ERROR CORRECTION FOR TEBA APPLICATION IN A 
BUILDING MANAGEMENT SYSTEM 
 
 
 
 
 
 
Janaka Gunatilake 
 
(8311) 
 
 
 
Degree of Master of Science 
 
 
 
Department of Electrical Engineering 
 
University of Moratuwa 
Sri Lanka 
 
 
January 2012 
ERROR CORRECTION FOR TEBA APPLICATION IN A 
BUILDING MANAGEMENT SYSTEM 
 
 
 
 
 
 
Janaka Gunatilake 
 
(8311) 
 
 
 
Thesis submitted in partial fulfillment of the requirements for the degree Master 
of Science 
 
  
 
Department of Electrical Engineering 
 
University of Moratuwa 
Sri Lanka 
 
January 2012 
i 
 
DECLARATION 
 
I declare that this is my own work and this thesis/dissertation does not 
incorporate without acknowledgement any material previously submitted for a 
Degree or Diploma in any other University or institute of higher learning and to 
the best of my knowledge and belief it does not contain any material previously 
published or written by another person except where the acknowledgement is 
made in the text. 
 
Also, I hereby grant to University of Moratuwa the non-exclusive right to 
reproduce and distribute my thesis/dissertation, in whole or in part in print, 
electronic or other medium. I retain the right to use this content in whole or part 
in future works (such as articles or books).   
 
 
Signature:       Date: 
 
 
 
The above candidate has carried out research for the Masters/MPhil/PhD thesis/ 
Dissertation under my supervision.  
 
  
Signature of the supervisor:     Date 
 
 
 
 
 
 
 
 
 
ii 
 
ACKNOWLEDGEMENT 
 
I wish to acknowledgement and express my sincere thanks to my supervisor  
Dr.K.T.M.U Hemapala  for the technical support and advise he gave me to work on a 
research having a greater opportunity to development which in the Building 
Automation Industry of Sri Lanka. I am also grateful to Prof. Lanka Udawaththa and 
all other members of Department of Electrical Engineering, University of Moratuwa 
for the support given to me from the beginning of Electrical Installation Msc Class.  
I would also like to thank all reviewers who attended in the progress review 
presentation for giving me their valuable comments and guidance. 
Without the help and support given by Staff of Energy Management Systems (Pvt) 
Ltd, I would not have been to able to complete this research project in time and I am 
very thankful to them for their support. 
Finally I wish to thank my parents and my wife for unwavering and resolute support 
given while this dissertation is being prepared.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
iii 
 
ABSTRACT  
 
Every increase in the unit cost of Energy just magnifies the importance of 
conserving energy and can’t accomplish that without tracking its use.  More than ever, sub-
metering is being applied in industrial as well as the traditional commercial and residential 
applications to encourage conservation and increase productivity. Smart Energy monitoring 
& Billing is new concept in the word and near future need the requirement & regulations for 
the smart Energy Billing for smart Building Owner and Tenant Energy User.  
Smart Energy monitoring & Billing is new concept for Sri Lanka and near future need the 
requirement & regulations for the smart Energy Billing. In Present many of the countries in 
the word are decided to intended regulations for commercial building & other energy 
consumers in their country. 
Although sub-metering can be used to perform most critical functions such as 
equipment monitoring, trending, alarming, predicative maintenance, communication, and 
power quality analysis. This research will concentrate on Tenant billing of the Energy. 
Cooling Energy billing is one of the particular areas of the energy billing in commercial 
building sector Including Electrical Energy Usage, Cooling Energy Generation, and Cooling 
Energy Distribution & Tenant Side Air Handling Unit Energy Consumptions.  
The thesis is based for identification of existing billing method for cooling Energy 
billing and introduced new strategy for chilled water cooling energy billing system. Using 
existing building energy billing system one month period real time energy data and 
mathematically functions analyzed new algorithm for error correction. In this error 
correction algorithm introduced estimation method for cooling energy loss & stored energy 
in the chilled water piping System.  The data simulation for the new method the existing 
energy billing error reduced around 50% of existing real time energy billing system. That 
strategy application of chilled water energy billing system be more smart Billing for tenant 
& building owner.   
 
 
 
 
 
 
 
 
 
 
 
 
 
iv 
 
TABLE OF CONTENTS 
            
Declaration of the candidate & Supervisor      i 
Acknowledgement         ii 
Abstract          iii 
Table of content         iv 
List of Figures          vi 
List of Tables          vii 
List of abbreviations                   viii 
List of Appendices         x 
1. Introduction         1 
 1.1 Level of TEBA System      1 
1.2 Type of Energy or Utility Billing Available     2 
1.3 Survey of Utility Rates                 3 
1.4 Motivations for Increased Advanced Metering  
  Systems in the world                  4 
1.5 Objective of the Research       5 
1.6 Motivation of the Research      5 
 
2. TEBA System Architecture       7 
2.1 BMS Server        7  
2.2 TEBA Data Server       8 
2.3 Data Storage Hardware      9 
2.4 DDC         10 
2.5 Metering Communications and Data Storage    11 
2.6 Traditional Metering Communication Options   11 
2.7 Modern Metering Communications     12  
2.8 Building Automation System      15 
2.9 Data Storage Software      16 
2.10 Energy Metering Devise      19 
2.11 TEBA Data Analysis and Energy Information Systems  20 
v 
 
2.12 Data Output Considerations      23 
 
3. TEBA System Model        27 
3.1 Chiller Plant Arrangement & Pump System    27 
3.2 Data Acquisition in the Chiller Plant     28 
3.3 AHU Details in the Selected System     33 
3.4 Data Acquisition in the Air Handling Units (AHU)   36  
3.5 Data Acquisition SCADA Software     37 
 
4. TEBA Energy Calculation Procedure      38 
4.1 Cooling Load Calculation      38 
4.2 Total Electrical Energy used by Cooling Plant   40 
 4.3 Tenant Energy Bill       40 
4.5 Disadvantage of the System      41 
 
5. Analyzing of the Collected Data      43 
         
6. Strategy of new Energy Billing System      52 
6.1 Energy Conservation of Chilled Water Plant    52 
6.2  Estimation the Valve for the Qloss Cooling Energy loss   53 
6.3  Result          58 
6.4 Implementation       59 
 
7. Conclusion and Recommendations      64 
 
Reference List          68 
Bibliography          71 
Appendix A: Hourly Energy Data for 2009 September    72 
 
 
 
 
vi 
 
LIST OF FIGURES 
         
                              Page 
 
Figure 2.1: TEBA System Architecture      7 
Figure 2.2: BMS Architecture HNB Tower      18 
Figure 3.1: Chiller Plant Lay out Diagram      27 
Figure 3.2: Power Transducer       29 
Figure 3.3: Power Transducer Functional Block Diagram    29 
Figure 3.4: AHU Equipment Layout       35  
Figure 5.1: Weekday Hourly Energy Profile      45 
Figure 5.2: Weekend Hourly Energy Profile      47 
Figure 5.3: Weekly Cooling Energy Difference     48 
Figure 5.4: Working Day Hourly Cooling Energy Difference   50 
Figure 6.1: New Energy Billing Flow Chart       56 
Figure 6.2: Existing System Hourly Energy Data for Week day Sample 01  60 
Figure 6.3: New System Hourly Energy Data for Week day Sample 01  60 
Figure 6.4: Existing System Hourly Energy Data for Week day Sample 02  61 
Figure 6.5: New System Hourly Energy Data for Week day Sample 02  61 
Figure 6.6: Existing System Hourly Energy Data for Week day Sample 03  62 
Figure 6.7: New System Hourly Energy Data for Week day Sample 03  62 
Figure 6.8: Summarized Daily Energy Data  from Existing System   63 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
vii 
 
LIST OF TABLES 
                       Page 
 
Table 3.1: Air Handling Unit Data       33 
Table 5.1: Hourly Energy data for Working day     44   
Table 5.2: Hourly Energy data for Saturday      46   
Table 5.3: Weekly Energy data for Saturday      48 
Table 5.4: Hourly Energy data for Working Day     49 
Table 6.1: Data for Zero Energy Input Condition         54 
Table 6.2: Error Calculation Table       57 
Table 6.3: Result         58 
Table 7.1: Cooling Energy Distribution Loss      66 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
viii 
 
LIST OF ABBREVIATIONS 
 
Abbreviation Description 
A Ampere 
AC Alternative Current 
AC Air Conditioning  
AHU Air Handling Unit 
AMR Automated Meter Reading  
BAS Building Automation System 
BMS Building Management System 
BTU British Thermal Unit 
CDD Cooling Degree Day 
CPP Cost per person 
CT Current Transformer 
DC Direct Current 
DCS District Cooling System 
DDC Direct Digital Controller 
E Total Electrical Energy Input to the Central AC Plant  
EBI Enterprises  Building  Integrator 
EIS Energy Information System 
𝐸𝑟 Total electrical energy input to the AC Plant in kWh. 
𝑒𝑟  Total electrical energy input to the AC Plant in kWh 
HDD Heating Degree Day 
IP Internet Protocol 
IT Information Technology 
kWh Kilo Watt Hour 
LAN Local Area Network 
m/s Meters per second 
mA Mille Ampere 
MF Maintenance Factor 
ix 
 
Qb Balanced Cooling Energy in the System 
𝑄ℎ 
 
Heat flow rate in kW Qi ith AHU Consumed Energy Qp Chiller Generated Cooling Energy 
𝑄𝑟 Total Cooling load for AC Plant (Zone 1 & 2) only for time t in kW. QS Stored Cooling Energy of the System 
𝑄𝑇 Total refrigererent tons generated at the AC plant 
𝑄𝑡 Total refrigererent tons used by tenant AHU 
R Rate of change for Electricity Rs/kWh. 
RF Radio frequency  
RTU Remote Terminal Units 
SCADA Supervisory Control and Data Acquisition 
SQL structured query language  
SS Stainless Steel 
TCP Transmission Control Protocol 
TEBA Tenant Energy Billing Application 
𝑻𝑬𝑩𝒕 Tenant Energy Bill 
VA Volt Ampere 
WAN Wide Area Network 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
x 
 
LIST OF APPENDICES 
                
                 Page 
APPENDICES A:     Hourly Energy Data 2009 September    72 
1 
1. INTRODUCTION 
 
An “advanced meter” is commonly considered an energy meter that provides 
short interval measurements and can be read remotely. The term “smart meter” is also 
used but generally refers to meters with the capability to send and receive messages 
regarding pricing, along with other sophisticated utility functions. 
Tenet Energy Billing Application (TEBA) refers to a feedback where advanced meters, 
remote database storage and software tools are employed to monitor and maintain 
energy billing application in a commercial Building. 
The TEBA collects energy consumption data from Building Management System on a 
continuous basis to provide feedback to Property Management Teams, operators and 
Tenant users who maintain and improve performance through equipment & Monthly 
Energy Rates & Charges. TEBA System and features are deployed at different levels 
(i.e. whole building, or component) depending on the size and complexity of the 
building. Significant advantages over reliance on utility bills for performance feedback 
include: 
• Automatic billing for Tenant utility (Water, Electricity, Chilled water, hot water, 
etc). 
• Much easier and more reliable access to energy usage information for portfolio 
managers, designers, energy efficiency programs and energy service consultants. 
• Immediacy of information, compared to waiting for bills to arrive at fixed 
intervals. 
• Additional detail (daily, hourly, sub-metering where desired), facilitating further 
investigation into problems and tenant usage allocations. 
 
1.1 Level of the TEBA System 
 
The advanced meters that form the TEBA can be installed to monitor any Energy used in 
commercial buildings including natural gas, electric, fuel oil, heated or chilled water, or 
2 
steam. The most common Energy for commercial buildings are electricity & Chilled 
water cooling Energy. 
The installation and use of a TEBA can involve measurements at different levels of the 
building, referring to what energy end-uses are captured in the measurement. Following 
basic installation levels are commonly available for the TEBA Systems. 
1. Whole Building, premises or site: The advanced meter measures usage for the 
whole site including all systems, components and auxiliary loads. Installation 
may be by the owner or the utility. 
2. System or Subsystem: The meter measures the energy usage of a certain type of 
equipment installed in the building (e.g. lighting, elevators, heating, cooling, core 
and shell, tenant sub metering). sub metering installed to allocate the utility bill 
among tenants is considered system level metering in this report. 
3. Component or Equipment: The owner-installed meter measures the input to a 
single piece of building equipment, such as a boiler or chiller. Often this 
metering is combined with other of building equipment, such as a boiler or 
chiller. Often this metering is combined with other output as Electrical Power 
Meter data, Thermal Energy Consumption Data etc. 
 
1.2 Type of Energy or Utility Billing Available 
 
Many buildings are equipped with only a primary metering system for measuring and 
billing energy consumption for the entire building.  In buildings with this configuration, 
the tenants are typically billed for energy usage on either a fixed rate (cost per square 
foot) that is built into the lease, or the bill is allocated to tenants based on their square 
footage.  Each of these methods have inherent flaws, but both share the common 
problem that energy costs are unlikely to be accurately charged to the tenants.  Under a 
cost per square foot arrangement, the owner will almost certainly collect more or less 
than the actual bill, and the discrepancy will be even greater during times of energy 
volatility or low occupancy rates.  If the bill is simply divided amongst the tenants on a 
3 
per square foot basis, tenants with lower energy density (BTU per square foot) will 
subsidize the space costs for those with higher energy density (e.g., data centers).  These 
errors become particularly acute when there is a wide variance in occupancy schedules 
(retail vs. office space) and the building provides central services such as chilled water 
or conditioned air.  Additional complexity is added when the building owner must make 
decisions in advance on the cost to add when the rate structures for commercial 
buildings are taken into account. 
 
1.3 Survey of Utility Rates  
 
 When Analysis of Utility Rate Structures can be identified various type of billing 
strategy & Structures available in the world. The following parameters define the 
characteristics of rate structures from different perspectives: 
• Price trigger:  
• Time trigger (price period): seasonal rate, monthly rate, daily rate, time of 
use, and real-time pricing. 
• Event trigger (price event): CPP-fixed, CPP-variable, direct load control, 
interruptible rate, load curtailable rate, demand bidding, demand buyback, 
extreme day pricing. 
• Range of price period:  
• Season: seasonal rate  
• Month: monthly rate  
• Day: daily rate o Hours: daily time of use  
• Hour or less: real-time pricing 
• Price dynamics during price period:  
• Fixed price: energy rate, energy and demand rate, time of use. 
• Fixed price + spot price: two-part real-time pricing.  
• Spot price: one-part real-time pricing. 
 
4 
• Range of spot price  
• Upper bound: real time pricing with caps.  
• Upper and lower bound: real-time pricing with collars.  
• Unbounded: real-time pricing. 
• Advance notification of price event  
• Day ahead: real-time pricing  
• Day of: real-time pricing  
• Day after: daily pricing (Portland General Electric)  
• Hour ahead: real-time pricing  
• Half hour ahead  
• No notification: interruptible rate, direct load control.  
• Frequency of price even 
• Duration of price event  
• Fixed hours: critical peak pricing - fixed, extreme day pricing,  
• Variable hours with upper bound: critical-peak pricing - variable, direct 
load control, interruptible rate, demand bidding, demand buyback. 
Price dynamics during price event  
• Fixed price: critical peak pricing, extreme day pricing, direct load control, 
interruptible rate.  
• Spot price: market-based interruptible rate, demand bidding, demand buyback. 
 
1.4 Motivations for Increased Advanced Metering Systems in the world 
 
Increasing the energy cost and energy management in the world the energy users 
motivated to monitoring and analyzing their energy consumption. Mainly their 
motivations are based on, 
5 
Persistence in Building Efficiency:  Achieving and maintaining the performance of 
highly efficient buildings will require effective monitoring with owner/operator 
feedback.   
Evidentiary Design: There is little hard evidence of verified building performance; a 
2007 study of LEED buildings1  carried out by New Buildings Institute showed wide 
variation in predicted versus actual energy usage. For future buildings to improve, 
simpler and faster data collection methods are needed to acquire this critical feedback 
and proof of performance. 
 Advancing Building Performance Metrics: It’s likely that the next generation of 
energy codes and building programs like LEED will call for performance requirements. 
Building Performance Review and labeling programs will necessitate separation 
between tenant activity-driven loads (such as plugs) and processes and the core and shell 
loads (such as HVAC and common area lights) and require flexible metering and data 
acquisition. 
 
