An-Najah National University 
Faculty of Graduate Studies 

 
 
 
 
 
 
 
 

 
 
 
 
 

Study and Design of An Automatic Control System for 
Electric Energy Management - Case Study  

An-Najah National University 
 
 
 
 
 

 
 
 
 
 

By 
Mohammed Khaleel Sa'di "Rashid Al_Mubayed" 

 
 
 
 
 
 
 
 

Supervisor 
Dr. Samer Mayaleh 

 
 
 
 
 

 

 
 
Submitted in Partial Fulfillment of the Requirements for the Degree of 
Master in Clean Energy and Conservation Strategy Engineering, Faculty 
of Graduate Studies, at An-Najah National University, Nablus, Palestine 

2008 





 iii
 

DEDICATION 
 
To the owners of the glowing hearts and burning vigor.………………….. 

To those who sacrificed their money, souls and blood for their faith........... 

To those who faced the devil of evil and the devil of craving…………….. 

To Al-Aqsa Intifada martyrs and all  martyrs of  Palestine………………… 

To those who loved Palestine as a home land and Islam as a way of life…...  

To my tender mother, honored father and dear sisters. 

To all of them, 

I dedicate this work 

 

 

 

 
 
 
 
 
 

 
 
 
 
 



 iv

 
ACKNOWLEDGMENT 

 
It's an honor for me to have the opportunity to say a word to thank all 

people who helped me to carry out this study, although its impossible to 

include all of them here. 

To begin with, I'd like to thank Dr. Samer Mayaleh, assistance 

professor of electrical engineering for his great and continues effort helping 

me in all stages in this study. Dr. Samer gave me huge assistance through 

his long experience in this field; he was also patient and scientific. 

My thanks also go to the staff of  Clean Energy and Conservation 

Strategy Engineering Program in An-Najah National University, especially 

Dr. Imad Ibrik, the director of Energy Research Center, and the coordinator 

of this master program, for his valuable and helpful suggestions.  

Finally, I couldn’t complete this  Acknowledgment without express 

my deep gratitude to my father for his support, my mother for her kindness 

and patient, my sisters for there encouragement, and my friends for there 

useful help, and to all people who contribute in this effort. Without all 

those mentioned above this study could not have seen the light. 

 
 
 



 v

Abbreviations 

ANSI American National Standards Institute
ASHREA American Society of Heating, Refrigerating and Air-

conditioning Engineers 
BACnet Building Automation Communications Network  
BAS Building Automation System 
CFL Compact Fluorescent Lamp 
Cu Coefficient of Utilization 
EC Energy Conservation 
ECO Energy Conservation Opportunity 
EMS Energy Management System
EPA Environmental Protection Agency 
EUI Energy Utilization Index  
FLA Full Load Ampere 
GHG Greenhouse Gases 
HVAC Heating Ventilating and Air Conditioning 
IEC Israeli Electric Corporation 
IP Internet Protocol
Km Maintenance Factor 
kVAR Kilovolt Ampere Reactive Power 
kWh Kilowatt hour 
LAN Local Area Network 
LLD Lamp Lumen Deprecation 
LMS Lighting Management System 
MAC Media Access Control 
MRS Monitoring Remote System 
NIS New Israeli Shekel 
O&M Operation and Maintenance 
PEA Palestinian Energy Authority 
PHP Hypertext Preprocessor 
PIC Programmable Interrupt Controller 
PIR Passive Infrared Sensor 
RLA Rated Load Ampere 
SNMP Simple Network Management Protocol
SPBP Simple Pay Back Period 
TCP/IP Transmission Control Protocol/Internet Protocol 
TQM Total Quality Management 
UDP User Datagram Protocol 
US Ultrasonic Sensor 
VBA Visual Basic for Application 
XML Extensible Markup Language 



 vi

 إقـرار 
  

   :أنا الموقع أدناه مقدم الرسالة التي تحمل العنوان

Study and Design of an Automatic control System for 
Electric Energy Management - Case Study  

An-Najah National University 
 

   - لي إلدارة الطاقة الكهربائيةآدراسة وتصميم نظام تحكم 

  نجاح الوطنيةدراسة حالة جامعة ال
  

اقر بأن ما اشتملت عليه هذه الرسالة إنما هي نتاج جهدي الخاص، باستثناء مـا تمـت   

اإلشارة إليه حيثما ورد، وان هذه الرسالة ككل، أو أي جزء منها لم يقدم من قبل لنيل أية درجة 

  .علمية أو بحث علمي أو بحثي لدى أية مؤسسة تعليمية أو بحثية أخرى
  

Declaration  
 

The work provided in this thesis, unless otherwise referenced, is the 

researcher's own work, and has not been submitted elsewhere for any other 

degree or qualification.           

