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PG&E’s Emerging Technologies Program ET12PGE1381

FIELD ANALYSIS OF COMMERCIAL VARIABLE

REFRIGERANT FLOW HEAT PUMPS

ET Project Number: ET12PGE1381

Product Manager: Peter Biermayer Pacific Gas and Electric Company Prepared By: Harshal Upadhye Electric Power Research Institute 942 Corridor Park Blvd. Knoxville, TN 37932

Issued: December 2, 2014

Copyright, 2014, Pacific Gas and Electric Company. All rights reserved.

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ACKNOWLEDGEMENTS

Harshal Upadhye, of Electric Power Research Institute (EPRI), conducted this technology evaluation for Pacific Gas and Electric Company and is published as ‘Field Analysis of Commercial Variable Refrigerant Flow Heat Pumps. EPRI, Palo Alto, CA: 2014. 3002004364. The work was performed under the guidance and management from Chris Li and Keith Forsman of PG&E, which is responsible for this project. It was developed as part of Pacific Gas and Electric Company’s Emerging Technology – Technology Assessments program under internal project number ET12PGE1381. For more information on this project, contact Chris Li at [email protected].

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THIS IS AN EPRI TECHNICAL UPDATE REPORT. A TECHNICAL UPDATE REPORT IS INTENDED AS AN INFORMAL REPORT OF CONTINUING RESEARCH, A MEETING, OR A TOPICAL STUDY. IT IS NOT A FINAL EPRI TECHNICAL REPORT.

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FIGURES

Figure 1 PG&E Customer Service Office- Auburn, California ........... 7

Figure 2 Birds-eye View of PG&E Auburn Office Building (From

maps.google.com) ........................................................ 8

Figure 3 Basement Plan and Indoor Units ................................... 8

Figure 4 1st Floor Plan and Indoor Units ...................................... 9

Figure 5 2nd Floor Plan and Indoor Unit Locations ......................... 9

Figure 6 3rd Floor Plan and Indoor Unit Locations ....................... 10

Figure 7 Schematic of the Data Acquisition ............................... 14

Figure 8 Cooling Degree Day (CDD) and Heating Degree Day

(HDD) (Base 65°F) ..................................................... 15

Figure 9 Measured Temperature (68-80°F Comfort Zone) ........... 15

Figure 10 Measured Relative Humidity (20-80% Comfort Zone) .... 16

Figure 11 Outdoor Conditions Split in Temperature and Relative

Humidity Bins ............................................................ 17

Figure 12 Outdoor Conditions Split in Temperature and Relative

Humidity Bins (VRF System in Occupied Mode) .............. 17

Figure 13 Load Shape of VRF System (All Year Average; Summer

and Winter) ............................................................... 18

Figure 14 Comparison between PG&E Meter Data and EPRI HVAC

Monitoring Data ......................................................... 20

Figure 15 Recorded Billing Demand and VRF System HVAC

Demand .................................................................... 21

Figure 16 Average Power Draw versus Temperature Bins ............. 22

Figure 17 Indoor Unit Operating Hours in Heating or Cooling

Mode (All 13 Units Combined) ...................................... 24

Figure 18 Operating Hours in Each Mode (Fan, Cooling, Heating

and Mixed) for the VRF System .................................... 25

Figure 19 Indoor Unit 8A and 8B Operating in different Modes

during the Same Time ................................................ 26

Figure 20 Number of Hour’s Indoor Unit 8A and 8B are Operating

in Opposite Mode ....................................................... 26

Figure 21 Operating Mode and Hours for Indoor Unit in Data

Center ...................................................................... 28

Figure 22 Minimum Temperature Recorded for Each Month for

Return Air in the Data Center....................................... 28

Figure 23 Monthly Capacity Delivered for Each Floor .................... 30

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Figure 24 Average EER versus Temperature Bins ......................... 31

Figure 25 Calibrated VRF Systems Modeled Energy Use vs

Metered Energy Use ................................................... 34

Figure 26 Energy Use Intensity for the VRF and PSZ Models

Highlighting the Source of Energy Savings .................... 35

TABLES

Table 1 Summary of VRF Systems Considered for Monitoring ....... 6

Table 2 California Climate Zone (CZ) for Sites Considered ........... 6

Table 3 Outdoor Units ........................................................... 10

Table 4 Indoor Units ............................................................. 11

Table 5 Accuracy of Sensors Used .......................................... 13

Table 6 Comparison of PG&E Billing Data and EPRI VRF System

Monitoring Data ......................................................... 19

Table 7 Maximum Demand from VRF System ........................... 21

CONTENTS

FIELD ANALYSIS OF COMMERCIAL VARIABLE REFRIGERANT FLOW HEAT PUMPS 1

EXECUTIVE SUMMARY ____________________________________________________ 1

INTRODUCTION _________________________________________________________ 3

BACKGROUND __________________________________________________________ 4

ASSESSMENT OBJECTIVES __________________________________________________ 5

TECHNOLOGY/PRODUCT EVALUATION ________________________________________ 5

site selection ......................................................................... 5

Site Details ............................................................................ 7

Emerging Technology/Product ................................................ 10

System Control Scheme ........................................................ 11

Fan Mode ....................................................................... 11 Cooling Mode .................................................................. 12 Heating Mode ................................................................. 12

TECHNICAL APPROACH/TEST METHODOLOGY _________________________________ 12

System Monitoring ............................................................... 12

Equipment Used ................................................................... 12

EVALUATIONS/ANALYSIS _________________________________________________ 14

Weather .............................................................................. 14

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Electrical Characteristics ....................................................... 18

Thermal Characteristics ......................................................... 22

Determining mode of operation of indoor unit ..................... 22 Outdoor unit operating mode ............................................ 23

Operating Hours ................................................................... 23

Capacity Measurements ........................................................ 29

MODELING ____________________________________________________________ 31

Model Development .............................................................. 31

Input Assumptions .......................................................... 32

Envelope ............................................................................. 32

Internal Gains ...................................................................... 32

HVAC - VRF .................................................................... 32

Model Calibration ................................................................. 33

Weather Data ................................................................. 33 Metered Data .................................................................. 33 Calibration Process .......................................................... 33

Packaged Single Zone Model .................................................. 34

Energy Savings .................................................................... 34

DISCUSSIONS AND CONCLUSIONS __________________________________________ 35

RECOMMENDATIONS ____________________________________________________ 37

APPENDICES __________________________________________________________ 38

Monitoring Equipment ........................................................... 38

Obvius AcquiSuite A8810 – Main Data Acquisition Server ..... 38 Obvius Modhopper R9120-5 .............................................. 39 Obvius Flex IO – A8332-8F2D ........................................... 40 Dwyer Series RHP – Humidity/Temperature Transmitter ....... 41 Dwyer Series RH-R – Humidity/Temperature Transmitter ..... 42 ACCU-CT – Split-Core Current Transformer ........................ 43 ELKOR WattsOn .............................................................. 44

Installed mitsubishi equipment .............................................. 45

PURY-P288TSJMU-A ......................................................... 45 PVFY-P18E00A ................................................................ 46 PKFY-P06NAMU-E ............................................................ 47 PKFY-P30NFMU-E ............................................................ 48 PEFY-P36NMAU-E ............................................................ 49 PEFY-P24NMAU-E ............................................................ 50 PEFY-P48NMAU-E ............................................................ 51 PLFY-P08NCMU-E ............................................................ 52 PLFY-P15NCMU-E ............................................................ 53 CMB-P1013NU-GA ........................................................... 54

filters applied to monitored data ............................................ 55

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MODELING APPENDIX ........................................................... 61

ZONING ......................................................................... 61

REFERENCES ___________________________________________________________ 62

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EXECUTIVE SUMMARY There is a need for detailed measurement of field performance of variable refrigerant flow

heat recovery systems (VRF-HR) to both help characterize actual yearly energy savings

potential, and to provide quality data for use in energy modeling verification. This project

comprised instrumenting and measuring the in-situ performance of such a system in the

Northern California region.

Data representing thermal and electrical characteristics of the VRF system was collected

from the site for a period of 1 year – from June 2013 to May 2014. The electrical

characteristics were used to determine the energy used, load profile, and demand imposed

by the system on the grid.

As a part of this project, the building and the VRF system were modeled by PECI, Inc. The

results from the modeling exercise are presented in this report. The energy model was

developed using AecoSim Energy Simulator (AES), which is a front end for EnergyPlus.

PROJECT GOAL

This report documents the findings from a monitoring exercise on a 13 zone VRF-HR (heat

recovery) system. The project had the following objectives:

To collect operational performance data on an installed VRF-HR system

To collect a data set that is appropriate to provide energy modeling developers with

a validation tool

To model and compare VRF performance to a companion 2008 Title 24 code

compliant HVAC system in the same, or a similar, building

Provide objective analysis and performance characterization of a field installed VRF-

HR system

The data set will also be available for any further analysis or validation of new VRF

models.

PROJECT DESCRIPTION

The selected site for this VRF field monitoring project is a 4-Floor PG&E office building in

Auburn, California which is in California Climate Zone 11.