1.5 Objective of the Research 
 
This research is designed to help regulators, program managers and other interested 
parties understand the error corrections available in advanced metering as used in tenant 
energy billing system Applications (TEBA) for sub metering in centralize Chilled water 
plant with Chilled water distribution systems in commercial building or District Cooling 
System (DCS). 
 
1.6 Motivation of the Research 
 
With incising the trend of Enterprises Energy management systems and green building 
technologies in Sri Lankan building sectors also interested to Integrated Cooling Energy 
billing systems with their building Management systems. The HNB Bank Head office 
6 
tower building is 1st and only building that installed TEBA Integrated cooling energy 
billing systems in Sri Lanka. 
The system is based on real time cooling energy balancing for the cooling energy billing 
in 6 min time intervals. But considering the energy difference between cooling energy 
production of the chiller plant and cooling energy consumption of the Air Handling units 
is nearly 8 to 9% of the cooling energy production of the day. That is actually 
uncomfortable satiation for Building Owner and the tenant. This situation is effect to 
discourage the industry to install the TEBA systems their buildings. 
. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7 
2. TEBA SYSTEM ARCHITECTURE 
 
 
 
Figure 2.1: TEBA System Architecture 
 
2.1 Building Management System (BMS) Server 
 
Building Management System Server is the Management Level Processors, at the top of 
the BAS system hierarchy, exercise control and management over the connected 
subsystems. An Operator at this level can request data from and issue commands to 
point anywhere in the system(as which most operations –Level processors).Day to day 
operation is normally a function of the operations-Level processor; However ,complete 
control can be transferred to management level processor during the emergencies or 
unattended periods. The management-level processor primary collects, stores, and  
processes historical data such as energy use, Operating costs and alarm activity, and 
generate reports that provide a tool for the long term management and use of the facility. 
Chilled water Supply Temperature Sensor 
Chilled water Return Temperature Sensor 
Chilled water Flow Sensor 
8 
When using multiple operation/management level processors, one is defined as the 
database server, where current database resides. Any processor may initiate a system 
change (graphic or text modification, operator assignment, schedule, etc), but all 
changes are made to the server database. The server is a software function and may be a 
dedicated Computer or any other LAN processor. 
 
2.2 TEBA Data Server 
 
2.2.1 Data Storage Software 
 
Assuming proper data collection and communication, some form of data storage system 
will be needed for the TEBA System development. The data storage needs will depend 
on the number of meters connected, the number of parameters metered, the data interval, 
and the expected need for access to historic data. In most cases, one of any number of 
commercially available database software systems will function well for data storage 
and software interface. The specific requirements of the data storage/database system 
should be decided with assistance from site IT staff or others knowledgeable, or those 
who will be using the system.  
 
2.2.2 Data Storage Specification Considerations 
 
Data for the TEBA shall be stored in a structured query language (SQL) compliant 
database format or time series format. Minimum requirements are a SQL server or 
equivalent. The database shall allow other application programs to read and access the 
data with appropriate password protection while the database is running. The database 
shall not require shutting down in order to access or have data added. 
Trend data shall be archived in a database from field equipment in time intervals no less 
than once per day. Storage on the field equipment will be reset once data are exported to 
9 
allow for trending if communication is disrupted. Data will be uploaded once 
communication is re-established. 
Blank or null values in the database will be replaced with actual data using past recorded 
data or manually feed data to the system. Calculations and other metrics will be updated 
once controller data is uploaded. This overall system update to check for new data 
should be automated to run once a day. 
 
All data shall be stored in database file format for direct use by third-party application 
programs. Sufficient data storage capacity will be able to store at least two years of data 
for all data points. In addition, storage capacity will also allow for compression of one 
year of data for historic trends and archiving. 
Time stamps shall be collected on all data. The time stamp, depending on system 
architecture, will be captured at the field controller or system controller and directed to 
the database archive. 
Exported data shall contain no duplicate records or duplicate time stamps in output files. 
Each date/time stamp for a specific point shall be unique. The export query shall be for a 
specific point or multiple points in a defined group. 
Date/Time fields shall be in a single column in a format automatically recognized by 
common spreadsheet, database software tools, or EIS. 
The data shall be fully contained in a single file or table for each point. Data shall not 
span multiple files or database tables. Users can have the option to modify export file 
start and end file date span depending on third-party program requirements to evaluate 
the data. Key to productive use of data is the access for analysis, whether done in-house 
or as part of a third-party EIS package or agreement. 
 
2.3 Data Storage Hardware 
 
The computer hardware for data storage and software execution should have ample 
processing power and memory to run the chosen database system and to process, store, 
10 
and archive all collected data. Fortunately, such activities can be handled quite easily 
with modern stand-alone personal computers and/or workstations. One key 
recommendation is that whatever system is chosen, it be dedicated to this activity. It is 
also recommended that this system have an automated back-up function (typically daily) 
to a separate system/server for data protection and archiving. An increasingly popular 
option for data storage involves an agreement with a third-party organization (e.g., an 
EIS vendor or other data-hosting entity) 
whereby all data are collected, stored, and backed-up on vendor computer servers. In 
this case, the client is given access, usually over the web, to all data and analyses for 
addition processing, reporting, and downloading. 
 
2.4 Direct Digital Controller (DDC) 
 
DDC is a types of microprocessor-based controllers used in commercial buildings. 
These controllers measure signals from sensors, perform control routines in software 
programs, and take corrective action in the form of output signals to actuators. Since the 
programs are in digital form, the controllers perform what is known as direct digital 
control (DDC). Microprocessor-based controllers can be used as stand-alone controllers 
or they can be used as controllers incorporated into a building management system 
utilizing a personal computer (PC) as a host to provide additional functions. A stand-
alone controller can take several forms. The simplest generally controls only one control 
loop while larger versions can control from eight to 40 control loops. As the systems get 
larger, they generally incorporate more programming features and functions. This 
section covers the controller as a stand-alone unit. Refer to the Building Management 
System Fundamentals section for additional information on use of the controller in 
networked and building management systems. 
 
 
 
11 
2.5 Metering Communications and Data Storage 
 
An integral part of the overall metering system is the mode of communications from the 
sensors to the meter and then from the meter to the point of data storage, analysis, and 
archiving.  The communication from sensor to meter is usually handled internal to the 
meter and largely transparent to the user.  The communication from the meter to the 
ultimate storage, analysis, and archiving is the focus of this section. Regardless of the 
meter type, once data are collected they need a communication pathway to a location 
where the data will be processed, stored, and used.  This pathway should be amenable to 
the various meter output types – some of the more common output types include:   
• Analog output – typically, 4 to 20 mA or 0 to 5 volts dc   
• Contact closure – pulse type output   
• Digital output – digital pulse   
• Digital signal – outputs using networked communications (e.g., Ethernet, 
Modbus, HART). 
Many of the newer digital-signal output meters can output multiple signal types offering 
a variety of communications options.  These meters can be serially addressed, affording 
a lowered installed cost through reduced wiring installation and expense (i.e., multiple 
meters communicating on one pair of wires back to the data-collection terminal).  Often 
these outputs can be viewed on local displays integral to the meter.  These displays are 
quite useful for field set-up, calibration, verification of function, and troubleshooting. 
 
2.6 Traditional Metering Communication Communications Options (Non-
Automated) 
 
Over the past 20 years, communications have moved from requiring a hand-written 
recording of the metered value to a manually entered electronic recording to a locally 
transmitted electronic value.  These data collection/communications modes are still in 
practice and are described below. 
12 
 
2.6.1 Sneaker-net Data Collection.  
 
 A largely outdated, yet still practiced, method of manual meter reading involving 
writing down or keying in to a hand recorder the metered data.  This data collection 
practice is inefficient, inaccurate, and discouraged in most applications. 
 
2.6.2 Mobile-Radio Data Collection. 
  
 This technology makes use of close-proximity radio frequency (RF) communications 
where by data are transmitted by the meter to a receiver – usually located in a slowly 
moving vehicle.  While more accurate than sneaker-net, it still has an in-field manual 
collection component – driver and vehicle. 
With the enactment of EP Act 2005, which explicitly states that metered data will be 
collected automatically, via automated meter reading (AMR) and made available at least 
daily, federal agencies are now required to use AMR – where practicable.  As such, the 
following section presents the AMR systems that are more common and applicable to 
the federal sector. 
 
2.7 Modern Metering Communications:  Automated Meter Reading (AMR) 
 
AMR systems, both wired and wireless, are increasingly being used owing to their 
availability, reliability, and decreasing cost.  Many utilities, large corporate campuses, 
and universities are finding AMR not only to be convenient, but to make good business 
sense.  When developing the communications portion of your metering program, it is 
important to consider what existing communications infrastructure you can take 
advantage of (e.g., building automation system, local area network) to potentially lower 
the cost of AMR.  In addition, if you have a large site with distributed buildings you may 
find benefit in considering multiple communications technologies (e.g., networks in one 
13 
area, phone lines in another, and wireless in a third) to gain the necessary 
communications coverage. Below are the predominant AMR technologies along with 
some of the benefits and challenges of each. 
 
2.7.1 Phone Modem.   
 
Taking advantage of telephone modem technology in both hardwire and wireless (i.e., 
cellular), this communications solution is the oldest and traditionally most reliable of the 
technologies.  In typical applications, automated software (usually from the metering 
equipment vendor) is used to dial (phone-in) the modem daily to retrieve accumulated 
data.  In addition to the phone-in systems, there are meters that can phone-out at preset 
times or at specified data accumulation levels.  It should be noted that phone lines do not 
have to be dedicated to the meter(s) they serve; there is no reason meters cannot share a 
phone line with other applications – even personal office phones.  Shared phone line 
applications can use off-hours for data communications and, therefore, do not interfere 
with other business-related uses. 
 
2.7.2 Local Area Network.  
 
 Using an existing building or site’s computer network to serve as the communications 
path for the metering system can be very economic.  When properly configured, meters 
can communicate over this network using a variety of open protocols, including 
Modbus, HART, TCP/IP, BACnet, etc.  In addition, these meters usually can be serially 
addressed and linked together (daisy-chained) to minimize wiring installation and 
expense. 
Beyond the local area network (LAN), wide-area networks (WANs) can be developed 
by linking more than one of these networks together (usually via phone lines or through 
wireless solutions).  This becomes useful to large sites with many distributed buildings 
and locations.  Additional benefits to the LAN solution include the ability to share data 
14 
throughout the network and view data in real time.  Prevalent concerns with using a 
LAN for data communications stem from perceived security issues with transferring data 
over secure networks and potential access to the LAN via the metering points.  In both 
cases, these concerns can be addressed with typical LAN security protocols.  As is often 
the case, some level of education on the system, its operation, and security may be 
necessary – a small demonstration of the system may help convince skeptical IT or 
information-security staff. 
 
2.7.3 Radio Frequency/Wireless Networks. 
 
   Becoming increasingly available and economic, wireless radio frequency (RF) 
communications makes use of wireless transmitters and receivers to communicate 
metered data.  Wireless communication (FEMP 2007) offers the benefits of lowered 
installation cost, flexibility in metering locations, and minimizes disruption in service 
when compared to other options.  Some of the limitations to wireless communications 
include the effective distance of communication (typically less than 300 feet) and the 
building’s materials of construction that may impede or block the RF signal.  Both 
situations can be mitigated by using a repeater or mesh network configuration.  Similar 
to the LAN solution, wireless communications has perceived challenges including 
security issues and potential for interference with other sensitive communications 
equipment.  In many cases these concerns are unfounded, yet some level of education on 
the system, its operation, and security may be necessary – a small demonstration of the 
system may help convince skeptical IT or information-security staff. 
 
2.7.4 Power Line Carrier.  
 
  This technology uses existing electrical wiring, both internal and external to 
buildings, as the communications conduit.  While making use of the existing 
infrastructure gives this technology and economic advantage, some of the limitations 
15 
relate to speed and quantity of data transfer and the ability to transfer data across 
standard electrical transformers.  Organizations making productive use of this 
technology, notably utilities and sites with many distributed buildings, do so by 
spreading the considerable installed cost over many metering points. 
 
2.8 Building Automation System.  
 
 By using an existing Building Automation System (BAS), we again take 
advantage of a site’s previous investment in existing infrastructure.  In this case, the 
wiring used for BAS communication becomes the metering communications path.  In 
this case, the meters are treated as other “points” on the BAS and function much as other 
sensors or points on the system (i.e., communicate to and from the central host 
computer).  The BAS is a workable solution only when there is excess capacity to add 
points and system software is capable of using the meter’s data output protocol – both of 
these factors need be verified with the BAS and metering equipment vendors.  An 
additional constraint to the BAS solution relates to the host computer’s ability to allocate 
memory for these data and offer an ability to retrieve data sets in an automated fashion. 
 
2.9 Data Storage Software 
 
Assuming proper data collection and communication, some form of data storage 
system will be needed.  Data storage needs will depend on the number of meters 
connected, the number of parameters metered, the data interval, and the expected need 
for access to historic data.  In most cases, one of any number of commercially available 
database software systems will function well for data storage and software interface. The 
specific requirements of the data storage/database system should be decided with 
assistance from site IT staff or others knowledgeable, or those who will be using the 
system.  Below are draft specifications based on work done for the California Energy 
16 
Commission Public Interest Energy Research Program and the Building Technologies 
Program of the U.S. Department of Energy (CEC 2007). 
 
2.9.1 Data Storage Specification Considerations 
 
Data shall be stored in a structured query language (SQL) compliant database 
format or time series format.  Minimum requirements are a SQL server or equivalent. 
The database shall allow other application programs to read and access the data with 
appropriate password protection while the database is running.  The database shall not 
require shutting down in order to access or have data added. Trend data shall be archived 
in a database from field equipment in time intervals no less than once per day. 
Storage on the field equipment will be reset once data are exported to allow for trending 
if communication is disrupted.  Data will be uploaded once communication is re-
established. Blank or null values in the database will be replaced with actual data.  
Calculations and other metrics will be updated once controller data is uploaded.  This 
overall system update to check for new data should be automated to run once a day. 
All data shall be stored in database file format for direct use by third-party application 
programs. Sufficient data storage capacity will be able to store at least two years of data 
for all data points.  In addition, storage capacity will also allow for compression of one 
year of data for historic trends and archiving. 
Time stamps shall be collected on all data.  The time stamp, depending on system 
architecture, will be captured at the field controller or system controller and directed to 
the database archive. 
Exported data shall contain no duplicate records or duplicate time stamps in output files.  
Each date/time stamp for a specific point shall be unique.  The export query shall be for 
a specific point or multiple points in a defined group. 
Date/Time fields shall be in a single column in a format automatically recognized by 
common spreadsheet, database software tools, or EIS. 
17 
The data shall be fully contained in a single file or table for each point.  Data shall not 
span multiple files or database tables.  Users can have the option to modify export file 
start and end file date span depending on third-party program requirements to evaluate 
the data. 
 
