Pulse Energy: Dashboard with Energy Manager - Phase B Report

PG&E’s Emerging Technologies Program ET11PGE3162

Pulse Energy: Dashboard with Energy Manager - Phase B Report ET Project Number: ET11PGE3162

Project Manager: Mark Haberman

Pacific Gas and Electric Company

Prepared By: James Russell and Amber Buhl

PECI

100 SW Main Street, Suite 1600

Portland, OR 97204

Issued: March 12, 2013 Copyright, 2013, Pacific Gas and Electric Company. All rights reserved.


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 Scaled Field Placement program under internal project number ET11PGE3162. PECI conducted this technology evaluation for Pacific Gas and Electric Company with overall guidance and management from Mark Haberman. For more information on this project, contact Mark Haberman, [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.


ABBREVIATIONS AND ACRONYMS CEUS California End Use Survey

CDW Customer Data Warehouse

EMIS Energy Management Information System

O&M Operations and Maintenance

PAM Pulse Adaptive Model

RCM Resource Conservation Management

SA ID Service account identification

SEM Strategic Energy Management


FIGURES Figure 1. A sample view of the Pulse Energy Home screen ............... 11

Figure 2. A sample view of the Pulse Energy Dashboard screen ........ 12

Figure 3. A sample view of the Pulse Energy Management screen ..... 13

Figure 4. A sample view of the Pulse Energy Reporting screen ......... 13

Figure 5. Comparison of resource conservation management and the current program ................................................... 17

Figure 6. EMIS architecture using existing metering ....................... 18

Figure 7. EMIS architecture with real time data .............................. 19

Figure 8. Actual versus baseline energy use (Pulse software) ........... 32

Figure 9 . Monthly Energy Savings Report Building CT (Cumulative savings decrease) ...................................................... 36

Figure 10. Monthly Energy Savings Report Building EL (Cumulative savings increase) ....................................................... 36

Figure 11. Monthly Energy Savings Report for Energy Manager B (Cumulative savings decrease) .................................... 37

Figure 12. Monthly Energy Savings Report for Energy Manager B (Cumulative savings decrease) .................................... 38

TABLES Table 1. Target Customer Characteristics Stipulated for the

Assessment ............................................................... 14

Table 2. Buildings in Group A ....................................................... 15

Table 3. Buildings in Group B ....................................................... 16

Table 4. Costs of real time metering ............................................. 19

Table 5. Initial Data Request ....................................................... 20

Table 6. System quality control checks ......................................... 22

Table 7. Origin and attribution of energy saving opportunities .......... 25

Table 8. Three measure types ...................................................... 26

Table 9. Energy Managers' survey responses related to training ....... 29

Table 10. Baseline exceptions and exclusions ................................. 33

Table 11. Energy savings: implemented measures ......................... 34

Table 12. Energy savings: implemented measures by building size ... 34

Table 13. Energy savings claimed under other PG&E programs ........ 39


Table 14. Estimated program costs for 32 buildings ........................ 40

EQUATIONS Equation 1. Avoided energy use calculation ................................... 31


CONTENTS EXECUTIVE SUMMARY ____________________________________________________ 7

INTRODUCTION ________________________________________________________ 10

BACKGROUND _________________________________________________________ 10

Pulse Energy ........................................................................ 11

ASSESSMENT OBJECTIVES _________________________________________________ 14

PRODUCT EVALUATION __________________________________________________ 14

Participating Customer Profiles ............................................... 15

Building and Energy Profiles ............................................. 15

Energy Manager Profile .................................................... 16

TECHNICAL APPROACH __________________________________________________ 17

EMIS Technology .................................................................. 18

Existing Metering ............................................................ 18

Real Time Data Delivery ................................................... 19

Data Integration ............................................................. 19

Describing Customers’ Spaces ..................................... 20

Data Ownership and Security ....................................... 21

Software Configuration .................................................... 22

Quality Control ................................................................ 22

Training .............................................................................. 23

Software Training ............................................................ 23

Energy Management Workshop ......................................... 24

Energy Coaching .................................................................. 25

Activity 1. Identify energy saving opportunity ..................... 25

Activity 2. Define energy saving measure ........................... 26

Activity 3. Evaluate business case ..................................... 26

Activity 4. Implement ...................................................... 27

Documentation ............................................................... 27

RESULTS ______________________________________________________________ 28

Customer Acceptance ........................................................... 28

Survey Results ................................................................ 28

Software Usage ............................................................... 29

Debrief .......................................................................... 29

Energy Savings .................................................................... 31


Pulse Adaptive Model ....................................................... 31

Baseline & Reporting Periods ............................................ 31

Non-Routine Adjustments ................................................. 32

Energy Savings ............................................................... 33

Energy Manager A ...................................................... 35

Energy Manager B ...................................................... 37

Savings Claimed Outside of Program ................................. 38

Costs Estimates ................................................................... 39

EVALUATIONS _________________________________________________________ 40

Overall Program Effectiveness ................................................ 40

Market Barriers .................................................................... 41

Lack of information .......................................................... 41

Split incentives ............................................................... 42

RECOMMENDATIONS ____________________________________________________ 42

APPENDIX A – CUSTOMER INFORMATION REQUEST _____________________________ 44

APPENDIX B - ENERGY MANAGER TRAINING __________________________________ 46

APPENDIX C - ENERGY MANAGER SURVEY ___________________________________ 51

APPENDIX D – CHANGE TRACKING _________________________________________ 57

APPENDIX E – OPPORTUNITIES AND MEASURES _________________________________ 59

APPENDIX F – EMIS FUNCTIONAL REQUIREMENTS ______________________________ 66

APPENDIX G –SAVINGS CLAIMED OUTSIDE OF PROGRAM _______________________ 69


EXECUTIVE SUMMARY The growing availability of detailed energy information for California’s utility customers makes possible new programmatic approaches for delivering energy efficiency and demand management services. A 2011 technology assessment that provided a grocery customer with an Energy Management and Information System (EMIS) to manage energy use concluded that additional technical support was needed for the customer to convert the energy information to energy-saving actions. This scaled field placement incorporates the Pulse Energy EMIS and technical support in an energy management program to deliver energy efficiency and demand management services to small and medium buildings.

PROJECT GOAL This project set out to evaluate the effectiveness of an energy management program that combines an EMIS with technical support, in the form of an Energy Coach, to drive energy savings for small and medium business customers in PG&E’s service territory. To do so, we deployed a test program and estimated the energy savings and costs ten months after customers were recruited.

PROJECT DESCRIPTION This scaled field placement provided a customer-designated Energy Manager with an EMIS and a remote Energy Coach. The Energy Coach’s role was to support the Energy Manager’s goals for reducing energy use through a mix of retrofit, operational and behavioral measures. Pulse Energy’s EMIS provided a continuous stream of energy use information through a website with a variety of customizable displays and analysis tools. The EMIS supported collaboration between the Energy Manager and Energy Coach, aided the identification and quantification of energy savings opportunities, and measured the impact of energy saving measures.

Two customers’ Energy Managers participated in the project. In their regular duties, together they were responsible for building engineering activities in a total of 78 buildings. They enrolled 32 buildings in this project. The buildings ranged in size from roughly 18,000 ft2 to 250,000 ft2; 16 were under the size limit of 100,000 ft2 used to define “medium-sized” buildings in this project. Two Energy Coaches, engineers from PECI, were assigned to assist the Energy Managers.

The Pulse Energy EMIS was integrated with PG&E’s electric and gas meter data for each Energy Manager. Following integration, Pulse Energy provided training for the Energy Managers on use of the EMIS. Energy Coaching then began with training on energy management and several walk-through building audits. Over the next six months, the Energy Managers and Energy Coaches worked together, using the EMIS, to identify and implement energy saving projects. This final report summarizes the process and results of this scaled field placement based on the energy savings measured using the EMIS, feedback collected from the Energy Managers, and observations of PECI’s Energy Coaches and project manager.

PROJECT FINDINGS/RESULTS There are five principal findings from the project:

1. Customers valued the program and showed a willingness to invest in energy management: The Energy Managers responded positively to the Pulse EMIS and


Energy Coaching. They reported that the program led them to make new investments in the energy efficiency of their facilities and that they expected to realize significant energy savings and improved asset values. Both Energy Managers indicated that absent the continuation of the program they were very likely to purchase a commercial EMIS, though probably only for the large buildings in their portfolios.

2. Substantial energy savings were achieved in a few buildings, but overall savings were modest and difficult to isolate from changes in occupancy: Based on the EMIS’s whole building estimates, energy savings were as high as 11% in one building but negative in some buildings where occupancy increased. All considered, total portfolio savings are estimated to have reached 2.3% after 10 months. Both Energy Managers reported that widespread increases in building occupancy during the second half of the program had probably masked energy savings. The project team intended to adjust energy use for this factor, however accurate occupancy records were difficult to obtain. Unless a future program targets buildings with stable occupancy, accounting for occupancy changes will be necessary before deploying a full-scale program that measures savings at the whole building level.

3. The time constraints of the target customers were only partly addressed by the EMIS and technical support: Both Energy Managers were leaders in the facilities and engineering departments of their companies. With their responsibilities came a lack of time to dedicate to the program. Both Energy Managers and Energy Coaches described their working relationship as positive and beneficial, yet they often struggled to find the time to review the Energy Coaches’ analyses or to examine the information presented by the EMIS. Over the course of eight months, on average the Energy Managers used the EMIS about once per week and the Energy Coaches used the EMIS roughly every other day. So while the Energy Coaches sometimes sought rapid progress, the Energy Managers were comfortable with a more deliberate pace, fitting the project in amongst their other responsibilities.

4. Data integration in the leased commercial buildings was complicated by changes in ownership: During EMIS integration, it was found that parts of four buildings’ energy data were held by other parties. In one of the four, some historical data was held by a previous owner, and tenants controlled some data in the other three buildings. In the latter situation, the Energy Manager worked to obtain tenants’ agreement to access the energy data, but doing so was time consuming. The Energy Manager ultimately concluded that it wasn’t worthwhile, because those tenants were responsible for their own energy bills.

5. Customers prefer real time data: The Energy Managers reported a very clear preference for “real time” data. The default in this scaled field placement was to receive data through PG&E’s existing metering infrastructure, with one to five days delay. One Energy Manager installed new meters on two large buildings early in the project to obtain data with only a 15 minute delay. The other Energy Manager stated his intention to do the same at the end of this project. While real time data offers clear opportunities, it must be paired with active energy management to achieve most benefits. It seems likely that these busy Energy Managers would have to assign responsibility to their in-building operators, whose capacity for active energy management is unknown. Thus, in spite of its appeal, the benefits of real time data will not be realized without ensuring active participation by staff with adequate time to devote to the activity.


PROJECT RECOMMENDATIONS The program approach tested in this scaled field placement did not prove cost effective in the first year, but the findings it generated provide guidance for the design of programs to reach small and medium customers and programs incorporating EMIS tools.

1. Focus energy management programs on owner-occupied buildings: Some of the challenges leading to difficulties in data integration and low energy saving results can be traced to problems of split incentives that are common in leased space. Owner-occupied buildings have been the target of successful resource management programs and this project has shown that there is good reason for that.

2. Establish an energy champion on the inside: The Energy Coaches were the most frequent users of the EMIS and spent the most time on the program, but they were outside of the customer organization and thus could only make suggestions, not changes. The Energy Managers were enthusiastic and experienced supporters of energy efficiency, but they had little time to spare and were often one step removed from day to day building operations. A person who is routinely on the property, has a hand in operations and a line to the building tenants, needs to have a strong role in energy management.

3. Strengthen commitments to energy savings goals: Though energy savings goals were set early in the program, they were referred back to infrequently and there were no rewards for meeting the goals or penalties for falling short. Given the many competing commitments of project stakeholders, a more public commitment to goals, possibly accompanied by financial incentives or penalties, is needed to motivate timely progress.

4. Create a protocol for EMIS-aided energy savings estimates: Energy savings estimates were confounded by changes in tenant occupancy and equipment. Both Energy Managers and Energy Coaches saw great potential in the ability to quantify savings using the EMIS, but without a method for reconciling tenant changes and energy savings, a clear result was not obtained. Working with owner-occupied buildings would help, but there may still be occupancy and equipment changes to document and reconcile with energy saving. A protocol for EMIS-aided energy savings estimates that offers clear guidance for addressing non-routine adjustments would clear a significant obstacle to the use of EMIS for estimating savings from an energy management program.

This project set out to determine whether providing facilities managers who oversee small and medium buildings with an EMIS and technical support would produce cost-effective energy savings. The results are inconclusive as to the cost-effectiveness of this scaled field placement. Yet the customer-appeal of the EMIS, its ability to foster collaboration and the promise of streamlined energy savings calculations are strong arguments for revisiting this energy management approach. To this end, this project has provided valuable insights toward successful implementation of future energy management programs and other approaches that leverage emerging EMIS technologies.

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INTRODUCTION Many of California’s small and medium building owners and managers lack detailed information about their building’s energy use. Due to recent meter upgrades, PG&E now possesses detailed, 15-minute electric and daily gas use data for a majority of commercial customers. This study tests the hypothesis that by providing that energy information to the building managers along with some technical support, the utility can stimulate energy saving projects in those small and medium buildings.

In aggregate, small and medium commercial buildings consume a large amount of energy. PG&E defines small and medium business customers as accounts with less than 200 kW demand (500,000 kWh/yr if demand is not available) for at least 9 billing periods over the past 12 months. Noting that the average commercial sector electric energy intensity in PG&E territory is 13 kWh/ft2, this means most small and medium business customers occupy buildings less than 50,000 ft2 in size.1 Such buildings account for roughly 12% of California’s commercial building floor space.2 The California End Use Survey (CEUS) estimated statewide commercial floor space at 4.9 billion ft2 and average energy intensity at 13.6 kWh/ft2 and 26.0 kBtu/ft2, putting the total annual energy demand for small and medium buildings at nearly 8,000 GWh and 150 million therms per year.3

Despite their sizeable energy use, the number of customers and their diversity has made this group hard to reach with energy efficiency programs. Programs that target large commercial buildings can invest time in detailed audits and analysis, because each building’s energy saving potential is large enough to offset the cost. In contrast, small and medium customers may need the same quality of information to make an investment decision, but each site’s saving potential is too small to justify the cost of obtaining that information. A 2001 survey of hard to reach customers identified the greatest barrier to investment in energy efficiency to be uncertainty about the bill savings they would achieve.4

BACKGROUND Greater access to energy information may support customers’ pursuit of improved energy efficiency. In 2011, PG&E supported an assessment that provided a grocery customer with

1 Itron (2006). California Commercial End-Use Survey Results. Prepared for the California Energy Commission. http://capabilities.itron.com/CeusWeb/Default.aspx. 2 EIA (2006), 2003 Commercial Building Energy Consumption Survey, U.S. Energy Information Administration, http://www.eia.gov/consumption/commercial/data/2003/. 3 Itron (2006). California Commercial End-Use Survey Results. Prepared for the California Energy Commission. http://capabilities.itron.com/CeusWeb/Default.aspx. 4 Quantum Consulting Inc. (2001), “Statewide Nonresidential Customer Hard-to-Reach Study; Final Report,” http://www.calmac.org/publications/Nonres%20HTR%20Report.pdf.