 

 :Student's name   :اسم الطالب

 :Signature              :التوقيع

   :Date                                                                   :التاريخ

 



 vii

Values used 

Cost of one kWh = 0.73 NIS 

Cost of one liter of diesel #2 = 5.5 NIS 

NIS = $ 0.285 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



 viii

TABLE OF CONTENTS 
No. Content Page 

 LIST OF TABLES  XI 
 LIST OF FIGURES XIII 
 LIST OF APPENDECE XV 
 ABSTRACT  XVI 

CHAPTER ONE 
 INTRODUCTION

1.1  Scope   2 
1.2  Objectives of the Study 6 
1.3 Methodology 6
1.4 Thesis Outline 7 

CHAPTER TWO 
LITERATURE REVIEW

2.1 Introduction  11
2.2 The Need for Energy Management 12 
2.3 Control Systems and Computers 13 
2.3.1 Lighting controls 14
2.3.1.1 Occupant needs 16 
2.3.1.2 Building operation 17 
2.3.2 Control selection guidelines 18 
2.3.2.1 Control devices 19 
2.3.2.2 Occupancy sensors 20 
2.3.3 Daylighting controls   23 
2.3.4 Building controls integration 23 
2.3.4.1 Protocols 24
2.3.4.2 Integrated controls 25 
2.3.5 Energy savings 26 
2.4 Previous Studies 27

CHAPTER THREE 
DESCRIPTION OF THE AUDITED UNIVERSITY 

3.1 Introduction  32 
3.2 New Campus Description 33 
3.3 University Layout 33 
3.4 University Faculties 35 
3.4.1 Building description 35 
3.4.2 Major energy consuming equipment 35 
3.4.3 Electricity bills 37 
3.4.4 Weekly load curve  39 
3.4.5 Data collection  41 
3.4.5.1 Boilers 41 



 ix
No. Content Page 

3.4.5.2 HVAC distribution system 41 
3.4.5.3 Power factor improvement 42 
3.4.5.4 Lighting system 44 

CHAPTER FOUR 
 ENERGY AUDIT IN DIFFERENT FACULTIES OF THE 

UNIVERSITY
4.1 Introduction 46 
4.2 Heating System Saving Opportunities 47
4.3 Cooling System Saving Opportunities 52 
4.4 Lighting System Saving Opportunities  53 
4.5 Summary of the Saving Opportunities 59 

CHAPTER FIVE 
ENERGY CONSERVATION SOFTWARE DEVELOPMENT 

5.1 Introduction 63 
5.2 Software Components 64 
5.3 Software Language 66 
5.4 Energy Conservation Measures Flow Charts 66 
5.4.1 Lighting system (Lumen Method) 67 
5.4.2 Heating system 71 
5.4.3 Cooling system 73
5.4.4 Power factor improvement 75 
5.5 Software Verification 78 

CHAPTER SIX 
 SYSTEM DEVELOPMENT AND ANALYSIS 

6.1 Introduction 80 
6.2 Methodology 81 
6.2.1 Total energy savings potential (Baseline Data) 83
6.2.2 Time of day/week impacts on energy savings 85 
6.3 Scheduling Using EMS 86 
6.4 Implementation 88 
6.5 System Schematic Diagram and Its Main Components 89 
6.6 The Benefits of Networked Management 98 

CHAPTER SEVEN 
Light Management and Control Web-Based Software Development

7.1 Introduction 100 
7.2 Software Components 100 
7.3 Software Language 102 
7.4 Flow Charts 102 
7.5 Software Design 105
7.6 Principle of the Software 108 



 x
No. Content Page 

CHAPTER EIGHT 
TESTING AND RESULTS

8.1 Introduction 111 
8.2 PIC and Serial Interface Testing 111
8.3 Occupancy Sensor Testing 112 
8.3.1 Commissioning adjustments 112 
8.3.2 Sensitivity to motion 113 
8.3.3 Timeout adjustment 114 
8.3.4 Daylight distribution 114 
8.4 XPort Configuration 115 
8.5 Energy and Cost Savings Results from Our System 116 
8.6 Economical Evaluation of the System 118