 
18 
 
Figure 2.2: BMS Architecture HNB Tower 
19 
2.10 Energy Metering Devise 
 
2.10.1 Electrical Power Analyzers 
 
Electrical Power Analyzers are most important devises for the TEBA Systems for 
gathering the data. Following applications are applied electrical power analyzers for the 
TEBA Systems. 
To Measure Plant power consumptions in the chilled water plant including Chillers, 
Chilled water pumps, Condenser water pumps etc. 
To measure power consumption AHU, Lighting Systems and other power consumed 
equipments power consumptions. 
The High End multifunction power meter used in BAS & TEBA Systems including 
following measuring & monitoring futures with the integrated to the system via 
communication interfaces, 
• True-RMS Measuring Parameter   
• ANSI C12.20(0.2 Class) and IEC 62053-22(0.2S Class)  
• Power Quality Analysis   
• Over Limit Alarm   
• Multi Communication Ports (Eg: Ethernet, Modbus,Plofi Bus) 
 
2.10.2 Thermal Energy BTU Meters 
 
Thermal energy BTU meters are used for measured thermal energy consumption through 
hot water or chilled water in the system. The BTU meters are consist of water flow 
meter & two temperature sensors for measure supply & Return water Temperature 
through AHU Cooling or Heating coil.  
The Flow meters may be Electromagnetic type, Turbine type, Positive displacement type 
or vane types. The temperature sensors may be Negative thermo couple, PT 100 or PT 
1000.The measurement accuracy is depending on sensor type and their applications. 
20 
Typical digital BTU meters is a fully user programmable digital flow meter capable of 
measuring flow rate along with totalized flow, & batching of conductive liquids. 
Manufactured using latest technology, the microcontroller and embedded software used 
in the instrument offers better accuracy and user convenience. The flow meter is 
supplied as two components. The sensor and transmitter The sensor converts the flow of 
the fluid in the pipe to an electrical signal and transmits it through a cable to the 
Transmitter. The second component is the transmitter, which consists of the sensor drive 
and a flow computer. The sensor drive provides the excitation voltage for the field coils 
in the sensor. The flow computer converts the velocity signal to actual flow and also 
totalizes the flow. Proper signal conditioning is done using special algorithms to 
compensate for undesired flow patterns. All the programmable values , are stored in the 
internal non volatile memory.  
The totalized flow is also backed up in this non volatile memory during power down, 
and recalled during power up. This feature enables the instrument to totalize only on the 
last value, Front key panel can be used to reset to talizer to zero. The nonvolatile 
memory is capable of storing all the user settable data and retain the data even during 
power down. The memory is capable of storing this data for a period of 100 years. Each 
data value , that is being programmed is stored in allocations and also in two additional 
backup locations. 
 
2.11 TEBA Data Analysis and Energy Information Systems (EIS). 
 
Depending on the interval and collection frequency, metered data can accumulate 
quickly and become overwhelming unless some level of automated data processing is 
implemented.  At the outset of any metering activity, it should be made clear that meters 
provide data and these data generally do not constitute information or knowledge.  The 
reality of data analysis comes in the recognition that data needs to be processed to create 
information (knowledge) before any proactive actions can be taken.  To be successful in 
their metering activities, the federal sector must recognize that meters and data alone are 
21 
not the answer; success comes when the data are processed to create information and 
this information used for action. This chapter focuses on suggestions for productive uses 
for metered utility data as well as discusses some of the options for data analysis and 
processing. 
An Energy Information System (EIS) is an integrated development combining 
analytical software and hardware (sensors and meters) with a communications system to 
collect, analyze, and report building energy/resource data.  While these systems can be 
installed in a “turnkey” sense (i.e., all sensors, meters, and software are installed), many 
applications make use of existing hardware and communications and the EIS becomes 
strictly a software solution.  The balance of this section will focus on the software data 
analysis aspects of the EIS solution. 
The software aspect of the EIS can take the form of a very simple (in-house 
developed) spreadsheet-based routine for processing metered data, to a very complex 
(third-party purchased/licensed) software package with many sophisticated routines and 
statistical analysis capabilities. 
As with the different offerings, there are a variety of fee arrangements available 
through these vendors.  Some EIS organizations offer their service under a licensing 
agreement allowing only a certain number of users or “seats.”  Other EIS organizations 
offer unlimited users under a time-based subscription service and still others offer their 
product as a one-time software purchase with fee-based technical support.  A list of EIS 
vendors can be found in the following references:  CEC (2007) and LBNL (2002). 
 
2.11.1 EIS Development/Selection Considerations. 
 
Prior to making the decision to develop an in-house EIS versus 
purchasing/licensing a third-party product (or something in between), your organization 
needs to determine the options and expectations of the EIS in at least the following areas 
(CIPEC 2004): 
22 
Definition of facility objectives – need to be clear on how the EIS will be used, how it 
will improve resource efficiency, and its contribution to the financial payback of the 
overall metering system. 
EIS integration with other IT systems – an important consideration prior to EIS 
selection/development is what existing infrastructure can be used.  Prior to the EIS 
decision, a survey of existing facility software, hardware, communications, meters, and 
capabilities is recommended. 
 
Identify key reporting outputs – How will the outputs of this system be used to fulfill 
the objectives of the facility and its management. How will the outputs be made 
available (paper copy, email reporting, web-based reporting) and what sort of summary 
options are available. 
Data-collection needs – what are the data-collection requirements necessary to achieve 
the key reporting outputs.  Are these available with existing metering elements.  
Data analytics – what analysis, statistical and/or regression routines are needed to 
transform the data to into the information desired?  Are the chosen analytics capable of 
handling the size, frequency, and complexity of anticipated data?  
Management support – has a budget been developed addressing expenses such as 
ongoing training, periodic testing, technical assistance, and troubleshooting?   
Data Storage- What is the database compatibility for the EIS?  Is it compatible with the 
following systems?  
Web-service client with Extensible Markup Language (XML)  Open Database 
Connectivity (ODBC) compliant to interface third-party software application  Structured 
Query Language (SQL)  Application Program Interface (API) to communicate with 
specific field devises such as handheld equipment  Is the database and the data transfer 
through the Internet encrypted. 
 
 
 
23 
 2.12 Data Output Considerations.  
 
 The final element for consideration in EIS development or selection is the output 
information.  Prior to development or selection, facilities staff need to review the 
objectives and goals of this entire metering system.  Once identified, these can be used 
to help shape the type and form of EIS output necessary to achieve these objectives.  
Assembled below are a variety EIS output options collected from different vendors and 
resources.  These are grouped into the categories of graphical outputs, analytical outputs, 
system-specific outputs, and utility outputs.  While these categories are not all-inclusive, 
they should provide some guidance in identifying the capabilities and outputs 
advantageous to you and your systems.  One additional caution, as you make your 
decisions on vendors and levels of service/outputs, keep in mind the associated volume 
of data and the necessary time to process and act on the data.  The recommendation is to 
start with a manageable set of outputs that can be useful in the expected time allocated.  
Then, as the system becomes more integrated, look to add features and other options.  
To start – keep it simple. 
 
2.12.1 Graphical Outputs:  
 
Consider these as the plots you and your staff interact with on a daily, weekly, 
and monthly basis.  Make certain axes are scaled and labeled for intuitive understanding 
now and into the future. 
Daily profile:  Time-series daily load profiles are displayed with time, in intervals of an 
hour or less, along the horizontal axis and load along the vertical axis. 
Day overlay:  Overlay plots display multiple daily profiles on a single 24-hour time-
series graph. 
Multi-point overlay:  Allows viewing of multiple time series data points on the same 
graph. 
24 
3-D surface chart:  Three-dimensional surface charts often display the time of day, date, 
and variable for study. 
Calendar profile:  View up to an entire month of consumption profiles on a single 
screen as one long time series. 
X-Y scatter plots:  X-Y scatter plots are useful for visualizing correlations between two 
variables. 
 
2.12.2 Analytical Outputs:  
  
Consider which analyses will be most useful and incorporate those into the EIS 
as an automated function.  The goal is to minimize the amount of exporting and re-
analyses needed. 
Basic statistical analysis:  Perform statistical calculation, such as mean, median, 
standard deviation, correlation, and regression. 
Benchmarking: Benchmark against building energy standards or public database such 
as EnergyStar.   
Intra/inter-facility comparisons:  Benchmark against the building’s historical data or 
across multiple buildings in the enterprise.   
Aggregation:  Aggregate data among multiple data points.  Integrate different energy 
units using energy conversions (e.g., kWh, Therm, etc., into Btu). 
 Data mining (data slice/drill-down):  Sum-up/drill-down time series data by monthly, 
weekly, daily, hourly, or trended interval.   
Normalization:  Normalize energy usage or demand by some factors such as building 
area, number of occupants, outside air temperature, and cooling or heating degree-days 
(CDD, HDD) to make a fair comparison between buildings. 
Hierarchical summary:  Summarize usage and cost information by different levels.  
For example, starting from equipment energy cost, individual building energy cost, site 
energy cost, to regional energy cost. 
 
25 
2.12.3 System-Specific Outputs: 
 
Look for customized analyses beyond the “graphical and analytical” outputs 
mentioned above.  This type of analysis often takes multiple data points and use more 
complicated algorithms. 
Power quality analysis:  Monitor the voltage or current phases for conditions that could 
have adverse affect on electrical equipment. 
Steam charts:  Calculate temperature, pressure, specific volume, and enthalpy for 
saturated steam and water. 
Forecasting:  Forecast future trends by historical data and related parameters. 
Validation, editing, estimation:  A process performed to ensure quantities (kWh, kW, 
kVar, etc.) retrieved from meters are correct.  The process includes validation of data 
within acceptable error tolerances, editing or correcting erroneous data, and estimating 
missing data.  
Equipment fault detection and diagnostics:  Diagnose equipment failure or degradation 
based on customized algorithm and parameters.  
 
2.12.4 Utility Outputs:  
 
Consider how these data can be useful in interactions with your utilities.  
Typically, there are tools allowing rate comparisons, bill verification, etc.  
Invoice verification (bill validation):  Utility bills are compared to meter readings (so 
called “shadow” metering) to validate accuracy of bills. 
 Energy cost drilldown:  Using energy tariff and usage data, calculate daily or hourly 
energy cost breakdown, instead of the usual cost that can only be seen in monthly utility 
bills. 
 Real-time cost tracking:  Calculates electricity costs every day or hour using real-time 
meter reading and rate tariffs. 
26 
 End-use cost allocation:  According to user-defined parameters and algorithms, 
estimates end-use energy consumption from whole building energy. Generally used for 
cost allocation to building tenants.  A common parameter definition is energy use per 
square foot. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
27 
3. TEBA SYSTEM  MODEL 
 
3.1. Chiller Plant Arrangement & Pump System 
 
Figure 3.1: Chiller Plant Lay out Diagram 
 
In primary/secondary systems, water flows through the chiller primary loop at a constant 
rate, and water flows through the secondary loop, which serves air handlers or fan coils, 
at a variable rate. The constant speed pumps in secondary circuit are replaced with 
“variable speed” pumps. The speed of the secondary pumps is determined by a 
controller measuring differential pressure  across the supply-return mains or across the 
selected critical zones. The decoupled section isolates the two systems hydraulically.  
Also the system uses two-way valves in the air handlers that modulate secondary loop 
flow rate with load requirements. During light load condition, the 2-way control valves 
28 
will close (partially or fully) in response to load conditions, resulting in pressure rise in 
the secondary chilled water loop. A differential pressure sensor measures the pressure 
rise in the secondary loop and signals variable frequency drive of secondary pumps to 
alter the speed (flow). 
Primary-secondary variable-flow systems are more energy efficient than constant-flow 
systems, because they allow the secondary variable-speed pump to use only as much 
energy as necessary to meet the system demand. Refer to the schematic below.  
  
3.2 Data Acquisition in the Chiller Plant. 
 
3.2.1 Chiller Electrical Consumption- 
 
Individual Chiller Power Consumption measured using Current Transformer 
connected Power Transducers with following specifications. 
• Quantity – 4 Numbers 
• Type – Active Power Transducer 
• Communication Signal- 4-20mA Signal 
• Input Range- 0-5A 
• Manufacturer- Adision 
• Accuracy:  0.2%  
• Rated of output Input frequency: 50Hz  3Hz or 60Hz  3Hz  
• Input burden:  0.1 VA (ampere input)   0.2 VA (voltage input) Aux. 
• Power supply: 50/ 60Hz   AC 220V  15%,  
• Power effect:  0.1% RO.  
• Power consumption:  4 VA,  DC  
29 
 
 
Figure 3.2: Power Transducer 
 
 
Figure 3.3: Power Transducer Functional Block Diagram 
 
3.2.2 Chilled water, Condenser water & Cooling Tower Power Consumption  
 
 Separate pumps Set power consumption measured using Mod-Bus communication type 
electricity power Analyzers. 
 
30 
3.2.2.1 Property of the power analyzer 
Applications 
• Metering of distribution feeders, transformers, generators,   capacitor banks and 
motors  
• Medium and low voltage systems  
• Commercial, industrial, utility  
• Power quality analysis  
• Data Logging 
 
Metering Parameters 
• Voltage V1, V2, V3, V ln avg, V12, V23, V31, Vl lavg 
• Current I1, I2, I3, In, Iavg  
• Power P1, P2, P3, Psum  
• Reactive Power Q1, Q2, Q3, Qsum  
• Apparent Power S1, S2, S3, Ssum  
• Frequency F  
• Power Factor PF1, PF2, PF3, PF  
• Energy Ep_imp, Ep_exp, Ep_total, Ep_net  
• Reactive Energy Eq_imp, Eq_exp, Eq_total, Eq_net  
• Apparent Energy Es  
• Demand Dmd_P, Dmd_Q, Dmd_S, Dmd_I1, Dmd_I2, Dmd_I3Monitoring  
• Power Quality  
• Voltage Harmonics 2nd to 63rd and THD  
• Current Harmonics 2nd to 63rd and THD  
 
 
 
 
31 
3.2.2.2 Futures of the Power Analyzer  
 
1. Alarms Limits: can be set for up to 16 indicated parameters and can be set with a 
specified time interval.  If any input of the indicated parameters is over or under its 
setting limit and persists over the specified time interval, the event will be recorded 
with time stamps and trigger the Alarm DO output.  The 16 indicated parameters can 
be selected from any of the 51 parameters available. 
  
2. I/O option module : The E-module® technique was adopted for its flexibility and 
easy expansion of the I/O function of Acuvim II.  A maximum of 3 modules can be 
used for one meter.  Digital input, digital output, pulse output, relay output, analog 
input and analog output are provided by I/O option module. 
 
3. Communication : RS485, Industry standard Modbus™ protocol Module Option: 
Ethernet module, Profbus-DP module Dual communication ports Display Clear and 
large character LCD Screen display with white back light Wide environmental 
temperature endurance 
 
4. Display Load percentage, 4 quadrants power and load nature 
 
5. Data logging The Acuvim II R model offers 2MB of onboard data logging memory 
to be used for historical trending.  There are 3 assignable historical logs where the 
majority of the metering parameters can be recorded.  A real time clock allows for 
any logged events to be accurately time stamped.  
 
3.2.3 Chilled water flow rate (Danffos MAG5000) 
 Individual riser water flow rate measured using electromagnetic type water flow meters. 
 
 
32 
3.2.3.1 Design details 
• Compact or remote mounting possible 
• Easy “plug & play“ field changeability of transmitter 
• Ex ATEX and FM/CSA versions 
• High temperature sensor for applications with temperatures up to 180°C (356°F) 
• Approvals for PTB, OIML R75 and OIML R117 
• Meets EEC directives: PED, 97/23/EC pressure directive for EN1092-1 flanges 
• Build-in length according to ISO13359 
• Onsite or factory upgrade to IP68/NEMA6P of a standard sensor. 
 
3.2.3.2. Mode of operation  
 
The flow measuring principle is based on Faraday’s law of elec-tromagnetic induction 
according to which the sensor converts the flow into an electrical voltage proportional to 
the velocity of the flow. Integration of the complete flow meter consists of a flow sensor 
and an associated transmitter MAG5000, 6000 and 6000I.The flexible communication 
concept USM II simplifies integration and update to a variety of fieldbus systems such 
as HART, FOUNDATION Fieldbus H1, DeviceNet, PROFIBUS DP and PA, Modbus 
RTU/RS485. 
 
3.2.3 Chilled water Riser supply and return Temperature (Honeywell TE 210) 
 
Measured by using PT100 type temperature transducers with following specifications. 
Signal conditioning is performed by industrial quality integrated circuits to provide a 
true linear output. The circuit is factory calibrated but zero and span trim measure 
provided to adjust the output if necessary. Output accuracy is not affected by long wire 
runs or electrical noise. The transducer can operate over a wide supply voltage range. 
The TE-210 is available in many different  housings to cover all applications. For space 
temperature sensing, the transducer is available in a unique plastic enclosure that has 
33 
two separate compartments divided by a solid partition. Each compartment is ventilated 
individually from three sides. One chamber incorporates the electronics and the other the 
sensing element. In this way there is total isolation between the electronics and the 
sensor to assure accuracy. For air duct temperature, the sensor is encapsulated in a 1/4 
inch OD aluminumor stainless steel probe. The probe protrudes from the bottom of the 
die cast aluminum transducer housing minimizing lead length error. The probe can be 
inserted directly into the duct and mounting holes are provided to rigidly support the 
assembly. TE-210 is also available in a bendable aluminum 3/8 inch OD extra long 
probe for averaging duct air temperature. The probe incorporates numerous sensors 
encapsulated at equal distances across the length of the probe. The complete assembly 
acts as a single sensor and any temperature change is averaged across the sensors. The 
probe can be easily bent to fit any size duct. For monitoring water temperature, the TE-
210 is available in a die cast aluminum enclosure with a 1/4 inch OD, probe with a brass 
fitting that can be screwed directly into any thermowell  providing a rigid support to the 
transducer. The TE-210 is also available with a remote probe to be strapped on a pipe or 
any other application in which high temperatures are encountered. For monitoring 
outside air temperature the TE-210 is also available in a weather proof enclosure with a 
suitable sun shield to be mounted outside. 
 
