i

Arnold Schwarzenegger Governor

Benchmarking Study of the Refrigerated Warehousing Industry Sector in California

PIER

FIN

AL

PRO

JEC

T R

EPO

RT

Prepared For: California Energy Commission Public Interest Energy Research Program

Prepared By: Department of Biological and Agricultural Engineering University of California Davis, CA 95616

July 2008

Prepared By:

R. Paul Singh Professor of Food Engineering Department of Biological and Agricultural Engineering University of California Davis, CA 95616

Prepared For: California Energy Commission Public Interest Energy Research (PIER) Program

Pramod Kulkarni

Contract Manager Rajesh Kapoor

Project Manager Name Manager NAME OF OFFICE Martha Krebs, Ph.D. Deputy Director ENERGY RESEARCH & DEVELOPMENT DIVISION B.B Blevins Executive Director DISCLAIMER This report was prepared as the result of work sponsored by the

California Energy Commission. It does not necessarily represent the views of the Energy Commission, its employees or the State of California. The Energy Commission, the State of California, its employees, contractors and subcontractors make no warrant, express or implied, and assume no legal liability for the information in this report; nor does any party represent that the uses of this information will not infringe upon privately owned rights. This report has not been approved or disapproved by the California Energy Commission nor has the California Energy Commission passed upon the accuracy or adequacy of the information in this report.

ii

Acknowledgements Daniel Voit, Graduate Research Assistant, contributed to this project in preparing the survey forms and conducting the survey. Dr. Jatal Mannapperuma’s guidance on various phases of this study, and the assistance provided by Mr. Benjamin Milk (IARW) in developing the questionnaire is gratefully acknowledged. We thank the time and effort of participating refrigerated warehouses in providing the requested information for this study. Citation Singh, R. Paul. 2008. Benchmarking Study of the Refrigerated Warehousing Industry Sector in California. Public Interest Energy Research (PIER) Program Contract and Research Project Reports. California Energy Commission, PIER Program.

i

Preface The Public Interest Energy Research (PIER) Program supports public interest energy research and development that will help improve the quality of life in California by bringing environmentally safe, affordable, and reliable energy services and products to the marketplace. The PIER Program, managed by the California Energy Commission (Energy Commission), conducts public interest research, development, and demonstration (RD&D) projects to benefit the electricity and natural gas ratepayers. The PIER program strives to conduct the most promising public interest energy research by partnering with RD&D entities, including individuals, businesses, utilities, and public or private research institutions. PIER funding efforts are focused on the following RD&D program areas: ! Buildings End-Use Energy Efficiency ! Energy-Related Environmental Research ! Energy Systems Integration ! Environmentally Preferred Advanced Generation ! Industrial/Agricultural/Water End-Use Energy Efficiency ! Renewable Energy Technologies ! Transportation Benchmarking Study of the Refrigerated Warehousing Industry Sector in California project contract number 400-99-005, work authorization number 11 conducted by University of California, Davis. The information from this project contributes to PIER’s Industry Agriculture and Water program. For more information about the PIER Program, please visit the Energy Commission’s website at www.energy.ca.gov/pier/ or contact the Energy Commission at 916-654-5164.

ii

Table of Contents

Preface i

Abstract and Keywords iv

Executive Summary 1

Chapter 1. Introduction 2

Chapter 2. Project Approach 3

Chapter 3. Project Outcomes 4

Chapter 4. Conclusions and Recommendations 12

References 12

Appendix 1. Survey questionnaire 13

Appendix 2: Area, volume, and year of construction of warehouses surveyed 17

Appendix 3: Monthly energy use profile 18

Appendix 4: Monthly profile of peak power demand 19

Appendix 5: Energy conserving technologies used by refrigerated warehouses 20

iii

Abstract A survey of refrigerated warehouses in California was conducted to determine the energy consumption patterns and energy saving practices. The survey included 67 public and 96 private warehouses. Total of 42 responses were received. Specific energy consumption (SEC) defined as kWh per year per cubic foot of storage volume was used as the measure of energy consumption. Typically the SEC decreased with increasing size (volume) of the warehouse according the regression equation