CHAPTER NINE 
CONCLOUSIONS AND RECOMMENDATIONS 

9.1 Introduction 123 
9.2 Conclusions   123 
9.3 Recommendations 125 
 REFERENCES 126 
 APPENDICES  130 
 ب  الملخص 

 



 xi

LIST OF TABLES 
No. Table Page 

Table (1.1) Electrical energy consumption in 2007, for the 
West Bank universities 3 

Table (2.1) Selecting control devices based on expected 
lighting profile 20 

Table (2.2) 
Lighting control energy savings examples by 
application and control type 27 

Table (2.3) FY 96/97 savings & cost avoidance 28 

Table (3.1) The main faculties and its operating schedules in 
the university 33 

Table (3.2) Buildings description 35 
Table (3.3) Major energy consuming equipments 36 

Table (3.4) Electrical energy use and cost for the university 
faculties 37 

Table (3.5) Diesel consumption and cost for the university 
faculties 38 

Table (3.6) Boilers flue gas data measured at university 
faculties 41 

Table (3.7) Chillers nameplate 42 
Table (3.8) Chillers nameplate (other types) 42

Table (4.1) Excess air and efficiency for the faculty of 
engineering boilers 48 

Table (4.2) Excess air and efficiency for the faculty of science 
boilers 49 

Table (4.3) Excess air and efficiency for the faculty of fine 
arts boilers 49 

Table( 4.4) Excess air and efficiency for the faculty of 
pharmacy boilers 49 

Table (4.5) Boilers saving for the university faculties 51 
Table (4.6) HVAC saving for the university faculties 53 

Table (4.7) Annual energy saving achieved upon lamps 
removal specified in appendix 2 54 

Table (4.8) Annual cost saving achieved upon lamps removal 
specified in appendix 2 54 

Table (4.9) Annual energy savings results when installing 
reflectors 55 

Table (4.10) Annual cost saving achieved upon the installing 
reflectors in lamp fixtures in specified lamps 56 

Table (4.11) Annual energy savings by installing high-
efficiency electronic ballasts 57 



 xii
No. Table Page 

Table (4.12) Annual energy saving achieved upon the 
replacement of the specified lamps 57 

Table (4.13) Annual cost saving achieved upon installing 
electronic ballasts, and high efficiency lamps 57 

Table (4.14) Domino Effect energy savings (DEES) 59 
Table (4.15) Domino Effect cost savings (DEES) 59 
Table (4.16) Summary of the saving opportunities 60 
Table (5.1) Energy saving report 78

Table (6.1) 
Average percentage of time each area was 
occupied with lights on and off, and unoccupied 
with lights on and off 

84 

Table (6.2) Average percentage of energy used and waste for 
weekdays and weekends 85 

Table (8.1) 
Descriptive statistics for room area, connected 
lighting load, and power density for each 
application 

117 

Table (8.2) The effects of time delay on energy and cost 
savings for the total monitoring period 118 

Table (8.3) Capital investment cost of the system 119 
 



 xiii

LIST OF FIGURES 
No. Figure Page

Figure (1.1) Electrical energy consumption in 2007, for the 
West Bank universities 4 

Figure (1.2) Percentage of electrical energy consumption for 
An-Najah National University campuses 4 

Figure (2.1) Occupancy sensor control system 21 
Figure (2.2) Selecting occupancy sensor types 22 
Figure (2.3) Control network running LonMark and BACnet 25 
Figure (3.1) New campus layout 34

Figure (3.2) Electrical energy consumption for the university 
faculties 38 

Figure (3.3) Energy cost distribution (elect. vs. fuel)   39 
Figure (3.4) Weekly load curve for the faculty of Engineering 40 
Figure (3.5) Weekly load curve for the faculty of Science 40
Figure (3.6) Weekly load curve for the faculty of  Fine Arts 40 
Figure (3.7) Weekly load curve for the faculty of  Pharmacy 40 