3.3 AHU Details in the Selected System. 
 
Selected Chilled water system including with 39 numbers of AHU’s with following 
capacities. 
No Level AHU No 
Area  
Electrical 
Moter 
Cooling Capacity 
m2 ( kW ) (W) 
1 Level Mez AHU-1 280 5.50 52030 
2 Level-01 AHU-2 1147 15.00 148940 
3 Level-02 AHU-3 848 11.00 115280 
34 
4 Level-03 AHU-4 1081 11.00 121220 
5 Level-04 AHU-5 459 7.50 79750 
6 Level-05 AHU-6 514 5.50 64460 
7 Level-06 AHU-7 514 5.50 64460 
8 Level-07 AHU-8 514 5.50 64460 
9 Level-08 AHU-9 514 5.50 64460 
10 Level-09 AHU-10 349 3.00 23650 
11 Level-09 AHU-11 349 4.00 39160 
12 Level-10 AHU-12 483 4.00 44880 
13 Level-10 AHU-13 483 7.50 106480 
14 Level-10 AHU-14 766 16.50 298650 
15 Level-11 AHU-15 774 11.00 110550 
16 Level-11 AHU-16 774 7.50 71830 
17 Level-12 AHU-17 782 11.00 110550 
18 Level-12 AHU-18 782 7.50 71830 
19 Level-13 AHU-19 782 11.00 110550 
20 Level-13 AHU-20 782 7.50 71830 
21 Level-14 AHU-21 1588 18.50 210100 
22 Level-15 AHU-23 788 11.00 110550 
23 Level-15 AHU-24 788 7.50 70950 
24 Level-16 AHU-25 781 11.00 110550 
25 Level-16 AHU-26 781 7.50 66770 
26 Level-17 AHU-27 775 11.00 110550 
27 Level-17 AHU-28 775 7.50 65230 
28 Level-18 AHU-29 769 11.00 110550 
29 Level-18 AHU-30 769 7.50 64460 
30 Level-19 AHU-31 763 11.00 110550 
31 Level-19 AHU-32 763 7.50 63580 
35 
32 Level-20 AHU-33 757 15.00 120890 
33 Level-20 AHU-34 757 7.50 66440 
34 Level-21 AHU-35 514 4.00 35420 
35 Level-21 AHU-36 514 5.50 43509 
36 Level-21 AHU-37 514 7.50 65077 
37 Level-22 AHU-22 374 5.50 49500 
38 Level-22 AHU-38 374 5.50 36121 
39 Level-22 AHU-39 374 11.00 248710 
 
Table 3.1: Air Handling Unit Data 
  
 
Figure 3.4: AHU Equipment Layout 
 
36 
3.4 Data Acquisition in the Air Handling Units (AHU). 
 
3.4.1 Chilled water Flow Rate   
 Measured using Turbine type water flow meter with following specifications. 
• Power Requirements: 5 to 24 V DC Output  
• Signal: Open collector, sinking, proportional to flow velocity Output  
• Current: 10 mA max. 
• Flow rate range: 0.3 to 20 fps (0.1 to 6 m/sec) 
• Pipe size range: 1.5 to 24 in. 
• Fitting thread size: 1.5 in. NPT 
• Linearity: ± 1% of full range 
• Repeatability: ± 0.5% of full range 
• Body diameter: 0.94 in. (2.4 cm) 
• Standard cable length: 25 ft (7.6 m)(1000 ft [305 m] max. recommended) 
• Cable type: Twisted pair with foil shield(Belden 8451) 
• Pressure / Temperature rating: 250 psig(17 bar) max. @ 212°F (100°C) 
• Sensor MaterialsBody: 316 SS 
 
Supply water Temperature - Measured using Honeywell TE 210 PT100 type temperature 
transducers. 
 
Return water Temperature - Measured using Honeywell TE 210 PT100 type temperature 
transducers. 
 
AHU Fan motor electricity consumption – Measured by using CT connected power 
transducers. 
 
 
 
37 
3.5 Data Acquisition SCADA Software 
 
The Selected BMS System with Honeywell Enterprises Building Integrator 
Software for data Acquisition. The Honeywell Enterprise Buildings Integrator uses 
client-server architecture on Windows NT to provide cost-effective scalability to any 
enterprise without the need for proprietary hardware. Operator stations can be connected 
using a variety of standard TCP/IP network topologies such as LAN and WAN as well 
as serial and dial-up access. Databases and applications can be integrated to provide 
various local, network and internet clients access to monitoring, control, past 
performance and management reporting. Honeywell EBI provides tight business level 
integration so that human resources information flows directly into the Honeywell 
Security Manager application. To help you achieve optimal maintenance strategies, 
maintenance management packages receive breakdown information and performance 
monitoring information from the Honeywell Building Manager application. Standard 
SQL access to building performance data allows boardrooms to truly see operational 
impact on their bottom line by linking this data into financial systems. 
 
 
 
 
 
 
 
 
 
 
 
 
 
38 
4. TEBA ENERGY CALCULATION PROCEDURE 
 
Tenant billing amount is calculated based on the energy utilized by a tenant and 
energy rate. Energy utilized by the tenant includes cooling load (refrigerant ton) at the 
AHU and electrical energy absorbed by equipment. 
 
4.1.1Cooling Load Calculation 
 
Tenant cooling load energy is calculated based on, 
• Total refrigererent tons generated at the AC plant  (𝑄𝑇) 
• Refrigerant tons used by the tenant AHU  (𝑄𝑡) 
• Total Electrical Energy Input to the Central AC Plant (E), which includes 
Total electrical energy input to the central AC plant except cooling towers (𝐸1)  
• Chillers 
• Primary Chilled water pumps 
• Secondary Chilled water pumps 
• Total electrical energy input to the cooling towers (𝐸2) 
• Cooling Towers 
• Water treatment System 
• Electrical energy input to the tenant Air handling unit equipments (𝑒𝑡) 
The each valve determination procedure as bellow, 
 
4.1.2 Total cooling load at the AC plant (𝑸𝑻) 
 
Refrigerant Ton value at the AC plant can be determine by following formula, 
𝑄 = 𝑤 ∗ 𝑐 ∗ (𝑇𝑖 − 𝑇𝑜)            (4, 1) 
Since there are two zones in the building the flow and temperature are measured at two 
locations. 
39 
The total cooling load can be calculated by following formulas. 
Cooling load low Zone  
𝑄𝑙 = 𝑤𝑙 ∗ 𝑐 ∗ (𝑡𝑜𝑙 − 𝑡𝑖𝑙)                  (4, 2) 
 
Cooling load high Zone  
𝑄ℎ = 𝑤ℎ ∗ 𝑐 ∗ (𝑡𝑜ℎ − 𝑡𝑖ℎ)               (4, 3) 
Total Cooling Load  
𝑄𝑇 = 𝑄𝑙 + 𝑄ℎ                                 (4, 4) 
 
TEBA shall communicate with EBI server and retrieve the cooling load data (Flow rate, 
Temperature Valves) for all the configured points at a fixed time interval of every 6 
minutes. This update prases shall be round the clock and any way make sure that any 
data that is not update in the previous scan cycle is updated in the next scan cycle. For 
this poupous, TEBA shall get the historical point data from EBI server. All the cooling 
load data shall be stored with correct data time stamp. 
 
4.1.3 Total Cooling Load  (𝑸𝒕 ) Used by Tenant AHU 
 
Total cooling load used by the tenant AHU (𝑄𝑡) can be calculated using two 
temperature Sensor in supply & Return Chilled water line and the flow meter .Cooling 
load value at the AHU can be determined by the following formulas. 
𝑄𝑡 = 𝑊𝑡 ∗ 𝐶 ∗ (𝑇𝑜𝑡 − 𝑇𝑖𝑡)               (4, 5) 
Where, 
Q  Heat flow rate in kW 
W Chilled water mass flow rate in kg/sec 
𝑇𝑖 Incoming Water temperature ˚C 
𝑇𝑜 Outgoing Water temperature ˚C 
c Specific Heat in kJ/kgK 
 
40 
4.2.1 Total Electrical Energy (𝑬𝒓) used by Cooling Plant. 
 
Electrical used by the AC plant is the summation of electrical energy used by central AC 
plant except cooling towers and electrical energy used by cooling towers. 
𝐸𝑟 = 𝐸1 + 𝐸2                 (4, 6) 
Where, 
𝐸𝑟(kWh)     Total Electrical energy input to the central AC Plant  (Chillers, CHWPs, 
CWPs and Cooling Towers) 
𝐸1(kWh)     Total Electrical energy input to the central AC Plant except Cooling Towers 
𝐸2(kWh)     Total Electrical energy input to the Cooling Towers 
All cooling plant electrical energy values shall be stored in a separate table. Total energy 
value is the summuation of all electrical point values at a given time instant. 
 
4.2.2 Electrical Energy (𝒆𝒕) used by Tenant AHU Equipments 
 
Electrical used by the tenant AHU is the summation of electrical energy used by AHU 
fan motor, outdoor fan motor. 
𝑒𝑡 = 𝑒1 + 𝑒2                 (4, 7) 
Where, 
𝑒𝑡    Total electricity energy input to Tenant air handling unit in kWh 
𝑒1    Electricity energy input to Tenant air handling unit fan motor in kWh 
𝑒2    Total electricity energy input to Outdoor Air Fan Motor in kWh 
𝑄ℎ = 𝑊ℎ ∗ 𝐶 ∗ (𝑡𝑜ℎ − 𝑡𝑖ℎ)      (4, 8) 
 
4.3 Tenant Energy Bill 
 
 Tenant Energy is calculated based on the amount of refrigerant and electricity 
being used by tenant’s AHU for short duration of time as declared in the application. 
41 
Since the parameters are varying ever time this kind of energy calculation is valid for 
small time interval only. 
 
4.4.1 Tenant Energy Bill (for time t) 
  
𝑻𝑬𝑩𝒕 = 𝑨𝒎𝒎𝒐𝒖𝒏𝒕 𝒇𝒐𝒓 𝑹𝒆𝒇𝒓𝒊𝒈𝒊𝒓𝒂𝒕𝒊𝒐𝒏 𝑻𝒐𝒏+ 𝑨𝒎𝒐𝒖𝒏𝒕 𝒇𝒐𝒓 𝑬𝒍𝒆𝒄𝒕𝒓𝒊𝒄𝒊𝒕𝒚 (𝒇𝒐𝒓 𝑨𝑯𝑼 𝒆𝒒𝒖𝒊𝒑𝒎𝒂𝒏𝒕) 
𝑇𝐸𝐵𝑡 = {((𝑄𝑡 ∗ 𝐸𝑟)/𝑄𝑟) + 𝑒𝑡}*MF*R                                   (4, 9) 
Where, 
MF  Maintenance Factor 
R Rate of change for Electricity Rs/kWh. 
𝐸𝑟        Total electrical energy input to the AC Plant in kWh. 
𝑒𝑟        Total electrical energy input to the AC Plant in kWh. 
𝑄𝑟       Total Cooling load for AC Plant (Zone 1 & 2) only for time t in kW. 
𝑄𝑡        Total Cooling load for tenant only for time t in kW. 
𝑻𝑬𝑩𝒕 Tenant Energy Bill for time t . 
 Since the above said calculation is only for a period of time, the monthly tenant 
energy bill is the summation of such values for a month period. TEBin Rs = TEBt1 + TEBt2 + ⋯… … … + TEBtn              (4, 10) 
 
4.4 Disadvantage of the System 
 
Following disadvantages are highlighted above calculations system, 
1. Real time energy balancing 
In above scenario the cooling Energy balancing is using the real time. That mean 
the energy generation is marched with AHU energy consumption in same time. 
The calculation method is not correction for the plant generated excess cooling 
Energy.   
42 
Cooling Energy Generation in the plant = Summation of Energy consumption of 
AHU’s 
2. There are no Correction methods of Cooling Energy Distribution loss in the 
system. Normally chilled water lines are insulated in the chilled water piping 
distribution System. But it is not indicate the distribution loss is in Zero 
condition. It also loss same amount of cooling energy from the system.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
43 
5. ANALYZING OF THE COLLECTED DATA 
 
In this chapter the results of the collected data analysis are presented the system 
behavior using one month hourly basis historical data for 2009 August Building 
Automation System (BAS) stored following data. 
• Chiller Plant Hourly average cooling energy production.  
• Individual Air Handling Unit cooling energy consumption data.  
Considering the month period gathered System generated and AHU Consumed  Energy 
data can be indicate following two major type of system behaviors. 
1. Week day (Working day)data variation – Monday to Friday without holiday 
2. Weekend (Saturday) data variations – Saturday and Sunday  
 
 Time 
Average Plant Generated 
Cooling Energy /(kWh) 
Average AHU Consumed Total 
Energy/(kWh) 
1 1:00:00 AM 589.91 196.06 
2 2:00:00 AM 760.54 315.64 
3 3:00:00 AM 2,604.12 1,196.31 
4 4:00:00 AM 1,526.87 629.07 
5 5:00:00 AM 1,731.36 936.97 
6 6:00:00 AM 8,221.94 5,496.97 
7 7:00:00 AM 14,468.39 13,403.11 
8 8:00:00 AM 14,815.28 13,935.71 
9 9:00:00 AM 15,445.69 14,348.90 
10 10:00:00 AM 16,133.34 15,402.23 
11 11:00:00 AM 17,039.36 17,348.19 
12 12:00:00 PM 16,740.27 16,389.26 
44 
13 1:00:00 PM 16,656.69 16,569.40 
14 2:00:00 PM 16,431.45 16,387.57 
15 3:00:00 PM 15,828.49 15,847.27 
16 4:00:00 PM 15,278.33 15,371.93 
17 5:00:00 PM 12,324.40 12,008.05 
18 6:00:00 PM 6,876.63 6,026.46 
19 7:00:00 PM 6,202.53 5,783.17 
20 8:00:00 PM 5,554.27 5,019.83 
21 9:00:00 PM 4,662.93 4,096.86 
22 10:00:00 PM 1,693.57 1,165.90 
23 11:00:00 PM 754.30 250.05 
 
Table 5.1: One month average Hourly Energy data for 2009 Aug (Working day) 
45 
 
Figure 5.1: Weekday Hourly Average Energy Profile 2009 Aug 
 
 
 Time 
Average Plant Generated Cooling 
Energy /(kWh) 
Average AHU Consumed Total 
Energy/(kWh) 
1 1:00:00 AM                                          1,170.21                                           285.51  
2 2:00:00 AM                                          1,273.71                                           595.91  
3 3:00:00 AM                                         1,398.94                                           795.18  
4 4:00:00 AM                                             761.71                                           269.95  
5 5:00:00 AM                                         2,373.10                                          949.08  
6 6:00:00 AM                                          1,581.51                                           563.65  
7 7:00:00 AM                            412.06                                             96.99  
 -
 2,000.00
 4,000.00
 6,000.00
 8,000.00
 10,000.00
 12,000.00
 14,000.00
 16,000.00
 18,000.00
 20,000.00
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Co
ol
in
g 
En
er
gy
 /
kW
h 
Time  / hr 
Monthly Average AHU Energy Consumption Monthly Average Plant Production Energy
46 
8 8:00:00 AM 1,904.91                                      722.75  
9 9:00:00 AM  4,129.62         2,106.04  
10 10:00:00 AM 4,276.03      2,885.70  
11 11:00:00 AM  3,966.60         3,021.43  
12 12:00:00 PM 3,350.86      2,492.07  
13 1:00:00 PM  2,788.84       2,037.68  
14 2:00:00 PM   2,110.52                  1,459.79  
15 3:00:00 PM 3,122.14          1,815.40  
16 4:00:00 PM         2,794.33           1,640.67  
17 5:00:00 PM                                         1,378.47                580.18  
18 6:00:00 PM                                             886.14   278.45  
19 7:00:00 PM 1,215.50    418.76  
20 8:00:00 PM                                          3,132.97  1,589.42  
21 9:00:00 PM                                         1,573.84                   880.76  
22 10:00:00 PM   1,166.63            367.60  
23 11:00:00 PM                                          1,407.63    467.08  
  