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an Energy Management Information System (EMIS). The system presented the customer with graphical display of energy consumption for the whole building and for major energy using systems – lighting, HVAC and refrigeration. That assessment concluded that the EMIS provided some benefit, but that the customer required additional assistance beyond the EMIS to move projects forward. Moreover, the sub-building level metering in that project appeared cost-prohibitive for most small and medium customers.5

The current scaled field placement differs from the 2011 assessment in three important ways. First, to address the specific barriers identified in the 2011 assessment, the approach that was tested here used only whole building level energy data, but combined it with additional technical support for the customer. Second, this project engaged customers for nearly a full year, providing a longer period to implement projects and quantify their benefits. Finally, a new EMIS software package, Pulse Energy, was used in this project.

PULSE ENERGY Pulse Energy offers an online EMIS known as Pulse Energy Manager using a software as a service model. Customer energy and resource usage data can be supplied to the Pulse Energy Manager software from a variety of sources, including existing utility meters, custom metering, or some building automation systems. The software then presents that data to the user in a variety of formats, several of which are described below.

1. The Home screen

This is where a user lands when opening the software in a browser. Figures on the home screen show the combined energy consumption of the user’s portfolio and a ranking of how the assets in that portfolio compare to each other in terms of energy performance.

5 Russell, J., S. Salanti, and J. Mitchell (2011), “Assessment of an Energy Information System for the Grocery Sector,” PG&E’s Emerging Technologies Program.

FIGURE 1. A SAMPLE VIEW OF THE PULSE ENERGY HOME SCREEN

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2. The Dashboard screen

This is a limited view of the building energy information that can be made available to the public. It can be customized using images and messages that are relevant to the intended audience.

FIGURE 2. A SAMPLE VIEW OF THE PULSE ENERGY DASHBOARD SCREEN

3. The Management screen

This is where a user can create and view load profiles on whatever timescale is preferred. One of the unique features of the Pulse Energy Manager software is the ability to create a model of the building’s performance, which can then be compared to the actual performance, as shown in the figure below.

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FIGURE 3. A SAMPLE VIEW OF THE PULSE ENERGY MANAGEMENT SCREEN

4. The Reporting screen

Here, the user can create and manage a variety of reports, ranging from scatterplots of temperature versus energy consumption to the type of cumulative savings report that is shown below. These can be automatically generated and sent to specific users periodically.

FIGURE 4. A SAMPLE VIEW OF THE PULSE ENERGY REPORTING SCREEN

Baseline

Actual

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This is meant to provide an introduction, not a comprehensive view of the Pulse Energy Manager software. Additional details on feature of the software that were used in this project, such as the energy savings estimation tools, are described later in the report.

ASSESSMENT OBJECTIVES The overarching objective for this assessment was to determine whether a program that provided an EMIS and technical support to existing facility managers would be an effective means of achieving energy savings for PG&E’s small and medium business customers. To respond to that overarching objective, this project had several subordinate objectives:

1. Deploy a test program leveraging PG&E’s whole building interval meter data

2. Estimate the energy savings and the costs of the test program

3. Identify customers’ barriers to energy efficiency and ways the program can reduce those barriers.

PRODUCT EVALUATION This scaled field placement was performed with two customers who fit a customer profile created at the outset of the project. That profile included both technical and organizational requirements. The technical requirements were driven by the need to integrate and access the EMIS. The organizational requirements flowed from the need for strong participation from the customer and also from the need to have a stable baseline against which to measure energy savings. Together these technical and organizational requirements defined the target customer profile that is presented in Table 1.

TABLE 1. TARGET CUSTOMER CHARACTERISTICS STIPULATED FOR THE ASSESSMENT

Technical 1. Meters reporting energy use for hourly or sub-hourly intervals installed on each building 2. An internet-connected computer

Organizational 1. Presence of a facility manager or energy manager, who can dedicate time and effort to the

identification and implementation of energy efficiency measures 2. Responsible for O&M in a portfolio that includes three or more buildings, each with a gross square

foot area under 100,000 ft2 or less than 200 kW demand for 9 of the past 12 months 3. Commitment from a manager who is able to authorize expenditures for O&M activities 4. No major changes to building operations or occupancy in the past year 5. No major occupancy or ownership changes planned for the next year

Preferred 1. Willing to engage building occupants

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PARTICIPATING CUSTOMER PROFILES The two PG&E customers who participated in this scaled field placement enrolled a total of 32 buildings. The Energy Managers are designated A and B, based on the order they enrolled in the project. Energy Manager A was responsible for six participating buildings, and Energy Manager B was responsible for 26 participating buildings. Both Energy Managers were also responsible for additional properties not enrolled in this project.

BUILDING AND ENERGY PROFILES The six buildings managed by Energy Manager A were located across three properties, including a single building, a two-building complex and a three-building complex. At the three-building complex, the buildings shared some meters, so the entire property was often treated as if it were one building. For reasons that are discussed later in the report, we were unable to obtain complete data for the two-building complex. Table 2 presents data for all six buildings in one column, which contains some estimates to fill in the gaps, and separately in the second column for the four buildings where we obtained complete data.

TABLE 2. BUILDINGS IN GROUP A

Total buildings managed by Energy Manager Approx. 48 Buildings managed in California Approx. 30 Estimated area of buildings in California 2,700,000 ft2 Estimated annual energy use of buildings in California 44.7 million kWh

490,000 therm Profile of Buildings Included in this Assessment All Buildings Enrolled Buildings with Complete Data Buildings enrolled 6 (3 properties) 4 (2 properties) Total area of buildings 330,000 ft2 163,000 ft2 Average area 56,000 ft2 40,750 ft2 Min area 18,000 ft2 a 18,000 ft2 a Max area 86,000 ft2 86,000 ft2 Total annual use 6.1 million kWh

62,000 thermb 2.5 million kWh 27,000 therm

Total peak demand 1,200 kWb,c 640 kW Average annual use 1.0 million kWh

10,000 therm 620,000 kWh 6,700 therm

Min annual use d 170,000 kWh 740 therm

170,000 kWh 740 therm

Max annual use d 1.8 million kWh 23,000 therm

1.6 million kWh 23,000 therm

Average peak demand 210 kW 160 kW Min peak demand 50 kW 50 kW Max peak demand 400 kW 400 kW

a The smallest building was one of three buildings grouped in a single property. The total property area is 77,000 ft2, and we estimate the area of the smallest building at 18,000 ft2. b Complete data for one property (two buildings) was never obtained, due to tenant control of the accounts. Here, the gap has been filled using average office consumption in climate zone 4 from CEUS (2006). c This is not a coincident peak, but rather the sum of the independent peaks of three properties. d Gas and electric min/max determined independently

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The 26 buildings enrolled by Energy Manager B were all located in a single large office park. More than half of the buildings included in Group B exceeded the 100,000 ft2 criteria for this project. The larger buildings were allowed at the request of the Energy Manager and also to allow us to contrast the experience in the larger buildings with that of the smaller buildings. Table 3 presents summary statistics for all buildings and for buildings under 100,000 ft2.

TABLE 3. BUILDINGS IN GROUP B

Total buildings managed 30 Buildings managed in California 30 Estimated area of buildings in California 4,400,000 ft2 Estimated annual energy use of buildings in California 49 million kWh / year

720,000 therm / year Profile of Buildings Included in this Assessment All Buildings Buildings under 100,000 ft2 Buildings enrolled 26 10 Total area of buildings 3,600,000 ft2 530,000 ft2 Average area 140,000 ft2 53,000 ft2 Min area 47,000 ft2 47,000 ft2 Max area 249,000 ft2 95,000 ft2 Total annual use 40 million kWh

440,000 therma 7.6 million kWh 190,000 thermb

Total peak demand 11,000 kW 2,600 kW Average annual use 1.5 million kWh

20,000 therm 760,000 kWh 21,000 therm

Min annual usec 500,000 kWh 4,300 therm

500,000 kWh 4,300 therm

Max annual usec 3.5 million kWh 37,000 therm

1.6 million kWh 27,000 therm

Average peak demand 423 kW 257 kW Min peak demand 190 kW 190 kW Max peak demand 928 kW 410 kW

a Four buildings are excluded due to incomplete gas use data b One building is excluded due to incomplete gas use data c Gas and electric min/max determined independently

ENERGY MANAGER PROFILE One of the first steps in the project, taken in the kickoff meeting, was to identify the customer Energy Manager. The two designated customer Energy Managers had similar characteristics. They were both managers of building engineering departments, with oversight over multiple buildings and over multiple building operators working in those buildings. Each had strong experience implementing energy efficiency projects and some familiarity with EMIS. Both managed sizeable O&M budgets, which they indicated they could apply toward measures with a quick payback.

Reliable data on the characteristics of facility or energy managers in the broader market of medium buildings is not available. However, PECI’s work in California with grocery, large office buildings, hospitality, and institutional customers has often been conducted with facility or energy managers with a similar scope of responsibility and authority as the two engaged in this project. We believe that the Energy Managers in this project are among the

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most experienced and proactive of this group, as evidenced by their track records of successful energy efficiency projects and also by their willingness to participate in this project.

The most obvious limitation of the Energy Managers was time. Both Energy Managers expressed a willingness to dedicate time to this project and declined to set limits on their time commitment to the project at the outset. However, as the project progressed, the Energy Managers struggled to make time for monthly check-ins and follow-up on action items. This is not meant as a criticism of the Energy Managers, but rather a reflection of their day-to-day reality, where critical maintenance issues, property transfers, budgeting, staffing and the myriad other responsibilities they hold may prevent them from engaging in active energy management of a subset of the buildings under their watch.

TECHNICAL APPROACH The program tested in this scaled field placement was modeled loosely on existing resource conservation management (RCM) and strategic energy management (SEM) programs. The State of Oregon’s RCM Guidebook defines an implementation plan to enlist management support, collect and analysis utility data, gain support of stakeholders, conduct audits, train staff and set goals.6 The ISO 50001 standard presents a plan, do, check, and act approach to SEM.7 The program was deployed to the Energy Managers as a combination of EMIS technology, training and ongoing Energy Coaching. Figure 5 below shows, at a high level, how the elements of the test program compare to those of an RCM program.

FIGURE 5. COMPARISON OF RESOURCE CONSERVATION MANAGEMENT AND THE CURRENT PROGRAM

6 Oregon Department of Energy (1998), “Resource Conservation Management Guidebook,” http://www.oregon.gov/energy/cons/pages/rcm/rcmguide.aspx. 7 ISO50001 (2011), “Energy management systems – Requirements with guidance for use.”

Resource Conservation Management Pulse Energy Management

Large Building Portfolio

New Resource Manager

Basic Tracking

Tool

Extensive Training Ongoing Energy

Coaching

Initial Training

Implement Resource Saving Projects

Small & Medium Building Portfolio

Existing Facility or

Energy Manager

Advanced EMIS Tool

Implement Energy Saving Projects

Energy Savings Resource Savings

Input Activities

Output

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One notable addition to this program, not present in the RCM or SEM frameworks, was the use of a consulting Energy Coach to train and guide the Energy Manager. The EMIS technology and the Energy Coaching introduced in this program are described in detail in the following sections.

EMIS TECHNOLOGY Two EMIS architectures were included in this scaled field placement. In the first (Figure 6), the Pulse software was fed data from PG&E’s existing metering infrastructure. In the second (Figure 7), the customer installed data logging and communications hardware to send data directly to Pulse.

EXISTING METERING

Obtaining data through the existing metering infrastructure was the default approach for all enrolled buildings. Most enrolled buildings had SmartMeter gas meters and SmartMeter or MV90 electric meters. These meters record daily gas use and 15-minute electricity use. The data is then transmitted to PG&E’s Meter Data Management System (MDMS), and on to PG&E’s Customer Data Warehouse (CDW). CDW stores the customer data, and custom scripts were created by PG&E’s IT group to extract the customers’ data from CDW and transmit it by secure file transfer to Pulse’s cloud-based servers. Once the automated processing is completed by Pulse, the data is accessible to any user with access to the password-protected account via Pulse’s online software.

FIGURE 6. EMIS ARCHITECTURE USING EXISTING METERING

MDMS – Meter data management system CDW – Customer data warehouse

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REAL TIME DATA DELIVERY

Both customers exhibited enthusiasm for viewing near real time information in the Pulse software. As this was not possible through the existing metering architecture, Energy Manager B elected to upgrade two large (over 100,000 ft2) buildings’ existing electric meters with pulse outputs (a service PG&E provides for a fee), and install a data manager and cellular modem at each building to collect the data and transmit it directly to Pulse. With this real time data delivery, electricity use data for the two buildings was available approximately 30 minutes after usage occurred. The costs of this real time metering are shown in the table below.

TABLE 4. COSTS OF REAL TIME METERING

Task Cost (incl. labor and materials)

Add pulse output to meter $900/building Install data manager and cellular modem $3,900/building Cellular service contract $400/building/year

DATA INTEGRATION Setup of the Pulse software entailed definition of spaces and points. Spaces correspond to buildings or properties. Points are the time series data presented by the software. In this project, points were: 1) meter readings from PG&E’s gas and electric meters, 2) interval data from real-time pulse output relays, and 3) temperature data from a purchased weather data service (supplied by Pulse Energy). Each point required historical data to establish a

FIGURE 7. EMIS ARCHITECTURE WITH REAL TIME DATA

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baseline in the software and also an interface by which the time series could be updated with the most recent data on an ongoing basis.

Both the customer and PG&E’s IT staff played important roles in the installation. The customer described the spaces that would be included in the assessment and identified the corresponding PG&E Service ID (SA ID) numbers. PG&E’s IT staff then used those SA ID numbers to identify the appropriate meter data.