Figure (3.8) Average power factor measured at the 
Engineering faculty 43 

Figure (3.9) Average power factor measured at the Science 
faculty 43 

Figure(3.10) Average power factor measured at the Fine Arts 
faculty 43 

Figure(3.11) Average power factor measured at the Pharmacy 
faculty 43 

Figure (4.1) Combustion efficiency chart for #6 fuel oil 50
Figure (4.2) Energy cost before and after improvements 61 
Figure (4.3) Percentage of energy saving by ECM 61 

Figure (5.1) Energy management program main data screen 
display 64 

Figure (5.2) Block diagram of the main data screen display 65 
Figure (5.3) Flow chart of Lumen Method function 69 
Figure (5.4) Flow chart of Lumen Method lighting distribution 70 
Figure (5.5) Flow chart of heating system function 72 
Figure (5.6) Flow chart of cooling system function 74 
Figure (5.7) Flow chart of power factor function 76 

Figure (6.1) Faculties distribution of the campus through the  
network 81 

Figure (6.2) Circuit diagram for EMS-based scheduling, large 
building 87 



 xiv

No. Figure Page

Figure (6.3) Circuit diagram for EMS-based scheduling, small 
building 87 

Figure (6.4) Wiring for combination occupancy and light 
sensors 88 

Figure (6.5) System block diagram 89 
Figure (6.6) Lighting control board schematic diagram 90 
Figure (6.7) Lighting control panel 91 
Figure (6.8) Pin diagram of PIC16F877 92 
Figure (6.9) RS232 Serial Port 92 
Figure (6.10) Pin diagram of ULN2003 93 
Figure (6.11) XPort Direct+ embedded device server 93 
Figure (6.12) XPort schematic carrier board 95 

Figure (6.13) a) DT-200 Dual Technology sensor. b) Coverage 
area 95 

Figure (6.14) Powerpack wiring diagram 96 
Figure (7.1) Block diagram of the main data screen display 101 
Figure (7.2) Flow chart of  the software main functions 103 
Figure (7.3) Flow chart of the lighting control procedures 104 
Figure (7.4) Software home page 106 
Figure (7.5) Software main display screen 106 
Figure (7.6) Software lighting control 107 
Figure (7.7) Room lighting monitor 107 
Figure (8.1) PIC16F877 and MAX232 testing board 111 
Figure (8.2) Lighting control kit 112 

Figure (8.3) 
Sensor placement: a) Classroom, b) Office, c) 
Laboratory, d) W.C 113 

Figure (8.4)  Classroom lighting distribution 115 
Figure (8.5)  Setup menu options 116 

 



 xv

LIST OF APPENDICES 
No.  Appendix Page 

Appendix 1 Illumination Standards 131 
Appendix 2 Existing Lighting System 133 
Appendix 3 Measured Weekly Load Curve 171 
Appendix 4 Sample of Measured Illumination 183 
Appendix 5 Sensors Drawing 190 
Appendix 6 XPort Direct Plus Data Sheet 192 
Appendix 7 DT-200 Occupancy Sensor Data Sheet 207 
Appendix 8 Software Sample Codes 214 

 



 xvi

Study and Design of an Automatic Control System for Electric Energy 
Management – Case Study An_Najah National University 

By 
Mohammad Khaleel Sa'di "Rashid Al_Mubayed" 

Supervisor 
Dr. Samer Mayaleh 

Abstract 

The energy situation in Palestine, the efficient use of energy, and the 

energy conservation in universities, is not in a better condition than most 

developing countries. In this thesis, we have established a start or a 

beginning step toward the efficient use of energy and energy conservation 

in universities through conducting several energy audits in some faculties 

of An-Najah National University which are considered as high energy 

consumers and allocate the potential for energy savings opportunities. 

In this thesis we have successfully proven that there is a huge potential 

for energy savings in the Palestinian universities sector (15-25%) by 

implementing some energy conservation measures (with no or low cost 

investment) on the most energy consumption equipment such as boilers, air 

conditioning, and lighting system. Where we have achieved a percentage of 

saving 24% in the lighting system (low cost), 7% in the cooling system (no 

cost), and 5% in the heating system (no cost).  