The VRF system installed at this location is a 24 ton Mitsubishi City Multi 2-pipe VRF system

with heat recovery capabilities (simultaneous heating and cooling operation is possible). The

system has a total of 13 indoor units connected to it.

PROJECT FINDINGS/RESULTS

The objective of this project was to monitor the in-situ performance of a VRF system and

provide performance characterization based on the data recorded. A summary of observed

characteristics is as follows:

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1. The monitored ambient conditions show slight variation from the published weather

data for Auburn, California. The variations can be attributed to the limited data set

that is available for the site - single point ambient measurements made only for one

year.

2. Summer load shape shows high demand during peak periods for utilities (coincident

load). The winter load shape shows a high demand imposed outside of the office

hours (early mornings). The trends from the demand data show that during the

winter time, the VRF system maximum demand is during the very early morning

hours (2:00 am to 5:00 am) whereas in summer time the maximum demand is

during the morning startup phase or during hot afternoon hours.

3. The high demand during summer peak hours makes the VRF installation a potential

candidate for a Demand Response program. The significant controls as well as

communications capabilities further necessitate investigation into the DR

possibilities.

4. The high demand during the early morning startup period could be eliminated by

staging the units during the initial ramp-up. This can be done by setting different

occupied / unoccupied time periods for different units.

5. The difference between PG&E billing data and EPRI measurements indicate that the

average energy usage by other loads in the building is 3,865 kWh per month.

6. The outdoor conditions in which a VRF system is operating have significant impact on

the power draw from the system. As expected, at extremes of temperature range,

the power draw is higher (either cooling mode or heating mode) and in the milder

ambient conditions the power draw is lower.

7. The second floor has the least heating or cooling needs. The third floor, due to the

roof, sees higher impact from ambient conditions. The first floor which has a

customer entrance and high ceilings in the customer service area is where most of

the capacity is delivered.

8. Indoor units 8A and 8B which serve third floor open space operated in opposite mode

(one in cooling and other in heating) at the same time for 39 hours during the period

of monitoring. Since the units serve the same space, it appeared that the units were

fighting each other. This can be remedied by grouping units together and forcing

them to operate in a single mode. That way the systems don’t fight each other. This

can also be done for indoor units 4A and 4B as well as 7A and 7B.

9. Indoor unit 2 serves a small data center which also has a backup split system. The

cooling from the backup system was potentially forcing the indoor unit 2 to operate

in heating mode. The data center is usually a cooling load so heating mode operation

of the indoor unit 2 isn’t expected. Through the control scheme, this indoor unit can

be locked in cooling mode or the setback temperature can be reduced significantly so

that the unit doesn’t kick into heating mode.

10. Modeling showed that the EnergyPlus model can predict the energy usage of the

modeled building within ±15% of actual energy use for the VRF system. Comparison

between a modeled baseline and a VRF system showed significant energy savings in

heating mode and fan energy savings.

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PROJECT RECOMMENDATIONS

Based on the data analysis and performance characterization, a few recommendations are

made that are applicable to this site but can also be extended across other VRF installations.

The biggest opportunity in terms of energy savings in a VRF technology is the ability to

modulate components as well as change local set points while maintaining occupant comfort

throughout the building. Control over fan speed and tying fan speeds, occupancy and

ventilation air (fresh air) supply together might reduce the load on the system. The control

scheme shared for the purpose of this project indicates that the fan runs when the system

has any indoor unit operating. Thus, in winter months the outdoor unit brings in outside

cold air when there is no need for fresh air (unoccupied mode).

Another energy savings opportunity based on findings of this study is the opportunity for

continuous commissioning. The indoor units fighting each other or the data center indoor

unit operating in heating mode are opportunities to save energy which is wasted if the

system operation is not reviewed. The existing sensors and controls on the system are

capable of determining these issues. If incentives for continuous commissioning are used in

such situations, further energy savings could be realized. Commissioning at time of install

can also be monitored carefully to make sure building characteristics are taken into

consideration. This building for example is a historic building with substantial air leakage

and minimum insulation. The winter operation of this system is heavily dependent on the

type of building and less so on the actual control scheme of the building.

There is an opportunity to investigate demand response potential of this technology

especially since this is a coincident load during summer time. The controls and

communications capability are already included in the product and unlocking the potential

could be the next step to further benefit from this technology.

INTRODUCTION At the heart of the drive towards making buildings highly energy efficient is the need to use

the precise amount of energy required to perform certain tasks, and no more. The historical

norm, with a source of plentiful and inexpensive energy, was to use energetically competing

systems that ultimately balance according to comfort and task execution needs, without

serious regard to energy consumption. The new approach is to understand the overall

exchange of energy on a temporal basis throughout a building, including the exchange with

the outside environment and the needs of the interior building functions. Using that

understanding, you can implement systems that provide for these needs – space

conditioning, lighting, appliances, etc. – treating energy as a valuable and limited resource

that should be expended only as necessary.

Technological improvements in the Heating, Ventilation, and Air Conditioning (HVAC)

industry focus on matching the energy supplied (e.g., cooling or heating) to the load

demanded, and doing so with smooth control and efficient delivery. New technologies like

Variable Refrigerant Flow (VRF) which employ inverter driven technology, variable speed

drives for motors and compressors, on-board diagnostics and inexpensive controls have

made it possible to provide highly efficient and flexible cooling and heating.

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In addition to energy efficiency, demand response (DR) for peak load reduction, reducing

facility loading, managing renewable integration, and other uses are important to utilities.

New technologies for adjustment of power used by air conditioners, water heaters and

appliances are being introduced around the country.

Many utility programs base incentive amounts and calculated energy savings on the

marginal difference between rated efficiencies of particular classes of HVAC equipment, such

as packaged rooftop air conditioners and heat pumps. The inherent variability in VRF

equipment lends the equipment to be characterized based on single point fixed operation

mode. This generates questions as to the direct applicability of the rating test as an

accurate representation of actual field performance relative to other unitary equipment. The

interaction of the HVAC system with the building is another important parameter that is not

addressed in laboratory testing.

This report documents the findings from a monitoring exercise on a 13 zone VRF-HR (heat

recovery) system.

BACKGROUND Over the course of the last several years, a VRF rating standard was developed and resulted

in the ANSI/AHRI standard 1230: Performance Rating of Variable Refrigerant Flow (VRF)

Multi-Split Air-Conditioning and Heat Pump Equipment. This standard identifies the

methodology for determining standard cooling, heating and simultaneous cooling & heating

operational efficiency. The intent of the standard was to allow comparison of VRF equipment

performance with that of unitary equipment at similar operating conditions.

Many utility programs base incentive amounts and calculated energy savings on the

marginal difference between rated efficiencies of particular classes of HVAC equipment, such

as packaged rooftop air conditioners & heat pumps. Comparison of VRF to traditional unitary

equipment in this similar manner represents a partial change in approach since two different

classes of HVAC equipment are being compared. The crafters of the 1230 rating standard

attempted to address this by making the testing conditions and methodology as similar to

the unitary standards (ANSI/AHRI 210/240 and 340/360) as possible by allowing for VRF

systems to be operated at manufacturer-determined fixed operating conditions (compressor

& blower fan speeds and expansion valve openings). This leaves a rating standard which

tests equipment at fixed operation, while the same equipment in the field will vary its

operation in accordance with changing load. This creates questions as to the direct

applicability of the rating test as an accurate representation of actual field performance

relative to other unitary equipment.

Much of the potential energy savings attributed to VRF systems may come from the

interaction of the system with the building—such savings would not be captured by a rating

test. Examples of this type of savings are: lower convection losses from refrigerant lines

compared to ductwork, delivery of conditioned air more directly to the occupied space,

rather than to the entire building volume and increased zoning with individual temperature

control.

Simple comparison of rating numbers may turn out to be a valid method for comparing VRF

to unitary systems, but there are currently sufficient questions that require further

understanding. Currently, energy savings derived from VRF use are generally considered

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difficult to characterize via any deem-able method and are thus typically modeled via

EnergyPro, Energy Plus, and related building simulation software packages.

Laboratory testing is used for characterization and verification of equipment performance,

but does not address the HVAC system interaction with the building. Field testing will be

used to develop energy and power consumption profiles of the integrated building/HVAC

(VRF-HR) system. Robust field data can then be used to vet and validate VRF modeling

modules, with the aim of producing reliable and repeatable models of energy and power

draw characteristics of buildings using VRF systems.

ASSESSMENT OBJECTIVES There is a need for detailed measurement of field performance of variable refrigerant flow

heat recovery systems (VRF-HR) to both help characterize actual yearly energy savings

potential, and to provide quality data for use in energy modeling verification. This project

will comprise instrumenting and measuring the in-situ performance of such a system with

the following objectives

To collect operational performance data on an installed VRF-HR system in the PG&E

service territory. This would include power and energy draw, ambient air conditions,

delivered zonal capacity and relevant system measures, sufficient to provide an

accurate picture of overall system operation.

To collect a data set that is appropriate to provide energy modeling developers with

a validation tool.

To model and compare VRF performance to a companion traditional HVAC system in

the same or a similar building.

Provide objective analysis and performance characterization of a field installed VRF-

HR system.