Table 5.2: Weekend Hourly Average Energy Profile 2009 Aug 
47 
 
Figure 5.2: Weekend Hourly Average Energy Profile 2009 Aug 
 
 Considering the above two hourly Average energy variation per a day there is an 
energy difference between plant generation cooling energy & AHU consumed cooling 
energy data. The daily energy difference calculated by Summation of hourly based Chiller 
Generated Energy & Summation of total AHU Consumed Cooling Energy. The Cooling 
Energy difference is varying in time of the operation in the system. 
Using collected Energy data calculated daily Cooling energy difference for One month 
period as bellow Table 5.3, 
 
 
 
 -
 2,000.00
 4,000.00
 6,000.00
 8,000.00
 10,000.00
 12,000.00
 14,000.00
 16,000.00
 18,000.00
 20,000.00
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Co
ol
in
g 
En
er
gy
 /
kW
h 
Time  / hr 
Monthly Average AHU Energy Consumption Monthly Average Plant Production Energy
48 
Day Date 
Plant 
Energy/(kWh) 
AHU Consumed 
Energy/(kWh) 
Energy 
Difference/(kWh) 
Percentage of 
Energy 
Difference (%) 
Mon 10 273021.27 251061.67 21959.60 8.04 
Tue 11 244120.61 242271.75 1848.86 0.76 
Wen 12 250106.73 240862.13 9244.60 3.70 
Thu 13 231468.12 230645.48 822.64 0.36 
Fri 14 221648.46 211975.14 9673.32 4.36 
Sat 15 65015.57 39195.05 25820.52 39.71 
Sun 16 47322.74 21558.11 25764.63 54.44 
Mon 17 238066.86 215626.48 22440.38 9.43 
 
Table 5.3: Weekly Energy data from Monday to Sunday 
 
 
Figure 5.3: Weekly Cooling Energy Difference 
0.00
5000.00
10000.00
15000.00
20000.00
25000.00
30000.00
Mon Tue Wen Thu Fri Sat Sun Mon
Co
ol
in
g 
En
er
gy
 D
iff
er
an
ce
 (k
W
) 
49 
 
Considering the above plot the energy loss indicate identical variation between week 
(working day) energy loss & Weekend non working day energy loss. To identify the 
energy loss variation of working day can be used following analysis of hourly energy 
loss profile.  
 
       
 Time /(hr) Average Cooling Energy Difference (kWh) 
1 1.00        393.85  
2 2.00        444.89  
3 3.00     1,407.81  
4 4.00        897.80  
5 5.00        794.39  
6 6.00     2,724.97  
7 7.00     1,065.28  
8 8.00        879.57  
9 9.00     1,096.79  
10 10.00        731.11  
11 11.00      (308.83) 
12 12.00        351.01  
13 13.00           87.29  
14 14.00           43.88  
15 15.00        (18.77) 
16 16.00        (93.60) 
17 17.00        316.35  
18 18.00        850.17  
19 19.00        419.36  
20 20.00        534.44  
50 
21 21.00        566.08  
22 22.00        527.67  
23 23.00        504.25  
 
Table 5.4: Hourly Energy data for Working Day 
 
Figure 5.4: Working Day Hourly Cooling Energy Difference Profile 
 
 Considering the above data variation from Figure 5.3 & 5.4 can be identified following 
two difference main scenarios for daily cooling energy profile for the system. 
Scenario 01 
Hourly Plant Generation Energy > Summation of AHU consumed Energy 
Scenario 02 
Hourly Plant Generation Energy < Summation of AHU consumed Energy 
 
 
 
 (500.00)
 -
 500.00
 1,000.00
 1,500.00
 2,000.00
 2,500.00
 3,000.00
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Co
ol
in
g 
En
er
gy
 D
iff
er
en
ce
  /
kW
h 
 
Time / hr Energy Diff
51 
Scenario 01 
Plant Energy generation is higher than the Summation total AHU’s Energy 
Consumptions. Those phenomena indicate the Distribution Energy loss and the Cooling 
energy stored in the system.  
Scenario 02 
Plant energy Generation is less than the Summation of total AHU’s Energy 
Consumption. Those phenomena indicate Distribution Energy loss and consumed stored 
energy from the system.   
 
Considering above two scenarios following two types of the cooling energy corrections 
to be required with the new billing strategies. 
1. Correction factors for Cooling Energy distribution loss through pipe. 
2. Correction factors for hourly stored energy components in the system. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
52 
6. STRATEGY Of  NEW ENERGY BILLING SYSTEM 
 
In the Chapter 05 explained collected data analysis and requirement of the new 
strategy for Chilled water cooling energy billing system. This chapter will introduced 
new energy billing concept based on Energy balancing equation. 
 
6.1 Energy Conservation of Chilled Water Plant 
 
Energy balancing equation can be applied as follow for the chilled water plant and 
distribution of the system. Qp + Qb = ∑ Qi𝑛𝑘=0 + Qloss + QS                                             (6, 1) 
 Qp − Chiller generated Cooling Energy Qi − ith AHU Consumed Cooling  Energy Qloss − Cooling Enegy loss from the system QS − Stored Cooling Energy in the System Qb − Balanced Cooling Energy in the System 
 
Considering Chiller plant Start and Stopping time Energy Balancing Equation for one 
chiller operation cycle.  
For the time interval 5.00. a:m to 10 P:m and 39 Numbers of Air Handling Units 
1st Hour Qp 1 = ∑ Qi39𝑖=1 + Qloss + QS1               (6, 2) 
 
2nd Hour Qp 2 + QS1 = ∑ Qi39𝑖=1 + Qloss + QS2        (6, 3) 
 Nth Hour Qp n + QSn−1 = ∑ Qi39𝑖=1 + Qloss + QSn    (6, 4) 
53 
 
6.2 Estimation the Valve for the 𝐐𝐥𝐨𝐬𝐬 Cooling Energy loss valve for the System  
 
Cooling energy loss valve of the system is depending on the chilled water piping system 
following characteristics.  
• Piping Materials 
• Insulation Materials 
• Length of the piping network 
• Diameter of the piping 
• Flow velocity 
• Chilled water in out Temperature  
• Outdoor Temperature 
• Outdoor Air movement  
Considering the above parameters are theoretical calculations are very complex and 
difficult in the System. Because can be follower following experimental analysis for the 
estimation valve factor for the cooling energy distribution loss. 
1. Generated Zero Cooling Energy input conditions to the System. 
Chillers – Off Mode 
Primary Chilled Water Pumps – Off Mode 
Cooling Tower – Off Mode 
Condenser Water Pumps – Off Mode 
 
2. Stat Secondary Chilled Water pumps and Circulate the chilled water One hour 
period and collect the following data 
• Header Energy circulation 
• AHU Energy Consumption  
• Plant Electrical Energy 
 
54 
Time 
Plant Supply 
stored cooling 
Energy/(kWh) 
Plant Electrical 
Energy/(kWh) 
AHU Consumed 
Energy/(kWh) 
Cooling Energy 
Diff/(kWh) 
8/4/09 11:00 PM 447.1242 12 228.85 218.27 
8/5/09 1:00 AM 410.7921 15 305.76 105.03 
8/5/09 2:00 AM 394.3917 21 280.63 113.76 
8/5/09 3:00 AM 374.0808 16 249.4 124.68 
8/5/09 4:00 AM 359.6238 21 208.87 150.75 
 
Table 6.1: Data for Zero Energy Input Condition 
 
In this condition system no generation of cooling energy and circulated cooling energy 
that stored in previous hours generated energy. 
Supply Cooling Energy = AHU consumed Cooling Energy + Cooling Energy 
Distribution loss through 
the System   
 
Chilled water pump maximum speed power consumption   = 22 kW 
By considering the pump maximum speed cooling energy loss as the cooling Energy 
distribution loss in the full load condition is constant for the system,  Qloss = 113 kWh 
By substituting above valve for Equitation (6, 1) following Table 6.1 can be completed. 
 
 
 
 
 
 
 
55 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
For  nth hr , n= 2 to 23, 
Chilled water 
Pumps On Status 
1st hr Chiller Plant Cooling 
Energy Production (Qp) 
1st hr Total AHU Consumed Cooling Energy    
1st hr , ( Qp 1 = ∑ Qi39𝑖=1 + Qloss +  
  
Qloss From the BAS Data Base 
1st hr Total Plant Consumed Cooling Energy   
1st hr Billing Rate (𝑄𝑝
𝐸𝑟
 ) To BAS Data Base 
QS1 to the BAS Data Base 
No 
Chiller plant 
On Status 
i th AHU Chilled Water Flow Rate 
  
i th AHU Chilled Water In & Out 
Temperature (Ti  & To) 
i th AHU Energy Consumption (Qi) 
i th AHU On Status 
Start 
No 
Yes 
𝐞𝐫 to the BAS Data Base 
𝐐𝐩 = Pump Consumed Energy 
Yes 
56 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 6.1: New Energy Billing Flow Chart 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
nth hr 
( Qp n + QS(n−1) = ∑ Qi39𝑖=1 + Qloss + QS n ) Q S (n−1) From the BAS Data  Q S n To the BAS Data 
 
End 
nth hr Billing Rate (𝑄𝑝
𝐸𝑟
 ) To BAS Data Base 
57 
Time 
(𝐐𝐩 𝐧 +
𝐐𝐒𝐧−𝟏) /kW ( 𝐐𝐩 𝐧)/𝐤𝐖 ∑ 𝐐𝐢𝟑𝟗𝒊=𝟏  /kW 𝐐𝐥𝐨𝐬𝐬/ kW 𝐐𝐒𝐧/kW Difference/kW 
1.00 a:m - 
 
- - - - 
2.00 a:m - 
 
- - - - 
3.00 a:m - 
 
- - - - 
4.00 a:m - 
 
- - - - 
5.00 a:m 4,501.28 4,501.28 1,675.47 113.00 2,712.81 2,825.81 
6.00 a:m 8,096.17 5,383.36 5,684.66 113.00 2,298.51 2,411.51 
7.00 a:m 18,254.63 15,956.12 15,629.45 113.00 2,512.18 2,625.18 
8.00 a:m 17,700.03 15,187.85 15,250.16 113.00 2,336.87 2,449.87 
9.00 a:m 17,811.47 15,474.60 15,513.94 113.00 2,184.53 2,297.53 
10.00 a:m 18,581.04 16,396.51 18,741.74 113.00 (273.70) (160.70) 
11.00 a;m 20,389.92 20,663.62 23,502.65 113.00 (3,225.73) (3,112.73) 
12.00 p:m 19,296.71 22,522.44 21,056.21 113.00 (1,872.50) (1,759.50) 
13.00 p:m 19,305.34 21,177.84 22,763.39 113.00 (3,571.05) (3,458.05) 
14.00 p;m 18,874.63 22,445.68 21,639.15 113.00 (2,877.52) (2,764.52) 
15.00 p;m 18,311.98 21,189.50 22,278.57 113.00 (4,079.59) (3,966.59) 
16.00 p:m 17,820.39 21,899.98 21,794.88 113.00 (4,087.49) (3,974.49) 
17.00 p:m 15,311.73 19,399.22 15,242.81 113.00 (44.08) 68.92 
18.00 p:m 8,784.14 8,828.22 6,367.69 113.00 2,303.45 2,416.45 
19.00 p:m 7,709.71 5,406.26 5,471.31 113.00 2,125.40 2,238.40 
20.00 p:m 6,697.70 4,572.30 4,441.92 113.00 2,142.78 2,255.78 
21.00 p:m 5,449.00 3,306.22 2,832.65 113.00 2,503.35 2,616.35 
22.00 p:m 1,224.74 (1,278.61) 508.48 113.00 603.26 716.26 
23.00 p:m - (603.26) 160.21 113.00 (273.21) (160.21) 
Total 244,120.61 242,429.13 240,555.34 2,147.00 
  
 
Table 6.2: Error Calculation Table 
58 
 
6.3 Result 
The Table 6.3 illustrates the result comparison between before the correction of the data 
& after correction of the data in the Chilled water cooling energy billing system. 
 
Date 
(Aug 
2009) 
Plant 
Generated 
Cooling 
Energy 
(kWh) 
AHU 
Consumed 
Cooling 
Energy 
(kWh) 
Corrected 
Plant 
Generated 
Cooling 
Energy 
(kWh) 
Existing 
System 
Energy 
Error 
(kWh) 
New 
System 
Error 
(kWh) 
Percenta
ge of 
Existing 
System 
Error 
(%) 
Percentage 
of New 
Calculation 
Error (%) 
Percentag
e of Error 
Correctio
n (%) 
3 285,775.06 265,602.82 276,282.90 20,172.24 10,680.08 7.06 3.87 47.06 
4 259,235.77 240,687.72 250,620.35 18,548.05 9,932.63 7.15 3.96 46.45 
5 107,527.29 98,090.30 103,745.01 9,436.99 5,654.71 8.78 5.45 40.08 
6 253,021.43 238,652.40 248,523.97 14,369.03 9,871.57 5.68 3.97 31.30 
7 246,909.89 230,109.87 239,725.17 16,800.02 9,615.30 6.80 4.01 42.77 
10 262,709.11 243,021.27 253,023.91 19,687.84 10,002.64 7.49 3.95 49.19 
11 207,671.26 192,356.00 200,838.68 15,315.26 8,482.68 7.37 4.22 44.61 
12 228,706.40 212,902.21 222,001.28 15,804.19 9,099.07 6.91 4.10 42.43 
13 231,468.12 217,484.81 226,721.35 13,983.31 9,236.54 6.04 4.07 33.95 
14 221,648.46 206,584.36 215,493.89 15,064.10 8,909.53 6.80 4.13 40.86 
17 238,066.86 221,309.91 230,661.21 16,756.95 9,351.30 7.04 4.05 44.19 
18 234,738.53 222,121.50 231,497.15 12,617.03 9,375.65 5.37 4.05 25.69 
19 224,771.45 206,988.22 215,909.87 17,783.23 8,921.65 7.91 4.13 49.83 
20 229,115.57 214,338.28 223,480.43 14,777.29 9,142.15 6.45 4.09 38.13 
21 201,546.86 186,419.77 194,724.36 15,127.09 8,304.59 7.51 4.26 45.10 
24 239,587.72 220,645.25 229,976.61 18,942.47 9,331.36 7.91 4.06 50.74 
25 218,769.75 200,066.71 208,780.71 18,703.04 8,714.00 8.55 4.17 53.41 
59 
26 210,455.01 191,666.30 200,128.29 18,788.71 8,461.99 8.93 4.23 54.96 
27 215,473.80 199,195.65 207,883.52 16,278.15 8,687.87 7.55 4.18 46.63 
28 206,300.10 188,925.17 197,304.93 17,374.93 8,379.76 8.42 4.25 51.77 
 
Table 6.3: Result 
 
6.4 Implementation 
 
Using the flow chart illustrated in Figure 6.1 developed new software module for 
calculate new energy billing corrections through the Building Management System. The 
new software testing in existing data from server is a difficult task and a high risk 
operation. There for using parallel computer running with TEBA server generated new 
corrected data. New software development is based on dotnet & Microsoft Excel 
software.       
By considering of the data transfer from 13th Sept 2011 to 16th Sept 2011 following data 
comparison windows are obtained.  
The Figure 6.2 is indicated the existing system generated report for the week day daily 
(13th Sept 2011) Energy production details. The Figure 6.3 is indicating the newly 
developed software module generated Hourly energy report in the same day with the 
billing strategy followed in Figure 6.1. The Figure 6.4 & Figure 6.5 are illustrate the data 
comparison between existing System and new System for 14th of sep 2011. 
The Figure 6.8 is the Daily summarized Data Table from The Existing System Plant 
Generated Cooling Energy data, Summation of Total AHU Consumed Energy Data 
&Indicated  Daily Energy Difference . 
  