In addition, we succeeded in developing a new energy management 

software, which is used to estimate the total energy savings from each 

opportunity in our study, this program has several advantages through 

tabulating large quantities of energy use data, minimizing calculation 

errors, and providing reliable and neatly organized data for use in analysis 

and post-retrofit troubleshooting. 



 xvii

In this thesis also we have designed and implemented a new web-

based automatic light management and control system , in order to reduce 

the lighting consumption, by taking into account the classrooms schedule 

table, the occupancy sensors, and the daylight distribution, this system 

resulted in extra saving of 45%.    

 

 

 

 

 

 



 1

 

 

 

 

 

 

 

CHAPTER ONE 

INTRODUCTION 



 2

Chapter One 
Introduction 

1.1 Scope 

Electrical energy bill in the West Bank is very high, Palestine 

imports all its need of energy (electric, petroleum, and gas) from Israel 

electrical company (IEC), which make the price uncontrollable. The 

economic situation of the Palestinian people is very bad, the political and 

social situation is uncertain because of Israeli occupation. Due to the bad 

situation of all the factors given above, we  must take all the possible 

efforts to reduce electrical energy consumption in our country, because 

decreasing the consumption affects the economy and contributes to keeping 

our environment clean. 

Higher education sees much attention at various levels in all 

countries of the world, in addition to being a contributor to steady 

development to better meeting the needs of the individual and society. 

Undoubtedly, higher education has witnessed a remarkable 

development in Palestine during the last decade despite the difficulties 

faced by our Palestinian society, of which the Israeli occupation is the main 

cause.   

The higher education sector in Palestine consists of 46  institutions in 

the academic year 2006/2007, which provide  educational services for more 

than one hundred and thirty two thousand students [1], these institutions  

are distributed as follows: 



 3

- 13 universities which award Bachelors', Masters', and PhD degrees.  

- 12 university colleges, offering Bachelor's degree and 2 years Diploma. 

- 21 community colleges, offering Diploma level.  

The annual electrical energy consumption of the universities in the 

West Bank, is illustrated in table 1.1. 

Table (1.1): Electrical energy consumption in 2007, for the West Bank 
universities 

Universities Area 
(m2) 

Std 
# 

Consumption 
(kWh/Year) 

EUI 
(kWh/m2) 

An-Najah National University 106,825 16,000 3,215,432 30.1 
Palestine Polytechnic University 22,004 4,311 1,144,208 52.0 
Palestine Technical University 13,100 1,500 218,627 16.7 
Arab American University 31,263 3,051 1,258,222 40.2 
Al-Quds Open University 28,786 35,425 949,940 33.0
Bethlehem University 14,850 5,500 653,400 44.0 
Al-Quds University 36,886 7,600 1,426,746 38.7 
Hebron University 17,000 2599 637,520 37.5 
Birzeit University 66,000 7,172 2,350,000 35.6 
Total 336,714 83,158 11,854,095  

In our ongoing attempts to reduce the Palestinian electrical bill, we 

decided to study the energy consumption in a very important sector which 

is universities; in particular we took An-Najah National University, as a 

case study in this thesis to manage and reduce the energy consumption. 

Since it has four campuses, big buildings, huge and different loads, this will 

make the energy management more sensible and feasible. In fact, there was 

no any  previous or current experience in the field of energy management, 

which urged us to built our research. 

After reviewing the energy bills of An-Najah National University, it 

became obvious to us that it, like many commercial buildings and 



 4

establishments suffers from high consumption with respect to its connected 

loads, as shown in figure 1.1.  

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West Bank Universities

Electrical  Energy Consumption

kWh/year

 
Figure (1.1) : Electrical energy consumption in 2007, for the West Bank 
universities 

Also figure 1.2 shows the percentage of the total electrical energy 

consumption in 2007, distributed on the four campuses. The total electrical 

energy consumption was approximately  3,215,432 kWh. 

Percentage of electrical energy consumption for  
An-Najah National University Campuses

Khudouri Campus
4%

New Campus
42%

Hisham Hijawi 
Campus

8%

Old Camups
46%

Old Camups Khudouri Campus Hisham Hijawi Campus New Campus
 

 

Figure (1.2): Percentage of electrical energy consumption for An-Najah National 
University campuses 



 5

So, we suggest that the university must adopt new energy 

improvement projects, as developments in technology open up new 

opportunities. Such investment allows the university to maintain control of 

increases in utility costs.   