The data set will also be available for any further analysis or validation of new VRF

models.

TECHNOLOGY/PRODUCT EVALUATION

SITE SELECTION PG&E provided mechanical and electrical drawings for four PG&E buildings which were

retrofitted with VRF systems. EPRI was encouraged to select a PG&E owned site to keep

administrative tasks to a minimum. The four sites (referred to as Site 1, 2, 3 or 4) under

consideration were –

Site 1, PG&E Auburn Office Building, 1050 High Street, Auburn, California 95603

Site 2, PG&E Eureka Service Center, 2555 Myrtle Avenue, Eureka, California 95501

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Site 3, PG&E Martin Service Center, 731 Schwerin Street, Daly City, California,

94014

Site 4, PG&E Redding Ops, 3600 Meadow View Drive, Redding , California 96002

The sites were evaluated based on the following criteria –

1. Installed system size – Each indoor unit connected to the VRF system has to be

monitored for supply and return air temperature and relative humidity. Considering

the instrumentation, complexity and associated costs of measuring these parameters

at each indoor unit systems with minimum indoor units was preferred.

TABLE 1 SUMMARY OF VRF SYSTEMS CONSIDERED FOR MONITORING

Site 1 Site 2 Site 3 Site 4

Total refrigerant circuits 1 1 2 4

Installed Capacity (Tons) 24 24 20,24 18,18,6,8(OA)

Brand Mitsubishi Mitsubishi Mitsubishi Daikin

Heat Recovery / Heat Pump HR HR HR, HR HR,HR, HP,HP

Electrical 208 / 3 / 60 208/3/60 460 / 3 / 60 460 / 3 / 60

Number of Indoor Units 13 21 11, 10 17,15,2,2

2. Site 2, Site 3 and Site 4 have in excess of 20 indoor units for the entire site. Site 3

and Site 4 had multiple separate VRF systems installed (separate refrigerant circuits)

out of which one could be chosen. In order to monitor the entire site, such an

approach of measuring only one refrigerant circuit was not pursued. From an

installed system size perspective Site 1 (Auburn Office Building) seemed to be a

good fit.

3. Climate Zone – The climate in which the system operates is an important

consideration. Table 2 shows the California climate zones (CZ) for the sites

considered.

TABLE 2 CALIFORNIA CLIMATE ZONE (CZ) FOR SITES CONSIDERED

VRF Site Site 1 Site 2 Site 3 Site 4

Climate Zone 11 1 3 11

California CZ 11 (Red Bluff, Auburn) is characterized by distinct cooling and heating days.

Heating requirements dominate the months from November through March whereas June

through September is dominated by cooling requirements. April, May and October can be

considered as shoulder months. A heat pump system installed in this location will be loaded

in both the heating months and the cooling months.

California CZ 1 (Eureka, Klamath) is the coolest climate in California with mostly heating

only requirements. The summers are warm enough to call for cooling on a few days.

California CZ 3 (Oakland, San Francisco) has predominantly heating requirements with a

few days of cooling required. The overall climate is mild which keeps the energy

consumption low.

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CZ 11 was considered most demanding of the three CZ’s under consideration. Site 1 which

passed the system size muster is also in the CZ 11.

Based on the two criteria, Site 1 (PG&E Auburn Office Building) was selected. A few other

things were confirmed before a final decision was made on this particular site:

1. Baseline system – A baseline system will not be monitored for this site (the new VRF

systems were already installed when this project started). Instead, billing data prior

to the VRF system being installed will be used. The building did not have any other

efficiency improvement measures. The only change made was replacing the chiller

and boiler combo with a VRF system.

2. Site details – A site visit involving EPRI engineer, PG&E engineers and local HVAC

contractor was completed on March 6th 2013. Purpose of the site visit was to

understand the ‘as built’ system and the site specifics not shown in drawings. Items

investigated were:

a. Ceiling type for wiring purposes

b. Access to indoor and outdoor units and electrical panels

c. Available space or potential locations for mounting monitoring boxes

d. Briefing HVAC contractor on scope of the project

e. Cellular signal strength for data connection to remote EPRI server

f. Generating a picture library which will help in developing monitoring plan

Based on the information gathered during the site visit, site 1, PG&E Auburn Office Building,

was determined to be a good fit for this project.

FIGURE 1 PG&E CUSTOMER SERVICE OFFICE- AUBURN, CALIFORNIA

SITE DETAILS Figure 1 shows the elevation of the PG&E Customer Service Center in Auburn, California.

The selected site is a 4 floor (a basement and three above ground floors) office building with

approximately 8466 square feet of conditioned space. This building has a front (ground

level) customer service center with high ceilings and the remainder of the building space is

8


designated for cubicles, offices, conference room, kitchen, storage and bathrooms. Figure 2

shows the office building from a bird’s eye view.

FIGURE 2 BIRDS-EYE VIEW OF PG&E AUBURN OFFICE BUILDING (FROM MAPS.GOOGLE.COM)

FIGURE 3 BASEMENT PLAN AND INDOOR UNITS

Figure 3 shows the floor plan for the basement of the building. The basement floor space is

split into storage area and office area, a small data center seen in the right side of the plan

and an unoccupied area to the left side. Two indoor units serve the entire basement, IHP-1

and IHP- 2 (Table 4 ). The hashed area in the floor plan indicated tiled ceilings. The data

center side is the front side of the building facing the street. The orientation is the same for

all the plan views.

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FIGURE 4 1ST

FLOOR PLAN AND INDOOR UNITS

Figure 4 shows the first floor plan for the building. The first floor has a front customer

service area (right side area) and behind it is open cubicle space as well as partitioned office

and bathrooms. The first floor is served by indoor units IHP-3, IHP-4A and IHP-4B (Table 4).

FIGURE 5 2ND

FLOOR PLAN AND INDOOR UNIT LOCATIONS

Figure 5 shows the floor plan for the second floor. Second floor has reduced floor space due

to high ceilings from the first floor. The second floor has two offices, an open cubicle area

and a bathroom. The entire second floor is served by either ceiling cassettes or wall mount

units. This floor has no ducted units. IHP-5A, IHP-5B, IHP-6, IHP-7A and IHP-7B serve this

space.

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FIGURE 6 3RD

FLOOR PLAN AND INDOOR UNIT LOCATIONS

Figure 6 shows the plan for the third floor of the building. The third floor has three offices, a

large open cubicle space and a bathroom. This space is served by three ducted indoor units

– IHP-8A, IHP-8B and IHP-8C. The original plans included only two indoor units but

complaints from occupants from the office spaces in corner east office and the center office

required addition of the third indoor unit IHP-8C.

EMERGING TECHNOLOGY/PRODUCT The VRF system installed at this location is a 24 ton Mitsubishi City Multi VRF system with

heat recovery capabilities (simultaneous heating and cooling operation is possible). The

system has a total of 13 indoor units connected to it. Of the 13 indoor units, 6 are ducted

units, 2 wall mount units and 5 ceiling cassettes. The system also includes a ventilation

system bringing in fresh air from the outside and feeding on the return air side of one

indoor unit on each floor. The specification sheets for each component in the HVAC system

is attached in the Appendix A. An equipment summary is included in Table 3 (outdoor units)

and Table 4 (indoor units).

TABLE 3 OUTDOOR UNITS

Outdoor Unit Model Number Cooling Capacity (MBH)

Heating Capacity (MBH)

Input Power (kW)

Refrigerant

OHP-1

PURY-

P144TJMU-A 144 160 27.19 R410A

OHP-2

PURY-

P144TJMU-A 144 160 27.19 R410A

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TABLE 4 INDOOR UNITS

Indoor Unit

Floor Air Flow (cfm)

Cooling Cap (MBH)

Heating Cap (kW)

Model Number Type

IHP-1 Basement 385 18 5.86 PVFY-P18E00A Vertical AHU

IHP-2 Basement 989 30 - PKFY-P30NFMU-E Wall Mount

IHP-3 1st 1,376 15 5 PEFY-P36NMAU-E Ducted

IHP-4A 1st 635 24 7.9 PEFY-P24NMAU-E Ducted

IHP-4B 1st 635 24 7.9 PEFY-P24NMAU-E Ducted

IHP-5A 2nd

350 6 2 PLFY-P08NCMU-E Cassette

IHP-5B 2nd

350 6 2 PLFY-P08NCMU-E Cassette

IHP-6 2nd

208 6 2 PKFY-P06NAMU-E Wall Mount

IHP-7A 2nd

390 12 2.6 PLFY-P15NCMU-E Cassette

IHP-7B 2nd

390 12 2.6 PLFY-P15NCMU-E Cassette

IHP-8A 3rd

1,342 48 16 PEFY-P48NMAU-E Ducted

IHP-8B 3rd


IHP-8C 3rd


The branch controller is a Mitsubishi model CMB-P1013NU-GA. The central controller is a

GB-50A which is the controller that implements the system control scheme.

SYSTEM CONTROL SCHEME The system is on a central control which has defined modes of operations for indoor units,

setback and occupied / unoccupied modes. The building is considered occupied in between

6:00 am and 6:00 pm five days of the week. Saturday and Sunday’s are considered

unoccupied. The system is also in unoccupied mode during holidays. The fans are always ON

when the building is in occupied mode.