0.227538.978( )average practiceSEC storage volume "# This behavior was consistent with previously reported results from studies conducted in New Zealand, the Netherlands, United Kingdom and United States. The extent of use of eleven energy conservation technologies, namely, upgraded insulation, cool roofs, efficient lighting technology, aggressive evaporative condenser, thermosiphon oil cooling, computer control, compressor variable frequency drive (VFD), condenser VFD, Evaporator VFD, floating head pressure, and sensor controlled doors varied from 22% to 74%. This indicates potential for improvement. A web-based benchmark tool was developed to assist operators to compare the energy use of their warehouse with a survey-based benchmark for improving energy efficiency. Keywords: Refrigerated warehouse, energy saving.

iv

Executive Summary Perishable foods are stored at low temperatures to extend their shelf life. Refrigerated warehouses operate at a range of temperatures, from -25 to +5°C. Electrical energy is largely used to operate refrigeration equipment. Refrigerated warehouses are significant consumers of electrical energy in the food industrial sector of California. A survey of refrigerated warehouses in California was conducted to determine the energy consumption patterns and energy saving practices. The survey questionnaire was mailed to 67 public refrigerated warehouses and 96 private warehouses. Total of 42 responses were received. Specific energy consumption (SEC) defined as kWh per year per cubic foot of storage volume was used as the measure of energy consumption. Typically the SEC decreased with increasing size (volume) of the warehouse. This behavior was consistent with previously reported results from studies conducted in New Zealand, the Netherlands, United Kingdom and United States. The extent of use of eleven energy conservation technologies, namely, upgraded insulation, cool roofs, efficient lighting technology, aggressive evaporative condenser, thermosiphon oil cooling, computer control, compressor variable frequency drive (VFD), condenser VFD, Evaporator VFD, floating head pressure, and sensor controlled doors varied from 22% to 74%. This indicates potential for improvement. A web-based benchmark tool was developed to assist operators to compare the energy use of their warehouse with a survey-based benchmark for improving energy efficiency. It is recommended that additional surveys be conducted in the future to further enhance the database and the benchmark tool.

1

Introduction Refrigerated warehouses provide a vital link in the modern food processing chain extending from the farmer to the consumer. Many perishable foods must be kept under refrigerated conditions to extend their shelf life to meet the required constraints imposed during food distribution and marketing. Refrigerated warehouses operate at a range of temperatures, from -25 to +5°C. Electrical energy is largely used to operate refrigeration equipment. Because of the large amount of food crops grown and processed in California that require refrigerated storage, refrigerated warehouses are significant consumers of electrical energy in the food industrial sector. The California Energy Commission (CEC) implemented a Public Interest Energy Research Program for energy efficiency and conservation in refrigerated warehouses. The food and agricultural industry sector in California depends heavily on refrigerated warehouses for preservation and storage of products. The USDA – NASS Statistics Division in January 2004 estimated that California has 309 million ft3 3 and 139 million ft of storage volume in public and privately-owned warehouses, respectively. It has been estimated that this sector is responsible for 20% of the total electric energy consumption of the food industry. In 1997, the nationwide average energy use for cold storage was estimated by the International Association of Refrigerated Warehouses (IARW) to be 1.6 kWh/ft3-yr with an average rate of 5.5 ¢/kWh. Thus, the total annual cost of energy in the California’s cold storage sector is estimated to be 39.5 million dollars. Therefore, energy conservation in the refrigerated warehouses can produce significant benefits to electricity ratepayers. Previous surveys of electricity use by refrigerated warehouses conducted in the United States, Europe and New Zealand show considerable variation among different facilities (ESTU, 1994: Bosma, 1995; Elleson and Freund, 2004; Merts and Cleland, 2005). These variations are largely related to the size of the warehouses, storage temperatures, product load and the use of energy efficient technologies. In order to set targets for improvements of energy use by warehouses it is necessary to obtain reference data on energy-use by individual warehouses. Surveyed data can be useful to develop benchmarks for identifying facilities that can benefit from use of energy efficient technologies to reduce their energy consumption. Benchmarking the energy performance of this sector provides a means for comparing the energy intensity of installations and practices. It assesses energy efficient technologies, stimulates innovative approaches to improve energy management and provides a valuable tool for directing future research, development and demonstration projects and incentive programs for use of efficiency promoting practices. The objectives of this study were to: 1) develop a survey questionnaire and a mailing list of recipients, and conduct a survey of California refrigerated warehouses to obtain data on their size, monthly and annual energy requirements, and peak electrical demands; 2) survey the types of energy conserving technologies being implemented by the refrigerated warehouses; and 3) develop a web-based benchmarking tool that may be used in future to collect and provide data to warehouse operators to improve energy efficiency in their operations.

