HVAC %

Savings

Kern County 13 Retail 14% 6%

Alameda

County12 Retail 0% 20%

Nevada

County11 Assembly - 25%

Lake County 2 Assembly 36% 9%

Stanislaus

County12

Assembly /

Restaurant7% -

Santa Clara

County4

Assembly /

Restaurant-4% 31%

Santa Clara

County4

Sit Down

Restaurant-6% 19%

San Joaquin

County12

Sit Down

Restaurant8% 28%

Alameda

County12

Fast Food

Restaurant-5% 18%

Placer County 11Fast Food

Restaurant17% -

Merced

County12

Fast Food

Restaurant1% 11%

AVERAGE 6% 18%

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This report also explores the suitability of using efficiency program incentives - including

custom, deemed and hybrid-deemed incentive approaches - to encourage the adoption of

control retrofits (such as small commercial EMS) to save energy. These controls retrofit

projects present challenges in establishing baseline conditions, verifying installed results,

and estimating savings. With the custom incentive approach, the costs of project-specific

savings analyses are high relative to the cost of the project itself. Deemed incentive

programs offer lower costs but provide no data on actual results achieved. This report

proposes that hybrid-deemed incentive programs for controls projects, such as small

commercial EMS, can be developed which are simpler, faster, and less costly than

customized incentives, while still providing reliable estimates of energy savings in

aggregate.

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INTRODUCTION This report describes a retrofit isolation analysis performed by kW Engineering to evaluate

the energy savings from the installation of an energy management system (EMS) with

integrated HVAC and lighting control functionality in small commercial facilities throughout

PG&E’s service territory. A total of fifteen sites installed the EMS, which has the ability to

monitor and control lighting and HVAC systems, and to track the overall electrical

consumption and demand of a facility.

Eleven of the fifteen participating facilities were selected for the retrofit isolation study, for

which kW Engineering performed more intensive onsite monitoring of their EMS operation

and energy use at these facilities. Four types of information were collected and analyzed for

this evaluation:

“Before” surveys filled out by facility personnel to learn how lights and thermostats

were operated before the EMS was installed, and to obtain some basic information

about each building

Logged data for the subset of eleven facilities, installed to collect at least six weeks

of lighting and HVAC electricity use data, and some representative indoor

temperatures and lighting levels

EMS data for the subset of eleven facilities, with information about total facility

energy use, operating schedules, and thermostat settings obtained from online

accounts for each site

Weather data from nearby weather stations was collected to give us information

about outdoor temperatures

The collected data was used to analyze how each facility’s lighting and HVAC energy use

changed due to the use of the small commercial EMS.

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BACKGROUND Energy management systems are in common use in large commercial facilities. These

complex systems not only control lighting and space temperatures throughout large

buildings, they also deliver heating and cooling to the conditioned space more efficiently by

implementing strategies like economizer cooling, and temperature and/or static pressure

resets when outdoor and indoor temperatures permit. These systems have traditionally

needed to be hard-wired in order to send digital signals to a central controller. This has

made them somewhat expensive and difficult to install in existing buildings, but their cost

has been offset by their ability to save energy. EMS technology has not traditionally been

cost-effective in small commercial buildings, largely due to the fact that simpler HVAC

systems in these facilities present fewer efficiency opportunities and that EMS products have

heretofore been designed and priced primarily for larger facilities.

The advent of new EMS systems specially designed for small commercial lighting and HVAC

systems could address the cost effectiveness challenge of small commercial installations and

lead to improved market penetration among small commercial buildings. These systems

combine new wireless thermostats with pilot duty controllers, clamp-on current transducers,

and online software, to produce a cost-effective control system that is easy to install and

operate. These systems allow commercial facilities to control lighting and space

temperatures, and to visualize their energy use over time.

The energy savings opportunity in small commercial buildings is significant, especially with

regards to EMS technology1. Small commercial buildings represent the majority of

commercial facilities in PG&E’s service territory. According to PG&E’s 1999 Commercial

Building Survey Report2, premises of 5,000 square feet or smaller comprise 75% of the

1,764,630 commercial buildings served by PG&E in 1997. The table below is extracted from

this report, and shows the breakdown of building sizes by business type and climate region.

1 Estimation of EMS Presence in Commercial Buildings in PG&E Territory and a Snapshot of

Technologies in EMIS Landscape, ET Project Number ET11PGE4221, 2012

(http://www.etcc-ca.com/reports/estimation-ems-presence-commercial-buildings-pge-

territory-and-snapshot-technologies-emis).

2 Pacific Gas and Electric Company, Commercial Building Survey Report, 1999.

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TABLE 2. BUSINESS TYPE AND SQUARE FOOTAGE DATA FOR PG&E SERVICE TERRITORY AS OF 1999

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ASSESSMENT OBJECTIVES The data collected in this study aims to evaluate the energy savings potential from the use

of new EMS systems that have been developed specifically for use in small commercial

facilities. Achieving energy savings depends on how well these new systems are

implemented. Savings also depend heavily on how well each facility was being controlled

before the EMS was installed, and on other types of equipment used in each facility. Our

data collection is focused on measuring energy use, as well as figuring out the lighting and

HVAC system control strategies before and after the EMS installation, and understanding

where energy is used in each facility.

Out of the fifteen facilities participating in the overall project, eleven were included in the

retrofit isolation study to determine how their new EMS settings, schedules and other

features affected lighting and HVAC energy use. None of the sites studied used the EMS to

control refrigeration systems.

EMERGING TECHNOLOGY/PRODUCT The particular EMS product studied in this report is sold to third party distributors and

channel partners by an original equipment manufacturer (OEM). The EMS has the following

features:

an onsite central panel that is a touchscreen user interface, master controller, and

internet gateway for the EMS,

thermostats, with wireless communication to the central touchscreen panel, to

control HVAC or refrigeration equipment,

an 8DO (eight digital output) pilot-duty controller module used to switch up to eight

lighting or ventilation circuits on and off,

a multi-phase meter to measure total facility energy consumption, with split-core

current transducers to measure current, and voltage connections,

a web application that allows owners or managers to review current systems, view

historical trends, and change schedules and settings.

Note that the EMS application does not directly control the HVAC unit operation. Instead,

the EMS thermostat makes calls for cooling and heating like a traditional thermostat, and

separate controls within each HVAC unit are used to operate fans, compressors, and

economizers.

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DATA COLLECTION APPROACH We collected five sets of information to inform us about each facility, and the operation and

energy use of lights and HVAC equipment. We describe each data collection instrument or

data collection method below.

“BEFORE” AND “AFTER” SURVEYS Surveys are designed to identify how all forty buildings in the overall pilot project are being

controlled and operated both before and after the installation of the new EMS. The surveys

were administered online. The surveys are administered to the person with the most day-to-

day control of lighting and HVAC systems for each facility. This might be a general manager,

employee, or facility manager.

The “before” survey is designed to help us understand how the facility was operated prior to

the installation of its new EMS. The “before” survey has five sections:

1. Survey Intro & Screening lays out the reason for the survey, tries to make sure

the right person is being surveyed, and identifies who that person is.

2. General Business/Facility Info collects information about the type of business

including number of employees, operating hours, and information about the

building’s square footage, number of stories, and whether the facility shares a

building with other businesses. This information helps us understand the businesses

and facilities we’re studying, and allows us to compare them to the overall mix of

small commercial businesses in California.

3. Lighting Info asks how lights are currently being controlled (via switches, control

systems, etc.), who controls them, how many groups of lights there are, schedules

of use, if there are any occupancy sensors, dimmers, photocells or timers, and if

there are any current problems with lighting operation. This information will be

compared to the “after” survey info to see how lighting control changes.

4. HVAC Info asks about the type of thermostats or control systems, what

temperature settings and schedules are used, who can adjust the settings, whether

there are any current problems with comfort or control, and how often the systems

are serviced. This will be compared to “after” survey data to see how HVAC control

changes with the EMS.

5. Other Equipment asks the participant about other types of energy-using equipment

in the facility, including cooking, refrigeration, office, computer, or process

equipment. This helps us understand how much of the building’s energy loads are

not due to lighting or HVAC equipment.

Appendix A contains the actual online “before” survey used in this project.

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The “after” survey follows a format similar to the “before” survey, but questions are

designed to elicit information about changes in the facility or its operation since the EMS

was installed. There are six sections in the “after” survey:

1. Survey Intro & Screening describes the reason for this second survey, tries to

make sure the person who operates the EMS is being surveyed, and identifies who

that person is.

2. General Business/Facility Info collects information about any changes to

operating hours, employees, customers, or cleaning schedules since the installation

of the EMS. This includes details regarding the facility and its use, including the type

of business, number of employees, and operating hours.

3. Lighting Info asks if any lighting equipment changes have been made since the

start of the project, and then collects information about how the EMS is used to

operate lights, i.e. how many groups of lights are controlled, what their schedules

are, and who can override them. We also ask about the pros and cons of the EMS for

lighting.

4. HVAC Info asks if any HVAC equipment changes have been made since the start of

the project, and then collects information about how the EMS is used to adjust space

temperatures, i.e. what settings are used and when are they adjusted. We also ask

about the pros and cons of the EMS for HVAC system control, and about the

frequency of system servicing.

5. Other Equipment asks the participant about other types of energy-using equipment

being monitored of controlled by the EMS, including cooking, refrigeration, office,

computer, or process equipment, and whether they’ve changed the way this

equipment is being controlled because of the information they’re getting from the

EMS.

6. Alarms & Notifications is a new survey section, not included in the “before”

survey, where we ask about any notices the EMS may have sent and what was done

in response.

Appendix B has a copy of the “after” online survey questions.

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DATA LOGGERS Data loggers were installed at a subset of eleven project sites. The loggers were used to

record the energy use of lighting and HVAC equipment as well as some representative

indoor space temperatures, and lighting levels.

We used three types of data loggers in this project:

1. Current loggers recorded the current draw of various pieces of equipment in the

facility and use the current data plus spot typical measurements of voltage and

power factor to find energy use. Current loggers are current transducers (CTs) that

are connected to a data recording device. CTs are clamped around the wires of

particular circuits within an electrical panel. Current loggers were hooked up to a

representative sample of lighting and HVAC circuits in order to understand when this

equipment operates and how much energy it uses. Each measured circuit was also

spot-checked with a multimeter to measure the power factor of the equipment, and

the voltage.

2. Temperature loggers recorded the indoor temperature and humidity at various

locations in the facility. These loggers were placed above or below the “before”

thermostat locations.

3. Light loggers recorded the levels of illumination in the building. Loggers were

placed in locations that are representative of each group of lighting being controlled.

Loggers were set up to record data at least every fifteen minutes. We attempted to collect a

minimum of three weeks of data before installation of the new EMS, and another three

weeks of data after installation of the EMS. Table 3 below lists the installation dates and

monitoring periods in this study.

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TABLE 3. INSTALLATION DATES & MONITORING PERIODS FOR ELEVEN PROJECTS

Note that monitoring periods were less than three weeks for two facilities, although we were

still able to analyze data from these buildings:

The post-installation monitoring period was 11 days at the Alameda County Fast

Food Restaurant. We were told that installation of the EMS took place on December

13, 2013. However, the online EMS data for this site is not available until after

January 8, 2014.

The lighting circuits at the Lake County Assembly facility were initially connected

incorrectly to the EMS, so the wrong systems were being controlled. The problems

were fixed by December 28, 2013, so the post-installation period for lighting analysis

was 19 days.

In addition, lighting at the Nevada County Assembly facility was not connected to the EMS,

since the lighting system was already easily controlled by the facility staff. We kept the

results from the Nevada County facility in our final results, since the use of the EMS to

control only HVAC use is likely to occur in various facilities.

One major challenge for this study, regarding determining HVAC savings, was the

extrapolation to annual savings estimates from data covering only an incomplete range of

weather conditions. Most of the installations were completed during the winter season, so

that many sites experienced few or no hours of warm weather during the logging periods.