DESCRIBING CUSTOMERS’ SPACES

We held the kickoff meetings for the customers on March 22, 2012 and April 11, 2012. Attendees at those kickoff meetings were the customer contact person, the PG&E project manager and customer account executive, the Pulse Energy project team, and the PECI project team. The agenda for the kickoff meeting is shown in Box 1.

At each kickoff meeting, we requested the information required to setup the Pulse Software. We also requested information that the PECI Energy Coaches needed to begin to understand the buildings’ performance. The complete set of information requested is shown in Appendix A. Table 5 below shows only the subset of information requested that was needed to setup the software. Items assigned a software use of “S” or “P” in the table were required to define spaces and points. Items designated with a “B” were required for establishing baselines, against which energy savings were measured. The process of gathering information needed for the baselines continued into the implementation phase of the project.

TABLE 5. INITIAL DATA REQUEST

Basic Information Software Use Space, Point, Baseline

1 Building Name or ID S 2 Building Address S 3 Building City S,B 4 Building Zip Code S 5 Building Type S 6 Year Constructed S 7 Total Square Footage S 9 Electric Meter PG&E Account # P 10 Gas Meter PG&E Account # P Uses and Schedules 17 Date(s) of occupancy changes in the past year (if any) B 18 Does the building operate on Federal Holidays? B 19 Any additional holidays besides Federal Holidays? B Energy Efficiency Project History 5 Have any energy efficiency projects been completed in the past 5 years? B 6 If so, please note the projects and the dates they were completed. B

Box 1. Kickoff meeting agenda

1. Introductions 2. Program overview 3. Demo of Pulse Energy software 4. Designate the Energy Manager 5. Schedule training

a. Software b. Energy mgmt. workshop

6. Discuss building characteristics

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DATA OWNERSHIP AND SECURITY

In early April, the Pulse Energy connectivity team met with PG&E IT staff to design the Pulse interface with PG&E’s CDW. Two important themes emerged from that meeting: 1. The non-trivial challenge of linking a particular customer and building to meter data, and 2. Security and reliability of data transfers.

Building ownership and customer accounts change over time, and tracking the energy data for metered points can be difficult. For example, consider a building that was acquired by the customer last year, the customer then switched to a time-of-use rate schedule, and this year the customer leased half of the building to another company that took over responsibility for a portion of the utilities. When the building was acquired, the customer ID associated with all points connected to the building changed. When the rate changed, the SA ID associated with the points changed. And when a part of the building was leased, the customer IDs associated with some of the points changed again. This may seem extreme, but all of these changes were seen during this project and may occur frequently in leased commercial office buildings.

The constant identifier of each metered point that was identified by PG&E IT staff was the service point ID. Throughout all the changes described above, the service point ID would remain the same. Thus, for each SA ID presented by the customer, the PG&E IT staff identified the corresponding service point IDs so that the metered point could be tracked to obtain the historical and ongoing data. This solved the problem of identifying the correct data, but not that of ownership of the data. In some cases, tracking a service point through PG&E’s CDW sometimes revealed another party with ownership of some of the building’s energy data.

The first data extracted from the CDW was the two years of historical data used to establish a baseline. In a few cases, ownership of the data associated with service points had changed over time, either because the entire building had changed ownership or because tenants and their leasing agreements – specifically, which party held responsibility for utilities – had changed. If the entire building had changed hands, then presumably operations had changed significantly as well, and there was little purpose to pursuing the historical energy data of the previous owner. Tenant control of accounts was a more difficult challenge, which occurred not only in the historical data but also in the ongoing data feed.

The two customers enrolled in this project own multiple buildings. Their buildings are almost wholly tenant-occupied. In 29 of the 32 participating buildings, the customer Energy Managers’ companies held all the PG&E accounts for service points at the building. In such cases, the Energy Manager’s company authorized use of the energy data for this project. In the remaining three buildings, the tenants held PG&E accounts for some of the service points at the building, and their permission was needed to access the energy data.

Where necessary, the Energy Managers contacted tenants to obtain authorization to access energy data for their accounts. Most tenants granted that authorization, but it often required multiple requests. And when one large tenant declined to participate, the meter data provided an incomplete picture of the building’s energy performance. The Energy Manager tasked with most of these requests observed that it was probably not a good use of time, because the tenant’s control of the PG&E account was paired with tenant control and responsibility for energy management of their space. Hence, it would be more difficult for the Energy Manager to implement energy saving measures in those spaces.

As service points were identified and data access authorized, PG&E’s IT representative worked with Pulse Energy to ensure that the necessary policies and procedures were in place to protect the customer data. First, Pulse Energy was required to undergo PG&E’s vendor security review. Second, Pulse Energy and PG&E collaborated to setup a secure file

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transfer protocol. Finally, PG&E IT worked with Pulse Energy to test and debug the data transfer protocol.

SOFTWARE CONFIGURATION After the customer data was identified and security demonstrated, PG&E transferred two years of historical data to Pulse. This historical data set included three files containing customer data, billing data, and interval meter data. Pulse created a parser (a simple software program) to format that data for the Pulse software. At the same time, Pulse established an account for each customer and created spaces for each building or property based on the information collected from the customers. The customer data was mapped to points in the software and those points to spaces, with the end result that the customers could log in and view both gas and electric historical energy data for their buildings.

Further work was required to enable the ongoing data feed, which updated customer usage data on a nightly basis. On the PG&E side, this ongoing data feed was referred to as the incremental extract. The incremental extract pulled any new meter reads available in PG&E’s CDW since the previous extract and transferred the data to Pulse. Pulse created a separate parser to handle data in this ongoing meter read. And once that parser was tested and proven sound, Pulse automated the parser so the latest available data would automatically be presented through the online software.

The entire process from the kickoff meeting, where customer space descriptions were first obtained, until the historical data was available in the online Pulse software occurred over one month. This meant historical data was available shortly before the energy management workshops, which were conducted with each customer in May. It took another three weeks for the ongoing data feed to be established, as it had to be batched with PG&E’s regularly scheduled software updates.

QUALITY CONTROL Pulse and PECI performed several checks to ensure that the data presented to the Energy Managers was accurate. Those checks are summarized in Table 6 below.

TABLE 6. SYSTEM QUALITY CONTROL CHECKS

Check Description Results Initial inspection

Did each space show electric and gas service, where expected, and did the energy use data appear reasonable?

10 of 87 points had missing data problems. We worked with PG&E to determine causes and correct where possible. The following causes were identified:

1. Lack of SmartMeter or MV90 meter 2. Non-functioning meter 3. Previously unknown transfer of data ownership.

Billing data comparison

Where there were questions of data accuracy, we confirmed that interval meter data matched the billed use.

Billing data and interval meter data presented through the software were verified to be consistent.

Energy Intensity

Did the building energy intensity calculated by Pulse fall within the expected range and match other sources, if available?

We attempted to compare the EUIs in Pulse to those that the Energy Managers had previously generated in the EPA’s Portfolio Manager. A direct comparison was not useful, as Portfolio Manager allowed the Energy Managers to make adjustments for unique zones within the building (e.g., parking garage or data center).

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Check Description Results Site visit At one site with a particularly

confusing metering environment, the Energy Coaches inventoried meters during a site visit.

One property of three buildings was served by seven electric meters. During a site visit as part of the energy management workshop we were able to identify which spaces were served by each meter.

Not all the checks defined in Table 6 are required or recommended for all buildings. The initial inspection and billing data comparison proved most useful. The energy intensity check was less useful, due to the variety of ways that calculation can be adjusted. Additionally, detailed site information is only needed for properties with a complicated metering environment, where it isn’t clear which meters must be summed to arrive at whole-building consumption.

TRAINING Two types of training were conducted in May. First, the customer Energy Managers completed a 2-hour online training to learn how to use the Pulse Energy software. Second, the customer Energy Managers participated in a full day energy management workshop. Each Energy Manager was trained separately, which allowed the sessions to focus on the individual Energy Managers’ organization and buildings. The content of the trainings is summarized in the following sections.

SOFTWARE TRAINING The agenda of the software training is shown in Box 2. After beginning with introductions, this training introduced the Energy Managers to the logic of EMIS-aided energy management. In short, this was a description of the way the Energy Manager and Energy Coaches would use the software to aid identification of energy saving opportunities, track building energy performance, and measure savings from actions taken by the Energy Manager and his staff. This was a short introduction, which would be followed with greater detail during the energy management workshop.

Actual training on the features and use of the Pulse software occupied the majority of this training session. The learning outcomes anticipated for the training were for the Energy Managers to be able to accomplish the following tasks in the software:

1. Enter facility information, including occupancy schedules

2. Benchmark facilities in the portfolio against one another and against CBECs data

3. Create and view time series plots of facility energy demand

4. Create and view scatterplots of facility energy demand versus outside air temperature

5. Define a model for baseline building energy use, with time-of-day, occupancy and outside air temperature as drivers

6. Measure energy savings against a modeled baseline

The format of the training was an online meeting, with a Pulse customer success specialist guiding the Energy Manager through a real-time demonstration of the software’s features.

Box 2. Software training agenda

1. Welcome & Introductions 2. The logic of EMIS-aided

Energy Management 3. Software training 4. Review & Discussion

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First, the specialist described how the system had been populated with data for the Energy Managers buildings. Next he demonstrated how to navigate through the online software, and interpret and manipulate the data displayed on the Home page, the Management page, and the optional, public Dashboard. A detailed outline of the software training is provided in Appendix B.

ENERGY MANAGEMENT WORKSHOP The energy management workshop was a full day activity. It consisted of a morning, “classroom” session, and an afternoon site investigation. The morning session was hosted by the Energy Manager in his home office, and the afternoon session was conducted in one or more of the Energy Manager’s participating buildings. The learning objectives of the workshop were for the Energy Managers to be able to complete, with assistance from the Energy Coaches, a Portfolio Action Plan for their participating buildings, with the following contents:

1. Energy savings goals 2. Stakeholder assessment 3. Energy information strategy 4. Benchmarking 5. Measure identification 6. Business case 7. Implementation plan

The workshop was not intended to provide comprehensive knowledge of the above topic areas. It was meant to provide an introduction and familiarity with the concepts that could be built on over the subsequent two months as the Energy Coaches worked with the Energy Managers to create Portfolio Action Plans. Activities incorporated in the workshop were used to begin drafting the Portfolio Action Plan. Appendix B provides a detailed outline of the day’s topics and activities.

The format of the morning session was a discussion, facilitated by a PowerPoint presentation. It began with a definition of the Portfolio Action Plan and a description of how the plan would be created through the collaboration of the Energy Manager and the Energy Coach, would guide project activities, and would create a record of what had been done. Following this introduction, each content area in the plan was addressed. The key concepts in each content area were presented and then the Energy Manager and Energy Coaches engaged in a related activity. As an example, the Goal Setting portion of the class provided a definition of goals, introduced best practices of goal setting, and described how goals fit into the Portfolio Action Plan. Then the Energy Manager set goals for some or all of the participating buildings.

Special attention was given to the topic of energy efficiency measure identification. Here, the morning session introduced techniques for using the Pulse software to identify possible energy saving opportunities. Real world examples were given, some based on the historical data for the Energy Manager’s buildings that had by then been loaded into the software. The software-based techniques were then built on with the introduction of strategies for site investigations. And the entire afternoon was dedicated to practicing these field investigation techniques in one of the participating buildings.

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ENERGY COACHING The energy management workshop marked the start of the Energy Coaching. The Energy Coaching was designed to supply Energy Managers with on-demand energy management expertise and also to help track progress and document the measures that were taken. The PECI engineers who acted as Energy Coaches were experienced in-building energy auditors and were also well-versed in use of the Pulse EMIS. They aided the Energy Managers in defining energy saving projects and then followed up to confirm and document that the measures were implemented. The process followed by the Energy Coaches and Energy Managers included four main activities, each of which is described in detail below.

ACTIVITY 1. IDENTIFY ENERGY SAVING OPPORTUNITY Energy saving opportunities can be understood as the recognition, by the Energy Coach or Energy Manager, of a condition where a building appeared to use more energy than required to meet the needs of the occupants. They were ideas, which needed to be further defined and vetted, before being characterized as energy efficiency measures.

Opportunities originated in the project in one of four ways: 1) the Energy Manager brought the idea into the project, 2) the Energy Coach brought the idea into the project, 3) the EMIS prompted an idea, 4) or a site investigation prompted an idea. The end result was the same; an opportunity for energy savings was identified. But where to assign credit, and hence the attribution of energy savings, differed. Table 7 below shows how and why attribution differed between these different sources of opportunities.

TABLE 7. ORIGIN AND ATTRIBUTION OF ENERGY SAVING OPPORTUNITIES

Origin Example Expected Attribution Energy Manager brought into the project

The clearest example of this is that Energy Manager B had already purchased several VFDs before the project start, with the intention of installing them on cooling towers.

Only a portion, if any, of the resulting savings could be attributed to the program. In this example, the portion is zero, however there may be cases where a program would merit some savings from having helped the Energy Manager define and implement the corresponding energy saving measure.

Energy Coach brought into the project

The Energy Coach introduced the idea of a tenant engagement campaign, leveraging the EMIS’s public dashboard, to promote behavior-based energy savings.

Resulting savings could be attributed to the program. Absent the Energy Coach and EMIS, it’s very unlikely that these savings would have occurred.

The EMIS prompted

Visual inspection of load profiles in the EMIS showed that buildings were operating on holidays or weekends, when expected to be unoccupied.

Resulting savings could be attributed to the program. It’s possible that some of these opportunities could have been identified by routine inspection of building operations or analysis of interval data absent the EMIS. However, that type of scrutiny did not appear routine for either Energy Manager.

A site investigation prompted

A tenant space in the midst of renovations was found to be overlit

Resulting savings could be attributed to the program. Identification of these opportunities was due to the presence of a trained Energy Coach or Energy Manager, which would not have occurred without the program.

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All of the opportunities that were identified in this project are included in Appendix E, along with their origin.

ACTIVITY 2. DEFINE ENERGY SAVING MEASURE Additional work was required to convert those energy saving opportunities into actionable energy saving measures. Often, additional information gathering was required to determine if the idea was feasible. For example, one promising opportunity was to shut off a condenser water loop serving heat pumps that the Energy Coach’s review of a building’s load profile had indicated were operating continuously throughout the year. However, further discussion with the equipment vendor and building operator revealed that there were some small data closets in the building that required continuous cooling, and as the heat pump controls were not connected to those of the control of the condenser water loop, the system could not be turned on based on demand. A suitable measure was not defined for that opportunity.