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Project Approach A survey questionnaire (Appendix 1) was developed and modified based upon input received from industry representatives including the IARW, consultants and contractors. The key data requested in the questionnaire was as follows: ! Name of the company (later masked to protect confidentiality), contact person and communication information; ! Age of the facility; ! Location of the warehouse; ! Total storage area, ft2;

3! Total storage volume, ft ; ! Total installed horsepower; ! Total refrigeration (tons); ! Types of products stored (meats, poultry, fruits, vegetables, processed fruits, vegetables and juices); ! Product throughput; ! Monthly electric power consumption for one year; ! Monthly peak power demand for one year; and ! Energy conserving technologies employed. The survey questionnaire was mailed to 67 public refrigerated warehouses in California. Follow up telephone calls were made to encourage response. Additionally, a subcontract was awarded to USDA to send survey forms to 96 private warehouses to seek additional responses. Finally, personal visits were made to selected warehouses to obtain data on site. Out of 67 public warehouses, 28 responses were obtained (or 42%), and out of 96 private warehouses, 14 responses were obtained (or 15% response rate). Although the response rates were low, they were considered sufficient for the purpose of this study. It is hoped that the results of this study will encourage future participation by those who did not contribute to the survey in this phase. The information contained in the responses was analyzed to develop; ! monthly energy use profiles for different warehouses categorized based on size (volume); ! monthly peak power demand profiles for different warehouses categorized based on size (volume); ! specific electricity consumption (SEC) (kWh per year per ft3) ! predictive equation to estimate SEC based on the size of a warehouse ! a benchmark SEC for comparison purposes ! usage profile of energy conserving technologies

3

Project Outcomes The survey included refrigerated warehouses of various sizes, with storage volumes varying from 200,000 to 6 MM cubic feet (Appendix 2). As seen in Figure 1, approximately half of the warehouses surveyed had a storage volume of more than 2.5 MM ft3. Depending upon their size, these warehouses require large refrigeration equipment to maintain required storage temperatures. As seen in Table 1, the refrigeration systems ranged from 300 to 7000 horsepower and 178 to 4500 tons of refrigeration load. A range of products are stored in refrigerated warehouses. Many of the surveyed warehouses store mostly meat, poultry and seafood (Table 2). Other products stored include dairy products, fruits, vegetables and processed foods. Although the survey questions requested information on product throughput, insufficient information was obtained for meaningful analysis. Figure 2 shows the monthly energy use profiles for different size (volume) warehouses. Obviously, larger warehouses have higher energy demands (see Appendix 3 and 4). Furthermore, higher energy consumption occurs during summer months to operate refrigerated facilities. The specific electricity consumption on a per volume basis was calculated for each warehouse surveyed in this study. The following formula was used:

3

Annual power consumption (kWh)Storage Volume (ft )

SEC # (1)

Table 3 shows the SEC values for various warehouses. These data were plotted against storage volume as shown in Figure 3. Although there is a certain amount of data scatter, it is evident that SEC values decrease as the size of the warehouse increases, indicating economies of scale. The non-linear relationship between SEC and storage volume was further analyzed using non-linear regression. The following expression was obtained between SEC and storage volume.