Table 3 above also lists how many HVAC units or lighting circuits were successfully

monitored at each facility. We tried to monitor the energy use of all operating HVAC units at

Location Building TypeMonitoring

Start

EMS

Installation

Monitoring

Finish

Pre Period

Days

Post Period

Days

HVAC Units

Monitored

Lighting

Circuits

Monitored

Kern County Retail 10/29/2013 12/20/2013 1/14/2014 51 24 3 3

Alameda

CountyRetail 11/19/2013 12/14/2013 1/20/2014 24 36 1 5

Nevada

CountyAssembly 10/29/2013 12/11/2013 1/16/2014 42 35 3 5

Lake County Assembly 10/30/2013 12/12/2013 1/16/2014 42 34 3 5

Stanislaus

County

Assembly /

Restaurant10/29/2013 12/17/2013 1/20/2014 48 33 8 11

Santa Clara

County

Assembly /

Restaurant11/19/2013 12/16/2013 1/26/2014 26 40 9 11

Santa Clara

County

Sit Down

Restaurant6/17/2013 7/31/2013 8/30/2013 43 29 5 5

San Joaquin

County

Sit Down

Restaurant6/17/2013 7/22/2013 8/8/2013 34 16 3 3

Alameda

County

Fast Food

Restaurant11/12/2013

12/13/2013-

1/8/20141/20/2014 31 11 5 6

Placer CountyFast Food

Restaurant9/10/2013 10/24/2013 11/19/2013 43 25 3 3

Merced

County

Fast Food

Restaurant12/12/2013 1/2/2014 1/26/2014 20 23 5 6

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each facility, although we had a couple of data collection problems at one facility. At the

Lake County Assembly facility, three of the six loggers on AC units failed because of two

batteries that died unexpectedly, and one current transducer that opened sometime after

installation. At the Placer County fast food restaurant, one of the four rooftop units was

switched off (disconnect open) when we installed our loggers, and it was later turned on,

contributing cooling which the other units then did not need to provide. HVAC data for this

site was excluded from the results.

We did not monitor all lighting circuits at each facility, in order to keep the time and

expenses of this study at a reasonable level. We instead monitored a statistically significant

sample of lighting in each of the different space types at each facility. For example, in a sit

down restaurant we monitored lighting in the kitchen and at two or more areas of the dining

room. Larger facilities with more varied types of spaces had more lighting circuits

monitored. All of our installed lighting loggers appeared to function correctly over the

monitoring period.

EMS ONLINE DATA The EMS installed in these facilities has an online site where settings can be examined, and

energy use and temperature trends can be reviewed. We accessed the online sites for the

eleven facilities to collect the following information for the post-installation period:

Lighting control schedules

Thermostat settings and schedules for HVAC equipment

Trends in the total energy use of the facility

There is only a limited amount of historic total energy use data available for each facility.

The EMS saves energy use from the day of installation, but only the total facility energy use

for each day was made available and evaluated for this study.

13


ENERGY SAVINGS ANALYSIS AND RESULTS The analysis of eleven facilities included:

Analysis of monitored lighting energy use before and after the EMS installation

Analysis of monitored HVAC energy use before and after the EMS installation, and

extrapolation to estimated annual savings based on typical weather data.

Table 4 below includes a list of the weather data and building energy use reference data we

used to annualize our monitored results to typical weather conditions, and to normalize the

results to the building type and location.

14


TABLE 4. LOCAL WEATHER DATA, ANNUAL WEATHER DATA, AND BUILDING ENERGY USE REFERENCE DATA USED TO

ANNUALIZE AND NORMALIZE MONITORING RESULTS

LOCAL WEATHER DATA DURING

MONITORING PERIOD ANNUAL

WEATHER

FILE USED

(2010

CEC

FILES)

BUILDING ENERGY USE REFERENCE DATA BY BUILDING

TYPE & LOCATION

Location, Type

Airport Airport

Call Letters

CEUS Building Type

CEUS Climate Zone

# of CEUS Buildings

Kern County Retail

Bakersfield BFL CEC CZ13 Retail, all types Average of

Central Valley & Desert

8 & 1

Alameda

County Retail

Livermore LVK Livermore

AP Retail, all types

Average of

Central Coast & Central Valley

64

& 128

Nevada

County Assembly

Grass Valley

GOO CEC CZ11 Assembly, all types Central Valley 77

Lake County Assembly

Ukiah UKI CEC CZ2 Assembly, all types North Coast 13

Stanislaus

County Assembly/ Restaurant

Modesto MOD CEC CZ12

Average of

Assembly, all types & Restaurant, all

types

Central Valley 77 & 43

Santa Clara County

Assembly/ Restaurant

San Jose SJC CEC CZ4

Average of Assembly, all types

& Restaurant, all types

Central Coast 54 & 31

South Santa Clara

County Sit Down

Restaurant

Hollister CVH CEC CZ4 Restaurant, all

types Central Coast 31

San Joaquin County

Sit Down Restaurant

Stockton SCK CEC CZ12 Restaurant, all

types Central Valley 43

Alameda County

Fast Food Restaurant

Livermore LVK CEC CZ12 Restaurant, all

types

Average of Central Coast &

Central Valley

31 &

43

Placer

County Fast Food

Restaurant

Lincoln LHM CEC CZ11 Restaurant, all

types

Average of Central Valley

& Mountain

43 &

2

Merced County

Fast Food Restaurant

Merced MCE CEC CZ12 Restaurant, all

types Central Valley 43

15


LIGHTING ANALYSIS We analyzed the current drawn by monitored lighting equipment before and after the

installation of the EMS at each of the eleven facilities. This data is presented in plots of

average daily current draw that were developed from our collected data via the following

steps:

Monitored current from all lighting circuits was added together to get a total lighting

current draw at each time step over the monitoring period

Each time step was assigned to either the pre-installation or post-installation period

The day when EMS installation took place was not included in the analysis. To make

sure we had the correct installation day, we cross-checked to make sure the

installation date we were given from OEM personnel was the same as the first day of

collected data that was stored in the online control system for each facility. (This was

only a problem in one facility. System data availability suggests that the EMS

installation at the Alameda County Fast Food Restaurant may not have occurred until

January 8, 2014, although we were told that it took place on December 13, 2013.)

Operating hours in each facility were separated into times when the facility was

“occupied” or “unoccupied”. A third category was designated in the two Sit Down

Restaurants as “staff”, or the time when only the kitchen and wait staff were in the

facility preparing for the day or cleaning up afterwards, but no customers were

present. These different operating periods were designated according to what we

found in each facility’s EMS online control system settings.

Current was averaged at each time of the day, to get average daily lighting curves

for the pre- and post-installation periods

The average daily lighting currents were summed into the following categories:

o Pre-installation Unoccupied

o Pre-installation Staff (if the facility includes this category)

o Pre-installation Occupied

o Post-installation Unoccupied

o Post-installation Staff (if the facility includes this category)

o Post-installation Occupied

Percent savings were calculated between the pre- and post-installation current sums

for the Unoccupied, Staff and Occupied categories, and then summed into an overall

percent savings in lighting use for all time categories

Annualizing Percent Savings

In order to scale the lighting monitoring results up to the entire year, we assumed

that the savings found during the monitoring period would apply over a whole year.

HVAC ANALYSIS The analysis of HVAC energy use was similar to our analysis of lighting use. However, since

HVAC use is highly dependent on outside temperature, we used our collected data to find

correlations to annualize the energy use and savings results.

16


We analyzed the current drawn by monitored HVAC equipment before and after the

installation of EMS at each of the eleven facilities. This data is presented in plots of average

daily current draw (see Appendix D) that were developed from our collected data via the

following steps:

Monitored current from all HVAC circuits was added together to get a total HVAC

current draw at each time step over the monitoring period.

Each time step was assigned to either the pre-installation or post-installation period.

The day when EMS installation took place was not included in the analysis. To make

sure we had the correct installation day, we cross-checked the installation date we

were given from OEM personnel with the first day of collected data stored in the

online control system for each facility. (This was only an issue in one facility, the

Alameda County Fast Food Restaurant, where system data was not available until

January 8, 2014, nearly a month after system installation was reported to have

taken place on December 13, 2013.).

Operating hours in each facility were separated into times when the facility was

“occupied” or “unoccupied”. A third category was designated in the two Sit Down

Restaurants as “staff”, or the time when only the kitchen and wait staff were in the

facility before and after customer hours and that use different heating and cooling

set points. These operating periods were designated according to what we found in

each facility’s EMS online control system settings.

Current was averaged at each time of the day, to get average daily HVAC curves for

the pre- and post-installation periods. The average daily HVAC currents were

summed into the following categories:

o Pre-installation Unoccupied Hours

o Pre-installation Staff Hours (if the facility includes this category)

o Pre-installation Occupied Hours

o Post-installation Unoccupied Hours

o Post-installation Staff Hours (if the facility includes this category)

o Post-installation Occupied Hours

Annualizing HVAC Percent Savings

To scale the HVAC monitoring results to a typical year, we took the following steps:

o Outdoor temperatures were determined for each hour in the monitoring

periods at each site in the above categories. We did not measure outdoor

temperatures on site, but used weather data at the airport weather station

closest to each facility. The airport weather data used for each location is

listed in Table 4. Note that the current EMS configuration does not include

monitoring of outdoor air temperatures, and nearby airport weather data

provides high reliability.

o HVAC current monitored values were averaged into outdoor temperature bins

of 2-degrees Fahrenheit. Correlations were then established between HVAC

current and 2-degree outdoor temperature bins for each category of time

(Pre-Installation Unoccupied Hours, Pre-Installation Staff Hours, Pre-

17


Installation Occupied Hours, Post-Installation Unoccupied Hours, Post-

Installation Staff Hours, and Post-Installation Occupied Hours).

Most of the monitoring was completed in winter conditions. For most sites,

little or no data was collected in higher outside temperature conditions, when

economizers are closed and cooling is by (energy-intensive) compressor only.

Since these warm conditions mostly occur in the afternoons, when the sites

remained occupied and fully conditioned, the installation of the EMS normally

impact energy use during such periods only if the EMS is used to adjust

occupied cooling setpoints.

The correlations were as follows (See example graphs below):

For each 2-degree outdoor temperature bin value within the range of

monitored outdoor temperatures, the average HVAC current value

monitored at that outdoor temperature was calculated.

For each 2-degree outdoor temperature bin value below the range of

monitored outdoor temperatures, a linear extrapolation was done to

obtain the corresponding HVAC current value. The expression for the

linear extrapolation was Current = m x Tout + B, where m is the slope

of the line and B is the y-intercept. Note that heating in all cases was

gas-fired, so electricity use for HVAC in cold conditions is for fan

cycling only.

For each 2-degree outdoor temperature bin value above the range of

monitored outdoor temperatures, an extrapolation was performed

similar to that described above, generally using data for outside air

temperatures above 65 °F (cooling mode), for the base case. Due to

limited data in some cases, some engineering judgment was

necessary. No savings were calculated for these conditions. The annual

kWh usage projected for these conditions was included in the

denominator of the % savings calculations.

o Outdoor temperatures for an entire typical year were correlated into bins of

2-degree Fahrenheit increments. Annual temperatures were pulled from TMY3

data files developed by the California Energy Commission for sixteen

California climate zones. Table 4 lists the CEC climates zones that were used

for each facility in this study. Note that the Alameda County Retail facility

used TMY3 data from the Livermore airport, instead of the CEC climate zone

data.

o HVAC current was calculated from the derived correlations for each 2-degree

bin temperature value, multiplied by the number of hours in each bin, and

then summed to get the entire year’s estimated energy use under the

operating parameters for each category. Annual savings was found by

subtracting post-installation energy use from pre-installation energy use.

An example of HVAC current and outdoor temperature correlation results is shown for the

Santa Clara County sit-down restaurant site in Figures 1A-C, below. The dots indicate the

average HVAC current values per temperature bin as calculated from monitoring data. The

solid lines represent the model correlating the data. As seen in the graph for occupied hours

(Figure 1A, below), the range of monitored outdoor temperatures for which both Pre and

Post-installation data was obtained, is 54 to 80 °F. The model follows the monitoring data

points within this outdoor temperature range. Below 54 °F, the model follows a linear

18


extrapolation of the monitoring values. Above 80 °F, the model does not extrapolate values

and instead sets the HVAC Current value to zero for both pre and post-installation cases.

Finally, the solid olive line indicates annual hours per temperature bin in the TMY3 weather

data. The model only correlates HVAC current to outdoor temperature in the range of hours

in a typical year. For instance, in the example figure below, HVAC current in the model is

set to zero below 38 °F since there are no instances of outside air temperatures below 38 °F

in this typical year dataset.