For many opportunities, investigation progressed into definition of a measure. For example, for a building operating on weekends while unoccupied, the measure specification was to correct the schedule in the building automation system. Where lights were left on in unoccupied tenant offices, occupancy sensors were specified. Measure specifications were of three types: retrofit, O&M, or behavioral. A definition and example of each type is provided in Table 8, below.

TABLE 8. THREE MEASURE TYPES

Type Definition Example from this project Retrofit Replacement of existing equipment

with more efficient equipment that performs the same function

Replace exit signs with incandescent lamps with LED exit signs

O&M Adjusting the operations of building systems to address problems and to optimize performance based on the way the building is used

Modify the building HVAC operating schedule in the building automation system so that it does not operate when the building is not occupied

Behavioral Persuading building occupants to change the way they use the building systems and plug loads in a way that will reduce energy use

Tenant engagement campaign encouraged occupants to shut of computers and shared office equipment at the end of each day

The final part of defining an energy saving measure was to estimate the energy savings that would be achieved by implementing the measure. These estimates were generally made by the Energy Coaches based on experience in comparable projects, engineering calculations, and simple analyses of load profiles aided by the EMIS software. Measures and energy saving estimates are presented in Appendix E.

ACTIVITY 3. EVALUATE BUSINESS CASE Not all energy saving measures were equal and the Energy Managers’ resources to implement projects were finite, so the Energy Coaches summarized the estimated cost and benefits of all measures and presented the results to the Energy Managers for evaluation. This analysis had quantitative and qualitative components. The quantitative part of the analysis was an estimate of the lifecycle financial performance of the proposed measure, which was summarized as the measure’s net present value. The qualitative component of the analysis simply summarized expected project impacts with difficult to quantify benefits or costs. As an example, the addition of window film at one property was estimated to have a net present value of $5,000, and it was also expected to provide greater occupant comfort.

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The costs included in the financial analysis were typically limited to equipment purchase and installation costs. With agreement of the Energy Managers, O&M and behavioral measures that could be implemented with existing staff and the resources of the project were considered to have a negligible cost. The benefits included in the financial analysis were estimates of the reduced energy bills that would accrue from the measure’s energy (kWh and therm) and demand (kW) savings.

Both the quantitative and qualitative estimates of measure costs and benefits are presented in Appendix E. With this information, and taking into account other considerations such as available budgets and maintenance plans, the Energy Managers decided which measures to implement.

ACTIVITY 4. IMPLEMENT Implementation was the final activity in the process to achieve energy savings. What actually happened during the implementation step varied considerably based on the type of measure. For some measures, implementation was simply a matter of editing a number in the building automation system. For other measures, implementation required including the measure’s cost in next year’s budget, purchasing equipment, hiring contractors, and careful scheduling to minimize the impact on tenants.

As both Energy Managers held considerable authority within their organizations, they were often able to proceed to implementation without seeking approval from others in their organization. The existing facilities staff implemented several measures, such as thermostat replacements and building schedule modifications. The Energy Coaches aided in the implementation of a month-long tenant engagement campaign. Vendors were enlisted to complete other projects, such as installation of occupancy sensors and replacement of a cooling tower. The Energy Managers engaged other stakeholders in implementation only where measures required a large capital outlay or were expected to have high tenant visibility.

The Energy Coaches supported the Energy Managers by assembling basic implementation plans for many measures, by making recommendations, and by tracking progress. However, most of the burden of implementation fell on the Energy Managers. Even seemingly straightforward projects encounter barriers that require time and attention to resolve. For example, regasketing and rescheduling a hot water boiler to operate only when there was demand seemed easy enough, but proved difficult when new gaskets could not be procured due to the boiler’s advanced age. Barriers like this proved time-consuming for the Energy Managers to resolve and slowed implementation.

DOCUMENTATION Documentation was a companion to each of the four activities involved in Energy Coaching. The initial design of this program planned to use the Portfolio Action Plan and the EMIS to facilitate communication between Energy Manager and Energy Coach. This would simultaneously generate clear documentation of the plans, progress, and achievement of the program. In line with that initial design, the four activities described above were documented in a Portfolio Action Plan for each Energy Manager.

Though useful as a program record, in practice the Action Plans proved too cumbersome for the Energy Managers to review and update. The Energy Coaches alone maintained the Action Plans. Simpler tools, such as progress tracking spreadsheets similar to Appendix E, were created to facilitate communication with the Energy Managers.

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In the future, it may prove worthwhile to integrate the EMIS, documentation and other program management functions in a single tool. The Pulse Energy Manager software offers some feature to support such integration. Users may insert a message or record implementation of an energy conservation manager in the Management screen. These features were used extensively by the Energy Coaches, but not at all by the Energy Managers. With additional training and perhaps program requirements, this feature could create a useful record of investigation and action. An EMIS might further support program delivery by including more tools for defining and tracking projects, as well as linking them to utility programs and incentives. Though presumably those added capabilities would increase the cost of the EMIS and the difficulty of keeping the tool up to date.

RESULTS The results of this project were measured in terms of customer acceptance, energy savings and costs. Each of the sections below first describes how results were measured then reports the results.

CUSTOMER ACCEPTANCE PECI surveyed the Energy Managers in October to obtain their feedback on all aspects of the program. The survey questions covered their reasons for participation, the level of effort they dedicated, the results they expected, and their satisfaction with various aspects of the program. The survey form is provided in Appendix C. Usage data from the Pulse Energy website provides another simple indicator of their adoption of the software. The Energy Managers then participated in a project debrief in February, which provided an opportunity for more open-ended feedback. The Energy Managers’ survey responses, software usage, and feedback from the project debrief are summarized below.

SURVEY RESULTS The survey results indicated that both Energy Managers were highly satisfied with the program. They reported spending five to eight hours per week on the program and that it led them to make new investments in their facilities, estimated at $76,000 (A) and $50,000 (B).8 Both Energy Mangers reported that the EMIS and the Energy Coaching were helping them achieve energy savings for their participating buildings.

Energy Manager A reported using the software for tracking and comparing building performance. Energy Manager B reported using the software for those same purposes and for several additional purposes, including to identify efficiency opportunities, measure savings, review issues identified by the Energy Coach, and to share information with tenants and staff. They also indicated that the Energy Coaching was used to identify energy saving opportunities and to provide input to decisions on which energy saving projects to implement.

8 Other conversations indicate that most of these investments, if not already committed to specific projects, were at least allowed for in budgeting that occurred prior to this project.

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As training was a significant component of the program, the survey asked Energy Managers whether they considered the training sessions successful and whether they recommended spending more or less time on training. Their responses ranged from “somewhat” to “very successful.” The areas where at least one Energy Manager indicated more time should be spent were on the EMIS software training and on use of the EMIS as an aid to measure identification. Their responses related to training are summarized in Table 9, below.

TABLE 9. ENERGY MANAGERS' SURVEY RESPONSES RELATED TO TRAINING

Question Energy Manager A

Energy Manager B

The goal of the online software training was for you to know how to use the software. Was the activity successful in meeting that goal?

Somewhat Very

Do you recommend spending more/less time on the online software training?

More Same

The goal of the Portfolio Action Plan session was to learn a strategy for designing and implementing energy efficiency projects. Was the activity successful in meeting that goal?

Very Very

Do you recommend spending more/less time on the Portfolio Action Plan session?

Same Same

The goal of the Measure Identification session was to learn to use the Pulse EMIS to identify potential energy saving opportunities. Was the activity successful in meeting that goal?

Very Very

Do you recommend spending more/less time on the Measure Identification session?

More Same

The goal of the Site Investigation session was to know how to conduct a walk through and identify energy saving opportunities. Was the activity successful in meeting that goal?

Somewhat Very

Do you recommend spending more/less time on the Site Investigation session?

Same Same

SOFTWARE USAGE We also reviewed the frequency of EMIS use based on the website’s analytics. From May through December, the Energy Managers visited the EMIS website once every one to two weeks. Energy Manager A visited the EMIS software website 27 times. In the same time period, Energy Manager B visited the website 19 times. Other members of their companies also visited the site several times, and the number of total customer visits including both Energy Managers and others in their companies was 60. This works out to about one site visit per Energy Manager, per week on average.

The Energy Coaches were much more frequent users of the EMIS. From May through December, they visited the EMIS software website 237 times; just about every other day, on average. The Energy Coaches often summarized their findings from viewing the EMIS and communicated those findings to the Energy Managers. This probably lessened the need of the Energy Managers to view the EMIS more frequently. Moreover, starting in December the Energy Coaches subscribed the Energy Managers and themselves to weekly reports on building performance that the software automatically generated and delivered by email.

DEBRIEF The Energy Manager’s feedback in the February project debrief was largely consistent with the feedback that they had provided via the October survey. However, the discussion format

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allow for a more thorough exploration of topics. The key themes that emerged during the debrief were the desire for real time data, the need to provide actionable information to the right stakeholders, the time scale of change, and challenges to the automated measurement of energy savings.

In the survey, both Energy Managers had indicated that they would use the EMIS more frequently if it presented real time data. During the debrief, they elaborated on this message. In the dominant EMIS architecture used in this project, the time between when usage occurred and when Pulse received the data varied from one to five business days.9 The Energy Managers pointed out that if they knew, in real time, that energy usage was high, they could look at what was happening in operations to try to understand why. In contrast, seeing the high usage several days later made it very difficult to investigate. Further, Energy Manager B reported using the real time data that he had established for two large buildings to adjust HVAC controls in one building, compare the resulting performance against the other building, and then decide on the optimal control strategy. Both Energy Managers indicated a willingness to invest their own resources in an EMIS to achieve near real time information. They did, however, acknowledge that they didn’t have time to review all the data, so it would again be important to push that information to the onsite operators.

Ideally, the Energy Coach and EMIS would provide a clear message on how to act to save energy to the person best positioned to take action. The Energy Managers noted that the measure identification activities needed to be strengthened to move toward that ideal. They also observed that they, the Energy Managers, were often not the person best positioned to take action. Paraphrasing one Energy Manager, he couldn’t take time away from high priority issues to focus on small measures in small buildings with small expected energy savings. However, a property manager or building operator may be able to act. Ultimately, their message was to direct more training and coaching to onsite staff.

Pushing actionable information to the onsite staff might help implement small measures more quickly, but the Energy Managers were clear that, overall, the energy saving potential of an energy management program required more time to evaluate. As one Energy Manager pointed out, he couldn’t invest $60,000 in a chiller upgrade during the six month implementation period allowed by this project, but that was a project he was interested in undertaking that would have large energy savings. Clearly, they felt that they could achieve more energy savings if given more time.

The final segment of the debrief focused on the energy savings achieved to date, and specifically how those energy savings compared to the goals set forth in their Action Plans. In most buildings, the automated energy savings calculation performed by the EMIS showed that energy savings were below the goals. Both Energy Managers acknowledged that in some facilities not enough measures had been identified or implemented during the project timeframe to meet the goal. However, they also expressed quite strongly that the automated savings calculation was underreporting energy savings due to increases in occupancy in some facilities. This issue is explored further in the discussion of energy savings.

9 SmartMeters were usually at the shorter end of this reporting range and MV90 meters at the longer end.

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ENERGY SAVINGS The Pulse Energy software automates the measurement of energy savings using an avoided energy use methodology. With pre-project whole building energy data and a few independent variables, such as air temperature, the software generates a model that estimates the building’s baseline energy use. After the energy efficiency project, the actual energy use is compared to the baseline model driven with post project conditions (known as the adjusted baseline), and the difference between the two is the estimate of energy savings. IPMVP Volume 1, EVO 10000-1:2012, Option C describes this method in more detail. The avoided energy use equation is shown here.

EQUATION 1. AVOIDED ENERGY USE CALCULATION

𝐴𝑣𝑜𝑖𝑑𝑒𝑑 𝐸𝑛𝑒𝑟𝑔𝑦 𝑈𝑠𝑒 (𝑜𝑟 𝑆𝑎𝑣𝑖𝑛𝑔𝑠) = (𝐴𝑑𝑗𝑢𝑠𝑡𝑒𝑑 𝐵𝑎𝑠𝑒𝑙𝑖𝑛𝑒 𝐸𝑛𝑒𝑟𝑔𝑦 − 𝑅𝑒𝑝𝑜𝑟𝑡𝑖𝑛𝑔 𝑃𝑒𝑟𝑖𝑜𝑑 𝐸𝑛𝑒𝑟𝑔𝑦) ±𝑁𝑜𝑛𝑅𝑜𝑢𝑡𝑖𝑛𝑒 𝐴𝑑𝑗𝑢𝑠𝑡𝑚𝑒𝑛𝑡𝑠

PULSE ADAPTIVE MODEL Pulse refers to the adjusted baseline as the Pulse Adaptive Model (PAM). The PAM is generated using a proprietary algorithm based on a “nearest-neighbor” approach, similar to weighted averaging, where the historical energy performance for conditions most similar to those at the time of the prediction exert the greatest influence on the result. A recent evaluation of five building energy models included an evaluation of the PAM and concluded that it performed among the best of the models tested, with a typical error in predicting daily energy use of about 14% (the best performing model’s error was 13%). Looking at predictions on a monthly basis, the error of the PAM decreased to 10%.10

The PAM is generated using the historical time series data of the dependent variable, energy use, and the independent variables: outdoor air temperature, day, time, and a holiday indicator. These inputs for the PAM were all obtained during the software installation.

BASELINE & REPORTING PERIODS All buildings participating in this scaled field placement were mixed office space. For most buildings, the historical data provided by PG&E included at least one year of 15-minute electric data and daily gas data. The program start date, or the point from which energy savings is estimated, was the date of the first energy management workshop, May 7, 2012. The baseline period for most buildings was the full year prior to the program start, May 7, 2011 to May 7, 2012, except for those with large tenant, equipment, or operational changes as discussed in the next section.

For electricity use, the baseline created by the PAM was used to estimate the adjusted baseline energy use according to Equation 1 during the program implementation period. The implementation period extends from the program start date to January 27, 2013 and the difference between the actual energy use over this period and the adjusted baseline use may be viewed as energy savings (or in the case of a negative result, as energy waste). Figure 8, below, shows a building that is using less energy than predicted by the baseline model, which may indicate energy savings attributable to the program.

10 Granderson, J. and P.N. Price (2012), “Evaluation of the Predictive Accuracy of Five Whole-Building Baseline Models,” Lawrence Berkeley National Laboratory.

