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