FIGURE 1A. EXAMPLE HVAC ENERGY VS OUTSIDE AIR TEMPERATURE – OCCUPIED HOURS

0

200

400

600

0

50

100

150

200

250

300

20 40 60 80 100 120

TMY3

Ho

urs

Avg

. HV

AC

Cu

rren

t (A

)

Outdoor Temperature (°F)

HVAC VS OAT_Occ - Santa Clara County(Sit Down Restaurant)

Occ Occ

Pre Occ_Model Post Occ_Model

Weather TMY3 Hours

19


FIGURE 1B. EXAMPLE HVAC ENERGY VS OUTSIDE AIR TEMPERATURE – STAFF HOURS

FIGURE 1C. EXAMPLE HVAC ENERGY VS OUTSIDE AIR TEMPERATURE – UNOCCUPIED HOURS

0

200

400

600

0

50

100

150

200

20 40 60 80 100

TMY3

Ho

urs

Avg

. HV

AC

Cu

rren

t (A

)


HVAC VS OAT_Staff - Santa Clara County(Sit Down Restaurant)

Staff StaffPre Staff_Model Post Staff_ModelWeather TMY3 Hours

0

200

400

600

0

20

40

60

20 40 60 80 100

TMY3

Ho

urs

Avg

. HV

AC

Cu

rren

t (A

)


HVAC VS OAT_Unocc - Santa Clara County

(Sit Down Restaurant)

Unocc Unocc

Pre Unocc_Model Post Unocc_Model

Weather TMY3 Hours

20


The HVAC energy data at three sites was problematic. Following is a brief discussion of each

issue and the remedy applied. See also graphs of HVAC energy vs. outside air temperature

(OAT) in Appendix C.

1. Data for the Placer County fast food restaurant shows a very large drop in HVAC

energy use after EMS installation, which indicates changes beyond what the EMS

would impact. See Figure 2 below. We excluded HVAC savings in reported results for

this site. One possible contributor to the drop includes the fact that one of the four

rooftop units was switched off (disconnect open) when we installed our loggers, and

it was later turned on, contributing cooling which the other units then did not need to

provide.

FIGURE 2. DAILY AVERAGE MONITORED HVAC USE AT PLACER COUNTY FAST FOOD RESTAURANT FACILITY, PRE &

POST EMS

2. Data for the Stanislaus County assembly/restaurant facility (a golf and country club)

shows very little HVAC current use during the post-installation period, in late

December and January. See Figure 3 below. We excluded HVAC savings in reported

results for this site as well. Weather was little changed. We suspect that the data

primarily indicates seasonality of occupancy, and low current use during infrequent

(gas) heating. That is, it appears that the club was largely unoccupied during the

January post-installation monitoring period.

0

10

20

30

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50

60

70

80

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30

40

50

60

70

80

12:0

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M

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M

Ou

tdo

or

Tem

pera

ture

, d

eg

F

Avg

HV

AC

To

tal

Before 10-24-2013 - Occ - Average of HVAC Total Before 10-24-2013 - Unocc - Average of HVAC Total

After 10-24-2013 - Occ - Average of HVAC Total After 10-24-2013 - Unocc - Average of HVAC Total

Before 10-24-2013 - Occ - Average of TOUT Before 10-24-2013 - Unocc - Average of TOUT

After 10-24-2013 - Occ - Average of TOUT After 10-24-2013 - Unocc - Average of TOUT

21


FIGURE 3. DAILY AVERAGE MONITORED HVAC USE AT STANISLAUS COUNTY ASSEMBLY/RESTAURANT FACILITY, PRE & POST EMS

3. Finally, unusual data was observed at the Kern County retail clinic site for the

occupied post-installation periods. Measured HVAC current at this site drops

effectively to zero every day at 11:00 am and remains close to zero for the rest of

the Occupied hours. See Figure 4 below. We excluded HVAC savings during occupied

hours in reported results for this site. We suspect that the occupied hours were set

incorrectly in the EMS, where the end of the period was entered as 11:00 am instead

of 11:00 pm. Oddly, the site did not report any problems in the customer survey,

even though their HVAC is shutting off at 11:00 am each day.

FIGURE 4. DAILY AVERAGE MONITORED HVAC USE AT KERN COUNTY RETAIL CLINIC FACILITY, PRE & POST EMS

HOURS

0

10

20

30

40

50

60

70

0

5

10

15

20

25

30

35

12:0

0 A

M

2:0

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M

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M

6:0

0 A

M

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0 A

M

10:0

0 A

M

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M

2:0

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M

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M

6:0

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M

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Ou

tdo

or

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pera

ture

, d

eg

F

Avg

HV

AC

To

tal





22


TABLE 6. CEUS ELECTRICITY USE PER FLOOR AREA USED TO NORMALIZE SAVINGS IN THE FACILITIES

Location Building Type

Lighting

kWh/sf

HVAC

kWh/sf

Other

kWh/sf

Total

kWh/sf

Kern County Retail 104 64 38 206

Alameda County Retail 140 48 66 253

Nevada County Assembly 34 26 40 100

Lake County Assembly 70 27 81 178

Stanislaus County Assembly / Restaurant 94 114 242 449

Santa Clara County Assembly / Restaurant 94 46 259 398

Santa Clara County Sit Down Restaurant 154 83 477 714

San Joaquin County Sit Down Restaurant 153 201 443 798

Alameda County Fast Food Restaurant 153 142 460 756

Placer County Fast Food Restaurant 155 165 363 682

Merced County Fast Food Restaurant 153 201 443 798

AVERAGE 118 101 265 485

23


PRE- AND POST-EMS INSTALLATION RESULTS The following section provides the analysis results for the sites where the EMS was installed.

Table 7 shows a summary of the annual expected lighting and HVAC savings from the

installation of the EMS, as well as the overall building energy use savings. The table gives %

savings as well as a normalized value of energy use per floor area (kWh/sf).

The EMS system produced the most savings from its control of HVAC use, with included

HVAC savings ranging from 6% to 31%. On average, facilities were projected to save 18%

of their annual HVAC electricity use.

The EMS was less likely to save electricity when controlling lighting. Five of eleven facilities

used slightly more lighting energy after the EMS was installed, although the Nevada County

facility did not actually hook their lighting up to the EMS at all. The other six facilities had

lighting energy savings ranging from about 1% to 36%. Overall, facilities saved an average

of 6% of their lighting energy use with the EMS.

24


TABLE 7. ANNUAL LIGHTING AND HVAC ELECTRICITY SAVINGS DUE TO EMS INSTALLATION, IN PERCENT

Discussion of these results and variations is provided in the following sections, separately

for lighting and HVAC energy impacts.

LIGHTING MONITORING SAVINGS RESULTS Below we present details of the lighting savings found in the eleven facilities. Note that only

a sample of lighting circuits was monitored in each facility, so the overall level of lighting

current does not reflect the entire lighting energy use in the building. However, the lighting

use trends are expected to be representative of the control provided to the building’s

lighting system before and after the EMS was installed.

LocationCalifornia


Savings

HVAC %

Savings

Kern County 13 Retail 14% 6%

Alameda

County12 Retail 0% 20%

Nevada

County11 Assembly - 25%

Lake County 2 Assembly 36% 9%

Stanislaus

County12

Assembly /

Restaurant7% -

Santa Clara

County4

Assembly /

Restaurant-4% 31%

Santa Clara

County4

Sit Down

Restaurant-6% 19%

San Joaquin

County12

Sit Down

Restaurant8% 28%

Alameda

County12

Fast Food

Restaurant-5% 18%


Restaurant17% -

Merced

County12

Fast Food

Restaurant1% 11%

AVERAGE 6% 18%

25


Table 8 summarizes the lighting energy savings during occupied, staff, and unoccupied

periods in each facility.

TABLE 8. LIGHTING ELECTRICITY SAVINGS FROM EMS INSTALLATION DURING OCCUPIED, STAFF & UNOCCUPIED PERIODS

Savings in lighting energy use was most likely to occur during staff or unoccupied hours,

with 9 of 11 facilities saving between 3% and 51% of their lighting energy while the building

was unoccupied. Both facilities with staff-only periods saved lighting energy during those

hours, 3% and 11%. In contrast, only 5 of 11 facilities saved lighting energy during

occupied hours, with savings ranging from 2% to 41%. Overall, 6 of 11 facilities saved

lighting energy, for an average savings of 6%.

For many of these small commercial sites, lighting was already fairly well-controlled, with

staff shutting off lights at the end of the day. Although average savings from all lighting

control was just 6%, large lighting energy savings were measured in some facilities. The

Placer County fast food restaurant achieved 51% savings during unoccupied hours, and

41%/32% occupied/unoccupied savings were measured at the Lake County assembly

facility.

In this sample, there was no discernible pattern of lighting savings by building type. For

example, lighting savings for two very similar sit-down restaurants were -6% and 8%. Two

Location Building Type Occupied Staff Unoccupied Total

Kern County Retail 9% 29% 14%

Alameda County Retail -2% 3% 0%

Nevada County Assembly - - -

Lake County Assembly 41% 32% 36%

Stanislaus County Assembly / Restaurant 2% 22% 7%

Santa Clara County Assembly / Restaurant -4% -5% -4%

Santa Clara County Sit Down Restaurant -6% 3% -29% -6%

San Joaquin County Sit Down Restaurant 5% 11% 15% 8%

Alameda County Fast Food Restaurant -8% 3% -5%

Placer County Fast Food Restaurant 14% 51% 17%

Merced County Fast Food Restaurant -2% 18% 1%

AVERAGE 5% 7% 14% 7%

26


very similar fast food restaurants showed lighting savings of -5% and 1%. Two similar

assembly/restaurant facilities achieved -4% and 7% lighting energy savings.

Lighting energy savings depended on how well staff controlled lighting before the EMS

installation, and whether the EMS was used to more aggressively have lights turn off

automatically using the EMS.

27


Figures 5A through 5J, on the following pages, plot the lighting current monitored in each

facility before and after the EMS installation. Each plot shows the average daily current

drawn both before and after the EMS was installed. In addition, the different periods of use

(occupied, staff, and unoccupied) are delineated by different colored lines. The horizontal

axis of each plot shows the time of day, and the vertical axis is in amps of current. Note

that vertical scales of lighting current are different in each plot.

28

PG&E’s Emerging Technologies Program ET12PGE3461 FIGURE 5A. DAILY AVERAGE MONITORED LIGHTING USE AT KERN COUNTY RETAIL

CLINIC FACILITY, PRE & POST EMS

FIGURE 5B. DAILY AVERAGE MONITORED LIGHTING USE AT ALAMEDA COUNTY RETAIL

FACILITY, PRE & POST EMS

FIGURE 5C. DAILY AVERAGE MONITORED LIGHTING USE AT NEVADA COUNTY

ASSEMBLY FACILITY, PRE & POST EMS

FIGURE 5D. DAILY AVERAGE MONITORED LIGHTING USE AT LAKE COUNTY ASSEMBLY


0

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Pre Occ Pre Unocc Post Occ Post Unocc

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29

PG&E’s Emerging Technologies Program ET12PGE3461 FIGURE 5E. DAILY AVERAGE MONITORED LIGHTING USE AT STANISLAUS COUNTY

ASSEMBLY/RESTAURANT FACILITY, PRE & POST EMS

FIGURE 5F. AVERAGE MONITORED DAILY LIGHTING USE AT SANTA CLARA COUNTY


FIGURE 5G. DAILY AVERAGE MONITORED LIGHTING USE AT SOUTH SANTA CLARA

COUNTY SIT DOWN RESTAURANT FACILITY, PRE & POST EMS

FIGURE 5H. DAILY AVERAGE MONITORED LIGHTING USE AT SAN JOAQUIN COUNTY SIT

DOWN RESTAURANT FACILITY, PRE & POST EMS

0

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30

PG&E’s Emerging Technologies Program ET12PGE3461 FIGURE 5I. DAILY AVERAGE MONITORED LIGHTING USE AT ALAMEDA COUNTY FAST

FOOD RESTAURANT FACILITY, PRE & POST EMS

FIGURE 5J. DAILY AVERAGE MONITORED LIGHTING USE AT PLACER COUNTY FAST


FIGURE 5K. DAILY AVERAGE MONITORED LIGHTING USE AT MERCED COUNTY FAST


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31


HVAC MONITORING SAVINGS RESULTS Below we present details of the HVAC savings found in the eleven facilities due to the EMS

installation. Note that we monitored a sample of the operating HVAC units in these facilities,

so the overall level of current does not reflect the entire HVAC energy use in the building.

However, the HVAC trends are expected to be a representative sample of the control

provided to the building before and after the EMS was installed, from which an overall

savings percentage is determined.

Table 9 summarizes the annualized HVAC energy savings during occupied, staff, and

unoccupied periods in each facility. Values highlighted red in this table indicate data that

was excluded from the analysis based on the anomalous information gathered, as described

above.