 
 
60 
 
 
Figure 6.2: Existing System Hourly Energy Data for Weekday   
 
 
Figure 6.3: New System Hourly Energy Data for Weekday  
61 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 6.4: Existing System Hourly Energy Data Weekday  
 
 
Figure 6.5: New System Hourly Energy Data Weekday  
 
62 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 6.6: Existing System Hourly Energy Data for Weekday  
 
Figure 6.7: New System Hourly Energy Data for Weekday 
63 
 
Figure 6.8: Summarized Daily Energy Data from Excising System 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
64 
7.  CONCLUSIONS AND RECOMMENDATIONS 
 
Using the developed chilled water cooling energy Billing Algorithm enables the 
designing engineer to analyze several configurations of the Centralized Chilled water 
Billing System with specified cooling load profile. This provides the guideline for 
making more smart Chilled water Energy billing system for engineering point of view 
through the characteristic of cooling load profile and for economic point of view through 
the net present value analysis. This approach provides more benefit to the Building 
Automation systems designing engineer as well as to the project owner since the 
conventional way is to real time cooling energy balancing just concentrate only without 
Cooling energy loss of the distribution and stored energy in the system .These Chilled 
water cooling energy Billing correction method gain more and more important role 
when the system is getting larger and larger, especially when one mentions about the 
district cooling plant. 
The research in based on analyzing cooling energy generation & consumption of cooling 
energy profile on the selected building. The analyzing the data identitified main load 
pattern of the building and cooling energy calculation methods. The building operation 
in full load conditioning (Working day) and operation in partial load condition (Week 
end) the load behaviors are identified major phenomena of the system.  
When designing of the centralized cooling energy billing system designer shall consider 
thus two system pheromones and  shall included the correction methods of calculation 
for introduced more smart billing system for building owner and tenant cooling energy 
users.  
The research is mainly focus for error correction for full load condition energy billing 
with cooling energy distribution loss and stored system cooling energy corrections. 
The cooling energy distribution loss from the piping network is one uncountable valve 
and the stored energy component is other uncountable cooling energy valve of the 
system to be required correction with factors to be generated to smart automated energy 
bill through the BAS application. 
65 
The cooling energy distribution loss through the system is depend on system capacity, 
geometrical location, Climate conditions, Chilled water Inlet Outlet temperature & Flow 
rate etc. Because of theoretical calculation of the distribution loss is not practical for 
billing applications so the research applied experimental loss estimation method for find 
out the correction factors for the cooling energy loss.    
 
Date 
(Aug 
2009) 
Plant 
Generated 
Cooling 
Energy 
(kWh) 
AHU 
Consumed 
Cooling 
Energy (kWh) 
Corrected Plant 
Generated 
Cooling Energy 
(kWh) 
Percentage of Cooling 
energy distribution loss 
(%) 
3 285,775.06 265,602.82 276,282.90 0.98 
4 259,235.77 240,687.72 250,620.35 1.08 
5 107,527.29 98,090.30 103,745.01 2.61 
6 253,021.43 238,652.40 248,523.97 1.09 
7 246,909.89 230,109.87 239,725.17 1.13 
10 262,709.11 243,021.27 253,023.91 1.07 
11 207,671.26 192,356.00 200,838.68 1.35 
12 228,706.40 212,902.21 222,001.28 1.22 
13 231,468.12 217,484.81 226,721.35 1.20 
14 221,648.46 206,584.36 215,493.89 1.26 
17 238,066.86 221,309.91 230,661.21 1.18 
18 234,738.53 222,121.50 231,497.15 1.17 
19 224,771.45 206,988.22 215,909.87 1.26 
20 229,115.57 214,338.28 223,480.43 1.21 
21 201,546.86 186,419.77 194,724.36 1.39 
24 239,587.72 220,645.25 229,976.61 1.18 
25 218,769.75 200,066.71 208,780.71 1.30 
66 
26 210,455.01 191,666.30 200,128.29 1.36 
27 215,473.80 199,195.65 207,883.52 1.30 
28 206,300.10 188,925.17 197,304.93 1.37 
 
Table 7.1: Cooling Energy Distribution Loss  
 
As the illustration of the Table 7.1 the monthly average daily percentage of 
cooling energy loss in full load condition is 1.29% of the actual amount of cooling 
energy production from the system.  
The cooling energy correction for stored cooling energy from the system is uncountable 
& immeasurable energy component of chilled water distribution systems. To calculate 
those energy component used the algorithm illustrate in the   Figure 6.1. This algorithm 
also valid for full load condition chilled water systems.    
According to the result table in Table 6.3 the monthly average daily cooling energy 
billing correction is nearly 44% from the excising system energy error valve. 
The result is based on monthly system data analyzing method. That is valid for Sri 
lankan building TEBA systems because of there is no identifiable climate changes 
through the year. If applying the cooling energy billing correction in another location in 
any country with climate seasons that must analyze the data for each seasons & need to 
introduced sub correction factors for their climate seasonal conditioning changes.   
Using research data and analyzing can be suggested following further implementations 
to the TEBA billing systems. 
 
1. Introduced loss correction factors for the partial load conditions for week end & 
holiday application. 
2.  Introduced stored cooling energy correction factors for the partial load 
conditions for week end & holiday application. 
3. Introduced correction factors for Instrumentation sensitivity & Accuracy.  
4. Introduced distribution cooling energy loss distribution strategy as the, 
67 
Proportional to the cooling energy consumption 
According to the operational schedule 
Tenant location or Elevation 
To introduced more and more correction factors for the centralized cooling energy 
billing system to reach more and smarter for building owner & tenants. 
 
   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
68 
REFERENCE  
 
[1] Jean Lebran., “Simulation of a HVAC System with the help of an Engineering 
Equation Solver,” 7th International IBPSA Comferance, pp. 1119-1125, 2001. 
 
[2]  American Society of Heating Refrigerating and Air Conditioning Engineers, 
“ASHRAE 90.1 Energy Code,” 2003. 
 
[3] Lou Mane, “Sub metering A Practical Approach”, GE Sales Development Retail 
& Property Management, pp 1-13. 2005. 
  
[4] US Department Of Energy, “Metering Best Practice,” A Guide of  to Achieving 
Resource Efficiency, 2007. 
 
[5] Gregory Cmar, “Enterprise Energy Management Systems,” Interval Data 
Systems, 2005. 
 
[6] Gregory Cmar, “Optimizing Building HVAC through Data & Cost,”Interval 
Data Systems, 2005. 
 
[7] M.M.A. Pathmasiri, “Second Law Analysis of Steam Boiler in Sri Lanka,” 
Master of Engineering, University of Mortuwa, Sri Lanka, July 2002.   
 
[8] Sanjaya Rathnayake, “Energy Conservation on a Central Chiller Plant,” Master 
of Science Dissertation, University of Mortuwa, Sri Lanka, and December 2001. 
 
[9] Mahinda Gallage, “Development of Energy Center Cooling Plant,” Master of 
Science Dissertation, University of Mortuwa, Sri Lanka, October 2009. 
 
 
   
 
69 
[10] Abdul Majeed Muzathik, “Economic Potential of Energy Conservation in a Five 
Star Hotel,” Master of Engineering, University of Mortuwa, Sri Lanka, October 
2003. 
 
[11] L.A.A.N. Perera, “Optimal Allocation of Air Conditioning Services; A Case 
Study for a Hotel in Sri Lanka,” Master of Science Dissertation, University of 
Mortuwa, Sri Lanaka, January 2010.   
 
[12] Honeywell USA, “Engineering Manual for Automatic Control of Commercial 
Building, SI Edition,” 1997. 
 
[13] Honeywell Singapore, “Functional Description and Sequence of Operation, HNB 
Tower,” 2001. 
 
[14] Abdul Majeed Muzathik, “Economic Potential of Energy Conservation in a Five 
Star Hotel,” Master of Engineering, University of Mortuwa, Sri Lanka, October 
2003. 
 
[15] White Salmon, Advanced Metering & Information Systems, Grant Report, US 
Environmental Protection Agency, 2009. 
 
[16] Robert McDowall, “Fundamental of HVAC”; Inch/Pound Edition, 2006. 
[17] J.C.P. Kester, “Smart Metering Guide”; Energy Saving & Customer , Energy 
Research Center of Netherland,2010.  
[18] Rex Miller & Mark Miller, “Electricity & Electronics far HVAC”; McGraw-Hill 
Company, 2007. 
70 
[19] A.R Trott & T.Welch,“Refrigiration & Air Conditioning”; Batterwonth 
Heinemann, 3rd Edition,pp 224-330,2000. 
[20] “Precise Metering and Consumptions based Billing for cooling and water”, 
Techem Energy Systems. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
71 
BIBLIOGRAPHY 
1. ASHRAE Stranded, Fundamentals, 2003 
2. ASHRAE Stranded, Fundamentals, 2008 
3. Göpel, J.Hesse, J.N.Zemel, “SensorsApplicationsVolume2”, Sensors in Intelligent 
Buildings, 
 4. Jan F. Kreider “Introduction to the Buildings Sector” Handbook of Heating, 
Ventilation, and Air Conditioning  Ed. Jan F. KreiderBoca Raton, CRC Press LLC. 
2001 
5. “Precise Metering and Consumptions based Billing for cooling and water”, Techem 
Energy Systems. 
6. Honeywell USA, “Engineering Manual for Automatic Control of Commercial 
Building, SI Edition,” 1997. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
72 
APPENDIX A: Hourly Energy Data 2009 September 
 