0.227538.978( )average practiceSEC storage volume "# (2)

3 3where storage volume is in ft and SEC is kWh/ft . The SEC values obtained from the current study are similar to the ones determined previously in studies conducted in New Zealand, the Netherlands, United Kingdom and Wisconsin. Figures 4 and 5 show SEC data from the previous studies (Note: 1 kWh/ft3 = 35.13 kWh/m3), and (1 m3 = 35.13 ft3). While the non-linear regression curve in Figure 3 (drawn with equation 2) gives an indication of “average practice” in terms of energy use in a refrigerated warehouse, the data points below the curve identify warehouses with more energy efficient operation. Therefore, to calculate benchmark SEC, we used a procedure similar to that used by Merts and Cleland (2005). They determined “best practice” by determining standard error from the nonlinear regression analysis

4

and by subtracting one standard error from the SEC curve. From the data obtained in the present survey, we obtained the following equation for benchmark purposes.

0.227538.978( ) 0.1581best practiceSEC storage volume "# " (3) Figure 6 includes the “best practice” SEC curve (Equation 3) for benchmark purposes. This plot was used to predict benchmark SEC for different storage volumes. This equation was also programmed into the web based benchmark tool. A list of 11 energy conserving technologies relevant to refrigerated warehouses was developed. These technologies were as follows: ! Upgraded insulation (UI) ! Cool roofs (CR) ! Efficient lighting technology (ELT) ! Aggressive evaporative condenser (AEC) ! Thermo siphon oil cooling (TSC) ! Computer control (CC) ! Compressor variable frequency drive (Comp VFD) ! Condenser variable frequency drive (Cond VFD) ! Evaporator variable frequency drive (Evap VFD) ! Floating head pressure (FHP) ! Sensor controlled doors (SCD) In Figure 7 (and Appendix 5), the extent of the 11 identified Act’s used by different warehouses is shown. While 3 warehouses use more than 80% of the ECTs, 12 of the surveyed warehouses use less than half of the ECTs. This indicates considerable potential to promote the use of energy conserving technologies in refrigerated warehouses. Figure 8 shows the percent of warehouses using specific ECTs. As seen in this figure, computer controllers are used by 70% of surveyed warehouses. More than 50% of the surveyed warehouses use UI, ELT, AEC, FHP, and CC. Variable frequency drive is more often used with condensers than in compressors and evaporators. For the purpose of dissemination of results and to seek further input from refrigerated warehouse operators, a web-based benchmark tool was developed using Macromedia Flash. The tool allows a user to enter information related to the size and monthly (or annual) energy use of their warehouse. The tool calculates the Specific Electricity Consumption using the entered information and compares it with a benchmark (SECbest practice) calculated using Equation (3). The monthly energy use profiles are compared with warehouse of similar size (volume). A description of energy conserving technologies appropriate for refrigerated warehouses is provided to the user. Users are encouraged to participate in future energy surveys by providing information on energy use of their warehouses. This tool is available at http://bae.engineering.ucdavis.edu/WarehouseEnergy.swf

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01,000,0002,000,0003,000,0004,000,0005,000,0006,000,0007,000,000

Warehouse

Stor

age

Volu

me

(cu

ft)

Figure 1. Storage volume of surveyed warehouses.

Table 1 Refrigeration capacity of different warehouses

Total –refrigeration

tonnage Warehouse Total -HP

A 600.00 250.00

D 290.00 168.00

E 2,100.00 504.00

F 3,000.00 1,000.00

H -- 520.00

J 1,557.00 376.00

K 1,056.00 343.00

L 6,000.00 2,000.00

M 7,080.00 4,500.00

N 1,371.00 750.00

O 2,000.00 1,000.00

P 460.00 300.00

S 757.00 350.00

Y 265.00 --

Z2 450.00 450.00

V9 2,800 --

V10 2,800 --

V11 2,800 --

V12 300 --

6

Table 2 Percent distribution of type of products stored

Processed Fruits,

vegetables, juices

Meats, Poultry, Seafood

Fresh Fruits, Vegetables,

flowers Warehouse Dairy Other

A 80 10 10 0 0

D 90 2 2 1 5

E 80 0 0 20 0

G 40 50 10 0 0

H 80 15 0 0 0

J 80 10 0 10 0

K 80 0 0 20 0

L 35 0 0 65 0

M 25 5 25 10 35

P 95 1 0 1 3

Q 0 0 100 0 0

S 90 10 0 0 0

Z2 0 0 100 0 0

Energy Use Profiles of Different Size Warehouses

050,000

100,000150,000200,000250,000300,000350,000400,000450,000500,000

Jan

Feb

Mar

Apr

May Jun

Jul

Aug

Sep Oct

Nov

Dec

Mon

thly

Ene

rgy

Use

, kW

h

0.700.800.971.122.452.463.163.80

Figure 2. Monthly energy use profiles of selected warehouses. (Legend indicates volume of a warehouse in MMft3)