In all facilities, savings in HVAC energy use is higher during staff or unoccupied hours than

it is during occupied hours. Savings during unoccupied hours ranged from 13% to 73%,

with an average of 33% savings. Savings in the two facilities with staff hours saved even

more energy during this time, with an average of 60% savings.

During occupied hours, seven facilities had confirmed positive savings between 4 and 30%

of their HVAC energy use, while one facility used more energy during these hours.

In terms of overall HVAC savings, the nine facilities with confirmed HVAC savings used an

average of 18% less HVAC energy after the EMS was installed.

The ability to make broad conclusions from this study were impacted by the small number

of sites monitored (a common challenge with technology assessments), the limited range of

weather conditions monitored (with installation occurring in winter at many sites), and some

site anomalies and logger issues.

32


TABLE 9. HVAC ELECTRICITY SAVINGS FROM EMS INSTALLATION DURING OCCUPIED, STAFF & UNOCCUPIED PERIODS

Figures 6A through 6J, on the following pages, plot the HVAC current monitored in each

facility before and after the EMS installation. Each plot shows the average daily current

drawn both before and after the EMS was installed. In addition, the different periods of use

(occupied, staff, and unoccupied) are delineated by different colored lines. The horizontal

axis of each plot shows the time of day, and the vertical axis is in amps of current. Note

that vertical scales of HVAC current are different in each plot.

The average outdoor air temperatures are also included on Figures 6A through 6J. In all but

three facilities, our monitoring took place during fall or winter conditions, with average

outdoor temperatures at just 60°F or lower. The other three facilities (South Santa Clara

County, San Joaquin County, and Placer County) were monitored under warmer, summer

conditions.

Location Building Type Occupied Staff Unoccupied Total

Kern County Retail - 17% 6%

Alameda County Retail 5% 37% 20%

Nevada County Assembly -5% 55% 25%

Lake County Assembly 4% 17% 9%

Stanislaus County Assembly / Restaurant - - -

Santa Clara County Assembly / Restaurant 30% 32% 31%

Santa Clara County Sit Down Restaurant 11% 57% 33% 19%

San Joaquin County Sit Down Restaurant 17% 62% 73% 28%

Alameda County Fast Food Restaurant 17% 21% 18%

Placer County Fast Food Restaurant - - -

Merced County Fast Food Restaurant 9% 13% 11%

AVERAGE 11% 60% 33% 18%

33


TABLE 10. EXTREME OUTDOOR LOW AND HIGH TEMPERATURES DURING EACH FACILITY’S MONITORING PERIOD

Location Building TypeMonitoring

Start

EMS

Installation

Monitoring

Finish

Outdoor

Low

Outdoor

High

Kern County Retail 10/29/2013 12/20/2013 1/14/2014 28°F 84°F

Alameda

CountyRetail 11/19/2013 12/14/2013 1/20/2014 26°F 73°F

Nevada

CountyAssembly 10/29/2013 12/11/2013 1/16/2014 21°F 72°F

Lake County Assembly 10/30/2013 12/12/2013 1/16/2014 20°F 82°F

Stanislaus

County

Assembly /

Restaurant10/29/2013 12/17/2013 1/20/2014 25°F 75°F

Santa Clara

County

Assembly /

Restaurant11/19/2013 12/16/2013 1/26/2014 28°F 72°F

Santa Clara

County

Sit Down

Restaurant6/17/2013 7/31/2013 8/30/2013 46°F 100°F

San Joaquin

County

Sit Down

Restaurant6/17/2013 7/22/2013 8/8/2013 53°F 107°F

Alameda

County

Fast Food

Restaurant11/12/2013

12/13/2013-

1/8/20141/20/2014 27°F 79°F

Placer CountyFast Food

Restaurant9/10/2013 10/24/2013 11/19/2013 32°F 91°F

Merced

County

Fast Food

Restaurant12/12/2013 1/2/2014 1/26/2014 25°F 72°F

34

PG&E’s Emerging Technologies Program ET12PGE3461 FIGURE 6A. DAILY AVERAGE MONITORED HVAC USE AT KERN COUNTY RETAIL CLINIC


FIGURE 6B. DAILY AVERAGE MONITORED HVAC USE AT ALAMEDA COUNTY RETAIL


FIGURE 6C. DAILY AVERAGE MONITORED HVAC USE AT NEVADA COUNTY ASSEMBLY

RESTAURANT FACILITY, PRE & POST EMS

FIGURE 6D. DAILY AVERAGE MONITORED HVAC USE AT LAKE COUNTY ASSEMBLY


0

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35

PG&E’s Emerging Technologies Program ET12PGE3461 FIGURE 6E. DAILY AVERAGE MONITORED HVAC USE AT STANISLAUS COUNTY


FIGURE 6F. DAILY AVERAGE MONITORED HVAC USE AT SANTA CLARA COUNTY


FIGURE 6G. DAILY AVERAGE MONITORED HVAC USE AT SOUTH SANTA CLARA

COUNTY SIT DOWN RESTAURANT FACILITY, PRE & POST EMS

FIGURE 6H. DAILY AVERAGE MONITORED HVAC USE AT SAN JOAQUIN COUNTY SIT

DOWN RESTAURANT FACILITY, PRE & POST EMS

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Before 7-30-13 - Occ - Avg HVAC Total Before 7-30-13 - Staff - Avg HVAC TotalBefore 7-30-13 - Unocc - Avg HVAC Total After 7-30-13 - Occ - Avg HVAC TotalAfter 7-30-13 - Staff - Avg HVAC Total After 7-30-13 - Unocc - Avg HVAC TotalBefore 7-30-13 - Occ - Average of Tout Before 7-30-13 - Staff - Average of ToutBefore 7-30-13 - Unocc - Average of Tout After 7-30-13 - Occ - Average of Tout

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Before 7-22-13 - Occ - Average of AC Total Before 7-22-13 - Staff - Average of AC TotalBefore 7-22-13 - Unocc - Average of AC Total After 7-22-13 - Occ - Average of AC TotalAfter 7-22-13 - Staff - Average of AC Total After 7-22-13 - Unocc - Average of AC TotalBefore 7-22-13 - Occ - Average of TOUT Before 7-22-13 - Staff - Average of TOUTBefore 7-22-13 - Unocc - Average of TOUT After 7-22-13 - Occ - Average of TOUTAfter 7-22-13 - Staff - Average of TOUT After 7-22-13 - Unocc - Average of TOUT

36

PG&E’s Emerging Technologies Program ET12PGE3461 FIGURE 6I. DAILY AVERAGE MONITORED HVAC USE AT ALAMEDA COUNTY FAST FOOD


FIGURE 6J. DAILY AVERAGE MONITORED HVAC USE AT PLACER COUNTY FAST FOOD


FIGURE 6K. DAILY AVERAGE MONITORED HVAC USE AT MERCED COUNTY FAST FOOD


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37


QUALIFICATIONS OF EVALUATION FINDINGS Several factors limit the ability to make broad conclusions from this study. These include the

small number of sites monitored (a common challenge among technology assessments), the

limited range of weather conditions monitored (with installation occurring in winter at many

sites), and some site anomalies and logger issues.

In all but three facilities, the monitoring took place during fall or winter conditions, with

average outdoor temperatures at just 60°F or lower. This prevented the evaluation of

potential savings during warm conditions, which demand more energy use for cooling. The

other three facilities (South Santa Clara County, San Joaquin County, and Placer County)

were monitored under warmer, summer conditions.

In addition, the HVAC energy data at three sites was problematic. In each case, very large

changes in HVAC energy use were measured, which were concluded to be beyond what the

EMS installation alone would cause. Data for one site was impacted by a rooftop HVAC unit

being disconnected and reconnected, and likely by other factors as well. For another site, it

appeared that the site was not occupied during the post-installation period (January at a

golf and country club). For these two sites, no HVAC energy savings were reported. Finally,

data for a third site indicated that errors were made in programming the EMS, shutting off

all HVAC at 11:00 am each day. For this site, HVAC savings during occupied hours were not

reported.

Some of the survey wording regarding temperature setpoints appears to have been mis

understood by respondents, leaving some uncertainty to exact setpoints used.

Finally, the study was slightly impacted by the failure of two data loggers at one site. And

the post-installation monitoring period for one site was only 11 days due to a delay in online

availability of data.

Future studies could address the above limitations, thereby increasing the size of the study

population and range of monitored weather conditions, and hopefully minimizing the relative

impact of site anomalies and logger issues on study results.

PRE AND POST OCCUPANT BEHAVIOR Energy savings achieved through installation of the small commercial EMS depends on the

behavior of users. Incomplete customer understanding of features and functions can

adversely impact energy savings. The EMS provides the functionality that allows users to

save energy by setting optimum scheduling and set points, but it takes proper training and

follow-up to realize maximum savings. For example, two users commented that the EMS did

not shut systems off for holidays (see Appendix C). Yet the EMS does provide holiday

scheduling functionality.

This section summarizes the changes in scheduling and setpoints implemented by users

through the installation of the EMS.

We compared operating hours as reported in the pre-surveys to the operating hours actually

scheduled in the EMS. See Table 11 on the following page.

38


TABLE 11. WEEKLY OPERATING HOUR COMPARISON

Pre-Installation

Survey

Reported Hours

EMS

Scheduled Hours

Change

Occupied Hours 87.3 88.5 +1.2 hours

(+1.4%)

Staff Hours 35.8 6.7 -29.1 hours

(-81%)

Unoccupied Hours 44.9 72.8 +27.9 hours

(+62%)

Totals 168 168 0

For regular occupied hours, there is very good agreement between operating hours as

reported in the survey, and what was programmed in the EMS. However, for sites where

there are staff hours (periods when only staff are present in the facility), many of these

hours were actually programmed with more aggressive unoccupied hour settings in the

EMS. In other words, for most staff hours, the HVAC was programmed off. This means that

the schedules implemented in the EMS are reducing the amount of HVAC use during hours

when only staff is in the facility.

39


We also compared temperature setpoints used before and after EMS installation. Figure 7 on

the following page shows the average cooling and heating setpoints used in facilities pre-

and post-installation of the EMS. Pre-install setpoints were derived from the values reported

in facility manager surveys3. Post-install setpoints were confirmed by analysis of the EMS

online website for each facility.

Cooling setpoints were increased an average of 2°F during occupied periods, and increased

by less than 1°F during unoccupied periods. Heating setpoints were decreased an average

of about 1.5°F for both occupied and unoccupied periods. These setpoint changes are

drivers of energy savings at these facilities.

FIGURE 7. COOLING AND HEATING SETPOINTS DURING OCCUPIED AND UNOCCUPIED PERIODS PRE- AND POST- EMS

INSTALLATION

While the figure above presents averages for all sites, the following table shows the full

detail of setpoints for each site.

3 Some reported setpoints were considered incorrect and were removed from the average

calculation. Specifically, cooling setpoints lower than heating setpoints and vice versa.

70.872.3

62.3

80.6

69.2

74.3

61.0

81.2

45

50

55

60

65

70

75

80

85

OccupiedHeating

OccupiedCooling

UNoccupied Heating UNoccupied Cooling

Pre setpoints Post setpoints

40


TABLE 12. COMPARISON OF TEMPERATURE SETPOINTS, REPORTED PRE-INSTALL AND EMS POST-INSTALL

Finally, we also compared actual setpoints entered in the EMS with reported setpoints

provided in the post-installation survey. These results may have been affected by somewhat

confusing wording in the survey. About one-third of survey respondents correctly listed all

four setpoints as they were entered into their EMS. Another one-third of respondents

correctly listed most setpoints, and about one-third incorrectly listed most setpoints. Note

that about half of post survey respondents reported that building occupants can adjust

these setpoints.