FAN MODE

In fan mode, the units operate with providing any heating or cooling. The control scheme is

such that whenever the building is occupied, all zones run in fan mode if they are not

providing heating or cooling. This means that the units never actually stop moving air when

the building is occupied. This is done to make sure the fresh air (outdoor air) requirements

are met. The fresh air fan is in the third floor attic space with ductwork from the fan going

to one indoor unit on each floor. The ductwork is from fresh air fan is connected to the

return air side of the indoor units. The air is considered untreated since there is no separate

HVAC system handling the outside air. The fans are set in a fixed speed mode to provide

required airflow rate through each zone. The modulating (multi-speed) capability of the

indoor units is not utilized.

12


COOLING MODE

In cooling mode the supply air has lower temperature and higher relative humidity than the

return air. The set point in cooling mode is 72°F and can be adjusted ±2°F by the

occupants.

HEATING MODE

In heating mode the supply air has higher temperature and lower relative humidity than the

return air. The set point in heating mode is also 72°F and can be adjusted ±2°F by the

occupants.

The controllers are programmed with a dead band of 1.8°F between heating and cooling

mode. The indoor units cannot be changed from one mode to another by the occupants.

That control rests with the system which determines the operating mode based on the set

point and the dead band. Within the dead band the system operates in fan mode.

TECHNICAL APPROACH/TEST METHODOLOGY

SYSTEM MONITORING The system is monitored for two characteristics – electrical and thermal from the time of

install (approximately end May 2013) for a period of 1 year. Data from numerous channels

monitored is recorded every minute (1 minute resolution data).

The electrical characteristics include power draw (kW), energy consumption (kWh), voltage

(V), current (I) and power factor (PF) at the outdoor units and indoor units. The indoor units

on each floor of the building are connected to a single breaker. The electrical characteristics

at this breaker would be monitored (four in all) in order to keep the instrumentation effort

within reason.

The thermal characteristics will include temperature (T) and relative humidity (RH)

measurements at various points in the building. The T and RH are made at supply air and

return air of each of the 13 indoor units. The ambient (outside) T and RH will also be

measured close to the outdoor unit with precautions taken to keep the sensor away from

the exhaust air stream of the outdoor units. Based on the T and RH measurement and the

air flow measurements from the test and balance report (already provided) capacity

measurements for each indoor unit will be made. For the non-ducted units, the air flow will

be assumed to be the rated air flow from the manufacturer.

EQUIPMENT USED Power meter – Elkor WattsOn – Revenue Grade

Current Transformers (CT) – Continental Controls (100, 20 and 5 amps) – Revenue Grade

Temperature and Relative Humidity - Dwyer (2 different models)

Communications – Obvius products

13


- AcquiSuite – data acquisition server

- FlexIO – universal input / output module

- ModHopper – wireless Modbus transceiver

- Cell Modem – Airlink 3G

Specifications of all the monitoring equipment used are provided in the Appendices. The

accuracy of the sensors used is shown in Table 5.

TABLE 5 ACCURACY OF SENSORS USED

Instrument Accuracy

Dwyer RHP-2D11 RTD Temperature ±0.3°C @ 25°C

Dwyer RHP-2D11/2R11 RH ±2% 10-90% RH @ 25°C

Dwyer RHT-R016 Temperature ±2% @ 10-90%

Dwyer RHT-R016 RH ±2% @ 10-90%

Elkor WattsOn <0.2% @ 25°C

Accu-CT ±0.75%

Miscellaneous hardware includes NEMA 4X boxes, power supplies, fuses and power strips. A

schematic of data acquisition setup is shown in Figure 7. The AcquiSuite is the main on-site

data acquisition server and the entire site has only one AcquiSuite. The AcquiSuite collects

data from all the sensors (minute resolution) and stores it on its onboard memory. Data

from the AcquiSuite memory is uploaded to EPRI server every eight hours using a 3G cell

connection. Numerous fail safe software procedures are programmed into the AcquiSuite to

avoid any data loss.

The ModHopper is a wireless transceiver that can communicate with the AcquiSuite and with

other ModHoppers. The data is gathered from all the sensors attached to a FlexIO and

handed over to the ModHopper to transmit data wirelessly to the AcquiSuite. Numerous

ModHoppers, FlexIO’s and sensors can be connected to the system. For sake of simplicity

only one such ModHopper is shown. The site will have at least five ModHoppers (one for

each floor and one at the outdoor unit) that will talk to the AcquiSuite and amongst each

other to transmit the data.

14


FIGURE 7 SCHEMATIC OF THE DATA ACQUISITION

EVALUATIONS/ANALYSIS The monitored data, collected for 1 year, from June 2013 to May 2014, is analyzed in this

section. The charts show the data from January to December for ease of reading. It must be

noted that January through May data is actually from year 2014 whereas June through

December data is from year 2013.

WEATHER The site lies in California Climate Zone 11 (CZ11). CZ11 is in northern California region

south of mountainous Shasta Region, east of Coastal Range and west of Sierra Cascades

according to Pacific Energy Center’s Guide to ‘California Climate Zones and Bioclimatic

Design’

http://www.pge.com/includes/docs/pdfs/about/edusafety/training/pec/toolbox/arch/climate

/california_climate_zones_01-16.pdf accessed 07/19/2014)

Auburn, per the design guide, is expected to have 3095 Heating Degree Days (HDD) and

1292 Cooling Degree Days (CDD). The HDD and CDD are determined by summing up the

average temperature per day below or above 65°F (base temperature). Figure 8 shows the

HDD and CDD’s calculated based on the monitored outdoor temperature at the site. The

numbers based on the actual site measurements show that the HDD’s were 2447.5 and

CDD’s were 1971.7.

Figure 9 shows the average, minimum and maximum outdoor temperature for each month

and also highlights the comfort zone between 68°F and 80°F. Figure 10 shows the average

outdoor relative humidity measured at 4 am and 4pm for each month.

Figure 8, Figure 9 and Figure 10 are included to compare the monitored data with trends

from the design guide. The monitored data shows slight variation from the data presented

in the guide. The variations can be attributed to the limited data set that is available for site

http://www.pge.com/includes/docs/pdfs/about/edusafety/training/pec/toolbox/arch/climate/california_climate_zones_01-16.pdf

http://www.pge.com/includes/docs/pdfs/about/edusafety/training/pec/toolbox/arch/climate/california_climate_zones_01-16.pdf

15


- single point measurement made only for one year. The design guide data is compiled

based on significantly large data set and is representative for the entire area than just one

point measurement made at the site.

FIGURE 8 COOLING DEGREE DAY (CDD) AND HEATING DEGREE DAY (HDD) (BASE 65°F)

FIGURE 9 MEASURED TEMPERATURE (68-80°F COMFORT ZONE)

16


FIGURE 10 MEASURED RELATIVE HUMIDITY (20-80% COMFORT ZONE)

Figure 11 shows entire outdoor temperature and relative humidity data set split out in

temperature and relative humidity bins. The numbers in the square indicate number of

hours the outdoor conditions were in a particular bin. For example, the outdoor conditions

were in the range of 72.5°F and 77.5°F and relative humidity of 32.5% and 37.5% for

115.3 hours. This chart is a graphical representation of the outdoor conditions experienced

by the VRF system. The comfort zone designated in the design guide is also superimposed

on the chart – the total number of hours in the comfort zone is 1872.5. Figure 12 shows the

same chart but the data is filtered for actual office hours (system occupied mode) which are

defined as Monday through Friday 6:00am to 6:00pm. The hours in comfort zone are

reduced to 823.4.

It must be noted that although these hours are in comfort zone, it doesn’t mean the HVAC

system is not operating. There are internal building loads that will necessitate HVAC system

operating.

17


FIGURE 11 OUTDOOR CONDITIONS SPLIT IN TEMPERATURE AND RELATIVE HUMIDITY BINS

FIGURE 12 OUTDOOR CONDITIONS SPLIT IN TEMPERATURE AND RELATIVE HUMIDITY BINS (VRF SYSTEM IN OCCUPIED

MODE)

18


ELECTRICAL CHARACTERISTICS As a potential energy efficient technology, the system electrical characteristics (energy and

demand) are of great interest. This section presents the analysis of monitored and recorded

electrical data for the site. Billing data provided by PG&E is also analyzed.

PG&E’s ‘Electrical Schedule A-10 Medium General Demand-Metered Service’

(http://www.pge.com/tariffs/tm2/pdf/ELEC_SCHEDS_A-10.pdf accessed 07/16/2014) is

used as a reference for defining various times of the year like summer and winter.

Load shape of the VRF system is shown in Figure 13. The load shape in this document is

defined as the average power draw (kW) during the hour for the entire system. By definition

the load shape does not include the maximum demand imposed by the system but just the

hourly average. The load shape is further split out in terms of a summer shape and winter

shape. Summer is defined time between as May 1st and October 31st. Summer load shapes

shows high demand during peak periods for utilities. Winter is defined as time between

November 1st and April 30th. The winter load shape shows a high demand imposed outside

of the office hours (early mornings). This indicates that the temperature in the zones is

dropping below the setback temperature on the controllers which in turn drives the VRF

system in heating mode. Although demand response is not a topic of research for this

project, the high demand during peak hours during summer period makes this type of an

installation a potential candidate for DR programs.