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FIGURE 8. ACTUAL VERSUS BASELINE ENERGY USE (PULSE SOFTWARE)

NON-ROUTINE ADJUSTMENTS Many influences aside from the energy management program tested in the project can affect building energy use. Some of those, notably weather, are routine, and are accounted for in the baseline models. Others, such as large tenant movements, are non-routine and are not included in the model. For an accurate estimate of energy savings, we must consider the impact of those non-routine influences in both the baseline and program periods.

When creating the baseline models, we reviewed the record of historical energy data used to construct the model and investigated any point where the average building energy use appeared to change by more than 5%. In addition to reviewing the data, we asked the Energy Managers to report any changes to building occupancy, equipment, or operations that they expected to change building energy use by 5% or more throughout the baseline and the reporting period.

Based on reports from the Energy Managers, the largest non-routine influences of the buildings’ energy use during the baseline and program periods were related to tenant movements. Such movements included tenants moving in, moving out, or changing their use of the space (e.g. by introducing a data center). Appendix D details all the changes by building that have been reported to date. We do not expect this to represent a complete record of tenant movements. In practice, reporting of changes was reactive; the Energy Coaches noted an unexplained increase or decrease in energy use and contacted the Energy Manager to determine and document the cause.

Baseline

Actual

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Where tenant, equipment, or operational changes were documented that caused energy use to vary by more than 5%, we adjusted the baseline period to exclude the time prior to the change or simply excluded the building from the energy savings analysis. Table 10 lists all such non-routine adjustments made per building. One building in Energy Manager B’s portfolio was assigned a reduced baseline period and four were assigned a reduced reporting period. Two suites associated with one of Energy Manager A’s buildings and five buildings of the twenty-six in Energy Manager B’s portfolio were not modeled due to large tenant changes during the baseline or the program period.

TABLE 10. BASELINE EXCEPTIONS AND EXCLUSIONS

Customer Building Adjustment Explanation Energy Manager A CT Two suites

removed, and savings adjusted

Two suites were removed from data streams representing the baseline and program periods because data for these suites was missing during the program period. In addition the overall building occupancy increased from 88% to 95%

Energy Manager A EL Savings adjusted Overall building occupancy increased from 90% during the baseline period to 100% during the implementation period.

Energy Manager B J, K, L, M Reporting period changed to 5/7/2012-12/31/2012

1/1/2013 Major construction and tenant changes.

Energy Manager B M Baseline period changed to 2/1/2012-5/7/2012

2/1/2012 new tenant moved in and a two-rack server room was installed.

Energy Manager B N Not modeled One large tenant has down-sized during the program period.

Energy Manager B P Not modeled New tenant moved in the beginning of the program period.

Energy Manager B Q Not modeled New tenants moved in during the program period.

Energy Manager B GG Not modeled No tenants in space for most of the baseline period, and during the program period there were multiple tenant move-ins

Energy Manager B Z Not modeled Construction and new tenant move-in during the program period, and new tenant took over utility bill so data became unavailable

In addition in both Energy Manager A’s buildings energy savings reported from the Pulse EMIS were adjusted based on the overall change in percent occupied as reported by the Energy Manager. This was a simple adjustment, which may not accurately represent the relationship between occupancy and whole building energy use. However, further research is needed to define an appropriate methodology for making this type of adjustment. Energy Manager B did not report occupancy rates per building so the Pulse reported energy savings were not adjusted in this manner.

ENERGY SAVINGS Electric and natural gas energy savings have been estimated for both customers, from the program start in May 2012 through January 2013. Measures implemented by Energy Manager A include: HVAC and lighting scheduling, replacing mercury switch thermostats

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with programmable thermostats, lowering the boiler lockout temperature, and implementing a tenant engagement campaign. Measures implemented by Energy Manager B include: installation of a VFD on a cooling tower fan, reducing HVAC runtime, optimizing the sequence of operations of HVAC equipment for energy efficiency, and implementing a tenant engagement campaign. Appendix E provides a list of all measures identified and implemented as part of the program.

For nearly all measures, the Energy Coaches used simple engineering calculations to estimate savings before implementation; then, post implementation, the EMIS was used to estimate savings. For electric energy savings, both the savings estimates from engineering calculations and the EMIS are presented here. For natural gas, only the savings estimates based on engineering calculations are presented. The PAM did not provide precise predictions of natural gas usage, because the gas data was only daily, not 15-minute resolution.

The total estimated energy savings over the program period are shown in Table 11. The engineering calculation estimates of measure level savings are shown in Appendix E. Those engineering calculations produced annual savings estimates. To make those comparable to the savings values reported by the EMIS, the annual savings have been prorated to the program period and the result is included in Table 11. As shown below, the engineering calculations yielded savings estimates of between 4% and 18%, where the EMIS results indicated savings of between negative 2% and 11%.

TABLE 11. ENERGY SAVINGS: IMPLEMENTED MEASURES

Energy Manager Building ID

Ex-ante Engineering Estimates of Energy Savings

EMIS Reported Energy Savings

Therms kWh % of WB

Energy Use kWh % of WB

Energy Use A CT - 16,703 8% (3,668) -2% A EL 1,016 15,726 4% 44,358 11% A All 1,016 32,429 5% 40,690 7% B All 14,015 461,806 18% 31,456 1%

Total 15,032 494,234 16% 72,146 2.3%

The ex-ante engineering estimates of energy savings totaled 156,016 kWh for buildings less than 100,000 square feet and 338,218 kWh for buildings greater than 100,000 square feet as shown in Table 12. The energy savings reported by the EMIS were 19,487 kWh for buildings less than 100,000 square feet and 52,658 kWh for buildings greater than 100,000 square feet.

TABLE 12. ENERGY SAVINGS: IMPLEMENTED MEASURES BY BUILDING SIZE

Energy Manager

Number of

buildings Building Size

Ex-ante Engineering Estimates of Energy Savings

EMIS Reported Energy Savings,

kWh Therms kWh A 2 < 100,000 sq. ft 1,016 32,429 40,690

B 10 < 100,000 sq. ft -

123,588 (21,202) B 11 > 100,000 sq. ft 14,015 338,218 52,658 Total 12 < 100,000 sq. ft 1,016 156,016 19,487

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Though the ex-ante estimates were intended to be simple calculations to aid decision-making, the large divergence of the EMIS reported savings warrants some explanation. There are three main causes. First, the scope of what was anticipated did not match what was implemented. For example, an activity to reprogram a BAS was only partially completed within the program timeframe. Second, the ex-ante estimate was based on assumptions that proved inaccurate. For example, the tenant engagement campaign did not receive the assumed level of uptake by tenants. Third, the measurement of savings by the EMIS was distorted due to changes in building occupancy.

The Energy Managers attributed the lack of realized savings at the portfolio level in large part to tenant changes in the buildings. Moreover, the Energy Managers reported in the final debrief that they expected to see more savings in the future as a result of the program due to the more recently implemented measures and the future implementation of the planned measures listed in Appendix E.

ENERGY MANAGER A

The electric energy savings for Energy Manager A’s buildings, from May 2012 through January 2013, were 40,690 kWh (7% of predicted baseline use). This estimate includes four of the six buildings initially enrolled by Energy Manager A. As noted in the discussion of Installation of the EIS, tenants had ownership of the majority of PG&E accounts for the other two buildings, and consequently energy data for those buildings was not fully integrated and no work was done in those buildings. In one of the four buildings covered in this savings estimate, two independently metered tenant spaces were excluded due to large changes in occupancy during the program.

The four buildings included in analysis are situated on two properties. The estimated savings for property EL was 44,358 kWh (11% of predicted baseline use). For the other property, estimated savings were negative 3,668 kWh (negative 2% of predicted baseline use). The Energy Manager attributed the negative result not to a lack of energy savings, but instead to inadequate tracking of building occupancy changes. The cumulative summation reports from Pulse for each building are shown below.

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FIGURE 9 . MONTHLY ENERGY SAVINGS REPORT BUILDING CT (CUMULATIVE SAVINGS DECREASE)

FIGURE 10. MONTHLY ENERGY SAVINGS REPORT BUILDING EL (CUMULATIVE SAVINGS INCREASE)

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ENERGY MANAGER B

The estimated overall electric energy savings for the buildings of Energy Manager B from May 2012 through January 2013 was 31,456 kWh, indicating a small decrease in energy use. At 1% of predicted baseline use, this is difficult to distinguish from the normal variation of building energy use. As noted in the discussion of non-routine adjustments, five of the 26 buildings were completely excluded from this analysis due to known, large changes in occupancy during the program period.

The building level savings for Energy Manager B ranged from an increase in energy use of 126,677 kWh (negative 8% of predicted baseline use) to a savings of 152,504 kWh (6% of predicted baseline use). One of the four buildings this energy manager specifically focused on with a goal of 10% energy savings realized EMIS reported savings of 151,356 kWh (18% of predicted baseline use). The EMIS reported kWh savings in this case was also comparable to the 160,307 kWh ex-ante estimated energy savings associated with the controls upgrade Energy Manager B performed on this building. Samples of the building level cumulative summation reports for Energy Manager B are shown below.

FIGURE 11. MONTHLY ENERGY SAVINGS REPORT FOR ENERGY MANAGER B (CUMULATIVE SAVINGS DECREASE)

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FIGURE 12. MONTHLY ENERGY SAVINGS REPORT FOR ENERGY MANAGER B (CUMULATIVE SAVINGS DECREASE)

SAVINGS CLAIMED OUTSIDE OF PROGRAM Both Energy Managers received incentives from other PG&E programs for some of the measures that were implemented during this project period. Often the incentives were claimed by a vendor. For example, the installation of occupancy sensors in one of Energy Manager A’s buildings was performed by a vendor at little cost to the Energy Manager. This was possible because the vendor claimed the $5 per sensor incentive offered by PG&E.11

Table 13 below shows the energy savings claimed under other PG&E programs for each Energy Manager. In the table, the savings claimed under other programs, which are annual savings estimates, have been scaled down to represent only savings during this program’s implementation period. This adjustment allows us to compare them with the savings estimates derived from the Pulse EIS (Table 11). Deducting the claimed savings from the Pulse EIS savings gives the net unclaimed savings during the implementation period. Appendix G contains the full list of measures that were claimed through other programs during the project period.

11 Rebate code L82 in the PG&E Lighting Rebate Catalogue

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TABLE 13. ENERGY SAVINGS CLAIMED UNDER OTHER PG&E PROGRAMS

Energy Manager

Building ID

Claimed Savings Pulse EIS Savings Net Unclaimed Savings kWh kWh kWh Saved % of Building Use

A All 17,185 40,690 23,505 4% B All 32,979 31,456 (1,523) 0%

Total 50,164 72,146 21,982 0.7%

The amount of energy savings due to the combined EMIS and Energy Coach support falls somewhere between the Pulse EIS Savings and Net Unclaimed Savings shown in Table 13. The Energy Managers would not have pursued many of the projects included in the Claimed Savings without the prompting of the EMIS or Energy Coach. But perhaps they Energy Managers would not have followed through on those projects without the incentives provided by the other programs. We do not distinguish between claimed savings and unclaimed savings in the remainder of the report. However, we do note the $28,000 in rebates that PG&E paid for the claimed savings in our discussion of overall program effectiveness.

COSTS ESTIMATES Both Energy Managers and Coaches dedicated considerable resources to the program. The Energy Managers each reported spending between 110 and 176 hours from May through September, for a combined total of between 220 and 350 hours. In addition, they reported that their staff had spent additional time on the project and that the program led them to make additional investments in their facilities of $76,000 and $50,000.

The Energy Coaching team spent 60 hours training, 100 hours aiding in the development of Portfolio Action Plans, and approximately 250 hours supporting implementation of those Plans. The majority of this implementation support time was spent in one of four ways: 1) Gathering additional information (e.g. product information) related to proposed measures, 2) Facilitating month-long tenant engagement campaigns, 3) Regular monthly meetings with the Managers to track progress and define strategies to surmount obstacles, and 4) Ongoing monitoring of building performance using the EMIS.

Altogether, 410 hours of Energy Coaching have been shared by the two Energy Managers and their 32 buildings. We consider it highly likely that this level of effort would be reduced by 50% or more if a similar program were deployed to the target market. Most of that reduction could be achieved through a reduction in the number of staff dedicated to a particular task. For example, two Energy Coaches delivered each energy management training. In a scaled program, one Coach could deliver the training. If a program were to be built on this work, it would benefit from the learning and development achieved in this project and would require less staff time to deliver.

The estimated costs of delivering a program combining an EMIS and Energy Coaching are shown in Table 14, below. Costs are for a 32 building deployment, as was conducted in this scaled field placement. The labor for the test program and estimated labor for a mature program are shown separately to indicate the anticipated reduction in the labor requirement. Materials costs are not separated, as they are not expected to change substantially.

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TABLE 14. ESTIMATED PROGRAM COSTS FOR 32 BUILDINGS

Labor (hours) Other Direct Costs Costs for test program Estimated program costs

Energy Coach

Energy Manager1

Energy Coach

Energy Manager

Startup & Recruiting 80 40 Data integration 40 20 Training 60 20 30 20 Develop action plans 100 50 50 50 Implement action plans2 250 210 125 210 $126,000 1 Total Energy Manager labor is based on labor reported by the Energy Managers; the task-level labor is estimated by PECI. 2 Other direct costs for implementing the Action Plans are the Energy Managers’ self-reported cost estimates for hiring contractors and purchasing equipment to implement energy saving measures.

A total program cost is not shown in Table 14, because pricing information was not provided for the Pulse EMIS. The cost per building of the EMIS integration described in this report would most likely vary significantly with the number of participating customers. Readers who are interested in estimating the total cost of a similarly designed program might begin by requesting a cost proposal from an EMIS vendor. That proposal could be combined with the information presented in Table 14 to arrive at a total program cost estimate.

EVALUATIONS The Energy Managers were enthusiastic about the EMIS and the visibility that it afforded into their buildings’ energy use. Their response to both the EMIS and the Energy Coaching was strongly positive, as indicated by the survey results. Together, the Energy Coaches and Energy Managers generated a sizeable list of energy saving opportunities (Appendix E). However, the implementation of energy saving measures was slower than expected, and only a small amount of energy savings were realized in the first year of the program.

OVERALL PROGRAM EFFECTIVENESS The energy savings recorded after 10 months were low and difficult to distinguish from normal variation in building energy use. It is possible that in many buildings the energy savings were masked by changes in occupancy. Our best estimate is that the average building level energy savings was 2.3%. If we apply that savings estimate to the average annual energy consumption of a small to medium building, perhaps 675 MWh and 9,000 therms, it gives an estimated annual energy savings of 15,500 kWh and 207 therms per building.12

12 Estimated for a 50,000 square foot office building, using an energy intensity of 13.5 kWh/ft2 and 18 kBtu/ft2 as reported in the California Commercial End-use Survey.