COOLING HEATING

Occupied Hrs Unoccupied Hrs Staff Hrs Occupied Hrs Unoccupied Hrs Staff Hrs


'Before'

Report EMS D

'Before'

Report EMS D EMS

'Before'

Report EMS D

'Before'

Report EMS D EMS

Kern County Retail Clinic 72 73 1 85 85 0 0 72 70 2 68 65 3 0

Alameda

CountyRetail 74 76 2 80 80 0 0 73 72 1 55 62 -7 0

Nevada

CountyAssembly 72 74 2 50 80 30 0 68 70 -2 50 55 -5 0

Lake County Assembly 73 75 2 90 80 -10 0 70 71 -1 50 55 -5 0

Stanislaus

County

Assembly /

Restaurant72 75 3 78 80 2 0 72 72 0 78 65 13 0

Santa Clara

County

Assembly /

Restaurant72 74 2 80 78 -2 0 68 68 0 60 65 -5 0

Santa Clara

County

Sit Down

Restaurant72 75 3 82 85 3 78 70 67 3 60 55 5 65

San Joaquin

County

Sit Down

Restaurant72 75 3 82 85 3 78 70 67 3 60 55 5 65

Alameda

County

Fast Food

Restaurant72 74 2 74 80 6 0 72 68 4 72 65 7 0

Placer

County

Fast Food

Restaurant72 72 0 60 80 20 0 72 68 4 60 64 -4 0

Merced

County

Fast Food

Restaurant72 74 2 74 80 6 78 72 68 4 72 65 7 66

AVERAGE 72.3 74.3 2.0 80.6 81.2 0.9 21.3 70.8 69.2 1.6 62.3 61.0 1.3 17.8

41


SURVEY HIGHLIGHTS

PRE-INSTALLATION SURVEYS

All 15 responding sites reported that HVAC controls featured programmable thermostats

before the EMS was installed. Four sites had a single thermostat; 11 sites had multiple,

independent programmable thermostats. Just over half (8 sites) reported that tenants could

adjust or override programmed temperature settings, with 11 sites reporting that this

happens routinely including 5 sites where adjustments occur at least daily.

Regarding lighting control, 40% of sites reported that building management or the store

manager controls the lights, 60% said tenants control the lights, while one site reported

control by employees. (One site reported both management and tenant control.) Eighty

percent of reporting sites noted having photocell or timer control of exterior lighting, while

three sites (20%) reported having occupancy sensors for specific areas (exam rooms,

storage areas).

POST-INSTALLATION SURVEYS

All responding facilities reported that no changes had occurred to:

facility operating hours,

the number of employees,

the number of customers, or

to lighting and HVAC systems.

Only one site reported different light levels used through the day (using a dimmer for

special events).

Only two sites reported receiving alerts, which were reported as false alarms.

Respondents were asked to list EMS pros and cons. Their comments are shown below under

“Appendix C: Post-Installation Survey Responses.”

42


EVALUATIONS Based on our study of eleven facilities that participated in the study, the implementation of

the EMS is an effective measure for saving energy in small commercial buildings. The EMS

helped facilities save energy in the following ways:

1. During the installation and setup process, facility managers tended to adjust their

operating ‘occupied’ hours conservatively downward, especially during hours when

only staff is in the facility. This scheduling improvement was the driver of significant

but highly variable energy savings. These improvements and resultant savings

occurred despite all sites already having programmable thermostats before the EMS

was installed.

2. Facility managers reviewed and standardized HVAC setpoints during the installation

process, and instituted higher cooling setpoints and lower heating setpoints,

especially for occupied periods. In addition, they indicated that the central control

(and therefore persistence of) setpoints was a major advantage of the EMS. Both the

more conservative setpoints and their central control and persistence are additional

drivers of energy savings.

3. Facility managers implemented lighting schedules that were automatically controlled

and not dependent on daily behavior by individuals.

In addition, we also noted that the post-installation survey feedback about the EMS was

very positive, with users reporting few or no drawbacks.

Two users reported that the system did not shut down during holidays; however holiday

scheduling functionality is available for users to set-up. This highlights the importance of

thorough user training and follow-up to help ensure that all available energy-saving

functionalities are put to use by users.

The version of the EMS product studied offered a 15 minute demand trending function

through an optional firmware upgrade to the on-site touchscreen device. The data is

available via an engineering database tool and is also available via the customer facing web

application. Power monitoring, including interval data reporting, is an important feature to

help increase the energy savings achieved with a small commercial EMS, as such usage

trends clearly indicate the impact of scheduling changes, helping users to understand and

control energy use. Unfortunately this functionality was not evaluated as part of this study,

as it was not evident to the reviewer despite an extensive review of the product

documentation made available by the provider.

Overall, the EMS functioned mostly as expected. It is clear that the major differentiator of

this type of product is in the software interface and vendor support of implementation. The

hardware is fairly straightforward; the success of the system depends mainly on making it

easy for users to implement control changes via the software interface.

The following section provides background and suggestions regarding the potential to offer

efficiency program incentives, including hybrid-deemed incentives, to encourage both the

installation of small commercial EMS (and similar controls improvements) and

implementation of energy-savings functionalities enabled by such devices.

43


POTENTIAL FOR EFFICIENCY PROGRAM INCENTIVES

INTRODUCTION Small commercial EMS are one of many new building control devices and techniques

entering the market which claim to save energy. These control devices and techniques do

not inherently save energy. They enable new control functionality which can save energy.

This complexity provides challenges to developing incentives.

This section explores the suitability of using efficiency program incentives, including hybrid-

deemed incentive approaches, to encourage the adoption of control retrofits (such as small

commercial EMS) to save energy, including challenges in establishing baseline conditions,

verifying installed results, and estimating savings.

DEFINITIONS Following are key definitions which are particular to this section.

New Functionality (NF) – A New Functionality is an improvement to controls

capabilities or sequences of operations utilizing new control or signal response

logic. Controls measures such as small commercial EMS provide New

Functionalities, which can enable more efficient operation of HVAC and lighting

equipment -- yielding long-term, quantifiable energy savings. These New

Functionalities become possible when suitable Supporting Technology is installed,

such as a small commercial EMS which enables scheduling, setbacks, setpoint

enforcement and similar New Functionalities.

Supporting Technology (ST) - A controls Supporting Technology (ST) is a product

that provides additional signal response or control capability to the existing

equipment or control system. The example here is the small commercial EMS

control equipment. By design, it is used to provide a New Functionality that is not

inherently available with the existing equipment or control system.

Deemed Incentives - In their simplest form, deemed incentives are cash

payments that are given for replacing old equipment with new, energy efficient

equipment. The new equipment simply draws less power than the old equipment,

needing minimal adjustment or set up, thus directly saving energy whenever it

operates. Generalized per-unit energy and demand savings estimates are

calculated for deemed measures by making reasonable assumptions about the

typical equipment being replaced and its normal operating hours.

Deemed incentives can also be used for measures that help reduce the energy

use of existing facilities and equipment, like the installation of variable frequency

drives or window films. For these more complicated measures, deemed savings

can be dependent upon the climate zone, and the type and vintage of the

building where they are installed. Deemed incentives are largely determined

based on how much these savings are worth to the utility’s energy portfolio.

Deemed incentives provide a straightforward, low-cost approach to incentivizing

simple efficiency projects where typical savings can be reasonably developed.

44


Custom Incentives - Custom incentives are given on a case-by-case basis for

efficiency measures that are not common, or that depend heavily on the

conditions of their application. Incentives are based on the amount of energy

saved, and savings are determined by program participants based on engineering

calculations or building energy modeling. Custom incentives demand a higher

level of effort from both program participants and program implementers. This

makes them more expensive and difficult for programs to administer.

Hybrid-Deemed Incentives - In this section, “hybrid-deemed incentives” are a

hybrid of traditional deemed and custom program incentives. Hybrid-deemed

incentives are defined in this section as fundamentally deemed in nature, but add

custom aspects as needed. The added aspects may be needed in order to

adequately establish which projects are eligible (baseline conditions), to verify

installed results, or to provide reasonable, justifiable estimates of energy savings.

Regarding savings estimates, for example, a hybrid-deemed incentive may

provide a deemed incentive per unit, adjusted to key particulars of the

application. Particulars determining the assigned savings might include, for

example, climate zone, building type, base case equipment, base case settings,

or post case settings.

CUSTOM INCENTIVE MEASURES Custom incentives can be applied to some installations of small commercial EMS. Individual

projects could be enrolled in existing custom retrofit incentive programs. Once enrolled and

confirmed eligible, the process would likely be similar to the retrofit isolation analyses

completed at 11 sites for this study. The process may include a consultant to the utility first

visiting the site to confirm base case conditions and eligibility, and to install temporary

logging equipment. After project installation, the consultant would return to the site to

verify system installation and to collect data loggers. An analysis of the logged data would

include extrapolation to estimate annual savings achieved. Documentation of actual project

costs would be collected. Payment would then be made to the customer based on set rates

of dollars ($) per units of electricity and gas energy saved and peak demand reduction, if

any.

Baseline Considerations

Under current eligibility rules, the addition of controls alone qualifies as a retrofit add-on

project type. As such, the baseline is the existing system and incentives apply to actual

savings. However, code baseline applies if there was also an equipment replacement and

the existing HVAC or lighting equipment is past its corresponding DEER equipment useful

life (EUL). In that case, incentives apply to only savings beyond code minimum. More

critically, in cases with existing programmable thermostats (which includes all eleven sites

in this study), any HVAC savings is likely to be disallowed by existing programs because the

basic functionality to schedule setbacks already exists.

In addition, recent CPUC direction regarding analysis of lighting savings for incentive

purposes does not allow existing operating hours to be used for the baseline - DEER

standard hours would be taken as baseline for that building type. So savings due to excess

run hours in the pre-installation case would not be eligible for incentives.

Opportunities

The custom incentive approach provides the most accuracy in determining project-specific

verified savings. In turn, this approach pays the most incentives to where savings are

45


highest. For the small commercial EMS measure, savings vary significantly by site as

demonstrated by this study.

Challenges

Recent issues could impact custom incentives for some small commercial EMS installations.

Baseline requirements are evolving which causes confusion in the market. In addition,

current programs now have minimum project size requirements – for PG&E, eligible projects

must have savings that earn at least $2,000 in incentives to receive detailed analysis and

verification.

Generally, the custom incentive approach is the most complex, time-consuming, and costly

approach for both the utility and the customer. Customers may be discouraged from

undertaking projects and/or from applying for custom incentives due to the process and

uncertainty involved. For small commercial EMS, the costs of custom, project-specific

savings analysis are high relative to the cost of the project itself.

DEEMED INCENTIVE MEASURES Deemed incentives (rebates) could be applied to installations of small commercial EMS. With

this deemed approach, a “catalog” of rebates lists a fixed rebate value per project. A

customer submits a rebate request providing only an invoice or related documentation

confirming purchase of equipment.

For the small commercial EMS measure, a tiered deemed approach would be appropriate,

with savings credits and/or rebate payments depending on some project specifics. For

example, deemed rebates could be tiered by:

site scale (e.g. square footage, number of thermostats or lighting circuits

controlled),

site type (e.g. restaurant, assembly), and/or

climate zone.

A workpaper would need to be developed which reasonably indicates typical savings for

each sub-category. The data and conclusion from this study would provide a start to this

workpaper.

Opportunities

The deemed incentive approach provides the simplest path for both utility and customer.

The process is simple for the customer and there is little to no uncertainty in the incentive

payment to be paid and received. The cost and time required by both utility and customer is

low, so that more funding is dedicated to incentive payments rather than program

administration costs. At the program level, total savings achieved is expected to average

out individual high- and low-savings sites.

Challenges

The deemed incentive approach provides little differentiation of savings or incentives paid

by project. Incentives are paid simply based on hardware installed, without consideration of

actual pre- or post-case operating conditions, which impact achieved savings significantly as

shown in this study.

No data is collected through the deemed incentive program itself to indicate actual savings

achieved.

46


Program-level costs are incurred in developing quality workpapers supporting claimed

savings from installed projects.

Ongoing changes to baseline requirements could impact the ability to establish workpapers

supporting deemed savings estimates.

HYBRID-DEEMED INCENTIVE MEASURES Hybrid-deemed incentive measures could be effective in effecting resource acquisition and

market transformation. The hypothesis is that hybrid-deemed incentive programs for

controls projects such as small commercial EMS can be developed which are simpler, faster,

and less costly than customized incentives, while still providing reliable estimates of energy

savings in aggregate.

There are challenges to developing hybrid-deemed incentives for controls retrofits such as

small commercial EMS. We have grouped the primary issues into three categories:

1) Determining Eligibility (Baseline Conditions)

2) Estimating Savings

3) Verifying Savings (Post-case Confirmation)

The following discussion highlights the key differences of hybrid-deemed controls measures

from traditional deemed catalog measures. Specific discussion regarding installation of small

commercial EMS is provided later in this section.

Does the hardware directly save energy?

Traditional deemed measures normally involve new hardware additions or replacements

which result in energy savings. For example, installation of a more-efficient boiler saves gas

directly. Another example is an occupancy sensor which itself shuts off lights to save

energy.

With controls improvements like an EMS, new hardware alone does not directly save

energy. The new hardware must be correctly implemented to enable new, improved

controls, which in turn save energy. Specifically, when installing a small commercial EMS,

savings are achieved by using the new capabilities to reliably implement and maintain

equipment scheduling and setbacks.