7

Table 3 Specific electricity use coefficients per unit area and volume

Total Annual Energy use

Energy Coefficient

Energy Coefficient

kWh/ftWarehouse kWh kWh/ft2 3

A 3225000 16.13 0.54

D 936760 32.30 3.14

E 7813139 39.04 1.29

F 8171500 29.15 --

G 7776380 27.35 3.75

H 5103629 42.63 1.55

J 3735372 34.91 1.15

K 3735377.8 40.88 1.28

L 6880529 46.81 2.04

M 15563523 31.57 --

N 5367800 38.98 1.35

O 7274014 42.86 1.34

P 4352587 65.07 2.23

Q 2496820 33.29 --

S 4200000 26.58 1.13

Z2 609600 10.16 0.41

V1 2,601,911 -- 1.06

V2 3,353,031 -- 1.06

V3 909,725 -- 1.06

V4 1,705,369 -- 1.51

V5 877,185 -- 1.25

V6 4,747,408 -- 1.25

V7 3,233,666 -- 3.32

V8 3,877,697 -- 1.57

V9 2,237,118 -- 1.54

V10 2,468,544 -- 1.54

V11 5,399,939 -- 1.54

V12 1,463,500 -- 1.46

8

0

0.5

1

1.5

2

2.5

3

3.5

4

0 1,000,000 2,000,000 3,000,000 4,000,000 5,000,000 6,000,000 7,000,000

Storage Volume (cu ft)

SEC

( k

Wh/

ft3)

SECaverage practice

Figure 3 Specific electricity consumption of refrigerated warehouses surveyed in this study.

Figure 4 Specific electricity consumption of refrigerated warehouses operating in New Zealand, UK, and United States (Merts and Cleland, 2004) (Note: conversion factors: 35.31 kWh/m3 = 1

kWh/ft3; 1 m3 3 = 35.31 ft )

9

Figure 5. Specific electricity consumption of refrigerated warehouses (Elleson and Freund, 2004)

0

0.5

1

1.5

2

2.5

3

3.5

4

0 1,000,000 2,000,000 3,000,000 4,000,000 5,000,000 6,000,000 7,000,000

Storage Volume (cu ft)

SEC

( k

Wh/

ft3)

SECaverage practice

SECbest practice

Figure 6 Specific electricity consumption of refrigerated warehouses with SEC curve for “best practice.”

10

0

10

20

30

40

50

60

70

80

90

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28

Warehouse

Perc

ent o

f 11

ECTs

use

d

Figure 7 Percentage of 11 energy conserving technologies used by individual warehouses

Use of Energy Conserving Technologies

0

10

20

30

40

50

60

70

80

SCDTOC

COMPVFD CR

EVAPVFD

CONDVFD AECFHP UI

ELT CC

% o

f War

ehou

ses

Surv

eyed

Figure 8 Percent of warehouses surveyed using energy conserving technologies

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Conclusions and Recommendations The electricity consumption of the California refrigerated warehouse facilities surveyed in this study were consistent with previously reported results from studies conducted in New Zealand, the Netherlands, United Kingdom and United States. The energy survey of refrigerated warehouses provided new information on specific electricity consumption of cold storage facilities. Typically the SEC decreased with increasing size (volume) of the warehouse. Various energy conserving technologies were identified for potential applications in warehouse operations. A web-based benchmark tool was developed to assist operators to compare the energy use of their warehouse with a survey-based benchmark for improving energy efficiency. It is recommended that additional surveys should be conducted in the future to further enhance the database. This should result in improved statistically-based benchmark for comparison purposes. Similarly, accounting of energy use by in-warehouse measurements at selected energy efficient warehouses would be beneficial to develop additional benchmarks. References Bosma, J. 1995. Inventory study of the energy conservation potential in cold storage installations in the Netherlands. Proc. 19th International Congress of Refrigeration, vol II, 382-391 Elleson, J.S. and Freund, S.W. 2004. Benchmarking the energy performance of industrial refrigeration systems. Interim Draft Report, Industrial Refrigeration Consortium, College of Engineering, University of Wisconsin-Madison, WI ETSU. 1994. Energy Consumption Guide 37: Cold Storage Sector. Energy Efficiency Office, Department of the Environment, United Kingdom. Merts, I. and Cleland, D. 2004. Survey of Energy Use by the New Zealand Cold Storage Industry. Project # Cons307. Institute of Technology and Engineering. Massey University, Palmerston North, New Zealand.