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The estimated first year cost of delivering the program is 265 labor hours of Energy Coaching, $126,000 in other direct costs, and the EMIS software cost. The other direct costs are estimated based on the Energy Managers’ self-reported expenditures for implementation. The Energy Manager’s time, though a real contribution to the project, is not counted as a program cost. Assuming the rate of a consulting engineer is $125 per hour and dividing costs equally among buildings, the cost is roughly $5,000 per building. To that, we must also add the costs of rebates received through other PG&E programs – averaging $900 per building – and the cost of the EMIS, giving a total cost per building likely in excess of $6,000.

There is considerable uncertainty in the cost estimates. The scaled program cost may be 50% more or less than this estimate. There is additional uncertainty in the energy savings, which proved difficult to distinguish from normal variation in building energy use. As a result, an accurate program benefit cost ratio cannot be determined.

Despite the uncertainty related to overall cost-effectiveness, there are signs that benefits would increase over time. First, some of the buildings where the Energy Managers and Coaches focused their efforts performed far better than the average. One of Energy Manager A’s buildings reached an 11% savings and one of Energy Manager B’s buildings reached 18% savings. The Energy Managers may yet apply the lessons learned in those buildings to other buildings in their portfolios. Second, if the Energy Managers simply maintain the energy saving measures that they implemented by the end of the program, then they will see annual energy savings during the second year that are higher than their average savings to date. A check-in with the two Energy Managers six months after project completion would help to better understand the potential second year impacts.

The customer-appeal of the EMIS, its ability to foster collaboration, and the promise of streamlined energy savings calculations are strong arguments for revisiting this energy management approach. The next two sections describe market barriers encountered during this scaled field placement and our recommended improvements to the program model that was tested. Incorporating these recommendations would increase the likelihood of realizing measureable, cost-effective energy savings. A duly revised program model would be worth testing in a follow-up assessment.

MARKET BARRIERS The target market of the program tested in this scaled field placement is one of the most difficult to serve with energy efficiency products. The test program targeted and reduced some market barriers, but others remained. Important barriers to delivering energy efficiency in this target market and the extent to which they were addressed are described below.

LACK OF INFORMATION Most of the interventions of the program were designed to address the lack of information about energy use and energy saving opportunities in smaller buildings. The Pulse Energy EMIS was successfully deployed to provide better visibility into building energy consumption. The Energy Coaches used the EMIS and worked with Energy Managers to provide information about specific energy savings opportunities. By providing this information, Energy Managers were empowered to implement low cost operational measures. They were also able to undertake some low cost retrofits within the timeframe of the test program, particularly where a vendor could be brought in to provide turnkey delivery of the energy efficiency measure and claim existing PG&E incentives.

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Still, at the conclusion of the project the Energy Managers expressed a desire for more information. They asked for real time data in the EMIS and for strengthening the measure identification activities. Here, by measure identification activities we understand that they would have liked more training on use of the EMIS as an aid to identification of energy saving opportunities and also more support from the Energy Coaches in developing those opportunities into well-defined, ready-to-implement measures. The need for more information was not restricted to the Energy Managers. Without detailed, ongoing reports of building occupancy, the Energy Coaches, even aided by the EMIS, found it difficult to distinguish energy savings of the program from tenant movements.

SPLIT INCENTIVES Split incentives were an important barrier to implementation of the program. The building portfolios in this project were almost entirely leased commercial office space. In the clearest expression of the split incentive barrier, one Energy Manager ceased trying to gain tenant approval for access to the tenants’ utility data in two of the buildings. It was time consuming to get that approval, and ultimately the tenants were responsible for the utility costs so there was little incentive to continue the pursuit.

In the great majority of the participating buildings the Energy Managers’ companies had some responsibility, often a shared responsibility, for utility costs. Even here the problem of split incentives presented itself. Many energy saving measures require some tenant cooperation. A clear example is space temperature setpoints, where a single tenant can have a significant impact on whole building energy use by requiring an unusually low temperature setpoint. Even though an Energy Manager may have lease stipulations or building rules indicating that temperature setpoints will be within a certain range, they cost of an unhappy tenant is generally seen to outweigh the increased energy costs.

RECOMMENDATIONS This scaled field placement has provided some strong indications as to what is required for the success of an energy management program utilizing an EMIS and targeting small and medium business customers. The four recommendations below respond to the most significant barriers to the success of the test program:

1. We recommend focusing energy management programs on owner-occupied buildings. Data integration was complicated when tenants and owners each held some share of the energy data. More importantly, potential tenant dissatisfaction was an ever present concern for the Energy Managers. An owner-occupied building could more easily make the occupants a part of the energy management team. Owner-occupied buildings have been the target of successful RCM programs and this project has shown that there is good reason for that.

2. We recommend using publicly state goals and tying them to incentives. Energy savings goals were used in the test program, but they were referred back to infrequently and they were known only to the Energy Managers and Energy Coaches. There were no rewards for meeting the goals or penalties for falling short. Given the many competing commitments of project stakeholders, a public statement of goals would help to bring attention to the program and commitment to goals.

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Requirements to implement certain measures or to pay back project costs, as are used in RCM and RCx programs, would also help encourage timely implementation.

3. We recommend that the energy management team include in-building operators and property managers. The Energy Coaches were the most frequent users of the EMIS and spent the most time on the program, but they were outside of the customer organization and thus could only make suggestions, not changes. The Energy Managers were enthusiastic and experienced supporters of energy efficiency, but they had little time to spare and were often one step removed from day to day building operations. A person who is routinely on the property, has a hand in operations and a line to the building tenants needs to have a strong role in energy management. This would cut out a middleman and help speed implementation of simple, low-cost measures.

4. We recommend developing a protocol for EMIS-aided energy savings estimates that offers clear guidance for addressing non-routine adjustments. The EMIS was a key part of what attracted customers to the project, and both the Energy Managers and Energy Coaches found it to be a valuable tool. One of the most promising uses of the EMIS was to estimate energy savings. However, energy savings estimates were confounded by changes in tenant occupancy and equipment. Working with owner-occupied buildings would help, but there would still be occupancy and equipment changes that needed to be tracked and included in the process of estimating energy savings. A clear methodology for tracking and adjusting savings estimates for those changes would clear a significant obstacle to the use of EMIS for estimating the energy savings due to an energy management program.

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APPENDIX A – CUSTOMER INFORMATION REQUEST

Software Uses:

• S: Define Spaces • P: Define Points • B: Create Baselines

Building Information

Basic Information Software Use

1 Building Name or ID S 2 Building Address S 3 Building City S,B 4 Building Zip Code S 5 Building Type S 6 Year Constructed S 7 Total Square Footage S 8 Conditioned Square Footage 9 Electric Meter PG&E Account # P 10 Gas Meter PG&E Account # P 11 Notes

Uses and Schedules Software Use

12 Primary Use 13 Primary Use Estimated Square Footage 14 Secondary Use 15 Secondary Use Estimated Square Footage 16 Estimated number of occupants 17 Date(s) of occupancy changes in the past year (if any) B 18 Does the building operate on Federal Holidays? B 19 Any additional holidays besides Federal Holidays? B 20 Occupancy notes (e.g. weekend occupancy) Systems 21 Does the facility have a built up HVAC system? 22 Does the facility use packaged HVAC units? 23 Do tenants have control over zone temperatures? Please describe. Existing O&M 24 Who provides maintenance for the building?

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Customer Information Ownership and Occupants 1 Does your company own this building? 2 Does your company occupy this building? 3 If not, what type of lease or rental agreement is in place? Who pays utility bills? 4 Would you consider providing occupants with information on energy consumption? 5 Would you consider engaging occupants in an energy saving competition? Company Goals 6 Do you have company goals for energy or sustainability? 7 If so, please describe the goals. Planning 8 Is there a cap on the time the Energy Manager can spend on this program?

9

Please provide a brief description of the process for approving O&M expenditures. For example, how would the Energy Manager get approval to hire a technician to spend an hour reprogramming an HVAC unit?

10

Please provide a brief description of the process for approving capital expenditures, including financial criteria. For example, how would the Energy Manager get approval to install light fixtures?

Project History

Benchmarking Software Use

1 Has this building been benchmarked? 2 If so, please describe the approach and results. Audits 3 Has facility had any energy audits in the last three years? 4 If so, is the audit report available? Energy Efficiency Projects 5 Has the building completed any energy efficiency projects in the past 5 years? B 6 If so, please note the projects and the dates they were completed. B

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APPENDIX B - ENERGY MANAGER TRAINING Course Overview This training will prepare the Pulse Energy Management Pilot’s designated customer Energy Manager to develop the Portfolio Action Plan that will guide the rest of the program. The training will be divided into three parts: 1. An online software training, 2. An “in-class” session, and 3. Building walk-through(s). Parts 2 and 3 will be delivered on the same day.

The course will have its foundation in general principals of energy management, but we will make an effort to tailor the content to the customers facilities based on the data that we are able to collect beforehand. Thus, the program will have a general curriculum scope and content. But for each customer Energy Manager, we will further customize that general content to focus on his/her facility, systems, occupants, and data.

Learning Outcomes After attending this training participants will be able to:

1. Describe how energy information is used in this program to achieve energy savings: 2. Use the Pulse Energy Management software to:

a. Enter facility information, including occupancy schedules b. Benchmark facilities in the portfolio against one another and against CBECs data c. Create and view time series plots of facility energy demand d. Create and view scatterplots of facility energy demand versus outside air temperature e. Define a model for baseline building energy use, with time-of-day, occupancy and outside

air temperature as drivers f. Measure energy savings against a modeled baseline

3. Complete a Portfolio Action Plan, that includes: a. Goal setting b. Stakeholder assessment c. Energy information strategy d. Benchmarking e. Measure identification f. Business case g. Implementation plan

Course Instructors Pulse Software Training Brent Bowker, Customer Success Specialist, Pulse Energy

Brent Bowker promotes customers’ success through training, energy competitions, pilot program management and general customer support. Brent joined Pulse in 2010 coming from research roles at the National Research Council and the University of Waterloo.

Energy Manager Training Mark Effinger, PECI

Mr. Effinger is a Professional Engineer with extensive expertise in building HVAC systems and in deploying retrocommissioning projects through utility and owner-driven programs. He provides subject matter expertise to retrocommissioning programs and research

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projects, leads the use of measurement and verification in energy efficiency projects, and develops guidelines and training to promote industry knowledge of the retrocommissioning process.

Amber Buhl, PECI

Ms. Buhl is a versatile engineer with 8 years of engineering experience. At PECI, she performs technical research associated with HVAC systems, and supports the development of tools to improve and streamline the commissioning process.

James Russell, PECI

Mr. Russell is a program manager with international technical consulting experience in the energy efficiency and energy policy fields. For PECI, he focuses on developing, managing and delivering applied research projects for clients in PECI’s existing and emerging practice areas. He contributes technical content in focus areas including energy codes and standards, and energy monitoring and information systems.

Class Details Software Training Location: Online

Time Topic Presenter 8:30 – 8:40 Agenda review James Russell 8:40 – 8:55 The Logic of Software Aided Energy

Management James Russell

8:55 – 10:15 Learning to use Pulse Energy Management software

Brent Bowker

10:15 – 10:30

Questions or activity Discussion

Energy Management Training Location: Energy Manager’s Office

Time Topic Presenter 8:30 – 8:40 Agenda review James Russell 8:40 – 10:00 Portfolio Action Plan James Russell 10:00 – 10:15 Break 10:15 – 11:00 Remote Measure Identification Amber Buhl 11:00 – 12:00 Onsite Investigation Planning Mark Effinger 12:00 – 12:30 Lunch 12:30 – 1:00 Travel 1:00 – 5:00 Onsite Investigation Mark Effinger

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Course Outlines Part 1: Pulse Software Training (2 hours)

• Welcome and introductions • The logic of EMIS-aided Energy Management (PECI)

o Benchmarking and performance tracking o Measure Investigation

Fully remote Streamlined investigation

o Automated M&V • Lesson Road Map • Pulse Software Background

o Data collection and integration o Definition of terms – points, spaces o Core points o Building Metadata

• Pulse Software Overview o Four tabs o Getting help and support

• Pulse Home o Content overview o Navigation o Building Details o Benchmarking

Benchmark facilities in the portfolio against one another Benchmarking against CBECs data

o Activities: Find peak demand value date and time for past year How do various buildings compare to each other & CBECS?

• Management o Energy management tasks supported by this tab o Viewing charts o Creating charts o Activity: Using the charts, determine what might be a useful, off hours demand alert

• Create Baselines o Define baseline

Benchmark a facility against its past performance o Discuss data requirements (e.g. occupancy) o Creating baselines

Pulse/PECI versus customer responsibility for o Evaluating baselines

• Thresholds o Show what we've created and talk about what others might be of interest o Subscriptions o Activity: Test threshold discovered above

• Reporting o Scatterplots o Activity: Explore relationship between daily temperature & energy use o Generating reports o Subscribing to reports

• Dashboard o Show basic setup o Show a more customized setup

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o Activity: Discuss customization • Users

o Configuration tools o Adding users o Activity: Add a colleague as a user

• Review and Discussion o Describe what comes next in the program (PECI) o Review any features the customer wants more info on

Part 2: Portfolio Action Plan • Why a Portfolio action plan?

o What is a Portfolio action plan o How the plan will be used in this project

• Goal setting o Principles for goal setting o How to set a good goal

Estimating potential Alignment with other company goals/commitments

o Activity: Set a goal • Stakeholder analysis

o Purpose o Activity: Identify stakeholders and describe how they will be involved in the program

• Performance tracking o Benchmarking

Why do it How to do it

o Performance tracking Regular (progress toward goals) Project M&V

o Activity: Set up regular reports in Pulse • Building investigation overview

o Define measures o Estimate savings

• Business case o Progress toward goals o Financial analysis

Calculating financial metrics Factoring in utility incentives

o Identifying non-energy costs and benefits o Making sense of the results o Activity: Financial analysis of a simple project

• Implementation plan o Scheduling o Statement of Work o Contracting o Delivery o Hand-off o Project M&V

Part 3: Building Investigation • In Office

o Refresher on the logic of EMIS-aided Energy Management Potential measures Tools of analysis

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Preliminary analysis and applicable range of measures o Remotely identified measures

O&M measures • Applicable measures and associated identification methods • How & when to use each identification method • What we’ve found for building #1 • Exercise: Use identification methods for another building in portfolio

Behavioral measures • Applicable measures • How to define them • Exercise: Define an occupant engagement strategy

o Measures requiring in-building investigation Applicable measures Why does it seem like an opportunity for their buildings How are we going to figure it out with a site investigation

• In Field o Investigate specific measures in one of the buildings

Gather equipment data Document occupant control settings Perform simple functional tests & check sensor calibration

Next Steps • PECI engineering assistance • Pulse software support

Course Materials and Resources

Pulse Energy Software Energy Manager Training

Internet connected computer

Online meeting software

Email and phone support

Pulse User Guide

Portfolio Action Plan Template

Building Performance Tracking Handbook

Energy Information Handbook: Applications for Energy Efficient Building Operations

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APPENDIX C - ENERGY MANAGER SURVEY

Thank you for your participation in the Pulse Energy Management project. A key objective of this project is to understand how the services offered were (or were not) of use to the customer Energy Managers. The two principal services provided were Energy Information Software (EMIS) and energy engineering support (Energy Coaching). Please respond to the following questions evaluating different aspects of the EMIS and Energy Coaching services.