Eligibility (Baseline Conditions)

With traditional deemed measures, the baseline conditions for eligibility are made by

common-sense assumptions about the pre-hardware condition, or by surveys to determine

typical marketplace or facility conditions. For example, the baseline condition for a new

boiler would be a minimally-efficient boiler available for purchase today (or the efficiency of

the old boiler, in the case of an early retirement project).

With hybrid-deemed controls measures, the baseline conditions may need to be reviewed

for eligibility. It is possible that the control’s New Functionality could have been

implemented with the pre-existing equipment, which may be considered to make the

measure ineligible. For example, existing programmable thermostats may be capable of

applying schedules and setbacks. Installation of an EMS may not be strictly needed to

implement this energy-saving strategy. (However this study demonstrates that an EMS does

47


greatly improve the likelihood that scheduling and setback strategies are consistently and

reliably implemented, compared to individual programmable thermostats.)

Conversely, in another example the existing control system may include regular thermostats

not capable of scheduling temperature setbacks, but the staff reliably turned the thermostat

up and down by hand. In this case the new control system may save labor, but may not

save any energy.

Verification (Post-case Confirmation)

With traditional deemed measures, the purchase of new hardware is implicitly assumed to

mean that the hardware was installed and produced energy savings. There is no verification

process beyond a check of purchase documentation (i.e. invoices or receipts for hardware),

and perhaps visits to a sample of sites to make sure the hardware has been installed and is

functioning.

With hybrid-deemed controls measures, the purchase and installation of new hardware does

not necessarily indicate that new controls functionality was implemented or energy savings

were achieved. Some additional verification of operating characteristics will likely be

appropriate. The type of verification needed depends on the measure.

Savings Estimates

Controls improvements currently require that custom savings estimates be made for each

installation. This custom treatment is time-consuming and costly, requiring both detailed

understanding of the particular application and (often) extensive data logging and analysis.

For specific controls measures enabled by new technologies, the hypothesis of this section is

that methods of estimating savings can be developed which are simpler, faster, and less

costly – while still providing reasonable estimates of energy savings in aggregate.

A hybrid-deemed incentive approach needs to accurately estimate the energy savings of

typical measures and typical installations, in order to provide acceptable estimates of

program-level savings. While the resulting hybrid-deemed savings methodology is not

expected to provide the same level of project-level precision provided by customized

incentive procedures, it can improve customer experience, and reduce the time and expense

of developing site-specific energy savings estimates. Savings can be estimated using an

approach which applies building modeling to a range of scenarios (e.g. building type,

vintage, climate type), based on California Database for Energy Efficiency (CA DEER)

prototypical building models. Results from modeling are then regressed to give correlations

that can be used to more easily estimate savings. This approach was demonstrated in a

previous PG&E Emerging Technologies Program study4. That study used wireless pneumatic

thermostats as an example technology enabling multiple new functionalities. The regression

correlations were based on independent variables that are not only statistically significant,

4 Hybrid Deemed Incentive Methodology for HVAC Control Retrofits, ET Project Number

ET11PGE5172, 2013

(http://www.etcc-ca.com/reports/hybrid-deemed-incentive-methodology-hvac-control-

retrofits)

48


but have engineering significance in terms of their influence on energy use. Regression

correlations like those developed in that study could be used by incentive programs to

estimate savings of proposed projects. Protocols based on these regressions were developed

which incentive programs can use to determine fixed incentives for installing controls

technologies, plus additional incentives for correctly enabling various functionalities.

49


SCREENING PROJECTS FOR ELIGIBILITY AND VERIFICATION This section presents ways in which hybrid-deemed incentive programs could screen

supporting technologies and new functionalities for proposed control measures, in order to

check their eligibility and to verify effective implementation.

SUPPORTING TECHNOLOGIES

The Supporting Technologies (ST) for controls measures are relatively straightforward to

verify because they involve the installation of new hardware whose physical presence can

be readily documented. However, confirmation of eligibility can be more challenging, since

the capabilities of existing baseline controls equipment are often not obvious. Verification of

effective implementation for many of these technologies must rely on competent set-up or

commissioning of these systems. Please see Table 12 below listing only small commercial

EMS, and (similar) programmable communicating thermostats (PCTs). Due to the

proliferation of smartphones, photos can be quite easily submitted by customers.

TABLE 13: POTENTIAL INFORMATION TO COLLECT TO DETERMINE THE ELIGIBILITY AND VERIFY EFFECTIVE OPERATION OF

SUPPORTING TECHNOLOGIES

Supporting

Technologies, ST

Eligibility / Baseline Confirmation Post-Install Verification

ST1 –

Wireless Unitary

EMS

Photos of existing thermostats.

Photos of existing time clocks or

lighting control panels for time-

run systems.

Invoice for new system hardware.

Screen shots of at least 3 screens,

including main control screen and

two trends.

Additional screen shots to show

implementation of NF measures.

Consider requiring trending

capabilities for new controls.

New control sequences are likely to

have been implemented as part of

this improvement. Remote review of

trends will ensure sequences have

been implemented properly.

ST2 –

Programmable

Communicating

Thermostats

(PCT)

Photos of the existing

thermostats.

Invoice and photos of the new

thermostats.

Vendors may have documentation of

verification/commissioning of

systems.

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NEW FUNCTIONALITIES

The New Functionalities for controls measures are more difficult to verify than the more

straightforward installation of hardware. Additional information will be needed about

control system hardware and software. Trend data from the control system can also serve

to verify correct operation and energy savings. Please see Table 13 below.

TABLE 14: POTENTIAL INFORMATION NEEDED TO DETERMINE THE ELIGIBILITY AND VERIFY EFFECTIVE OPERATION OF NEW

FUNCTIONALITIES

New

Functionalities,

NF

Eligibility / Baseline Confirmation Post-Install Verification

NF 1 – Set Point

Enforcement5

Photographs of existing

thermostats with local user

controls.

Invoice and photo of new

thermostat showing set points.

NF 2 – Setback /

Setup /

Scheduling


thermostats with local user

controls and schedules.

Invoice and photo of new EMS

screen, showing different scheduled

settings.

NF 3 – Dead

Band

Cooling/Heating


thermostats showing single

temperature setpoint (no

deadband between heating and

cooling).

Sequence of operations and screen

shot of trend (cooling & heating

energy use versus zone

temperatures) or 1 day of trend

data (cooling & heating energy use

over time).

NF 4 – Optimum

Start/Stop (OSS)


thermostats will be evidence that

this capability is not in place.

Cut sheet of controller with

indication that it has OSS capability

and screen shot of at least 1 day of

trend data (heating and cooling

energy use and zone temperatures

around the beginning and end of

occupied periods).

NF 5 – Global

Temperature

Optimization


thermostats will be evidence that

this capability is not in place.

Sequence of operations and screen

shot of at least 1 day of trend data

for at least 10 zones (zone

temperatures over time).

5 Centralized control of set points. Reset overridden set points after a certain amount of

time.

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EMS CONTROLS: FIXED INCENTIVE AND FUNCTIONALITY

INCENTIVES Instead of providing a single incentive based on estimated savings of enabled functionalities

(e.g. scheduling, setbacks, setpoint enforcement, deadband, optimum start), an incentive

program may want to split incentives into two parts:

1. A fixed incentive for installation of a supporting technology (such as a small

commercial EMS or similar).

2. Additional incentive(s) that depend on the functionalities enabled (i.e. scheduling,

setbacks, setpoint enforcement, etc.).

The fixed incentive helps defray the costs for utility customers to install new controls

technologies such as small commercial EMS. Fixed incentives can be a particularly attractive

stimulus for smaller customers with limited financial resources. Additional incentives can be

offered to customers who take the time and effort to make sure their controls are

completely and properly enabled.

We propose that the fixed incentive be tied to savings of a specific baseline functionality.

The baseline functionality can be chosen for each supporting technology. Baseline

functionalities should meet the following criteria:

Commonly or easily enabled by a new technology,

Expected to deliver savings across all building types, vintages, and climate zones,

Savings estimates are based on conservative assumptions.

For small commercial EMS specifically, fixed incentives could be tied to expected savings

due to scheduling improvement. Since this technology enables relatively few and simple

new functionalities, a dual incentive may not be needed.

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RECOMMENDATIONS This study confirmed that installing a small commercial EMS results in generally significant

but highly variable energy savings for both HVAC and lighting systems. This result is typical

of control system improvements generally, where new hardware (Supporting Technology)

enables but does not guarantee improvements to operations and controls (new

functionalities) which provide energy savings. Achieved savings depend on both the existing

controls, and on how the new technology is put to use.

We recommend that incentives be developed for small commercial EMS and similar controls

improvements. Specifically we show in this report a proposed ‘hybrid-deemed’ approach

which is fundamentally deemed in nature, but with limited additional procedures for each

application to confirm baseline conditions for purposes of eligibility and savings

determination, and for post-install verification including both technology and functional

improvements. We show that savings could be determined using an approach which applies

building modelling based on DEER prototypical models, and then applies regression

correlation to the modelling results. This method provides low-cost standardized savings

results which are dependent on significant and readily-identified site specifics such as

climate zone, building type and vintage).

We recommend that hybrid-deemed incentives be developed which apply to a range of

controls products of various types, based on the functionalities those products enable.

Related simpler products offer a part of the functionality enabled by the small commercial

EMS studied here. As opposed to integrating controls for HVAC, lighting, refrigeration as

well as power monitoring into one system, much of the energy savings might be achieved

with simpler systems focused on the greatest opportunities. Since average savings in this

study were much higher for HVAC than for lighting, HVAC-specific controls measures may

be most cost-effective in these types of sites. For example, a variety of programmable

communicating thermostats (PCT) are available. These PCT’s are typically wireless with

centralized control and feedback. One of the major differentiators for these products is in

software. Wireless thermostat products tend to focus their marketing and functionality on

specific markets, with significant overlap between residential and small commercial

markets. There is a large and growing array of manufacturers of wireless PCTs.

Finally, we see an opportunity to expand the functionality of the EMS product to include

improved power monitoring data reporting and trending. Specifically, interval (e.g. hourly)

usage data and trends could be made available to users for more than one day.

POTENTIAL NEXT STEPS

COMPARISON OF SAVINGS WITH EXISTING MODELING RESULTS

In this study we measured actual savings results for a range of building types and climate

zones within PG&E service territory. We also already have estimated saving values (per

square foot) based on DEER model results for related measures (scheduling/setback,

setpoint enforcement and others) at four building types (small and large retail, small and

large office), 3 building vintages and 9 climate zones. The measured results could be

compared with the modeling results, to provide an initial indication of the validity of the

modeling approach.

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EXPAND AND DEVELOP INCENTIVE APPROACH AND TOOLS

We recommend proceeding with some next steps in preparation for launching a pilot hybrid-

deemed incentive program to promote the adoption of controls technologies including small

commercial EMS. Next steps to pursue would include:

Develop an easily usable and robust energy estimating spreadsheet tool based on

regressed modelling results. The spreadsheet tool can be expanded upon to add

more supporting technologies and their functionalities, as these are analyzed using

modeling and regression analysis.

Model additional functionalities and building types, and make additional runs using a

wider range of building characteristics in order to expand the set of energy savings

estimates. In particular, California schools are an important market where improved

controls will be installed statewide over the next few years using Proposition 39

funding.

Research and document the costs and functionalities of related controls technologies

available today. Prepare a database of available controls products, their primary

application targets, and the functionalities they can enable. Especially with the

advent of inexpensive wireless technologies, the controls field is undergoing rapid

development. Further research is needed to determine more clearly what

technologies are available, which functionalities they can enable, and what the costs

are to purchase, install, and commission them. This information is important input

for determining program incentives.

Determine program incentive structures based on energy savings, measure costs,

including any caps on customer incentives.

CONSIDERATIONS FOR FUTURE FIELD STUDIES This study suggests that energy savings were generally significant. However the study

sample also yielded a wide variation of savings results. Such variability is expected,

especially for small commercial facilities which can vary widely in their energy use patterns

given their high diversity of behavior and building use, existing control systems, building

and system types, and climate.

That said, additional field studies could help to clarify the energy savings opportunities for

this technology set in small commercial buildings. Sponsors of future studies would benefit

from incorporating some of the lessons learned from this study, specifically:

Record complete baseline information at studied sites, to help with confirmation

results from raw energy use data. For example,

o Setpoints and schedules in existing programmable thermostats should be

checked and recorded, rather than relying solely on customer survey self-

reporting.

o Any unusual conditions (such as an HVAC switched off) should be investigated

further to understand any consequences for the study.

o General photos and documentation of baseline conditions should be recorded

to allow confirmation that no significant site changes were made.