Date & Time Plant Generated Cooling Energy (kWh) 
Total AHU Consumed 
Cooling Energy (kWh) 
01/08/2009  15:00 3,628.27  1,560.32  
01/08/2009  16:00 4,437.49  3,920.54  
01/08/2009  17:00 2,152.62  1,132.46  
01/08/2009  18:00 577.63  239.12  
01/08/2009  19:00 524.07  327.45  
01/08/2009  20:00 507.79  268.27  
01/08/2009  21:00 594.69  289.95  
01/08/2009  22:00 7,031.44  4,307.64  
01/08/2009  23:00 2,498.19  1,405.35  
02/08/2009  01:00 522.43  295.16  
02/08/2009  02:00 502.56  313.39  
02/08/2009  03:00 473.95  258.12  
02/08/2009  04:00 886.96  226.37  
02/08/2009  05:00 5,094.90  2,096.37  
02/08/2009  06:00 981.78  252.65  
02/08/2009  07:00 25.35  84.01  
02/08/2009  08:00 2,864.43  2,130.92  
02/08/2009  09:00 5,499.15  2,947.67  
02/08/2009  10:00 1,454.86  1,015.59  
02/08/2009  11:00 686.51  199.66  
02/08/2009  12:00 555.58  272.54  
02/08/2009  13:00 509.49  215.32  
02/08/2009  14:00 472.57  138.28  
02/08/2009  15:00 559.76  53.95  
02/08/2009  16:00 4,585.41  2,008.25  
02/08/2009  17:00 1,341.11  582.13  
02/08/2009  18:00 902.40  253.09  
02/08/2009  19:00 542.00  176.07  
02/08/2009  20:00 4,228.56  2,119.24  
02/08/2009  21:00 1,861.76  1,223.98  
02/08/2009  22:00 614.12  200.34  
02/08/2009  23:00 1,943.59  648.67  
03/08/2009  01:00 564.80  236.14  
03/08/2009  02:00 528.80  364.74  
73 
03/08/2009  03:00 508.29  313.77  
03/08/2009  04:00 493.06  253.65  
03/08/2009  05:00 7,232.69  4,517.08  
03/08/2009  06:00 11,214.98  7,422.45  
03/08/2009  07:00 19,283.07  16,277.14  
03/08/2009  08:00 19,841.67  17,004.22  
03/08/2009  09:00 18,960.34  16,524.92  
03/08/2009  10:00 19,863.78  19,461.69  
03/08/2009  11:00 21,921.80  24,797.66  
03/08/2009  12:00 21,516.40  23,888.64  
03/08/2009  13:00 20,853.36  21,834.62  
03/08/2009  14:00 19,803.50  24,419.64  
03/08/2009  15:00 19,773.80  24,589.59  
03/08/2009  16:00 18,723.20  21,756.85  
03/08/2009  17:00 15,420.92  18,336.74  
03/08/2009  18:00 8,005.49  10,911.54  
03/08/2009  19:00 7,010.43  11,150.54  
03/08/2009  20:00 6,215.31  8,629.22  
03/08/2009  21:00 6,124.97  11,277.78  
03/08/2009  22:00 1,121.65  1,615.61  
03/08/2009  23:00 620.51  190.83  
04/08/2009  01:00 518.25  286.15  
04/08/2009  02:00 494.66  258.98  
04/08/2009  03:00 2,336.44  767.44  
04/08/2009  04:00 3,852.04  2,256.46  
04/08/2009  05:00 588.62  299.52  
04/08/2009  06:00 9,115.16  5,176.78  
04/08/2009  07:00 15,924.06  14,132.26  
04/08/2009  08:00 16,660.16  15,068.67  
04/08/2009  09:00 17,346.57  14,945.97  
04/08/2009  10:00 17,523.46  18,143.14  
04/08/2009  11:00 19,191.94  24,960.41  
04/08/2009  12:00 18,484.67  19,031.83  
04/08/2009  13:00 18,588.10  21,190.65  
04/08/2009  14:00 18,209.86  20,759.98  
04/08/2009  15:00 18,000.64  20,820.64  
04/08/2009  16:00 17,677.66  21,900.02  
04/08/2009  17:00 16,142.22  19,330.04  
04/08/2009  18:00 7,792.19  9,493.72  
74 
04/08/2009  19:00 7,355.78  9,764.02  
04/08/2009  20:00 6,958.63  9,759.60  
04/08/2009  21:00 5,373.55  8,661.98  
04/08/2009  22:00 1,987.08  1,998.66  
04/08/2009  23:00 565.98  228.85  
05/08/2009  01:00 519.99  305.76  
05/08/2009  02:00 499.23  280.63  
05/08/2009  03:00 473.52  249.40  
05/08/2009  04:00 455.22  208.87  
05/08/2009  05:00 3,411.82  1,234.43  
05/08/2009  06:00 3,196.53  2,493.58  
05/08/2009  07:00 1,036.53  990.69  
05/08/2009  08:00 5,693.00  2,742.23  
05/08/2009  09:00 6,737.39  4,390.62  
05/08/2009  10:00 6,386.11  4,226.96  
05/08/2009  11:00 6,685.27  4,759.51  
05/08/2009  12:00 7,234.81  6,921.00  
05/08/2009  13:00 7,607.10  11,016.91  
05/08/2009  14:00 5,688.28  8,679.69  
05/08/2009  15:00 5,728.93  9,525.30  
05/08/2009  16:00 5,467.85  9,306.28  
05/08/2009  17:00 5,379.90  7,718.54  
05/08/2009  18:00 5,221.99  6,975.20  
05/08/2009  19:00 4,922.28  6,569.60  
05/08/2009  20:00 4,653.78  6,442.27  
05/08/2009  21:00 5,496.98  7,267.55  
05/08/2009  22:00 4,350.63  4,185.79  
05/08/2009  23:00 1,243.16  1,036.48  
06/08/2009  01:00 549.74  329.99  
06/08/2009  02:00 517.62  310.44  
06/08/2009  03:00 1,317.24  683.83  
06/08/2009  04:00 2,951.53  1,506.87  
06/08/2009  05:00 636.59  334.62  
06/08/2009  06:00 3,666.79  2,637.51  
06/08/2009  07:00 19,954.44  16,535.34  
06/08/2009  08:00 17,952.03  16,394.47  
06/08/2009  09:00 17,499.29  15,518.41  
06/08/2009  10:00 18,207.05  18,535.07  
06/08/2009  11:00 19,832.60  24,688.10  
75 
06/08/2009  12:00 18,950.56  20,379.13  
06/08/2009  13:00 18,551.93  20,502.82  
06/08/2009  14:00 19,164.48  21,540.76  
06/08/2009  15:00 18,349.07  19,916.72  
06/08/2009  16:00 17,852.77  18,602.79  
06/08/2009  17:00 12,497.17  13,046.82  
06/08/2009  18:00 8,434.33  10,384.25  
06/08/2009  19:00 7,126.98  10,810.94  
06/08/2009  20:00 6,507.60  9,546.57  
06/08/2009  21:00 5,940.38  8,603.70  
06/08/2009  22:00 1,379.79  1,961.83  
06/08/2009  23:00 812.42  250.45  
07/08/2009  01:00 538.62  333.33  
07/08/2009  02:00 508.80  285.57  
07/08/2009  03:00 3,404.53  789.62  
07/08/2009  04:00 970.68  346.41  
07/08/2009  05:00 521.72  387.87  
07/08/2009  06:00 8,605.01  4,791.86  
07/08/2009  07:00 17,169.19  15,513.08  
07/08/2009  08:00 16,670.94  14,983.86  
07/08/2009  09:00 16,812.90  15,337.93  
07/08/2009  10:00 17,674.53  17,948.16  
07/08/2009  11:00 19,079.19  23,598.86  
07/08/2009  12:00 18,506.03  20,769.13  
07/08/2009  13:00 18,204.37  20,090.64  
07/08/2009  14:00 17,862.65  19,603.21  
07/08/2009  15:00 16,353.58  18,597.02  
07/08/2009  16:00 15,449.41  18,973.47  
07/08/2009  17:00 13,978.65  17,700.51  
07/08/2009  18:00 7,206.22  9,830.12  
07/08/2009  19:00 6,128.09  8,122.65  
07/08/2009  20:00 6,010.69  7,742.43  
07/08/2009  21:00 4,768.61  7,655.90  
07/08/2009  22:00 2,964.73  3,283.12  
07/08/2009  23:00 720.73  225.14  
08/08/2009  01:00 528.94  107.37  
08/08/2009  02:00 502.95  73.82  
08/08/2009  03:00 4,428.25  2,862.57  
08/08/2009  04:00 1,696.50  1,194.05  
76 
08/08/2009  05:00 570.67  170.79  
08/08/2009  06:00 519.21  132.85  
08/08/2009  07:00 510.87  98.71  
08/08/2009  08:00 4,071.11  1,639.37  
08/08/2009  09:00 4,155.15  2,625.66  
08/08/2009  10:00 5,171.27  3,426.05  
08/08/2009  11:00 4,903.96  3,491.34  
08/08/2009  12:00 4,704.94  3,282.02  
08/08/2009  13:00 4,517.92  3,192.14  
08/08/2009  14:00 4,523.72  3,174.09  
08/08/2009  15:00 4,357.77  2,885.83  
08/08/2009  16:00 1,657.30  773.93  
08/08/2009  17:00 653.45  123.65  
08/08/2009  18:00 562.50  82.35  
08/08/2009  19:00 939.52  428.67  
08/08/2009  20:00 6,117.41  4,413.51  
08/08/2009  21:00 3,898.51  3,107.68  
08/08/2009  22:00 1,453.84  884.00  
08/08/2009  23:00 663.14  168.52  
09/08/2009  01:00 515.62  97.01  
09/08/2009  02:00 5,268.10  3,329.18  
09/08/2009  03:00 2,878.43  2,111.15  
09/08/2009  04:00 830.56  209.66  
09/08/2009  05:00 534.84  171.55  
09/08/2009  06:00 528.98  132.84  
09/08/2009  07:00 509.70  110.66  
09/08/2009  08:00 1,079.40  128.16  
09/08/2009  09:00 6,740.79  3,384.18  
09/08/2009  10:00 2,969.74  1,854.18  
09/08/2009  11:00 943.09  252.96  
09/08/2009  12:00 533.02  176.38  
09/08/2009  13:00 529.92  121.92  
09/08/2009  14:00 533.17  149.51  
09/08/2009  15:00 5,346.49  1,690.59  
09/08/2009  16:00 738.49  191.50  
09/08/2009  17:00 630.29  196.79  
09/08/2009  18:00 538.97  135.23  
09/08/2009  19:00 517.97  92.55  
09/08/2009  20:00 6,697.58  2,970.51  
77 
09/08/2009  21:00 2,825.50  1,394.53  
09/08/2009  22:00 631.20  173.79  
09/08/2009  23:00 575.37  130.55  
10/08/2009  01:00 496.58  47.66  
10/08/2009  02:00 461.35  39.47  
10/08/2009  03:00 5,205.93  2,909.86  
10/08/2009  04:00 2,589.31  1,767.27  
10/08/2009  05:00 637.06  197.50  
10/08/2009  06:00 7,338.29  3,656.21  
10/08/2009  07:00 22,104.60  19,094.75  
10/08/2009  08:00 20,984.86  19,040.61  
10/08/2009  09:00 20,510.31  18,477.32  
10/08/2009  10:00 20,990.53  21,077.16  
10/08/2009  11:00 22,093.50  25,617.71  
10/08/2009  12:00 21,277.28  23,438.25  
10/08/2009  13:00 21,004.02  24,571.74  
10/08/2009  14:00 20,995.03  23,466.26  
10/08/2009  15:00 18,521.46  22,478.04  
10/08/2009  16:00 20,754.24  24,343.07  
10/08/2009  17:00 17,121.98  16,843.69  
10/08/2009  18:00 7,640.78  4,312.62  
10/08/2009  19:00 7,376.71  4,550.07  
10/08/2009  20:00 6,812.60  3,707.90  
10/08/2009  21:00 5,860.38  2,374.81  
10/08/2009  22:00 1,594.90  524.92  
10/08/2009  23:00 649.57  172.22  
11/08/2009  01:00 2,819.75  893.59  
11/08/2009  02:00 1,074.16  480.07  
11/08/2009  03:00 897.70  201.69  
11/08/2009  04:00 582.21  141.06  
11/08/2009  05:00 4,501.28  2,053.96  
11/08/2009  06:00 8,096.17  5,714.72  
11/08/2009  07:00 18,254.63  16,521.29  
11/08/2009  08:00 17,700.03  16,209.31  
11/08/2009  09:00 17,811.47  16,478.67  
11/08/2009  10:00 18,581.04  16,405.16  
11/08/2009  11:00 20,389.92  17,765.78  
11/08/2009  12:00 19,296.71  16,816.50  
11/08/2009  13:00 19,305.34  17,277.42  
78 
11/08/2009  14:00 18,874.63  16,950.59  
11/08/2009  15:00 18,311.98  16,205.92  
11/08/2009  16:00 17,820.39  15,857.81  
11/08/2009  17:00 15,311.73  12,895.97  
11/08/2009  18:00 8,784.14  6,054.58  
11/08/2009  19:00 7,709.71  5,194.21  
11/08/2009  20:00 6,697.70  4,306.67  
11/08/2009  21:00 5,449.00  2,631.33  
11/08/2009  22:00 1,224.74  454.75  
11/08/2009  23:00 612.30  160.21  
12/08/2009  01:00 506.15  86.88  
12/08/2009  02:00 486.74  52.83  
12/08/2009  03:00 5,166.90  2,705.15  
12/08/2009  04:00 896.27  182.10  
12/08/2009  05:00 506.55  132.80  
12/08/2009  06:00 8,969.49  5,456.33  
12/08/2009  07:00 15,578.93  14,779.94  
12/08/2009  08:00 15,142.00  14,715.31  
12/08/2009  09:00 15,819.86  15,057.49  
12/08/2009  10:00 16,890.44  15,650.60  
12/08/2009  11:00 18,526.20  16,784.65  
12/08/2009  12:00 18,202.47  16,373.41  
12/08/2009  13:00 18,166.28  16,240.12  
12/08/2009  14:00 17,801.37  15,687.96  
12/08/2009  15:00 16,641.59  14,483.83  
12/08/2009  16:00 17,117.21  14,677.41  
12/08/2009  17:00 14,447.83  12,034.66  
12/08/2009  18:00 7,374.15  4,850.49  
12/08/2009  19:00 6,759.29  4,928.12  
12/08/2009  20:00 6,334.09  4,503.46  
12/08/2009  21:00 5,385.16  2,833.70  
12/08/2009  22:00 1,347.64  516.62  
12/08/2009  23:00 639.79  168.35  
13/08/2009  01:00 515.77  83.95  
13/08/2009  02:00 5,875.33  3,644.36  
13/08/2009  03:00 1,698.62  896.31  
13/08/2009  04:00 612.89  152.06  
13/08/2009  05:00 536.41  113.26  
13/08/2009  06:00 9,728.52  6,608.23  
79 
13/08/2009  07:00 14,287.80  13,444.19  
13/08/2009  08:00 15,192.52  14,636.32  
13/08/2009  09:00 16,216.42  15,337.75  
13/08/2009  10:00 17,647.24  16,027.88  
13/08/2009  11:00 17,976.33  16,543.12  
13/08/2009  12:00 17,901.69  16,188.28  
13/08/2009  13:00 17,551.21  15,553.80  
13/08/2009  14:00 17,348.65  15,476.27  
13/08/2009  15:00 17,430.16  15,283.54  
13/08/2009  16:00 17,561.98  15,404.89  
13/08/2009  17:00 14,996.52  12,926.34  
13/08/2009  18:00 8,780.90  6,304.41  
13/08/2009  19:00 7,242.51  5,178.40  
13/08/2009  20:00 6,028.72  3,891.43  
13/08/2009  21:00 4,868.78  2,604.09  
13/08/2009  22:00 872.87  1,009.03  
13/08/2009  23:00 596.28  176.90  
14/08/2009  01:00 512.55  83.20  
14/08/2009  02:00 488.33  54.19  
14/08/2009  03:00 458.94  45.18  
14/08/2009  04:00 443.56  47.29  
14/08/2009  05:00 3,285.39  886.84  
14/08/2009  06:00 9,544.94  6,222.09  
14/08/2009  07:00 14,003.15  12,052.08  
14/08/2009  08:00 14,410.92  13,007.33  
14/08/2009  09:00 15,724.39  13,736.44  
14/08/2009  10:00 16,432.34  14,354.98  
14/08/2009  11:00 17,947.59  15,688.04  
14/08/2009  12:00 18,026.92  15,608.99  
14/08/2009  13:00 18,174.83  15,830.24  
14/08/2009  14:00 18,738.37  16,085.94  
14/08/2009  15:00 16,918.93  14,205.02  
14/08/2009  16:00 16,536.78  13,783.41  
14/08/2009  17:00 9,367.23  7,011.74  
14/08/2009  18:00 6,026.72  3,850.00  
14/08/2009  19:00 6,633.43  4,619.09  
14/08/2009  20:00 6,203.56  4,136.92  
14/08/2009  21:00 5,002.96  2,528.06  
14/08/2009  22:00 3,591.11  1,668.09  
80 
14/08/2009  23:00 3,175.52  1,079.20  
15/08/2009  01:00 1,149.50  347.47  
15/08/2009  02:00 632.54  135.52  
15/08/2009  03:00 541.77  108.47  
15/08/2009  04:00 509.54  76.49  
15/08/2009  05:00 490.30  54.68  
15/08/2009  06:00 466.57  34.84  
15/08/2009  07:00 449.76  37.32  
15/08/2009  08:00 3,142.85  456.61  
15/08/2009  09:00 5,390.97  3,115.11  
15/08/2009  10:00 5,640.71  4,783.36  
15/08/2009  11:00 6,640.59  6,244.42  
15/08/2009  12:00 6,704.36  5,639.71  
15/08/2009  13:00 6,315.24  5,537.96  
15/08/2009  14:00 3,946.72  3,388.72  
15/08/2009  15:00 6,607.53  5,113.72  
15/08/2009  16:00 6,009.32  4,727.06  
15/08/2009  17:00 5,047.71  2,802.08  
15/08/2009  18:00 2,679.50  1,218.83  
15/08/2009  19:00 414.28  165.53  
15/08/2009  20:00 646.83  148.48  
15/08/2009  21:00 566.52  97.18  
15/08/2009  22:00 520.07  52.02  
15/08/2009  23:00 502.39  38.16  
16/08/2009  01:00 4,366.52  969.89  
16/08/2009  02:00 1,015.26  199.92  
16/08/2009  03:00 527.99  125.49  
16/08/2009  04:00 516.89  79.34  
16/08/2009  05:00 491.80  53.93  
16/08/2009  06:00 5,640.24  2,261.74  
16/08/2009  07:00 0.00  69.73  
16/08/2009  08:00 1,012.13  191.60  
16/08/2009  09:00 567.36  123.61  
16/08/2009  10:00 4,163.29  1,949.90  
16/08/2009  11:00 6,506.77  5,032.88  
16/08/2009  12:00 4,736.25  3,692.20  
16/08/2009  13:00 2,825.72  1,901.35  
16/08/2009  14:00 558.71  176.19  
16/08/2009  15:00 548.01  133.10  
81 
16/08/2009  16:00 524.07  86.66  
16/08/2009  17:00 486.60  66.12  
16/08/2009  18:00 461.86  67.00  
16/08/2009  19:00 5,100.77  1,943.14  
16/08/2009  20:00 3,289.55  1,366.41  