Further analysis on the indoor temperatures is provided in the Thermal Characteristics sub-

section of this chapter.

FIGURE 13 LOAD SHAPE OF VRF SYSTEM (ALL YEAR AVERAGE; SUMMER AND WINTER)

Billing data for the building was made available by PG&E for the purpose of this analysis.

The tabulated data is presented in Table 6. The meter reading date does not exactly align

http://www.pge.com/tariffs/tm2/pdf/ELEC_SCHEDS_A-10.pdf%20accessed%2007/16/2014

19


with month end dates. For example when month of January 2014 is considered, the actual

readings are from 12/25/2013 to 1/26/2014. The time period between the two dates is

considered as month of January since majority of the time is in month of January. The EPRI

data is also filtered to make sure the data presented corresponds to PG&E billing dates. The

PG&E billing data is for the entire building – it covers more than just the VRF system. It

includes lighting loads, a small data center, computers in the building and other plug loads.

The EPRI monitoring data captures all the energy used by the VRF system only. Figure 14

shows the energy data in a chart format. The summer months from May to October show

higher energy usage than the winter months. Figure 15 shows the demand data in chart

format.

Month Reading Date PG&E Meter EPRI Monitoring (VRF)

Energy (kWh) Demand (kW) Energy (kWh) Demand (kW)

Jan 1/26/2014 6,996 29 2,761 23.3

Feb 2/25/2014 6,859 29 2,742 25.1

Mar 3/26/2014 6,418 26 2,489 19.3

Apr 4/27/2014 6,567 27 2,666 22.3

May 5/27/2014 6,661 27 2,790 18.6

Jun 6/25/2013 7,353 29 3,319 20.9

Jul 7/25/2013 8,614 31 4,844 22.7

Aug 8/25/2013 7,766 28 4,236 18.7

Sep 9/24/2013 6,879 28 3,339 20.3

Oct 10/23/2013 5,896 24 2,220 14.1

Nov 11/22/2013 6,155 25 2,068 20.2

Dec 12/25/2013 7,434 36 3,740 20.2

TABLE 6 COMPARISON OF PG&E BILLING DATA AND EPRI VRF SYSTEM MONITORING DATA

20


FIGURE 14 COMPARISON BETWEEN PG&E METER DATA AND EPRI HVAC MONITORING DATA

The difference between billing data and EPRI measurements indicate the energy usage by

other loads in the building. Based on the data the other loads average 3,865 kWh per

month. The average other loads during summer time (May through October) is 3,737 kWh

and during winter time (November through April) is 3,994 kWh. The difference in average

energy usage, although minor (~6.7%), may be due to use of portable heaters that are

used in certain offices. One such portable heater was seen during site visit and the occupant

of the office said she used it very often during heating season to keep her office warm.

The total energy usage of the building is 83,598 kWh for the year under consideration which

equates to 9.9 kWh/sq foot/year site energy use intensity (EUI). The total VRF energy use

for the entire year is 37,253 kWh which comes out to 4.4kWh/sq foot /year EUI. Figure 15

shows the billing demand created by the entire building during each billing cycle and the

corresponding VRF system maximum demand imposed during the same billing cycle. The

billing demand is defined as the maximum average kW for 15 minute block during the billing

cycle. The blocks are defined as 2:00 to 2:15, 2:15 to 2:30 and so on. From the billing data

provided it wasn’t clear at what date and time the maximum demand created by the

building. For the VRF system, since all the data is monitored, the exact 15 minute period for

the highest demand during each billing cycle can be deduced. From the data obtained from

PG&E it is not possible to determine if PG&E demand was recorded at the same time as VRF

systems maximum demand. Since the VRF system is the biggest building load, it is a safe

assumption that the times do correspond to the maximum billing demand as well.

21


FIGURE 15 RECORDED BILLING DEMAND AND VRF SYSTEM HVAC DEMAND

TABLE 7 MAXIMUM DEMAND FROM VRF SYSTEM

Month Season Max VRF

Demand Date

Time Frame PG&E Meter

Demand (kW)

EPRI Monitoring (VRF) Demand

(kW) From To

Jan Winter 1/13/2014 3:45 am 4:00 am 29 23.3

Feb Winter 2/4/2014 4:00 am 4:15 am 29 25.1

Mar Winter 3/3/2014 4:30 am 4:45 am 26 19.3

Apr Winter 3/31/2014 2:45 am 3:00 am 27 22.3

May Summer 4/28/2014 3:30 am 3:45 am 27 18.6

Jun Summer 6/7/2013 5:00 pm 5:15 pm 29 20.9

Jul Summer 7/1/2013 3:15 pm 3:30 pm 31 22.7

Aug Summer 8/7/2013 6:15 am 6:30 am 28 18.7

Sep Summer 9/16/2013 6:00 am 6:15 am 28 20.3

Oct Summer 9/25/2013 4:00 pm 4:15 pm 24 14.1

Nov Winter 11/4/2013 3:45 am 4:00 am 25 20.2

Dec Winter 12/7/2013 3:45 am 4:00 am 36 20.2

22


The trends from the demand data show that during the winter time, the VRF system

maximum demand is during the very early morning hours (2:00 am to 5:00 am) whereas in

summer hours the maximum demand is during the morning startup phase (6:00 am to 8:00

am) or during hot afternoon hours (12:00 pm – 6:00pm). The month of May 2014 falls

under the summer season but the maximum demand was measured during early morning

hours, a trend found in winter months. Further investigation revealed that the day of the

maximum demand 04/28/2014 had the lowest overnight temperatures (44°F) for that

billing period which forced the system to run in heating mode thus showing characteristics

like a winter month.

THERMAL CHARACTERISTICS The outdoor conditions in which a VRF system is operating has significant impact on the

power draw from the system. The full year data is filtered to include only weekdays and

working hours. The trend in power draw with respect to the outdoor temperature is as

expected. At the extremes of temperature range, the power draw is higher (either cooling

mode or heating mode) and in the milder ambient conditions the power draw is lower.

FIGURE 16 AVERAGE POWER DRAW VERSUS TEMPERATURE BINS

DETERMINING MODE OF OPERATION OF INDOOR UNIT

The mode of operation of each individual indoor unit is determined by the difference

between the return air temperature and supply air temperature of the same indoor unit.

There are three different modes of operation – auto fan, cooling and heating. The

temperature difference for determining the operating mode is set at 15°F. If the

temperature difference between return air and supply air is greater than 15°F then the unit

is assumed to be in cooling mode. If the temperature difference is less than -15°F then the

23


unit is assumed to be in heating mode. For the temperatures in between the unit is in fan

mode.

OUTDOOR UNIT OPERATING MODE

The outdoor unit can be operating in heating only mode, cooling only mode or mixed mode

depending on the total load on system.

In heating only mode all the indoor units are operating in either heating mode or some in

heating and some in fan mode. None of the units are in cooling mode.

In cooling only operating mode the indoor units are operating in either cooling mode or

some in cooling and some in fan mode. None of the units are in heating mode.

In mixed mode a combination of indoor units operating in heating, cooling and fan mode is

observed. The mixed mode operation is also known as the heat recovery mode where

energy from one zone (a warm zone) is transferred to another (a cold zone) whenever

possible.

OPERATING HOURS The indoor unit operating hours for the entire building are shown in Figure 17. These are

cumulative operating hours that 13 units have run for each month. For example, in July

combined operating hours were in cooling mode were 2,127 which makes sense due to the

hot weather in that month.

24


FIGURE 17 INDOOR UNIT OPERATING HOURS IN HEATING OR COOLING MODE (ALL 13 UNITS COMBINED)

The operating hours in each mode for various temperature bins is shown in Figure 18. The

figure shows that as the ambient temperature increases the cooling mode operation

increases (which makes sense due to the building getting hotter) and vice-versa. The mixed

mode operation is mostly during the 55°F to 70°F temperature range.

25


FIGURE 18 OPERATING HOURS IN EACH MODE (FAN, COOLING, HEATING AND MIXED) FOR THE VRF SYSTEM

When considering operating modes and hours of the indoor units, one important

consideration is to make sure indoor units operating in large open spaces are not fighting

each other, i.e. for units serving the same common space, one is running in heating mode

while the other is running in cooling mode. Figure 19 shows indoor units 8A and 8B showing

such behavior. These units serve the open space on third floor and during certain hours

showed signs of operating in opposite modes. Figure 20 shows the number of hours the

indoor units 8A and 8B are operating in opposite mode during the same time. There are lot

of hours in January and February where the units are running in opposite modes. All other

indoor units were compared against each other as well but none of them showed such

behavior

26


FIGURE 19 INDOOR UNIT 8A AND 8B OPERATING IN DIFFERENT MODES DURING THE SAME TIME

FIGURE 20 NUMBER OF HOUR’S INDOOR UNIT 8A AND 8B ARE OPERATING IN OPPOSITE MODE

The data center is also a unique zone where operating mode is of interest. The data center

has another smaller independent split system installed as a backup and there seems to be

evidence of influence from the split system on the operation of the VRF indoor unit. The

27


data center indoor unit runs in heating mode for quite some time which is counter-intuitive

considering that data center is usually a cooling load.