PG&E, PECI and Pulse are all committed to continuously improving the services they provide, and your honest opinion will be sincerely appreciated.

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Participation 1. Please rank the importance of the following factors to your decision to participate in

this project (1 = the most important factor; 4 = the least important):

___ Interest in testing EMIS software

___ Company’s sustainability-related goals

___ Desire to save energy and reduce costs

___ Other (please note): _________________________________

2. Please estimate how much time you’ve spent on this project.

1-4 hours/week

5-8 hours/week

9-12 hours/week

13-16 hours/week

more

3. Please estimate how much time all other staff or coworkers have spent on this project.

1-4 hours/week

5-8 hours/week

9-12 hours/week

13-16 hours/week

more

Results 4. Has this project led you to make any new investments? (Examples include

purchasing new equipment or paying vendors to service existing equipment.)

Yes. Please estimate the total amount ($) ________________

No

5. Has this program increased awareness of energy usage for the following groups: a. You (Energy Manager) Yes No Comments:_________________

b. Tenants Yes No Comments:_________________

c. Property Managers Yes No Comments:_________________

d. Building Operators Yes No Comments:_________________

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6. The project goals that you adopted for your buildings are shown here. Please indicate whether we have met, are on track to meet, or are not on track to meet each goal.

Goals Status (please circle one)

Goal statement 1 Met On track to meet

Not on track to meet





7. What, if any, other benefits have you and your buildings received by participating in this program?

8. Overall, do you feel this project was a success? Yes No Please describe why, or why not.

Pulse EMIS Please answer the questions in this section considering the Pulse EMIS with whole building electric and gas data delivered from PG&E 2 to 7 days after usage occurs.

9. Approximately how much time did you spend learning to use the Pulse EMIS?

2 hours (Just the time of the initial software training)

4 hours

8 hours

More

10. How comfortable are you using the Pulse EMIS?

Very comfortable (I can do everything I want)

Comfortable

Somewhat comfortable

Not comfortable (I can’t do anything I want)

11. Are there any software features that you would like additional training on?

No Yes (please identify):______________________________

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12. How do you use the Pulse EMIS? Please check all answers that apply.

Track the performance of a portfolio of buildings

Compare performance of different buildings

Track buildings’ performance over time

Help identify energy saving opportunities

Measure savings from actions taken to save energy

Review potential performance issues identified by the Energy Coach

Produce regular reports on building energy performance indicators

Engage building occupants

Share information with staff

Other: __________________________________________

13. How often did you share energy information with your staff or managers to promote changes in building operations?

Never 1-5 times 6-10 times over 10 times

14. Is the EMIS helping you to achieve energy savings for the participating buildings? Yes No

15. What are the greatest strengths of the Pulse EMIS?

16. What are the greatest weaknesses of the Pulse EMIS?

17. Would you have purchased an EMIS if it hadn’t been provided by this project?

Yes, for all buildings that participated in the project

Yes, for the larger buildings that participated in the pilot

Yes, for the smaller buildings that participated in the pilot

No

18. If you answered yes on the previous question, approximately how much did you expect to spend? ($/building)

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19. Would you use the Pulse EMIS more often if it incorporated real time data with only a 15-minute delay?

No

Yes, a little more

Yes, somewhat more

Yes, far more

Energy Coaching Please answer the questions in this section considering the building energy technical support provided by PECI from May 2012 until the present.

20. How do you use the Energy Coaching? Please select all that apply.

Help identify energy saving opportunities

Estimate energy savings

Provide input to decisions on which projects to implement

Plan project implementation

Track project progress

Engage building occupants

Other: ___________________________________________________

21. Is the Energy Coaching helping you to achieve energy savings for the targeted buildings?

Yes No

22. What are the greatest strengths of the Energy Coaching?

23. What are the greatest weaknesses of the Energy Coaching?

24. Are there other ways the Energy Coaching could have assisted you or your staff?

No Yes (please describe):

56


Project Activities

Event Goal

Was the activity successful in meeting its goal?

Do you recommend spending more/less time on this activity?

Please note any recommendations on how this activity could be improved

Project Kick Off Meeting

Introduce the project and the team

Very successful

Somewhat

Not successful

More

Same

Less

Online Pulse Software Training

Know how to use the software

Very successful

Somewhat

Not successful

More

Same

Less

Workshop: Portfolio Action Plan Development (morning)

Learn a strategy for designing and implementing energy efficiency projects

Very successful

Somewhat

Not successful

More

Same

Less

Workshop: Measure Identification (morning)

Learn to use the Pulse EMIS to identify potential energy saving opportunities

Very successful

Somewhat

Not successful

More

Same

Less

Workshop: Building Walk Through (afternoon)

Know how to conduct a walk through and identify energy saving opportunities

Very successful

Somewhat

Not successful

More

Same

Less

Monthly Meetings

Aid measure identification and implementation

Very successful

Somewhat

Not successful

More

Same

Less

57


APPENDIX D – CHANGE TRACKING

Energy Manager Building Date Start Date End

Information from Pulse Software Information from Energy Manager

Effect seen? Description

Type of Change Description

A CT 6/29/2012 n/a Yes Suite 100 data is missing since June 29th. Occupancy New tenant occupied space and took over PG&E account

A CT 7/27/2012 n/a Yes Suite 205 data is missing since July 27th. Occupancy New tenant occupied space and took over PG&E account

A CT 8/1/2012 n/a Yes Suite 110 average energy use increased by about 1 kW Occupancy

Tenant space build outs and overall building occupancy increased from about 88% occupied to 95% occupied.

A CT 10/1/2012 n/a Yes

Building A & B base load electric demand is consistently about 4 kW above predicted. Note that a similar discrepancy appears in the baseline period (see Nov 2011). It appears to correct when predicted energy use increases in December. Occupancy

A EL 5/1/2012 n/a No

This building appears to be savings energy and an increase in occupancy would mean that savings may be understated. Occupancy

Overall building occupancy increased from about 90% occupied to 100% occupied.

B A 3/1/2012 n/a No No change visible. HVAC Economizer repair

B A 7/1/2011 n/a No No change visible. Lighting 30 bulbs LED retrofit

B B 5/13/2012 5/23/2012 Yes Higher than normal nighttime base load (33% increase). n/a n/a

B B 10/15/2011 12/10/2011 Yes

No weekend operation between these dates base load at about 65 kW (same nighttime average as rest of data). n/a n/a

B B 5/11/2011 5/20/2011 Yes Higher than normal nighttime base load (72% increase). n/a n/a

B C 3/1/2012 n/a No No change visible. HVAC Economizer repair

B E 3/1/2012 n/a No No change visible. HVAC Economizer repair

B EE 5/1/2012 9/1/2012 Yes Increase in energy use of about 5,000 kWh/mo. evident in CUSUM report n/a

Energy Manager believes this may be due to change in overtime HVAC service requests or some build-out of vacant space into ready suites and judges that it is too small to worry about.

B FF 4/1/2012 n/a Yes Energy savings of roughly 14,000 kWh per month evident in CUSUM report HVAC

Possibly due to programming changes, though Energy Manager reported starting those only in Oct/Nov.

58


Energy Manager Building Date Start Date End

Information from Pulse Software Information from Energy Manager

Effect seen? Description

Type of Change Description

B GG 10/1/2011 n/a Yes

Reduced peak (~175kW) and base load (~75kW) 10/1/2011. Starts to creep back-up around 4/20/2012. 5/9/2012 base load increased to 110kW and stays fairly constant. Peak load increases to between 250kW and 350kW depending on weekday type (weekday/weekend) and OA temp. Occupancy

Unoccupied 10/1/2011. Construction began 5/7/2012. Two chillers for a tenant server room on 3rd floor started operating week of 5/28/2012. Tenant occupies several floors starting May 24, 2012. Tenant moved in 10/22/2012. Floors 1, 2, & most of 3 are still vacant.

B J 1/1/2013 n/a Yes Baseload and the peak load increased dramatically. Occupancy

. Construction and tenant changes starting in January.

B K 1/1/2013 n/a Yes Baseload and the peak load increased dramatically. Occupancy

B L 1/1/2013 n/a Yes Baseload and the peak load increased dramatically. Occupancy

B M 1/1/2013 n/a Yes Baseload and the peak load increased dramatically. Occupancy

B M 2/1/2012 3/1/2012 Yes

Occupancy & datacenter

A new tenant moved in 2/2012 to 3/2012 and a two rack server room was installed.

B N 5/1/2012 n/a Yes Consistent lower energy usage since ~ May 2012 Occupancy One large tenant has down-sized.

B N 1/1/2013 n/a Yes Baseload and the peak load increased dramatically. Occupancy Construction and tenant changes starting in January.

B P 3/10/2012 5/9/2012 Yes Increase in base and peak loads Mar - May 2012 Occupancy New tenant moved in 5/9, preceded by construction work

B Q 8/1/2012 n/a Yes Consistent higher energy usage since ~August 2012 Occupancy Tenants moved in on 8/1

B R 7/1/2012 n/a Yes

It looks like there is consistent savings of about 22,000/month from July to Sept. in CUSUM report, this could represent an average of 3.7 hours/day on at 200kW reduction. Lighting Upgrade metal halide 400W to induction 200W

B X 12/5/2011 12/30/2011 Yes Night time base load increases >200kW (48% increase) n/a n/a

B Z 5/1/2012 11/1/2012 Yes Consistent lower energy usage since ~ end of May 2012 Occupancy

Construction 5/2012-6/2012. Old tenant moved out in May 2012, building is currently empty (9/2012). New tenant is expected to fully occupy by November 2012. New tenant to take over bill and meter also so we won't have data as of November 2012.

59


APPENDIX E – OPPORTUNITIES AND MEASURES

Energy Manager

Building ID

Opportunity

Origin

Measure Annual Savings Estimates Evaluation

Implemented? Schedule Energy Savings Assumptions Description Description

Electricity (kWh)

Demand (kW)

Natural Gas

(therm) NPV Benefits Disbenefits

A EL

HVAC appears to start and meet space setpoints well before building is occupied

EMIS + Energy Coach

Reduce the number of hours the HVAC equipment is running; start equipment 1 hour later

26,000

-

-

Reduced equipment wear Yes Q3 2012

Used Pulse for energy use data & assumed M-F reduction of 1 hour during start-up (4am to 5am)

A EL Very low space temperature setpoints

Energy Coach

Increase space temperature setpoints

15,146

-

-

Potential occupant dissatisfaction No

Current average occupied setpoints are 70 cooling; change setting to 75. 12 hours a day.

A EL

Large base load suggests tenant equipment may be left on at night

EMIS + Energy Coach

Implement an occupant engagement strategy & conduct regular night walk throughs

31,915

-

-

$ 2,997 Yes Q4 2012

Used Pulse and assumed 2% savings on WB level for entire year.

A EL

Boiler is operating when no reheat is needed. Lockout temperature set at 85 F

Energy Coach

Change boiler lockout from 85F OAT to 70F OAT. If no problems occur, lower further to 60F.

4,990

-

4,066 Yes Q4 2012

Used Pulse and TMY data. Only gas usage in facility is for boiler.

A EL Garage lighting is on all the time

Energy Coach

Replace with bi-level lighting with integrated occ. Sensor

6,383

-

- No

Assumed garage lighting is 2% of total and 20% savings based on PIER Case Study.

A EL

4th floor lighting schedule extends 4 hours beyond occupancy

Energy Coach

Reduce lighting schedule to coincide with occupancy negligible Yes Q3 2012

Negligible energy savings because on 2 of 4 floors the lighting went off an hour earlier than required and this was also corrected.

60


Energy Manager

Building ID

Opportunity

Origin



Electricity (kWh)

Demand (kW)

Natural Gas


A EL Elevator room kept unnecessarily cool at 69F

Energy Coach

Increase elevator room setpoint to 74F negligible Yes Q4 2012

A EL

Warm air from the electrical room is vented directly to the return air plenum

Didn't become a measure No

A EL

Strong solar gain through the South and West exposures

Didn't become a measure

Improved occupant comfort No

A EL

Building automation system sweeps lights off once in the evening, but if they are turned on by tenants or janitorial staff they may be left on all night


A CT A,B

Old mercury switch thermostats are being upgraded to digital thermostats that can be programmed to setpoints and schedules prescribed by tenant leases

Energy Manager

Reduce the number of hours the HVAC equipment is running

32,484

-

-

$ 10,300

Potential occupant dissatisfaction Yes Q3 2012

Used Pulse to estimate kWh savings. Baseline 6am-8pm M-F, and 6am-6pm Sat-Sun. Post assumes HVAC schedule is 6am-6pm M-F, and off on Sat/Sun.

A CT A,B

Central plant water loop serving heat pumps runs continuously

EMIS + Energy Coach

Optimize central plant

48,927

-

-

$ 47,200 No

Assumes turning off the central plant for 10 hours a day, 365 days/yr. Pump & fan energy only.

A CT A,B

Central plant cooling tower equipped with two-speed fan. Tower near end of life.

Energy Coach

When replacing cooling tower, purchase model with VFD.