16/08/2009  21:00 956.25  231.72  
16/08/2009  22:00 601.85  172.75  
16/08/2009  23:00 2,424.85  743.23  
17/08/2009  01:00 559.94  94.14  
17/08/2009  02:00 530.79  49.25  
17/08/2009  03:00 6,499.08  3,669.74  
17/08/2009  04:00 3,286.36  1,749.54  
17/08/2009  05:00 576.56  122.78  
17/08/2009  06:00 8,606.42  5,217.49  
17/08/2009  07:00 20,126.76  16,187.56  
17/08/2009  08:00 18,639.53  15,515.51  
17/08/2009  09:00 18,359.98  14,826.97  
17/08/2009  10:00 18,166.68  14,910.59  
17/08/2009  11:00 19,157.22  16,112.77  
17/08/2009  12:00 19,393.11  16,148.76  
17/08/2009  13:00 18,263.36  14,848.22  
17/08/2009  14:00 17,844.77  14,208.68  
17/08/2009  15:00 17,420.89  13,647.94  
17/08/2009  16:00 17,161.50  13,506.36  
17/08/2009  17:00 11,983.27  8,702.39  
17/08/2009  18:00 5,116.32  2,759.52  
17/08/2009  19:00 5,371.07  3,355.29  
17/08/2009  20:00 5,258.26  3,308.22  
17/08/2009  21:00 4,033.09  1,872.56  
17/08/2009  22:00 1,085.68  359.72  
17/08/2009  23:00 626.22  135.91  
18/08/2009  01:00 508.25  43.30  
18/08/2009  02:00 482.86  12.91  
18/08/2009  03:00 3,243.90  886.24  
18/08/2009  04:00 1,521.61  802.72  
18/08/2009  05:00 613.02  97.69  
18/08/2009  06:00 10,508.52  6,380.57  
18/08/2009  07:00 14,631.14  12,507.38  
18/08/2009  08:00 15,729.22  13,282.65  
82 
18/08/2009  09:00 15,852.11  13,182.17  
18/08/2009  10:00 17,352.60  14,048.26  
18/08/2009  11:00 18,232.91  14,853.99  
18/08/2009  12:00 18,372.71  15,038.82  
18/08/2009  13:00 18,348.57  15,044.64  
18/08/2009  14:00 18,299.48  15,376.86  
18/08/2009  15:00 17,052.83  13,863.63  
18/08/2009  16:00 16,577.95  13,189.01  
18/08/2009  17:00 13,709.75  10,603.74  
18/08/2009  18:00 9,514.65  6,583.42  
18/08/2009  19:00 8,535.87  6,463.61  
18/08/2009  20:00 7,441.10  5,385.48  
18/08/2009  21:00 6,469.33  3,895.78  
18/08/2009  22:00 1,001.29  413.34  
18/08/2009  23:00 738.86  165.29  
19/08/2009  01:00 500.71  27.13  
19/08/2009  02:00 487.12  13.87  
19/08/2009  03:00 3,462.54  749.93  
19/08/2009  04:00 911.34  110.81  
19/08/2009  05:00 537.66  58.38  
19/08/2009  06:00 8,387.03  4,961.21  
19/08/2009  07:00 14,180.04  12,120.65  
19/08/2009  08:00 15,257.23  13,110.86  
19/08/2009  09:00 17,091.85  13,867.02  
19/08/2009  10:00 17,629.48  14,499.90  
19/08/2009  11:00 18,165.71  14,918.48  
19/08/2009  12:00 17,840.34  14,765.61  
19/08/2009  13:00 17,868.09  14,656.01  
19/08/2009  14:00 18,421.92  14,930.39  
19/08/2009  15:00 17,836.29  14,327.89  
19/08/2009  16:00 16,698.41  13,573.74  
19/08/2009  17:00 13,728.69  10,776.25  
19/08/2009  18:00 6,582.40  4,448.67  
19/08/2009  19:00 6,360.51  4,379.58  
19/08/2009  20:00 5,406.83  3,768.70  
19/08/2009  21:00 4,599.65  2,851.56  
19/08/2009  22:00 2,266.62  941.51  
19/08/2009  23:00 550.99  130.07  
20/08/2009  01:00 492.79  21.25  
83 
20/08/2009  02:00 476.38  3.41  
20/08/2009  03:00 6,324.28  3,568.57  
20/08/2009  04:00 946.50  121.05  
20/08/2009  05:00 513.50  60.68  
20/08/2009  06:00 7,989.11  4,481.77  
20/08/2009  07:00 14,024.00  12,119.61  
20/08/2009  08:00 15,042.72  12,763.62  
20/08/2009  09:00 16,992.43  13,789.63  
20/08/2009  10:00 17,086.93  13,981.22  
20/08/2009  11:00 17,989.64  15,073.14  
20/08/2009  12:00 17,824.04  14,921.60  
20/08/2009  13:00 16,793.07  13,793.60  
20/08/2009  14:00 18,181.85  14,962.20  
20/08/2009  15:00 17,688.08  14,434.95  
20/08/2009  16:00 16,149.76  13,277.39  
20/08/2009  17:00 14,544.96  11,674.89  
20/08/2009  18:00 8,813.76  6,098.05  
20/08/2009  19:00 7,730.20  5,849.40  
20/08/2009  20:00 5,662.26  3,939.97  
20/08/2009  21:00 4,869.35  2,521.64  
20/08/2009  22:00 2,234.13  771.06  
20/08/2009  23:00 745.83  109.58  
21/08/2009  01:00 506.12  21.41  
21/08/2009  02:00 480.67  1.58  
21/08/2009  03:00 3,939.43  2,003.57  
21/08/2009  04:00 850.55  125.22  
21/08/2009  05:00 493.40  51.27  
21/08/2009  06:00 8,777.77  5,416.07  
21/08/2009  07:00 12,186.90  10,458.24  
21/08/2009  08:00 13,193.58  12,097.61  
21/08/2009  09:00 14,343.83  12,834.90  
21/08/2009  10:00 15,128.05  13,034.02  
21/08/2009  11:00 16,703.22  14,201.88  
21/08/2009  12:00 16,126.98  13,738.11  
21/08/2009  13:00 16,897.00  14,040.97  
21/08/2009  14:00 16,490.52  13,813.61  
21/08/2009  15:00 15,702.87  13,071.14  
21/08/2009  16:00 14,740.54  12,191.71  
21/08/2009  17:00 12,817.18  10,142.22  
84 
21/08/2009  18:00 5,679.30  3,581.34  
21/08/2009  19:00 5,000.02  3,330.03  
21/08/2009  20:00 5,377.13  3,478.92  
21/08/2009  21:00 4,070.92  2,198.57  
21/08/2009  22:00 1,520.52  481.60  
21/08/2009  23:00 520.36  105.78  
22/08/2009  01:00 488.74  50.98  
22/08/2009  02:00 470.00  34.26  
22/08/2009  03:00 462.08  34.95  
22/08/2009  04:00 440.65  37.44  
22/08/2009  05:00 5,037.99  2,144.79  
22/08/2009  06:00 1,741.01  673.94  
22/08/2009  07:00 605.31  106.22  
22/08/2009  08:00 491.04  62.05  
22/08/2009  09:00 832.14  81.37  
22/08/2009  10:00 6,935.88  4,968.39  
22/08/2009  11:00 4,562.31  3,834.40  
22/08/2009  12:00 4,576.67  3,640.62  
22/08/2009  13:00 4,232.71  3,199.18  
22/08/2009  14:00 4,223.29  3,138.86  
22/08/2009  15:00 3,937.94  2,794.27  
22/08/2009  16:00 1,091.22  509.55  
22/08/2009  17:00 618.13  139.61  
22/08/2009  18:00 524.56  85.15  
22/08/2009  19:00 485.65  58.84  
22/08/2009  20:00 459.33  60.13  
22/08/2009  21:00 440.13  61.04  
22/08/2009  22:00 3,894.02  1,039.56  
22/08/2009  23:00 3,144.25  1,411.65  
23/08/2009  01:00 619.72  130.68  
23/08/2009  02:00 524.57  85.29  
23/08/2009  03:00 480.13  65.52  
23/08/2009  04:00 450.85  66.31  
23/08/2009  05:00 4,391.17  1,951.46  
23/08/2009  06:00 1,192.77  456.67  
23/08/2009  07:00 783.45  172.30  
23/08/2009  08:00 673.40  450.55  
23/08/2009  09:00 5,721.75  2,464.67  
23/08/2009  10:00 3,596.45  2,202.44  
85 
23/08/2009  11:00 3,522.98  2,094.36  
23/08/2009  12:00 1,645.19  741.05  
23/08/2009  13:00 590.89  95.92  
23/08/2009  14:00 515.44  52.89  
23/08/2009  15:00 497.49  36.33  
23/08/2009  16:00 4,954.52  3,187.71  
23/08/2009  17:00 872.02  150.86  
23/08/2009  18:00 533.20  107.48  
23/08/2009  19:00 508.28  66.52  
23/08/2009  20:00 491.52  47.68  
23/08/2009  21:00 468.22  49.20  
23/08/2009  22:00 451.31  50.74  
23/08/2009  23:00 599.79  128.81  
24/08/2009  01:00 2,369.49  758.54  
24/08/2009  02:00 620.86  148.86  
24/08/2009  03:00 494.37  92.26  
24/08/2009  04:00 510.72  62.21  
24/08/2009  05:00 492.64  62.22  
24/08/2009  06:00 10,027.11  5,470.18  
24/08/2009  07:00 18,213.39  15,823.08  
24/08/2009  08:00 17,150.56  14,965.85  
24/08/2009  09:00 17,606.44  15,547.47  
24/08/2009  10:00 18,449.39  15,832.16  
24/08/2009  11:00 19,550.05  16,599.65  
24/08/2009  12:00 18,442.76  15,513.76  
24/08/2009  13:00 19,052.68  16,437.33  
24/08/2009  14:00 17,346.11  14,346.65  
24/08/2009  15:00 17,740.84  14,712.70  
24/08/2009  16:00 17,402.79  15,140.86  
24/08/2009  17:00 15,151.33  12,775.56  
24/08/2009  18:00 7,848.62  4,746.69  
24/08/2009  19:00 6,559.79  4,058.30  
24/08/2009  20:00 6,021.49  3,562.87  
24/08/2009  21:00 5,383.61  2,842.45  
24/08/2009  22:00 2,414.40  950.36  
24/08/2009  23:00 738.28  195.24  
25/08/2009  01:00 532.27  67.01  
25/08/2009  02:00 513.32  39.34  
25/08/2009  03:00 493.75  36.25  
86 
25/08/2009  04:00 473.46  38.63  
25/08/2009  05:00 3,806.78  1,345.78  
25/08/2009  06:00 9,541.94  6,323.08  
25/08/2009  07:00 14,387.66  12,348.32  
25/08/2009  08:00 14,400.85  13,093.57  
25/08/2009  09:00 16,511.42  15,896.95  
25/08/2009  10:00 16,842.63  16,223.74  
25/08/2009  11:00 17,929.88  17,021.89  
25/08/2009  12:00 17,375.90  16,343.07  
25/08/2009  13:00 17,164.05  15,847.95  
25/08/2009  14:00 17,260.65  15,842.50  
25/08/2009  15:00 17,010.54  15,671.26  
25/08/2009  16:00 16,624.19  15,531.03  
25/08/2009  17:00 14,083.54  13,045.60  
25/08/2009  18:00 7,090.72  5,093.46  
25/08/2009  19:00 5,501.57  3,647.55  
25/08/2009  20:00 4,744.29  3,217.46  
25/08/2009  21:00 4,761.35  3,423.17  
25/08/2009  22:00 1,221.28  812.59  
25/08/2009  23:00 497.71  156.51  
26/08/2009  01:00 558.05  80.01  
26/08/2009  02:00 760.67  180.04  
26/08/2009  03:00 6,099.06  3,271.40  
26/08/2009  04:00 887.47  170.09  
26/08/2009  05:00 523.02  111.96  
26/08/2009  06:00 7,621.77  4,487.07  
26/08/2009  07:00 14,108.82  12,500.70  
26/08/2009  08:00 14,047.50  12,943.10  
26/08/2009  09:00 14,287.80  12,969.27  
26/08/2009  10:00 16,170.17  14,220.87  
26/08/2009  11:00 16,780.62  14,497.59  
26/08/2009  12:00 16,367.55  13,931.40  
26/08/2009  13:00 16,198.86  13,657.26  
26/08/2009  14:00 16,915.78  14,462.52  
26/08/2009  15:00 16,678.58  14,517.10  
26/08/2009  16:00 16,005.81  14,423.15  
26/08/2009  17:00 12,493.94  9,916.95  
26/08/2009  18:00 7,135.73  4,782.91  
26/08/2009  19:00 6,781.53  4,854.23  
87 
26/08/2009  20:00 5,810.91  3,811.32  
26/08/2009  21:00 3,739.59  1,732.11  
26/08/2009  22:00 0.00  18.61  
26/08/2009  23:00 481.78  126.64  
27/08/2009  01:00 536.81  82.56  
27/08/2009  02:00 501.56  52.72  
27/08/2009  03:00 476.41  43.97  
27/08/2009  04:00 4,297.97  1,362.37  
27/08/2009  05:00 1,452.66  522.96  
27/08/2009  06:00 7,830.98  5,204.48  
27/08/2009  07:00 13,567.99  11,506.32  
27/08/2009  08:00 14,616.17  13,421.99  
27/08/2009  09:00 16,066.59  14,583.88  
27/08/2009  10:00 17,110.59  14,863.90  
27/08/2009  11:00 16,836.14  14,791.22  
27/08/2009  12:00 16,654.57  14,090.10  
27/08/2009  13:00 16,987.16  14,501.38  
27/08/2009  14:00 16,529.34  14,090.50  
27/08/2009  15:00 16,483.15  14,337.91  
27/08/2009  16:00 15,757.90  13,279.07  
27/08/2009  17:00 12,570.81  9,977.55  
27/08/2009  18:00 7,120.66  4,249.85  
27/08/2009  19:00 6,257.16  4,518.87  
27/08/2009  20:00 5,425.46  3,684.25  
27/08/2009  21:00 5,448.34  3,652.13  
27/08/2009  22:00 2,302.95  1,233.47  
27/08/2009  23:00 642.43  144.20  
28/08/2009  01:00 531.04  61.30  
28/08/2009  02:00 511.32  39.27  
28/08/2009  03:00 495.64  39.62  
28/08/2009  04:00 479.15  41.92  
28/08/2009  05:00 3,586.82  1,176.72  
28/08/2009  06:00 8,261.18  6,147.87  
28/08/2009  07:00 13,768.41  11,817.77  
28/08/2009  08:00 14,599.37  13,149.67  
28/08/2009  09:00 15,680.06  13,717.01  
28/08/2009  10:00 16,173.80  13,674.16  
28/08/2009  11:00 17,114.81  14,599.07  
28/08/2009  12:00 16,187.39  13,689.36  
88 
28/08/2009  13:00 16,306.59  13,878.84  
28/08/2009  14:00 16,859.67  14,451.67  
28/08/2009  15:00 15,726.42  13,047.14  
28/08/2009  16:00 15,237.62  12,255.21  
28/08/2009  17:00 11,306.55  8,720.19  
28/08/2009  18:00 6,052.08  4,700.85  
28/08/2009  19:00 6,147.70  5,218.36  
28/08/2009  20:00 5,397.35  4,318.82  
28/08/2009  21:00 4,212.74  3,572.96  
28/08/2009  22:00 1,061.66  508.25  
28/08/2009  23:00 614.17  117.31  
29/08/2009  01:00 519.60  43.13  
29/08/2009  02:00 505.07  35.00  
29/08/2009  03:00 488.92  38.09  
29/08/2009  04:00 472.37  40.94  
29/08/2009  05:00 457.14  43.56  
29/08/2009  06:00 493.03  48.79  
29/08/2009  07:00 8,107.78  4,813.53  
29/08/2009  08:00 6,915.23  6,340.90  
29/08/2009  09:00 4,683.59  2,984.84  
29/08/2009  10:00 6,621.50  5,872.38  
29/08/2009  11:00 6,060.42  5,182.58  
29/08/2009  12:00 5,778.42  4,791.89  
29/08/2009  13:00 5,503.21  4,480.46  
29/08/2009  14:00 5,298.11  4,461.35  
29/08/2009  15:00 7,215.92  6,680.53  
29/08/2009  16:00 6,802.04  5,965.94  
29/08/2009  17:00 3,585.34  3,088.96  
29/08/2009  18:00 617.34  97.03  
29/08/2009  19:00 3,624.64  1,912.17  
29/08/2009  20:00 5,853.50  4,373.26  
29/08/2009  21:00 5,036.18  3,430.25  
29/08/2009  22:00 5,401.34  3,490.68  
29/08/2009  23:00 4,145.41  2,272.00  
30/08/2009  01:00 0.00  0.00  
30/08/2009  02:00 0.00  0.00  
30/08/2009  03:00 0.00  0.00  
30/08/2009  04:00 0.00  0.00  
30/08/2009  05:00 0.00  0.00  
89 
30/08/2009  06:00 0.00  0.00  
30/08/2009  07:00 0.00  0.00  
30/08/2009  08:00 0.00  0.00  
30/08/2009  09:00 0.00  0.00  
30/08/2009  10:00 0.00  0.00  
30/08/2009  11:00 0.00  0.00  
30/08/2009  12:00 0.00  0.00  
30/08/2009  13:00 0.00  0.00  
30/08/2009  14:00 0.00  0.00  
30/08/2009  15:00 0.00  0.00  
30/08/2009  16:00 0.00  0.00  
30/08/2009  17:00 0.00  0.00  
30/08/2009  18:00 0.00  0.00  
30/08/2009  19:00 0.00  0.00  
30/08/2009  20:00 0.00  0.00  
30/08/2009  21:00 0.00  0.00  
30/08/2009  22:00 0.00  0.00  
30/08/2009  23:00 0.00  0.00  
31/08/2009  00:00 0.00  0.00  
31/08/2009  01:00 0.00  0.00  
31/08/2009  02:00 0.00  0.00  
31/08/2009  03:00 0.00  0.00  
31/08/2009  04:00 0.00  0.00  
31/08/2009  05:00 0.00  0.00  
31/08/2009  06:00 0.00  0.00  
31/08/2009  07:00 0.00  0.00  
31/08/2009  08:00 0.00  0.00  
31/08/2009  09:00 0.00  0.00  
31/08/2009  10:00 0.00  0.00  
31/08/2009  11:00 0.00  0.00  
31/08/2009  12:00 0.00  0.00  
31/08/2009  13:00 0.00  0.00  
31/08/2009  14:00 0.00  0.00  
31/08/2009  15:00 0.00  0.00  
31/08/2009  16:00 0.00  0.00  
31/08/2009  17:00 0.00  0.00  
31/08/2009  18:00 0.00  0.00  
31/08/2009  19:00 0.00  0.00  
31/08/2009  20:00 0.00  0.00  
90 
31/08/2009  21:00 0.00  0.00  
31/08/2009  22:00 0.00  0.00  
31/08/2009  23:00 0.00  0.00  
01/09/2009  00:00 0.00  0.00  
01/09/2009  01:00 0.00  0.00  
01/09/2009  02:00 0.00  0.00  
01/09/2009  03:00 0.00  0.00  
01/09/2009  04:00 0.00  0.00  
01/09/2009  05:00 0.00  0.00  
01/09/2009  06:00 0.00  0.00  
01/09/2009  07:00 0.00  0.00  
01/09/2009  08:00 0.00  0.00  
01/09/2009  09:00 0.00  0.00  
01/09/2009  10:00 0.00  0.00  
01/09/2009  11:00 0.00  0.00  
01/09/2009  12:00 0.00  0.00  
01/09/2009  13:00 0.00  0.00  
01/09/2009  14:00 0.00  0.00  
01/09/2009  15:00 0.00  0.00