Use clear and consistent wording in customer surveys to avoid ambiguity and

improve the usability of survey feedback.

54


Collect data through as wide a range of weather as possible.

Check and confirm any changes in building occupancy or use between the pre and

post-installation periods.

Consider installing occupancy loggers at doors to record occupant first entrance and

final exit, as appropriate to the site.

Seek to have sites leverage the refrigeration monitoring and control capabilities as

well, to demonstrate the full potential for savings.

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APPENDICES

APPENDIX A: PRE-INSTALLATION SURVEY PG&E Energy Management System (Pre-Installation Survey)

Please identify yourself and the location for which you will be answering these questions.

Your name: _______________________

Facility name: _______________________

Your role: _______________________

Address line 1: _______________________

Address line 2: _______________________

City, ST, ZIP: _______________________

G1. What are the standard facility operating hours? Be sure to specify AM or PM.

G2. Do any people come in early or stay late beyond the normal operating hours?

1. Yes 2. No – Go to G3.

If G2 = Yes

G2a. Outside of normal operating hours, when is the earliest personnel would come in?

G2b. Outside of normal operating hours, when is the latest personnel would leave?

G3. Is maintenance or cleaning done on a regular basis outside of normal operating hours?

G4. How many people work at this facility? ____

G5a. How many customers visit this facility daily on weekdays? ____

G5b. How many customers visit this facility daily on weekends? ____

The next few questions are about the lighting at your facility.

L1. Who controls the lights? Please select all that apply.

Open 24/7 Closed Open Time Close Time

Weekdays g1a1 g1a2 g1a3 g1a4

Weekends/Holidays g1b1 g1b2 g1b3 g1b4

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1. Building management

2. Individual tenants

3. Other - Specify ______________________

L2. When are lights turned on and off on weekdays and weekends? Be sure to specify AM or PM.

L3. Are there different sets of lights (interior, exterior, other) that are used at different times of day?

1. Yes 2. No

L4. Which of the following does your facility have? (Check all that apply)

Occupancy Sensors Daylight Sensors Photocells Timers Dimmers None of the above – Go to L6.

For those that were selected:

L5. For each one, please list the type of space that it controls. For instance, some customers use photocells to control exterior lighting or dimmers to control conference room lighting.

What does it control?

Occupancy Sensors

Daylight Sensors

Photocells

Timers

Dimmers

L6. In your opinion, what are some of the biggest problems, challenges, or concerns, if any, with your current lighting system operation? ________________________________________________

On 24/7 Facility Closed Turned on at Turned off at

Weekdays l2a1 l2a2 l2a3 l2a4

Weekends/Holidays l2b1 l2b2 l2b3 l2b4

57


The next few questions are about the HVAC (Heating, Ventilation and Air-conditioning) system at your facility.

H1. Which of the following describe how the temperatures at your facility are being controlled? 1. A single programmable thermostat 2. Multiple programmable thermostats 3. A single manual thermostat – Go to H5 4. Multiple manual thermostats – Go to H5 5. On-site control system 6. Control system operated off-site 7. Control system operated via the internet

If H1 < 3

H2. Are the programmable thermostat(s) programmed to automatically adjust the temperatures on different days or at different times?

1. Yes – Go to H5 2. No – Go to H5

If H1 > 4

H3. Does the same system control both the lighting and HVAC systems?

1. Yes 2. No

H4. Who originally programmed this system?

1. The original engineers who installed the system 2. The facilities manager 3. Other - Specify ______________________

H5. Who operates this system today, and makes changes if they’re needed? ______________________

H6. Can tenants adjust or override the programmed temperature settings?

1. Yes 2. No – Go to H7

H6a. What limits are there to the temperature adjustments that can be made by the tenants?

1. None – they can adjust them at will 2. Can only raise or lower by 4 degrees Fahrenheit 3. Can only raise or lower by 2 degrees Fahrenheit 4. They can’t change them at all 5. Other - Specify ______________________

58


H7. How often are temperature settings adjusted?

1. Never – Go to H9 2. Once a month – Go to H9 3. Once a week – Go to H9 4. Once a day 5. 2-3 times a day 6. More than 3 times a day

H8. How many days a week are temperatures adjusted for the following?

The space is too hot h8a1

The space is too cold h8a2

Beginning of day h8a3

End of day h8a4

Other- h8a5

-Specify h8a5s

H9. Please list the typical temperature settings when the building is OCCUPIED and when it is UNOCCUPIED for both summer and winter.

H10. In your opinion, what are some of the biggest problems, challenges, or concerns, if any, with space temperatures in your building?

1. Poor comfort 2. Hot or cold areas 3. Hard to adjust 4. Too many people can control the temperatures 5. Adjusting during unoccupied hours 6. Other – specify ____________________________________________

H11. How often is your HVAC unit serviced?

1. Monthly 2. Every three months 3. Every six months 4. Every year

Temperature when

Occupied

Temperature when

Unoccupied

Summer h9a1 h9a2

Winter h9b1 h9b2

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5. Other – specify ______________________________

H12. Who performs the servicing?

1. Outside HVAC contractor 2. In-house maintenance employee 3. Other – specify ______________________________

This last section is about other equipment in your building (besides lighting and HVAC) that uses a lot of energy, either natural gas or electricity.

O1. Please review the list of equipment below and check the ones that you feel use a lot of energy (natural gas or electricity) in your building.

For those that were selected: O2. Who controls this equipment?

On-site facility

manager

Asset/ or Property manager

Office Manager

Individual Users

o1a Gas cooking equipment o2a1 o2a2 o2a3 o2a4

o1b Electric cooking equipment o2b1 o2b2 o2b3 o2b4

o1c Appliances o2c1 o2c2 o2c3 o2c4

o1d Refrigeration o2d1 o2d2 o2d3 o2d4

o1e Ventilation o2e1 o2e2 o2e3 o2e4

o1f Gas water heating o2f1 o2f2 o2f3 o2f4

o1g Electronic office or computer equipment o2g1 o2g2 o2g3 o2g4

o1h Electric water heating o2h1 o2h2 o2h3 o2h4

o1i Fork lift battery charger o2i1 o2i2 o2i3 o2i4

o1j Space heaters o2j1 o2j2 o2j3 o2j4

o1k Other – specify 1 o1ks o2k1 o2k2 o2k3 o2k4

o1l Other – specify 2 o1ls o2l1 o2l2 o2l3 o2l4

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O3. When is this equipment turned on and off? Be sure to specify AM or PM.

1 = Always on 2 = On during biz hours

Time(s) turned on

Time(s) turned off

Gas cooking equipment o3a1 o3a2 o3a3

Electric cooking equipment o3b1 o3b2 o3b3

Appliances o3c1 o3c2 o3c3

Refrigeration o3d1 o3d2 o3d3

Ventilation o3e1 o3e2 o3e3

Gas water heating o3f1 o3f2 o3f3

Electronic office or computer equipment o3g1 o3g2 o3g3

Electric water heating o3h1 o3h2 o3h3

Fork lift battery charger o3i1 o3i2 o3i3

Space heaters o3j1 o3j2 o3j3

Other – specify 1 _______________________ o3k1 o3k2 o3k3

Other – specify 2 _______________________ o3l1 o3l2 o3l3


O4. Which of these requires warm-up, cool-down or standby time? (Check all that apply)

Warm-up required

Cool-down required

Standby required

None required

Gas cooking equipment o4a1 o4a2 o4a3 o4a4

Electric cooking equipment o4b1 o4b2 o4b3 o4b4

Appliances o4c1 o4c2 o4c3 o4c4

Refrigeration o4d1 o4d2 o4d3 o4d4

Ventilation o4e1 o4e2 o4e3 o4e4

Gas water heating o4f1 o4f2 o4f3 o4f4

Electronic office or computer equipment o4g1 o4g2 o4g3 o4g4

Electric water heating o4h1 o4h2 o4h3 o4h4

Fork lift battery charger o4i1 o4i2 o4i3 o4i4

Space heaters o4j1 o4j2 o4j3 o4j4

Other – specify 1 _______________________ o4k1 o4k2 o4k3 o4k4

Other – specify 2 _______________________ o4l1 o4l2 o4l3 o4l4

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O5. Which of these stay running when not in use? (Check all that apply)

o5a Gas cooking equipment

o5b Electric cooking equipment

o5c Appliances

o5d Refrigeration

o5e Ventilation

o5f Gas water heating

o5g Electronic office or computer equipment

o5h Electric water heating

o5i Fork lift battery charger

o5j Space heaters

o5k Other – specify 1

o5l Other – specify 2

Please provide the following information for the $50 thank-you check.

Name on the check: _______________________

c/o (if applicable): _______________________

Address line 1: _______________________

Address line 2: _______________________

City, ST, ZIP: _______________________

Best contact number (+ext): _______________________

We will contact you again in a few months for a second survey to see how things are going. For completing that survey, we will mail you another $50 thank-you check.

Last Screen:

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62


APPENDIX B: POST-INSTALLATION SURVEY

PG&E Energy Management System (Post-Installation Survey)

General Business/Facility Info

1) Have your facility operating hours changed since installing the EMS system?

YES NO

IF YES:

a. What are the new operating hours?

Open 24/7 Open Close

Weekdays AM / PM AM / PM

Weekends/Holidays AM / PM AM / PM

2) Do any employees come in early or stay late?

YES NO

IF YES:

a. Outside of normal operating hours, when is the earliest an employee would come in? __________ AM / PM

b. Outside of normal operating hours, when is the latest an employee would leave? __________ AM / PM

3) Is any cleaning or maintenance work done outside of normal operating hours?

YES NO

IF YES:

a. When is the earliest someone would come in? __________ AM / PM

b. When is the latest someone would leave? __________ AM / PM

4) Have the number of employees and/or customers in your facility changed since the EMS was installed?

YES NO

IF YES:

a. How many people work at this facility? __________

b. How many customers visit this facility on weekdays? __________

c. How many customers visit this facility on weekends? __________

New1

w2g1a1 w2g1a2 w2g1a3

w2g1b1 w2g1b2 w2g1b3

w2g2

w2g2a

w2g2b

w2g3

w2g3a

w2g4

new4

w2g3b

w2g5a

w2g5b

63


5) Who has access to the control system?

Building Management

Individual Tenants

Other – Specify: ________________________________________________________________________

________________________________________________________________________

6) How many people are able to adjust the lights, space temperatures, or other equipment?

__________

7) After installing the EMS, have you noticed any difference with your building’s energy usage and energy bills?

YES NO

Lighting Info

8) Other than the EMS installation, have any other changes been made to your lighting systems? (new or replaced fixtures, lamps with different wattages, installation of occupancy sensors, timers or photocells)

YES NO

IF YES:

a. What were these changes? _________________________________________________________________

_________________________________________________________________

9) How many different groups of lights does the EMS control in your facility?

__________

10) When are lights turned on & off by the EMS for each group of lights?

Repeat for number of groups in Q9

On Off

Group 1 AM / PM AM / PM




w2l1c

w2l1b

w2l1a

w2l1cs

new6

new7

new8

new8a

new9

new10a1 new10a2

new10e1

new10d1

new10c1

new10b1 new10b2

new10c2

new10d2

new10e2

new10h1

new10g1

new10f1 new10f2

new10g2

new10h2

64


11) Are different light levels scheduled for different purposes or times of the day?

YES NO

IF YES:

a. Please describe… _________________________________________________________________

_________________________________________________________________

12) Do any employees have the ability to override or adjust the EMS lighting settings?

YES NO

13) What are the pros and cons of EMS’s control of your lighting system?

___________________________________________________________________________

___________________________________________________________________________

HVAC Info

14) Have any changes been made to your HVAC equipment since the EMS was installed?

YES NO

15) When does the EMS adjust space temperatures?

(Time of day, day of week, frequency of changes)

___________________________________________________________________________

___________________________________________________________________________

16) What are temperature settings in summer and winter, when the building is OCCUPIED?

Temp when Occupied Temp when Unoccupied

Summer

Winter

new11

new11a

new12

new13

new14

new15

w2h8a1 w2h8a2

w2h8b1 w2h8b2

65


17) Are different temperature settings used for different purposes or different times of day?

YES NO

IF YES:

a. Please describe… _________________________________________________________________

_________________________________________________________________

18) Can the building occupants adjust these settings?