To understand the operation of the indoor unit in the data center, return air temperature at

the indoor unit was reviewed. The minimum return air temperature for the indoor unit in the

data center is shown in Figure 22. The temperatures do not indicate very cold temperatures

where there is need for heating to be provided.

28


FIGURE 21 OPERATING MODE AND HOURS FOR INDOOR UNIT IN DATA CENTER

FIGURE 22 MINIMUM TEMPERATURE RECORDED FOR EACH MONTH FOR RETURN AIR IN THE DATA CENTER

29


CAPACITY MEASUREMENTS Capacity is measured for each indoor unit by using the air enthalpy method. The capacity of

each indoor unit is the product of mass flow rate of air (lb/hr) and the change in enthalpy

across the indoor unit (BTU/lb).

The airflow rate for each individual indoor is obtained from the test and balance (TAB) report provided by PG&E.

The TAB report provides airflow rates in CFM for each of the ducted units installed in the building. For ductless

units (wall mount or cassette) published airflow from the manufacturer at the medium fan speed setting are used.

The airflow is measured in CFM (cubic feet per minute) and then converted into mass flow rate of pounds per hour.

This mass flow rate is assumed to be constant throughout the data monitoring period.

Enthalpy measurements are derived from the dry bulb temperature and relative humidity (RH) measurement taken at

return and supply air of each indoor unit. The enthalpy is calculated based on perfect gas relationships for dry and

moist air elaborated in 2009 ASHRAE Handbook – Fundamentals, chapter 1 Psychrometrics.

h = enthalpy of moist air

t= dry bulb temperature

W=humidity ratio

Humidity ratio is not measured by the installed instrumentation but the relative humidity

(RH) is. Saturation pressure over liquid water (pws) at a given temperature (between 32F

and 392F) is given by –

Where C8 thru C13 are constants, T is absolute temperature.

C8=-1.044 039 7 E+04

C9=-1.129 465 0 E+01

C10=-2.702 235 5 E-02

C11=1.289 036 0 E-05

C12=-2.478 068 1 E-09

C13=6.545 967 3 E+00

Based on pws, pw the partial water vapor pressure of a moist air sample can be calculated

Humidity ratio W is calculated by

Where p is atmospheric pressure assumed to be 14.695 psia.

Field capacity measurements are difficult. The calculations made in this report give an

estimate of the capacity delivered. For accurate capacity measurement significant additional

instrumentation and resources would be required.

30


Figure 23 shows the total capacity (heating and cooling) delivered by the VRF system

broken down by each floor. The data shows that the second floor has relatively less heating

or cooling needs. The area of second floor is the least due to the high ceiling for the first

floor. The third floor due the roof sees higher impact from ambient conditions. The first floor

which has a customer entrance and high ceilings in the customer service area is where most

of the capacity is delivered.

FIGURE 23 MONTHLY CAPACITY DELIVERED FOR EACH FLOOR

Energy efficiency ratio (EER) can be defined as the ratio of energy output (BTU of cooling or

heating) from the VRF system to the electrical input energy (kWh) during the same period.

The EER of the VRF system is strongly correlated to the ambient temperature conditions.

Figure 24 shows the EER and outdoor temperature correlation for the entire duration of the

test. The data is filtered to include only when the system is in occupied mode. This is done

to avoid skewing the data due to system being in standby mode where no heating or cooling

capacity is delivered. Such situations are encountered when the system is in unoccupied

mode (outside of working hours).

31


FIGURE 24 AVERAGE EER VERSUS TEMPERATURE BINS

The EER trend is as expected with EER dropping at the extremes (low ambient or high

ambient conditions).

MODELING The objective of modeling exercise is to calibrate a VRF simulation in EnergyPlus and to

calculate the energy savings associated with a VRF system installation a the PG&E facility in

Auburn. As of June 2014, one full year of VRF sub-metered data was available. To calculate

energy savings, PECI created baseline and proposed whole building energy simulations. The

proposed model was constructed per the Auburn Office Building design with a VRF system.

This was also calibrated to the sub-metered VRF energy data. The baseline model included a

code compliant packaged single zone gas fired rooftop unit HVAC system. This memo

describes model development, calibration, and the resulting energy savings.

MODEL DEVELOPMENT The energy model is developed using AecoSim Energy Simulator (AES), which is a

comprehensive front end for EnergyPlus that allows the user to define all model input

parameters, run simulations, and analyze results. AES build 08.11.09.46 was used for this

project, which uses EnergyPlus version 7.2 as the simulation engine.

32


INPUT ASSUMPTIONS

As built drawings dated November, 18th 2011 that document the HVAC replacement were

used as the basis for most of the model input assumptions including model geometry and

HVAC system assumptions. These plans however are not comprehensive because they were

only for the HVAC replacement. Supplemental information was provided by site staff and

EPRI staff who had previously been on location.

ENVELOPE Envelope assumptions are based on conversations with site staff, as built drawings and

images from google maps. Exterior walls are assumed to be brick veneer walls with batt

insulation in the wall cavity and gypsum board finish. A flat membrane roof is modeled with

wood decking and insulation. Windows are assumed to be clear and single pane. Based on

the age of construction, presence of single pane windows and conversation with PG&E staff,

the building was modeled with relatively a high infiltration rate.

INTERNAL GAINS Internal gains were input based on data reported from EPRI staff that had been onsite and

counted the number and types of lights, significant plug loads and occupants. ASHRAE

Fundamentals was used to determine reasonable assumptions for nominal power draw of

office equipment found onsite. Equipment power density and lighting power density were

broken out on a per floor basis.

A small data closet is situated in the basement of the site. The IT load of this data closet

was unknown. It was estimated at 1.5 kW. This value was based on the available VRF

cooling capacity of the site and from a photo of the data closet.

Domestic hot water was assumed to be provided by a natural gas tank water heater located

in the basement. The system is assumed to have a flow rate of 4 gallons per occupant per

day during working days.

HVAC - VRF

The HVAC system was modeled as defined on the as built drawings with two exceptions. The

drawings show that the building is served by Mitsubishi Lossnay Energy Recovery Ventilator.

However, PG&E staff revealed that this ERV was not actually installed and in its place is

actually a dedicated outside air system with no space conditioning or heat recovery

capability. The other exception is that IHP3 is shown to have 1,376 CFM of supply air and 15

MBH of cooling capacity. This comes out to 1,100 CFM/ton, which is very high. Additionally,

based on the initial model, this seemed to be an inadequate amount of cooling capacity.

Therefore an assumption was made that the plans were incorrect and this unit actually had

a cooling capacity of 45 MBH and a heating capacity of 45 MBG. This equates to 367

CFM/ton which is more aligned with how all other indoor units at this site are designed and

also agrees better with industry standard practice.

The Mitsubishi VRF Heat Recovery system was simulated using the VRF module in AES.

Outdoor unit capacity, indoor unit capacity and supply air flow rates were hardcoded based

on the as built plans. For ceiling and wall cassette type indoor units, fan power could be

taken directly from the unit specification sheet. For ducted indoor units, a range of possible

static pressure requirements was investigated and the fine-tuned using the sub-metered

33


data. This exercise resulted in a static pressure assumption of six tenths of an inch of water

for ducted units. The default VRF performance curves in AES were used for this exercise

because they are based on a Mitsubishi unit of the same line as the one installed at the

Auburn site.

The HVAC was assumed to have typical office operation, with occupied mode defined as

Monday – Friday 6:00 am – 6:00 pm.

MODEL CALIBRATION The Auburn building was calibrated to sub-metered data provided by the monitoring

exercise of this project. When the model was calibrated, only 11 months of data was

available so the model was only calibrated to the available 11 months of data. The model

was calibrated on a monthly basis using HVAC energy as the calibration target.

WEATHER DATA

National Oceanic and Atmospheric Administration (NOAA) weather data was used from the

Auburn Municipal airport site. Weather data used was from June 1st 2013 to May 31st 2014.

This weather data contains drybulb temperature, relative humidity, wind speed, wind

direction and barometric pressure. Other parameters not specified in by the NOAA Auburn

weather station but still needed for the simulation were taken from a Sacramento TMY3

weather file.

METERED DATA

Metered data of the HVAC system was provided by EPRI. This building is sub-metered per

floor for indoor units and per unit for outdoor units. The provided data was reported at one

minute intervals; however it was aggregated for per month for the purposes of the model

calibration.

CALIBRATION PROCESS

While the target calibration was for HVAC energy the model was calibrated on both fan

energy and outdoor unit energy. This approach provides a more robust model calibration

and allows for easier analysis of modeled results. Critical parameters impacting the

calibration of the indoor units were the fan static pressure, fan efficiency and motor

efficiency. Critical parameters impacting the calibration of the outdoor units were the

infiltration, and temperature setpoints.