Our research focused specifically on lighting efficiency in campus 

classrooms.  We identified electrical energy waste as one of the current and 

most pressing obstacles to the fulfillment of our committed goal - 

sustainability.  In an attempt to solve this problem, we design an automatic 

light and management control system in a more efficient way to light 

classrooms by installing occupancy (motion) sensors in these rooms.  This 

will not only reduce the total energy consumption of the university, but it is 

projected to significantly reduce energy costs to the university over time.   

However, in all occupancy lighting control situations, the operation 

of the lighting by the occupants emerges as the dominant factor in 

determining potential lighting energy savings. Generally, lighting energy 

reductions from occupancy sensors will roughly follow room vacancy 

rates. Savings will be, of course, modified by occupant responsiveness in 

turning off lights in unoccupied areas. Such behavior is also impossible to 

evaluate within a laboratory environment. Thus, we intended to conduct a 

series of tests of the technology using a "before and after" measurement to 

determine actual potentials. 

Moreover, the utilization of this new developed light and 

management control system will keep An-Najah National University on the 

forefront of environmental technologies, a goal that is extremely important 

to primary educational institutions.   



 6

1.2 Objectives of the Study 

In this study we will concentrate on the following activities: 

Main objective: 

"Study and Design of an Automatic control System for Electric 

Energy Management - Case Study: An-Najah National University". 

Specific objectives: 

 Reduce the energy consumption of An-Najah National University and 

consequently energy bills by designing light and management control 

system. 

 Designing a well-structured software to supervise and monitor the 

lighting system remotely through the internet. 

 Make strategies to increase energy performance in universities sector.  

 Contribution in keeping our environment clean. 

1.3 Methodology 

The methodology is divided into three categories: 

• First category: Collecting data and energy audit. 

1. Establishing energy audit for the new campus of An-Najah National 

University. 

o Identifying the types and costs of energy use, to understand how 

that energy is being used and possibly wasted. 



 7

o Identifying and analyzing the alternatives, such as operation 

techniques and/or new equipments that could substantially reduce 

energy cost. 

o Performing an economic analysis on those alternatives and 

determine which ones are cost effective for our target. 

2. Utilizing the energy audits recommendations to determine the energy 

conservation opportunities. 

3. Making some suggestions on the best lighting fixtures which have 

been tested world wide and approved in energy conservation. 

• Second category: Designing a well-structured energy management 

software, to realize the energy conservation opportunities. 

• Third category: Designing a lighting panel for controlling lights 

remotely from any computer connected to intranet of the university, 

through a user graphical interface software that we have designed.        

1.4 Thesis Outline 

This thesis is divided into (9) chapters including this introductory 

chapter. 

In chapter one of this thesis, a brief  description of the energy 

situation in Palestine was presented, together with the objectives of the 

study and the methodology.  

In chapter two, literature review in the field of energy efficiency and 

conservation in universities was presented. The most energy consumption 



 8

systems were lighting system, boilers, and air conditioning. Also the 

control strategies for lighting system were discussed. 

Chapter three presents, a brief description for the audited university 

in this thesis , the annual electric and fuel energy consumption in addition 

to the energy bill analysis for each faculty were also discussed. 

Chapter four presents, the energy conservation measures 

implemented on each system from the technical and economical sides, the 

amount of energy savings in each energy conservation opportunity of each 

system with the required investment and the simple payback period were 

found and analyzed. 

The amount of energy saving that could be achieved through the 

no/low cost investment in university is 15 - 25%, as a result of decreasing 

the demand on energy, which enhances the national economy and leads to a 

huge reduction in the harmful environmental emissions such as CO2.  

Chapter five presents, the developed energy conservation software, 

illustrating the methods employed in energy conservation, and transforming 

them into mathematical models and flow charts, to find the total energy 

saving from each opportunity in our study. 

In chapter six the system development and analysis of the occupancy 

sensors were presented, descriptive statistics were calculated and cost 

analysis were performed for weekdays, weekends, and for the total 

monitoring period.  the percentage of saving in each area were measured 

for the occupancy sensor. Description of the system main components and 

operation, and the installation of the sensors were also presented in this 

chapter. 