YES NO

IF YES:

a. Are there limits to the adjustments that can be made?

YES NO

19) What are the pros and cons with the EMS’s control of your space temperatures?

___________________________________________________________________________

___________________________________________________________________________

20) How often is your HVAC system serviced by an HVAC contractor?

___________________________________________________________________________

21) Does the EMS give you reminders about the need for servicing?

___________________________________________________________________________

Other Equipment

22) Besides lighting and HVAC systems, what other equipment in your building does the EMS monitor? (Cooking equipment, refrigeration, ventilation, office equipment, computers/servers, etc.)

Cooking equipment

Appliances

Refrigeration

Ventilation

Gas water heating

Electronic office or computer equipment

Electric water heating

Fork lift battery charger

Space heaters

w2h9

w2h9a

w2h6

w2h6a

new19

new20

new21

new22a new22b

new22c

new22d

new22e

new22f

new22g

new22h

new22i

new22j new22s

66


Other: __________________________________________________________________

________________________________________________________________________

23) Have you changed the way this equipment is controlled as a result of the monitoring information you’re seeing?

YES NO

IF YES

a. What have you changed? _________________________________________________________________

_________________________________________________________________

24) Have you set up a control schedule for this equipment within the EMS?

YES NO

IF YES:

a. What is the schedule? _________________________________________________________________

_________________________________________________________________

Alarms & Notifications

25) Will the EMS send notices or alarms when systems aren’t operating as expected?

YES NO

IF YES:

a. What notices will it send? _________________________________________________________________

_________________________________________________________________

b. Have you received any notices/alarms?

YES NO

IF YES:

i. What were they, and what did you do in response to them?

_________________________________________________

_________________________________________________

_________________________________________________

_________________________________________________

new23

new23a

new24

new24a

new25

new25a

new25b

new25bs

67


APPENDIX C: POST-INSTALLATION SURVEY RESPONSES

As part of the post-installation surveys, respondents were asked to list EMS pros and cons.

Their following are their comments, first for lighting and then for HVAC control:

Pros and Cons of EMS Control of your Lighting:

“There are no cons. The system in general is pretty foolproof. It takes everything

out of the hands of people, which has been a problem in the past.”

“Pro: Energy savings. Con: As of yesterday, we still had problems with it not working

properly.”

“Pro: Lights aren't left on 24/7 like they are in some stores. Can't think of a con.”

“Pro: Being able to set back during times the building is not occupied. Con: Not

being able to communicate at the beginning and after hours stuff. When you

energize the alarm, it shuts the lights off.”

“You can shut them down and turn them off in a perfect world, but that doesn't

necessarily work. If [vendor] spent more time with better installation, it would be

better for me.”

“Don't really have any negatives except the ability to schedule more events that way

I can program for a holiday without having to change my regular weekly schedule.

Just having greater control over the whole system is nice, being able to customize it

for the time of day… not having to adjust it on a regular basis for chasing the

sunset.”

“The pro is basically that we can more easily adjust the schedule. And beyond that,

there's really no downside.”

“Pro: Trimming a little bit of time instead of using the photocells when it's starting to

get a little dark and there's no benefit to having the lights on. Gaining efficiency

without loss of lighting. Con: Interior lighting is less efficient, comes on before

building is occupied. The [EMS] is still turning lights on and off on holidays.”

“Pro: Prevents our managers, employees or even customers from going and

adjusting the settings constantly to meet their individual wants. Cons: Something

wasn't set right and we had lights going off and a heater pumping heat so people

were burning up in the lobby. We couldn't get ahold of [vendor] to fix it remotely.

That was an issue initially.”

“Pro: It's enabling us to save energy, save costs. Cons: It's somewhat complex.”

Pros and Cons of EMS Control of your Space Temperatures:

“No cons, huge pros: One of the issues we had in the past before the installation of

the [EMS] was people playing with the thermostats and adjusting them up and down

and sometimes not adjusting them properly... Or guests in the front of the house in

one section was a little bit cold and would expect you to adjust the temperature even

though everyone else in the dining room was perfectly comfortable. It's really easy

now to tell the guests we don't have the ability to do that.”

“Employees don't have access. Now it's stable, as far as the temperatures go. I don't

have any cons at all.”

68


“It will be great when my employees aren't able to get on and turn it down to 50

degrees and ice up my stuff and cost me thousands of dollars.”

“Pro: Cost, can lockout staff, the display, Con: Phone app, text file, support,

software, no explanation of features at installation.”

“Idea is good.”

“Pro: Having such specific control of the auditoriums and being able to stage when

they come on/off. Much more easier to use than the individual thermostats. No

drawbacks.”

“Pro: Can adjust temperatures to match business hours. Con: Default range was not

large enough.”

69


APPENDIX D: GRAPHS OF HVAC ENERGY VS OUTSIDE AIR

TEMPERATURE

The figures on the following pages plot average measured HVAC energy use (amps) against

outside air temperature. Data is averaged into 2 °F bins. Each figure is for either the

occupied, unoccupied, or staff hours as defined in the report. Data is shown for the pre-

installation period (blue dots) and the post-installation period (orange dots). In addition,

solid lines indicate the model used to reflect the data, including any extrapolations. Note

that the HVAC energy use shown is not for all HVAC systems – at most sites a sample of

HVAC units was measured.

Each figure also includes the typical annual hours at each temperature bin (“Weather TMY3

Hours”), during the hours period. These hours are from local TMY3 data, and are presented

with the same scale on all figures, to allow comparisons.

70


FIGURE D - 1A. KERN COUNTY RETAIL HVAC ENERGY VS OUTSIDE AIR

TEMPERATURE – OCCUPIED HOURS

FIGURE D – 1B. KERN COUNTY RETAIL HVAC ENERGY VS OUTSIDE AIR

TEMPERATURE – UNOCCUPIED HOURS

FIGURE D - 2A. ALAMEDA COUNTY RETAIL HVAC ENERGY VS OUTSIDE AIR


FIGURE D – 2B. ALAMEDA COUNTY RETAIL HVAC ENERGY VS OUTSIDE AIR


71


FIGURE D – 3A. NEVADA COUNTY ASSEMBLY HVAC ENERGY VS OUTSIDE AIR


FIGURE D – 3B. NEVADA COUNTY ASSEMBLY HVAC ENERGY VS OUTSIDE AIR


FIGURE D – 4A. LAKE COUNTY ASSEMBLY HVAC ENERGY VS OUTSIDE AIR


FIGURE D – 4B. LAKE COUNTY ASSEMBLY HVAC ENERGY VS OUTSIDE AIR


72


FIGURE D – 5A. STANISLAUS COUNTY ASSEMBLY/RESTAURANT HVAC

ENERGY VS OUTSIDE AIR TEMPERATURE – OCCUPIED HOURS

FIGURE D – 5B. STANISLAUS COUNTY ASSEMBLY/RESTAURANT HVAC

ENERGY VS OUTSIDE AIR TEMPERATURE – UNOCCUPIED HOURS

FIGURE D – 6A. SANTA CLARA COUNTY ASSEMBLY/RESTAURANT HVAC


FIGURE D – 6B. SANTA CLARA COUNTY ASSEMBLY/RESTAURANT HVAC


73


FIGURE D – 7A. SANTA CLARA COUNTY SIT DOWN RESTAURANT HVAC


FIGURE D – 7B. SANTA CLARA COUNTY SIT DOWN RESTAURANT HVAC

ENERGY VS OUTSIDE AIR TEMPERATURE – STAFF HOURS

FIGURE D – 7C. SANTA CLARA COUNTY SIT DOWN RESTAURANT HVAC


74


FIGURE D – 8A. SAN JOAQUIN COUNTY SIT DOWN RESTAURANT HVAC


FIGURE D – 8B. SAN JOAQUIN COUNTY SIT DOWN RESTAURANT HVAC

ENERGY VS OUTSIDE AIR TEMPERATURE – STAFF HOURS

FIGURE D – 8C. SAN JOAQUIN COUNTY SIT DOWN RESTAURANT HVAC


75


FIGURE D – 9A. ALAMEDA COUNTY FAST FOOD RESTAURANT HVAC ENERGY

VS OUTSIDE AIR TEMPERATURE – OCCUPIED HOURS

FIGURE D – 9B. ALAMEDA COUNTY FAST FOOD RESTAURANT HVAC ENERGY

VS OUTSIDE AIR TEMPERATURE – UNOCCUPIED HOURS

FIGURE D – 10A. PLACER COUNTY FAST FOOD RESTAURANT HVAC ENERGY


FIGURE D – 10B. PLACER COUNTY FAST FOOD RESTAURANT HVAC ENERGY


76


FIGURE D – 11A. MERCED COUNTY FAST FOOD RESTAURANT HVAC ENERGY


FIGURE D – 11B. MERCED COUNTY FAST FOOD RESTAURANT HVAC ENERGY


76


APPENDIX E: ESTIMATES OF WHOLE BUILDING SAVINGS

USING CEUS BENCHMARK DATA We translated the percent of lighting and HVAC energy savings in this report into estimated

percents of total building energy savings, using benchmark data from the California

Commercial End Use Study (CEUS, accessed via the website

http://energyiq.lbl.gov/benchmark.jsp). This study of 2,790 commercial facilities collected

energy use information from numerous building types in all areas of California.

In order to determine what portion of electricity is typically used in buildings for lighting

and HVAC purposes, we collected CEUS information about the average electricity end-use

per square foot (kWh/sf, converted from kBTU/sf) for buildings of different type and

location. Table 4 (page 13) lists which types and locations were used, and how many

buildings were contained in the CEUS sample for each category. Note that this data included

all building vintages and sizes.

Table E - A below lists the resulting typical values from CEUS for Lighting, HVAC, Other, and

Total building electricity use in kWh per square foot.

TABLE E - A. CEUS ELECTRICITY USE PER FLOOR AREA USED TO NORMALIZE SAVINGS IN THE FACILITIES


Lighting

kWh/sf

HVAC

kWh/sf

Other

kWh/sf

Total

kWh/sf

Kern County Retail 104 64 38 206

Alameda County Retail 140 48 66 253

Nevada County Assembly 34 26 40 100

Lake County Assembly 70 27 81 178

Stanislaus County Assembly / Restaurant 94 114 242 449

Santa Clara County Assembly / Restaurant 94 46 259 398

Santa Clara County Sit Down Restaurant 154 83 477 714

San Joaquin County Sit Down Restaurant 153 201 443 798

Alameda County Fast Food Restaurant 153 142 460 756

Placer County Fast Food Restaurant 155 165 363 682

Merced County Fast Food Restaurant 153 201 443 798

AVERAGE 118 101 265 485

77


We multiplied the kWh/sf for lighting use by the annualized values of % savings we

estimated from our monitoring results, to get kWh/sf savings for lighting use. Similarly, we

multiplied the kWh/sf for HVAC use (sum of heating, ventilation, and cooling kWh/sf) by the

annualized values of % savings we estimated from our monitoring results, to get kWh/sf

savings for HVAC use.

Total building electricity use, as estimated using CEUS benchmarking data, went down with

the use of the EMS in all 11 facilities. Savings ranged from 1% to 17%, as the effects on

HVAC energy use outweighed the effects of lighting use. We estimated that the lighting and

HVAC savings from the eleven buildings translated into an average building savings of 6%,

or 25 kWh per square foot. Note, we did not validate these estimates using a whole building

approach.

TABLE E - B. TOTAL BUILDING ELECTRICITY SAVINGS ESTIMATES BASED ON TYPICAL CEUS DATA

LocationCalifornia


Savings

HVAC %

Savings

Building %

Savings

Building

kWh/sf

Savings

Kern County 13 Retail 14% 6% 9% 18

Alameda

County12 Retail 0% 20% 4% 9

Nevada

County11 Assembly - 25% 6% 6

Lake County 2 Assembly 36% 9% 15% 28

Stanislaus

County12

Assembly /

Restaurant7% - 1% 7

Santa Clara

County4

Assembly /

Restaurant-4% 31% 3% 10

Santa Clara

County4

Sit Down


San Joaquin

County12

Sit Down

Restaurant8% 28% 9% 68

Alameda

County12

Fast Food



Restaurant17% - 4% 26

Merced

County12

Fast Food

Restaurant1% 11% 3% 22

AVERAGE 6% 18% 5% 20

Small Commercial EMS Scaled Field Placement - … Commercial EMS Scaled Field Placement ET Project Number: ET12PGE3461 ... Alameda County Retail HVAC Energy vs Outside …

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