The goal of the calibration was to achieve modeled energy use within 15% of the metered

data. As shown in Figure 25, this was achieved for all months except March which was at

23.5% of the metered energy use.

34


FIGURE 25 CALIBRATED VRF SYSTEMS MODELED ENERGY USE VS METERED ENERGY USE

The red line shows the average temperature for the month as a departure from the

balance temperature f or the space.

PACKAGED SINGLE ZONE MODEL A packaged single zone (PSZ) HVAC system with gas heat was modeled as the baseline

scenario for this building. This model was created to comply with 2008 Title 24. Zoning

was maintained the same as in the building design and in the VRF model. Set points and

schedules were also kept constant between the VRF model and the PSZ model.

The PSZ model consists of 12 SEER 13 units that do not have economizers. The capacity

and airflow rates of these units were auto sized by AES.

ENERGY SAVINGS Energy use for the PSZ model was compared to the energy use for the VRF model. The VRF

model used significantly less energy. The resultant HVAC savings are 126 kWh/ton and 52

therms/ton, which is equal to 51% of the PSZ HVAC energy use. To help demonstrate the

source of these savings, Figure 26 outlines the energy use intensity for the VRF and PSZ

models.

35


FIGURE 26 ENERGY USE INTENSITY FOR THE VRF AND PSZ MODELS HIGHLIGHTING THE SOURCE OF ENERGY SAVINGS

As Figure 26 shows, the majority of the savings for this project come from heating. The

packaged single zone model uses an 80% efficient forced air finance, whereas the VRF

system is able to take advantage of its heat pump heating and thus achieve significant

savings. Additionally, there are considerable fan savings. These fan savings arise because

with a VRF system the static pressure requirement is significantly less because of the

reduced ductwork. Also the indoor unit fans are able to cycle with heating and cooling load

because ventilation air is decoupled from the VRF supply fan operation.

DISCUSSIONS AND CONCLUSIONS This report provides analysis of a field installed VRF-HR system in Auburn, California. The

data gathered is grouped into two main types – electrical and thermal. The data set

collected can be used for further model validation purposes.

The monitoring and analysis of the VRF-HR system shows that the operating characteristics

were in line with the expectations based on understanding of HVAC systems. Summary of

the findings and discussion is presented in a numbered list -

1. The monitored ambient conditions shows slight variation from the published weather

data for Auburn, California. The variations can be attributed to the limited data set

that is available for site - single point ambient measurements made only for one

year.

2. Summer load shape shows high demand during peak periods for utilities (12:00 pm

to 6:00 pm). The winter load shape shows a high demand imposed outside of the

office hours (early mornings). The trends from the demand data show that during

the winter time, the VRF system maximum demand is during the very early morning

hours (2:00 am to 5:00 am) whereas in summer hours the maximum demand is

during the morning startup phase or during hot afternoon hours.

36


3. The high demand during summer peak hours makes the VRF installation a potential

candidate for Demand Response program. The significant controls as well as

communications capabilities further necessitate investigation into the DR

possibilities.

4. The high demand during the early morning startup period could be eliminated by

staging the units during the initial ramp-up. This can be done by setting different

occupied / unoccupied times for different units.

5. The difference between PG&E billing data and EPRI measurements indicate that the

average energy usage by other loads in the building is 3,865 kWh per month.

6. The outdoor conditions in which a VRF system is operating has significant impact on

the power draw from the system. As expected, at extremes of temperature range,

the power draw is higher (either cooling mode or heating mode) and in the milder

ambient conditions the power draw is lower.

7. The second floor has the least heating or cooling needs. The third floor due the roof

sees higher impact from ambient conditions. The first floor which has a customer

entrance and high ceilings in the customer service area is where most of the capacity

is delivered.

8. Indoor units 8A and 8B which serve third floor open space operated in opposite mode

(one in cooling and other in heating) at the same time for 39 hours during the period

of monitoring. Since the units serve the same space, it appeared that the units were

fighting each other. This can be remedied by grouping units together and forcing

them to operate in a single mode. That way the systems don’t fight each other. This

can also be done for indoor units 4A and 4B as well as 7A and 7B.

9. Indoor unit 2 serves a small data center which also has a backup split system. The

cooling from backup system was potentially forcing the indoor unit 2 to operate in

heating mode. Data center is usually a cooling load and heating mode operation of

the indoor unit 2 operating in heating mode isn’t expected. Through the control

scheme this indoor unit can be locked in cooling mode or the setback temperature

can be reduced significantly so that the unit doesn’t kick into heating mode.

10. Modeling showed that the EnergyPlus model can predict the energy usage of the

modeled building within ±15% of actual energy use for the VRF system. Comparison

between a modeled baseline and a VRF system showed significant energy savings in

heating mode and fan energy savings.

The VRF system shows overall energy savings based on modeling results, but more energy

savings can be realized by following recommendations deduced from data analysis.

37


RECOMMENDATIONS The biggest opportunity in terms of energy savings in a VRF technology is the ability to

modulate components as well as change local set points while maintaining occupant comfort

throughout the building. A slightly liberal policy for the local controllers might result in

added energy savings (this has potential disadvantages as well – thermostat fights are a

possibility). This can be reduced by providing occupants training on how to use and interact

with the system.

Another energy savings opportunity based on findings of this study is the opportunity for

continuous commissioning. The indoor units fighting each other or the data center indoor

unit running in heating mode are opportunities to save energy which are wasted if the

system operation is not reviewed. The existing sensors and controls on the system are

capable of determining this issues. If there is an incentive for reviewing information and

data gathered on the system, further energy savings could be realized. Commissioning at

time of install can also be monitored carefully to make sure building characteristics are

taken into consideration. This building for example is an historic building with substantial air

leakage and minimum insulation. The winter operation of this system is heavily dependent

on the type of building and less so on the actual control scheme of the building.

Outdoor air fan presents another opportunity for energy savings. The control scheme shared

for the purpose of this project indicates that the fan runs when the system has any indoor

unit operating. This, in winter months can mean that the outdoor air brings in outside cold

air when there is no need for fresh air (unoccupied mode). This could not be verified

through the data collected.

There is an opportunity to investigate demand response potential of this technology

especially since this is a coincident load. The controls and communications capability are

already included in the product and unlocking the potential could be the next step to further

benefit from this technology.

38


APPENDICES

MONITORING EQUIPMENT

OBVIUS ACQUISUITE A8810 – MAIN DATA ACQUISITION SERVER

39


OBVIUS MODHOPPER R9120-5

40


OBVIUS FLEX IO – A8332-8F2D

41


DWYER SERIES RHP – HUMIDITY/TEMPERATURE TRANSMITTER

42


DWYER SERIES RH-R – HUMIDITY/TEMPERATURE TRANSMITTER

43


ACCU-CT – SPLIT-CORE CURRENT TRANSFORMER

44


ELKOR WATTSON

45


INSTALLED MITSUBISHI EQUIPMENT

PURY-P288TSJMU-A

46


PVFY-P18E00A

47


PKFY-P06NAMU-E

48


PKFY-P30NFMU-E

49


PEFY-P36NMAU-E

50


PEFY-P24NMAU-E

51


PEFY-P48NMAU-E

52


PLFY-P08NCMU-E

53


PLFY-P15NCMU-E

54


CMB-P1013NU-GA

55


FILTERS APPLIED TO MONITORED DATA

Figure 8 Cooling Degree Day (CDD) and Heating Degree Day (HDD) (Base

65°F)

Description: Sum of HDD and sum of CDD for each Local Time Month. For pane Sum of HDD:

Color shows details about Local Time Month. For pane Sum of CDD: Color shows sum of CDD.

Local Time Month has 12 members on this sheet

Members: August; July; June; May; September; ...

Sum of HDD ranges from 5.0 to 551.3 on this sheet.

The formula is IF (65-([Outdoor Air T]))<0 THEN 0 ELSE ((65-[Outdoor Air T])/(24*60)) END

Sum of CDD ranges from -520.8 to -2.2 on this sheet.

The formula is IF (65-([Outdoor Air T]))>0 THEN 0 ELSE ((65-[Outdoor Air T])/(24*60)) END

Figure 11 Outdoor Conditions Split in Temperature and Relative Humidity

Bins

Description: Sum of Number of Records Hours (color) broken down by Outdoor T vs. Outdoor

RH. The data is filtered on LocalTime (MY), which excludes May 2013 and June 2014. The

view is filtered on Exclusions (Outdoor RH,Outdoor T), which keeps 203 members.

Outdoor RH has 19 members on this sheet

Members: 15; 20; 25; 30; 35; ...

Outdoor T has 18 members on this sheet

Members: 70; 75; 80; 85; 90; ...

LocalTime (MY) has 12 members on this sheet

Members: August 2013; July 2013; June 2013; October 2013; September 2013; ...

Figure 12 Outdoor Conditions Split in Temperature and Relative Humidity

Bins (VRF System in Occupied Mode)

Description: Sum of Number of Records Hours (color) broken down by Outdoor T vs. Outdoor

RH. The data is filtered on LocalTime (MY), LocalTime Weekday and LocalTime Hour. The

LocalTime (MY) filter excludes May 2013 and June 2014. The LocalTime Weekday filter keeps

Monday, Tuesday, Wednesday, Thursday and Friday. The LocalTime Hour filter keeps 13 of 24

members. The view is filtered on Exclusions (Outdoor RH,Outdoor T), which keeps 203

members.