 9

Chapter seven presented, the light management and control web- 

based software development, illustrating the main components, its 

language, flow charts, the designing procedures, and the principle work.  

Chapter eight presents, the system testing and results of the new 

developed automatic light and management system, the PIC and serial 

interface, the XPort Direct+ configuration and its kit, the placement and 

adjustment of the occupancy sensors, the daylight distribution, the impact 

of time delay on energy saving, and the economical evaluation of the 

designed system. 

In chapter nine the conclusion and recommendations for our thesis 

are presented. 

 

 

 

 

 

 



 10

 

 

 

 

 

 

 

CHAPTER TWO 

 LITERATURE REVIEW  

  



 11

Chapter Two 
Literature Review 

2.1 Introduction 

The energy management program is a systematic on-going strategy 

for controlling a building's energy consumption pattern. It is meant to 

reduce waste of energy and money to the minimum permitted by the 

climate where the building is located, its functions, occupancy schedules, 

and other factors. It establishes and maintains an efficient balance between 

a building's annual functional energy requirements and its annual actual 

energy consumption [2]. 

A whole systems viewpoint to energy management is required to 

ensure that many important activities will be examined and optimized. 

Presently, many businesses and industries are adopting a Total Quality 

Management (TQM) strategy for improving their operations. Any TQM 

approach should include an energy management component to reduce 

energy costs [2]. 

The primary objective of energy management is to maximize profits 

or minimize costs. Some desirable sub-objectives of energy management 

programs include: 

1. Improving energy efficiency and reducing energy use, thereby reducing 

costs. 

2. Cultivating good communications on energy matters. 

3. Developing and maintaining effective monitoring, reporting, and 

management strategies for wise energy usage. 



 12

4. Finding new and better ways to increase returns from energy 

investments through research and development. 

5. Developing interest in and dedication to the energy management 

program from all employees. 

6. Reducing the impacts of curtailments, brownouts, or any interruption in 

energy supplies. 

2.2 The Need for Energy Management 

Business, industry and government organizations have all been under 

tremendous economic and environmental pressure in the last few years. 

Being economically competitive in the global marketplace and meeting 

increasing environmental standards to reduce air and water pollution have 

been the major driving factor in the most of the recent operational cost and 

capital cost investment decisions for all organizations. Energy management 

has been an important tool to help organizations meet these critical 

objectives for their short term survival and long term success [2]. 

Energy management is necessary to Palestine because:  

1. Electric energy management is good for the Palestinian economy, as the 

balance of the payments becomes more favorable. 

2. Electric energy management make us less vulnerable to energy cutoffs 

or curtailments due to political unrest. 

3. Energy management is friendly to our environment as it eases some of 

the strain on our natural resources and may leave a better world for 

future generation. 



 13

2.3 Control Systems and Computers 

Energy use can be controlled in order to reduce costs and maximize 

profits. The controls can be as simple as manually turning off a switch, but 

often automated controls ranging from simple clocks to sophisticated 

computers are required. Our view is that the control should be as simple 

and reliable as possible.  

As one moves through this hierarchy of controls, each level of 

automation and complexity requires additional expenditure of capital. That 

is, the automated controls are more expensive, but they do more. Because 

choosing the proper type of control is often a difficult task, we will explore 

this decision process. 

Computers can also help the energy manager in the analysis of 

proposed and present energy systems. Some excellent large-scale computer 

simulation programs have been written that enable the energy analyst to try 

alternative scenarios of energy equipment and controls, such as BLAST 3.0 

and DOE-2.1D [3]. 

Every piece of energy-consuming equipment has some form of 

control system associated with it. Lights have on-off wall switches or panel 

switches, and some have timers and dimmer controls. Motors have on-off 

switches, and some have variable speed controls. Air conditioners have 

thermostats and fan switches. Large air conditioning systems have 

extensive controls consisting of several thermostats, valve and pump 

controls, motor speed controls, and possibly scheduling controls to 

optimize the operation of all of the components. Large heating systems 



 14

have modulating controls on the boilers and adjustable speed drives on 

pumps and variable air volume fans [3]. 