7,404

-

-

$ 9,762

Reduced equipment wear Yes Q1 2013 Engineering estimate

A CT A,B

RTUs may function inefficiently if they have not been tuned-up recently

Energy Coach RTU tune-up

7,098

-

-

$ 1,900 No

Extrapolated from estimated average unit energy savings from an RTU tune-up program. Assumed 6 RTUs

A CT A,B

Boiler connected to the central plant water loop is sometimes on in the morning, even during the summer months

Energy Coach

Lockout boiler at high OA temperatures or outside of occupied hours

-

-

55

$ 280 No

Used Pulse and assumed boiler would be locked out for June-September

61


Energy Manager

Building ID

Opportunity

Origin



Electricity (kWh)

Demand (kW)

Natural Gas


A CT All

Many lights in unoccupied spaces are left on and do not have occupancy sensors

Energy Coach

Install switch mounted occupancy sensors for lights where possible

1,297

-

-

$ 1,400

Potential occupant dissatisfaction Yes Q3 2012

Assumes half office, half classroom; 10% of spaces don't have occ. sensors now; average office space LPD from 'An analysis of the energy and cost savings potential of occupany sensors for commercial lighting systems'

A CT All Some exit signs use incandescent lamps

Energy Coach

Convert incandescent exit signs to CFL or LED

3,060

0.4

-

$ 2,900 No

Savings from 'Save Energy, Money and Prevent Pollution with Light-Emitting Diode (LED) Exit Signs'. Assumed 10 exit signs.

A CT C Some tenant spaces were overlit

Energy Coach

Delamp where appropriate

19,263

7

$ 19,600 No

Assumed lights on 8am-6pm only, and 10% of total building area has opportunity.

A CT B

South facing windows fully exposed to sun, suggesting strong solar gains

Energy Manager

Add window film to the south and west facing windows

8,398

-

-

$ 4,900 Yes Q3 2012

Assumed windows are dual clear type, window film is high performance, and 10% of space needs window film. Vendor calculation.

A CT All

The property exhibits a high base to peak load ratio, suggesting additional equipment could be shut off at night

EMIS + Energy Coach


17,227

-

-

$ 2,400 Yes Q3 2012

Used Pulse energy use data and assumed 2% savings on whole building level for entire year.

A CT All

Cleaning crews operate at night, causing an increase in night time energy usage

Energy Coach

Change cleaning crew schedule to daytime.

2,190

-

-

$ 1,400 No

Used Pulse enegy use data and assumed cleaning is 365 days per year from about 8-10 pm. Based on load profile for 5/18/2012

B 6

Refrigerants that are less expensive than R-22 are also more energy efficient

Energy Manager

Replace R-22 refrigerant in RTUs with R-422

34,477

-

-

$ 24,800

Avoid R-22 price increase & environmental impact No

Energy manager estimated savings. Includes 5 buildings

62


Energy Manager

Building ID

Opportunity

Origin



Electricity (kWh)

Demand (kW)

Natural Gas


B 1

Gravity dampers on large supply fan cause pressure drop when fan operates

Energy Coach

Replace gravity dampers with motorized dampers

9,855

-

- No

Assumed total damper motor HP is 1 & operates 1 hour a day total. Includes 3 buildings.

B 1 Cooling tower fans have constant speed drives

Energy Manager

Cooling tower VFD retrofit

33,922

-

- Yes Q1 2013

Average savings per building sq. ft from 'A study on Energy Savings and Measure Cost Effectiveness of EBCx' and used average sq. ft of 11 central plant buildings. Includes 3 buildings.

B 11, 12 RTUs are very old and new models are more efficient

Energy Coach

Replace RTUs with new efficient RTU

1,497,600

-

- No

Assumed EER improvement from 8 to 11, cooling hours 7am to 7pm M-F. Includes 5 buildings.

B B Exterior lighting on during the middle of the day

Energy Coach

Fix photocell control to turn off all exterior lights during the day

158

-

- No

Assumed 2 bulbs on security circuit that can be turned off. Bulbs are CFLs 18W. One building.

B 6

Hot water boiler runs constantly, even when there is no demand

Energy Coach

Turn boiler off from June 21st to Sept 21st

-

-

13,208

$ 35,500

Possible increase in wear due to heating and cooling Planned Q2 2013

Used Pulse energy use data and assumed shut off July through September. Includes 5 buildings.

B 6 Interior stairwell lighting on all the time

Energy Coach

Retrofit stairwell lighting with occupancy sensors

3,526

-

- No

Assumed 3 T-8 28W per stairwell and 1 stairwell per building on 24/7 now and with occupancy sensor would be on for 1 hour a day total. Includes 5 buildings.

B 6 High power lighting in entryways is on all the time

Energy Coach

Replace high power entrance area lighting with CFL or LED downlights

57,816

-

-

$ 29,000

Longer life lamp means less frequent maintenance Planned Q2 2013

Assumed lights will be off 7pm to 7am M-F and all hours on weekends. Now lights are on 24/7. Includes 5 buildings.

B 6, 8

There are still some T-12 fluorescent lamps in these buildings

Energy Manager Retrofit T-12s

69,046 Planned Q2 2013

Used Pulse for energy use and estimated savings based on CEUS % end use allocation. Includes 8 buildings.

63


Energy Manager

Building ID

Opportunity

Origin



Electricity (kWh)

Demand (kW)

Natural Gas


B 6, A, B, C, D, E

HVAC appears to start and meet space setpoints well before building is occupied

EMIS + Energy Coach No

B 6, E

Holiday operation uses more energy than other unoccupied period operation

EMIS + Energy Coach No

B All

Cleaning crews operate at night, causing an increase in night time energy usage

Energy Coach

Change cleaning crew schedule to daytime

81,120

-

- No

Assumed 2 hours M-F and lighting reduction would save 6 kW. Includes all 26 buildings.

B B

Baseload of one building is much higher than that of a building of identical construction

EMIS + Energy Coach

Conduct night walk through and investigate what major equipment is on and if the high baseload is necessary

196,560

-

- No

Used Pulse energy use data and assumed 12 hours/weekday & all weekend every week of year (5,616 hours total/yr). One building.

B All 26

Weekend operation exceeds the duration of the tenant's overtime request

EMIS + Energy Coach

Building personnel to verify on a weekly basis that HVAC overtime requests match the actual HVAC overtime as seen in Pulse

585,130

-

-

$ 8,650

Reduced equipment wear Yes Q3 2012

Compared reported building occupancy for weekend beginning 6/15/2012 with estimated operation observed in Pulse. Difference between request hours and observed hours is savings. Assumed same for every other weekend 52 weeks a year.

B J

Night time spikes in energy use seem to indicate HVAC operation that does not appear to provide any benefits

EMIS + Energy Coach


B M

A steady rise in the base load indicates more equipment is being left on at night

EMIS + Energy Coach

Conduct night walk through and determine if baseload can be reduced back to 35 kW

196,560

-

-

$ 117,000 No

Used Pulse energy use data and assumed 12 hours/weekday & all weekend every week of year (5,616 hours total/yr). One building.

64


Energy Manager

Building ID

Opportunity

Origin



Electricity (kWh)

Demand (kW)

Natural Gas


B N

Baseload of one building is much higher than that of a building of identical construction

EMIS + Energy Coach

Conduct night walk through and investigate what major equipment is on and if the high baseload is necessary

645,840

-

- No

Used Pulse energy use data. 12 hours/weekday & all weekend every week of year (5,616 hours total/yr). One building.

B N

Large pressure differential between fan room and building

Energy Coach


B O, P, R

Hot water boiler must be on constantly for DHW heat exchanger

Energy Manager

Install DHW heater and shut boiler off based on demand

-

37,547 Yes Q4 2012

Used Pulse for average therm usage per year during baseline period. Estimated savings based on CEUS % end use allocation. Includes 3 buildings.

B All 26

Tenant equipment is left on when not in use (e.g. monitors)

Energy Coach


700,181

-

-

$ 72,000

Educational & builds tenant relationship Yes Q3 2012

Assumed 2% savings on WB level for entire year, used Pulse energy use data. Includes 23 buildings only because the baseload reduction measures above account for savings at 3 buildings.

B X, 6, 7, 9, 12

Outside air supply appears higher than required to maintain indoor air quality

Energy Coach

Reduce OA supply to minimum specified in ASHRAE Standard 62.1

1,339,346

-

-

Partially (2 buildings of 10) Q4 2012

Assumed OSA above 30% and reduction to ASHRAE minimum, used Pulse energy use data, and CEUS % end use allocations. Includes 10 buildings.

B X Two large chillers have constant speed drives

Energy Manager

Chiller VFD retrofit

200,000

-

-

$ 138,000 No

Used the SPC calculator. Conservatively assumed 1 chiller sized at 400 tons. Ignores benefits achieved when the second chiller is on. Similar estimate to vendor calc result. One building.

65


Energy Manager

Building ID

Opportunity

Origin



Electricity (kWh)

Demand (kW)

Natural Gas


B X, FF

Sequence of operations has not been optimized for energy efficiency

Energy Manager

Central Plant Control Reprogramming

1,282,459

-

18,513

$ 1,600,000

Partially (1 buildings of 2) Q4 2012

Average savings per building sq. ft from 'A study on Energy Savings and Measure Cost Effectiveness of EBCx'. Assumed 3 measures will be implemented per building. Includes 2 buildings.

California Energy Commissions Public Interest Energy Research Program (PIER). Bi-level Fluorescent Parking Garage Luminaires Case Study. University of California, Santa Barbara.

An analysis of the energy and cost savings potential of occupancy sensors for commercial lighting systems. IES Paper #43. August 2000.

'Save Energy, Money and Prevent Pollution with Light-Emitting Diode (LED) Exit Signs'. Energy Star. Portland Energy Conservation, Inc. "A Study on Energy Savings and Measure Cost Effectiveness of EBCx". Submitted to Lawerence Berkley National Laboratory. December, 2009.

Itron, Inc. "California Commercial End-Use Survey". Prepared for California Energy Commission. March, 2006.

Southern California Edison Standard Performance Contract SPC Software.

66


APPENDIX F – EMIS FUNCTIONAL REQUIREMENTS This appendix describes the EMIS needs of the Energy Managers and Energy Coaches in the program model tested by this project. The appendix is organized into the following sections:

1. Integration – Connection of the system to utility meter data 2. Accessibility – How user(s) access the system 3. Information Display – Viewing energy information in different formats 4. Measurement and verification (M&V) – Measuring energy savings 5. Persistence – Supporting persistence of energy savings over time

Integration To meet any of the Energy Coaches’ and Energy Managers’ needs in this program model, the software must first be capable of integrating with PG&E’s existing meter data systems. Requirements:

1. The EMIS can accept delivery by sFTP of compressed tab-delimited files containing customer data, extract the files and parse them to the correct customer accounts.

2. Maintain customer data in a secure, password protected environment. ISO 27001 is one possible indicator of compliance with this requirement.

Accessibility Fast, reliable and broadly available access was important to be sure that all project stakeholders could access the energy information when and where they needed it. Requirements:

1. Accessible from any computer with an internet connection. 2. Offering fast service. To a busy Energy Manager, waiting 10 seconds for a screen to load is a

frustration that distracts from the value of the EMIS. However, it is clear that the user’s connection speed has an influence here that cannot be controlled by the EMIS.

3. The system should be reliable, including redundancy as needed to avoid loss of data and to provide continuous service.

4. Limit user access to certain spaces/buildings and certain levels of information. The tenants in this program needed to see overall building level energy data, but not the variety of reports and analyses created by the Energy Coaches and Energy Managers.

Information Display One of the core features required of the EMIS is the ability to present energy information in an understandable way. This is the largest set of requirements, as it underpins all the other uses of the EMIS in this program.

67


Requirements: 1. Create calculated data streams to supplement the meter data streams. As an example, it should

be possible to create a point that is the sum of two or more of the incoming meter data streams. 2. Easy conversions between units. Some users are most familiar looking at btus, others with

therms. It should be easy to switch between these and other units. 3. Ability to change timescale to view highly detailed data over a short interval or less detailed data

over a long interval. 4. Benchmark building performance against other buildings in the portfolio. Energy Coaches and

Energy Managers found this a useful feature for focusing initial efforts on relatively high use buildings in the portfolio.

5. Create automated reports. Reports were created that automatically updated as new data entered the EMIS. These reports were periodically delivered by email to Energy Coaches and Energy Managers.

6. Support information views that aid in measure identification. While there are many views that might conceivably aid in measure identification, at least the following are recommended:

a. Time series plots with actual performance and an available indicator of expected performance.

b. Energy signature plots showing energy use versus outside air temperature. c. Time series overlays allowing energy use of different time periods to be overlaid on one

another. Measurement & Verification Nearly all stakeholders in the project expressed enthusiasm for being able to measure the energy impacts of their actions. This is a key feature to a program incorporating an EMIS that is expected to deliver cost reductions

Requirements: 1. Provide a whole building predicted energy use baseline against which to compare energy

savings. IPMVP Option C and D present preferred methods for creating this baseline, but others may be acceptable.

2. A method of recording when energy efficiency measures are implemented. 3. Reporting that compares actual energy use against the predicted energy baseline to estimate

energy savings following implementation of energy efficiency measures. 4. Annualized estimates of energy savings based on the predicted versus actual energy use

comparison. 5. Statistical measures that can be used to determine the uncertainty associated with estimated

energy savings consistent with IPMVP

Persistence

68


This study did not extend far enough into the post implementation period to directly assess the EMIS impacts on the persistence of energy savings, but that is an expected benefit. Extending the persistence of energy savings measures will increase the lifecycle benefits of energy saving measures and improve overall program cost-effectiveness. Requirements:

1. Ability to define performance thresholds and automatically generate alerts when the building’s performance crosses the threshold.

2. Automatically generate weekly or monthly reports on energy savings and send them to select users.

69


APPENDIX G –SAVINGS CLAIMED OUTSIDE OF PROGRAM The following projects received rebates through other PG&E programs.

Energy Manager

Building ID Origin

Measure Annual Savings Estimates Project Period Savings Estimates

Description Electricity

(kWh) Demand

(kW) Natural Gas

(therm) Electricity

(kWh) Demand

(kW) Natural Gas

(therm) A CT All PG&E Occupancy Sensor: Plug Load 68,738 13.3 (666) 17,185 3.3 (167) B Many PG&E Occupancy Sensor: Plug Load 53,945 17.0 -241 13,241 4.2 (59)

B Many PG&E Fixture Ext Induction - 400 W Baseline 57,487 1.0 -144 14,148 0.3 (36)

B A PG&E Lighting Retrofit/New-Ext-Linear-Fluorescent 17,630 1.6 0 4,408 0.4 -

B A PG&E Lighting Retrofit/New-Ext-Controls 4,709 1.1 0 1,177 0.3 -

B D PG&E Hi Eff Dishwasher Level 2 19 0.0 1 5 - 0


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Pulse Energy: Dashboard with Energy Manager - Phase B Report

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