Filters: Exclusions (Outdoor RH,Outdoor T), Month, Year of LocalTime, Weekday of

LocalTime, Hour of LocalTime

Outdoor RH has 19 members on this sheet

Members: 25; 30; 35; 40; 45; ...

56



Members: 65; 70; 75; 80; 85; ...

LocalTime Hour has 13 members on this sheet

Members: 10; 6; 7; 8; 9; ...



LocalTime Weekday has 5 members on this sheet

Members: Friday; Monday; Thursday; Tuesday; Wednesday

Figure 13 Load Shape of VRF System (All Year Average; Summer and

Winter)

All Year Average

The trend of average of Total Power for LocalTime Hour. The data is filtered on LocalTime

Weekday, which keeps Monday, Tuesday, Wednesday, Thursday and Friday.

Average of Total Power ranges from 0.58 to 11.13 on this sheet.

The formula is [Total Indoor Power]+[Total Outdoor Power]

Summer


Weekday and LocalTime Month. The LocalTime Weekday filter keeps Monday, Tuesday,

Wednesday, Thursday and Friday. The LocalTime Month filter keeps 6 of 12 members.

LocalTime Month has 6 members on this sheet






Winter


Weekday and LocalTime Month. The LocalTime Weekday filter keeps Monday, Tuesday,

Wednesday, Thursday and Friday. The LocalTime Month filter keeps 6 of 12 members.


Members: April; February; January; March; November; ...





57


Figure 14 Comparison between PG&E Meter Data and EPRI HVAC

Monitoring Data

Description: EPRI HVAC (kWh) and PG&E Meter (kWh) for each MONTH. Color shows

details about EPRI HVAC (kWh) and PG&E Meter (kWh).

Measure Names has 2 members on this sheet

Members: EPRI HVAC (kWh); PG&E Meter (kWh)

MONTH has 12 members on this sheet

Members: Apr; Dec; Jan; May; Nov; ...

Figure 15 Recorded Billing Demand and VRF System HVAC Demand

Description: HVAC Demand and Billing Demand for each MONTH. Color shows details about

HVAC Demand and Billing Demand.


Members: Billing Demand; HVAC Demand

Measure Names is sorted manually.

MONTH has 12 members on this sheet

Members: Apr; Dec; Jan; May; Nov; ...

Figure 16 Average Power Draw versus Temperature Bins

Description: Average of Total Power for each Outdoor T. The data is filtered on LocalTime

Hour and LocalTime Weekday. The LocalTime Hour filter keeps 15 of 24 members. The

LocalTime Weekday filter keeps Monday, Tuesday, Wednesday, Thursday and Friday. The

view is filtered on Outdoor T, which excludes Null.


Members: 50; 55; 60; 65; 70; ...


Members: 6; 7; 8; 9; ...


Members: Friday; Monday; Thursday; Tuesday; Wednesday Average of Total Power ranges from 4.50 to 26.69 on this sheet.


Figure 17 Indoor Unit Operating Hours in Heating or Cooling Mode (All 13

Units Combined)

Description: Sum of HOURS IN HEATING MODE and sum of HOURS IN COOLING MODE

for each LocalTime Month. For pane Sum of HOURS IN HEATING MODE: Color shows

details about LocalTime Month. For pane Sum of HOURS IN COOLING MODE: Color shows

sum of HOURS IN COOLING MODE. The data is filtered on EXACT ONE YEAR, which

keeps 12 months.

58



Members: August; July; June; October; September; ...

Sum of HOURS IN HEATING MODE ranges from 1 to 1,491 on this sheet.

The formula is

([HM1]+[HM2]+[HM3]+[HM4A]+[HM4B]+[HM5A]+[HM5B]+[HM6]+[HM7A]+[HM7B]+[H

M8A]+[HM8B]+[HM8C])

Sum of HOURS IN COOLING MODE ranges from -2,127 to -17 on this sheet.

The formula is

([CM1]+[CM2]+[CM3]+[CM4A]+[CM4B]+[CM5A]+[CM5B]+[CM6]+[CM7A]+[CM7B]+[C

M8A]+[CM8B]+[CM8C])

EXACT ONE YEAR has 12 members on this sheet


Delta T has the value 15.

Figure 18 Operating Hours in Each Mode (Fan, Cooling, Heating and

Mixed) for the VRF System

Description: Sum of Number of Hours for each Outdoor Air T (bin). Color shows details about

FAN HEAT COOL MIXED. The marks are labeled by sum of Number of Hours. The data is

filtered on LocalTime Weekday, LocalTime Hour and LocalTime (MY). The LocalTime

Weekday filter keeps Monday, Tuesday, Wednesday, Thursday and Friday. The LocalTime Hour

filter keeps 12 members. The LocalTime (MY) filter excludes May 2013 and June 2014. The

view is filtered on Outdoor Air T (bin), which excludes Null.

Outdoor Air T (bin) has 18 members on this sheet

Members: 65; 70; 75; 80; 85; ...


Members: 10; 6; 7; 8; 9; ...



There are 4 members on this sheet

Members: COOLING; FAN; HEATING; MIXED

The formula is IF([UNITS IN COOLING MODE]=0 AND [UNITS IN HEATING MODE]=0)

THEN "FAN" ELSEIF([UNITS IN COOLING MODE]0) THEN "MIXED" ELSEIF([UNITS IN

COOLING MODE]=0 AND [UNITS IN HEATING MODE]>0) THEN "HEATING" ELSEIF

([UNITS IN COOLING MODE]



The formula is [Number of Records]/60


59


Figure 20 Number of Hour’s Indoor Unit 8A and 8B are Operating in

Opposite Mode

Description: Sum of 8A 8B FIGHTING for each LocalTime Month. The data is filtered on

EXACT ONE YEAR, which keeps 12 members.



Sum of 8A 8B FIGHTING ranges from 0.00 to 14.52 on this sheet.

The formula is IF [MODE 8A]=0 THEN 0 ELSE(IF [MODE 8B]=0 THEN 0 ELSEIF[MODE

8A]!=[MODE 8B] THEN (1/60) END) END




Figure 21 Operating Mode and Hours for Indoor Unit in Data Center

Description: Sum of HM2 and sum of CM2 for each LocalTime Month. Details are shown for

LocalTime Month. For pane Sum of CM2: Color shows sum of CM2. The data is filtered on

EXACT ONE YEAR, which keeps 12 members.



Sum of CM2 ranges from -67.92 to 0.00 on this sheet.

The formula is IF [MODE 2]=1 then -(1/60) else 0 end

Sum of HM2 ranges from 0.00 to 50.92 on this sheet.

The formula is IF [MODE 2]=-1 then (1/60) else 0 end




Figure 22 Minimum Temperature Recorded for Each Month for Return Air

in the Data Center

Description: The trend of minimum of Indoor 2 Return Air T for LocalTime Month.



Minimum of Indoor 2 Return Air T ranges from 66 to 69 on this sheet.

Figure 23 Monthly Capacity Delivered for Each Floor

60


Description: Basement, First Floor, Second Floor and Third Floor for each LocalTime Month.

Color shows details about Basement, First Floor, Second Floor and Third Floor


Members: Basement, First Floor, Second Floor and Third Floor

Measure Names is sorted manually.



Figure 24 Average EER versus Temperature Bins

Description: Average of EER for each Outdoor T. Color shows average of EER. The marks

are labeled by average of EER. The data is filtered on Exclusions (Outdoor RH,Outdoor T),

LocalTime Hour and LocalTime Weekday. The Exclusions (Outdoor RH,Outdoor T) filter

keeps 203 members. The LocalTime Hour filter keeps 12 members. The LocalTime Weekday

filter keeps Monday, Tuesday, Wednesday, Thursday and Friday.


Members: 50; 55; 60; 65; 70;...


Members: 10; 6; 7; 8; 9; ...



Average of EER ranges from 12 to 27 on this sheet.

The formula is [Total Capacity]/ ([Total Outdoor Power]*1000)

Parameters:


CFM 4B has the value 630.

CFM 5A has the value 320.


CFM 6 has the value 225.






CFM 8C has the value 800.




61


MODELING APPENDIX

ZONING

62


REFERENCES

http://www.pge.com/includes/docs/pdfs/about/edusafety/training/pec/toolbox/arch/climate

/california_climate_zones_01-16.pdf (accessed 07/19/2014)

http://www.pge.com/tariffs/tm2/pdf/ELEC_SCHEDS_A-10.pdf (accessed 07/16/2014)

ANSI/AHRI Standard 1230 ‘2010 Standard for Performance Rating of Variable Refrigerant

Flow (VRF) Multi-Split Air-conditioning and Heat Pump Equipment’ Air-Conditioning, Heating,

and Refrigeration Institute, Arlington, Virginia.

ASHRAE Handbook 2009, Fundamentals, American Society of Heating, Refrigerating and Air-

Conditioning Engineers, Inc., Atlanta Georgia.

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