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Appendix 1. Survey Questionnaire

Contact Information:

>

Please fill in the following or attach a business card:

Company

Site name

Primary contact

Primary contact mailing address

Telephone

Fax

Email

OR

1

All organization, site, and individual names are requested for internal use only. Such data will not be given out or published in any form.

Place business card here

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Throughput and Capacity:>

Age of original facility

Age of storage additions

Total storage area Frozen ft2

Chilled ft2

Blast freeze ft2

Convertible ft2

Total storage volume Frozen ft3

Chilled ft3

Blast freeze ft3

Convertible ft3

Total installed kW/Hp KW/Hp

Total refrigeration Tons

Type of product

Meat, Poultry or Seafood (products) % total

Dairy % total

Fresh fruit, vegetables, flowers % total

Processed fruit, vegetables, juice % total

Other % total

Total blast freeze capacity lbs/day

Total Pre-cool capacity lbs/day

If possible roughly sketch the building orientation

Questions on this page pertain to the total capacity of your cold storage facility and usage. This survey is primarily focused on storage and blast freezing.

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2

North

15

Facility and Energy Reduction Strategy>

Please indicate the total number of

Facilities

Pre-coolers

Blast Freezers

Other Freezers/chillers

Loading docks

Refrigerated docks

Compressors

Questions on this page pertain to the number of stores, docks, etc as well as some general questions about energy reduction strategies.

Condensors

Evaporators

Upgraded insultation Yes No

Cool roofs Yes No

Efficient lighting technology Yes No

Aggressive evaporative condensor Yes No

Thermosiphon oil cooling Yes No

Computer control Yes No

Compressor VFD control Yes No

Condensor fan VFD control Yes No

Evaporator fan VFD control Yes No

Floating head pressure Yes No

Sensor controlled doors Yes No

Would you like to participate in a more detailed survey of your facility?Yes No

3

Please indicate which of the following energy reduction strategies have been implimented by your organization

Do you have any ideas how funds can be directed for research and development or rebates?

>

Tariff code

Energy Provider

Month - year

Energy Use Peak Demand

(kW-hr) (kW) Received (lbs)

Dispatched (lbs)

Received (lbs) Dispatched (lbs)

Frozen (lbs)

Chilled (lbs)

Jan-04

Feb-04

Mar-04

Apr-04

May-04

Jun-04

Jul-04

Aug-04

Sep-04

Oct-04

Nov-04

Dec-04

4

Frozen Storage Chilled storage Blast freezing/chilling use

In this section we ask you questions for data on your facilities monthly schedule and energy use. Please use the table below or attach photocopies, printouts, etc as convenient. If data is unavialable for any point, please note and provide a reasonable estimate.

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Appendix 2: Area, volume, and year of construction of warehouses surveyed

Warehouse Year of

Construction

Area for Frozen storage

ft2

Area for Chilled storage

ft2 Total Area

Volume for frozen storage

ft3

Volume for chilled storage

ft3Total Volume

ft3

A 1895 150,000.00 50,000.00 200,000.00 4,500,000.00 1,500,000.00 6,000,000

D 1938 21,464.00 7,534.00 28,998.00 265,681.00 32,238.00 297,919

E 1965 194,778.00 5,362.00 200,140.00 5,886,812.00 162,111.00 6,048,923

F 1925 257,860.00 22,500.00 280,360.00 827,500.00 225,000.00 1,052,500

G 1975 210,000.00 74,280.00 284,280.00 210,000.00 1,863,920.00 2,073,920

H 1988 61,761.00 57,965.00 119,726.00 1,852,830.00 1,438,950.00 3,291,780

J 1967 82,000.00 25,000.00 107,000.00 2,624,000.00 625,000.00 3,249,000

K 1975 71,000.00 20,365.00 91,365.00 2,272,000.00 651,680.00 2,923,680

L 1960 135,000.00 12,000.00 147,000.00 3,180,000.00 200,000.00 3,380,000

M 1943 401,000.00 92,000.00 493,000.00 -- -- -

N 1965 129,637.00 8,052.00 137,689.00 3,739,183.00 241,560.00 3,980,743

O 1997 159,547.00 10,156.00 169,703.00 5,105,504.00 324,992.00 5,430,496

P 1950 29,859.00 37,033.00 66,892.00 955,000.00 1,000,000.00 1,955,000

Q 1992 37,500.00 37,500.00 75,000.00 -- -- --

S 1980 9,000.00 149,000.00 158,000.00 216,000.00 3,490,000.00 3,706,000

Z 1963 -- 60,000.00 60,000.00 -- 1,500,000.00 1,500,000

V1 1997 -- -- -- -- -- 2,452,600

V2 1999 -- -- -- -- -- 3,160,616

V3 2000 -- -- -- -- -- 857,520

V4 1954 -- -- -- -- -- 112,5384

V5 1950 -- -- -- -- -- 702,654

V6 1989 -- -- -- -- -- 3,802,832

V7 1953 -- -- -- -- -- 973,780

V8 1984 -- -- -- -- -- 2,460,986

V9 -- -- -- -- -- -- 1,450,000

V10 -- -- -- -- -- -- 1,600,000

V11 -- -- -- -- -- -- 3,500,00

V12 -- -- -- -- -- -- 1,000,000

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Appendix 3: Monthly Energy use profile

Warehouse JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

A 250000 250000 250000 250000 275000 275000 300000 300000 300000 275000 250000 250000

D 83040 73840 79040 84000 86160 8440 102240 97520 97360 74240 74240 76640

E 485636 488632 877138 652465 622081 754708 639707 628692 801585 636990 583557 641948

F 633600 534900 732000 698400 724200 806400 567600 610200 811200 635200 624000 793800

G 540,760 559,480 619,280 627,960 642,080 640,060 668,400 747,200 727,440 693,520 680,000 630,200

H 386,289 391,661 404,610 394,455 416,950 424,613 471,608 440,738 461,704 494,587 405,075 411,339

J 345,957 286,046 332,469 325,466 321,864 295,456 318,427 325,687 305,032 307,104 289,226 282,638

K 345958 286046 332470 325466 321864 295457 318427 325687 305034 307104 289226 282638

L 543637 347623 357699 487795 711974 647404 683482 752079 539394 726898 579418 503126

M 1197793 1022422 1230888 1276234 1312756 1539809 1602076 1580251 1414243 1304710 1057524 1024817

N 1036400 862200 837600 822000 992400 817200

O 551584 488452 563536 558352 568720 794063 692154 638721 644824 644824 564392 564392

P 265699 292873 336291 1211871 351064 339011 337566 334171 308869 48850 252561 273761

Q 121780 131780 15040 111680 157460 449420 172360 444740 309820 216460 201580 164700

S 350000 350000 350000 350000 350000 350000 350000 350000 350000 350000 350000 350000

Z2 18000 12600 14400 10800 30600 85200 130500 122100 97800 48900 27600 11100

V1 212,627 185,138 213,597 211,632 215,562 212,022 233,120 235,390 223,081 228,573 217,485 213,685

V2 274,008 238,583 275,258 272,726 277,790 273,228 300,417 303,343 287,480 294,558 280,269 275,372

V3 74,342 64,731 74,681 73,994 75,368 74,131 81,507 82,301 77,997 79,918 76,041 74,712

V4 124,090 121,131 137,305 133,844 147,137 143,586 156,219 163,026 144,686 156,528 145,146 132,671

V5 70,143 61,032 66,622 66,097 73,249 78,287 82,815 81,258 79,579 77,803 74,710 65,590

V6 379,623 330,312 360,562 357,722 396,432 423,695 448,203 439,774 430,691 421,078 404,336 354,980

V7 248,466 219,552 251,516 242,706 286,259 281,303 299,392 278,812 268,086 317,431 291,935 248,208

V8 257,604 292,873 336,301 319,629 351,064 339,011 350,050 366,479 338,257 334,325 321,928 270,176

V9 141,467 146,737 193,577 167,536 185,104 211,456 205,789 220,382 222,295 186,875 185,387 170,511

V10 156,101 161,917 213,602 184,867 204,253 233,331 227,078 243,180 245,291 206,207 204,565 188,150

V11 341,472 354,193 467,254 404,397 446,803 510,412 496,733 531,957 536,574 451,078 447,487 411,579

V12 119,500 111,500 102,500 122,000 135,000 120,500 127,000 140,000 125,000 123,000 126,000 111,500

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Appendix 4: Monthly profile of peak power demand

Warehouse JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

A 500 500 500 500 510 510 560 560 560 510 500 500

D 135 135 136 140 142 151 167 168 168 168 139 139

K 566 547 547 586 586 499 586 595 499 499 470 470

L 2025 1233 1258 1651 1968 1896 1733 1826 1589 1786 1747 1879

M 2028 1954 2175 2599 2284 2977 2570 2531 2495 2221 1837 1689

O 500 489 499 503 552 558 601 583 586 557 547 496

P -- 568 545 537 640 638 652 609 584 507 447 496

S 516 516 516 516 516 516 516 516 516 516 516 516

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Appendix 5: Energy conserving technologies used by refrigerated warehouses

Warehouse Upgraded Insulation

Cool Roofs

Efficient Lighting

Aggressive Evaporative Condenser

Thermo- Siphon

Oil CoolinComputer Control

Compressor VFD control

Condenser VFD

Control

Evaporator VFD

Control

Floating Head

Pressure

Sensor Controlled

Doors A 1 0 0 1 0 1 0 1 0 1 0 D 1 0 1 1 0 0 1 1 1 0 0 E 1 0 1 1 0 1 0 0 0 1 0 F 0 0 0 0 1 0 0 0 0 0 0 G 1 1 1 0 1 1 0 0 0 0 0 H 1 0 1 1 0 1 0 1 1 1 0 J 0 0 1 1 0 0 0 0 0 1 0 K 0 0 1 1 0 1 0 1 1 1 0 L 1 1 1 0 1 1 1 1 1 1 0 M 0 0 0 0 0 0 0 0 0 0 0 N O 1 0 1 1 1 1 0 0 0 0 1 P 0 0 0 1 0 1 0 0 0 0 0 Q 1 1 1 1 1 1 1 1 1 1 0 S 1 1 1 0 1 1 0 1 0 1 1 T 1 0 0 0 0 0 0 0 0 0 0 U 1 1 0 1 0 1 1 1 1 1 0 V 1 0 1 0 0 1 0 0 1 1 1 W 0 0 0 0 0 1 0 0 0 1 0 X 1 1 0 1 0 1 1 1 1 1 0 Y 0 0 1 0 0 1 1 1 1 1 0 Z2 0 0 1 1 0 1 1 0 0 1 0 V1 1 0 1 1 1 1 0 0 0 0 1 V2 1 0 1 1 1 1 0 0 0 0 1 V3 1 0 0 1 1 1 0 0 0 0 1 V4 0 0 0 0 0 0 0 0 0 0 0 V5 0 0 1 1 1 1 0 0 0 0 0 V6 0 0 1 1 1 1 0 0 0 1 1 V7 0 0 0 1 0 1 0 1 0 1 1 V8 0 0 0 1 0 0 0 0 0 0 0 V9 0 0 1 1 1 0 0 1 0 0 0 V10 1 0 1 1 1 0 0 1 0 0 0 V11 1 0 1 1 1 0 0 1 0 0 0 V12 0 0 0 1 0 0 0 0 0 0 0

0 = No, 1 = Yes