These controls are necessary for the basic safety of the equipment 

and the operators, as well as for the proper operation of the equipment and 

systems. Our interest is in the energy consumption and energy efficiency of 

this equipment and these systems, and the controls have a significant 

impact on both of these areas. Controls allow unneeded equipment to be 

turned off, and allow equipment and systems to be operated in a manner 

that reduces energy costs. This may include reductions in the electric power 

and energy requirements of equipment, as well as the power and energy 

requirements associated with other forms of energy such as oil, gas and 

purchased steam. 

2.3.1 Lighting controls 

Controls are an excellent way to reduce lighting energy while 

enhancing lighting quality. Occupancy sensors can eliminate wasted 

lighting in unoccupied spaces. Daylighting controls or advanced load 

management can reduce lighting demand when energy is most expensive. 

And manual dimmers, which allow occupants to adjust light levels to their 

preference, are becoming more affordable. Lighting controls have been 

shown to reduce lighting energy consumption by 50% in existing buildings 

and by at least 35% in new construction [4]. 

Lighting control systems are becoming digital. Digital lighting 

control systems have been developed as stand-alone systems or as part of 

building- wide automation systems. In a digital system, each segment of 



 15

the lighting system has its own device-specific address. That allows 

commands to be issued to specific portions of the building’s lighting 

system. 

Digital systems can perform the same lighting automation functions 

that independent, stand-alone systems perform, only better. They can 

schedule the operation of lights in any area within the facility. They can 

override the set schedule to match changes in operating schedules. They 

can monitor occupancy patterns in an area and adjust the operation of the 

lighting systems as required [5]. 

Digital systems also give facility executives the ability to control 

building lighting energy use from any location. In addition to providing a 

central control station for the building’s lighting systems, most digital 

systems are Internet compatible, allowing managers to monitor and control 

building lighting systems from any location that has Internet access.  

The ability to remotely control building lighting systems is 

particularly important for facilities facing high or uncertain electricity 

costs. One method of reducing those costs is to limit the facility’s demand 

for electricity during peak-use periods when rates are the highest. During 

these times, the lighting control system can turn off as many lighting 

system components as possible, or dim those systems that are equipped 

with dimming ballasts. With building lighting systems accounting for such 

a large portion of the electrical load, any reduction in lighting load during 

peak-rate periods will translate into savings, in both energy use and energy 

demand charges [5]. 



 16

Another benefit of digital lighting control systems is their ability to 

monitor the operation of the lighting systems. At the minimum, the digital 

system can receive feedback from each lighting system, confirming that it 

is on or off as commanded. The digital system can also monitor the 

number of hours that the lights are operated in a given area, as well as the 

number of times the lights are turned on, which are the most important 

factors in determining lamp life. Using this information, managers can 

schedule the group relamping of particular areas in the building before the 

number of lamp burnouts becomes excessive while ensuring that the lamps 

have been used for as long as possible [5]. 

Most facility executives can expect to achieve a 25 to 45 percent 

reduction in lighting energy use by implementing an automated lighting 

control program [6]. Most facilities will recover their investment in 

lighting automation in two years or less. The actual savings and payback 

that will be achieved depend on a number of factors, including how the 

facility uses lighting, the type of lighting systems installed, the hours that 

lighting is required, the lighting level needed, when the lights are required 

and the ability of the facility to make use of daylighting. 

2.3.1.1 Occupant needs 

Lighting controls are intended to fulfill two, potentially conflicting, 

objectives: (1) reduce lighting energy costs and (2) maintain or improve 

occupant satisfaction and comfort. Except for the most humble of lighting 

controls -the manual wall switch- lighting controls have historically had 

little to offer the building occupants. In the past, the occupants' lighting 

control needs were thought to be adequately served if they could turn their 



 17

lighting on or off when arriving or leaving work. In the modern work 

environment, this attitude is no longer sufficient. Changing visual needs is 

now the norm rather than the exception and controls can help to meet this 

variety of needs [7]. 

2.3.1.2 Building operation  

Cognizant building managers use the building lighting control 

system as a tool to control building operation costs. Since lighting energy 

is a substantial fraction of electric energy in many buildings, improved 

lighting controls can have a major positive impact on building energy 

consumption and peak demand.  

Savings from lighting controls may come from:  

•  Reduced electric lighting use. 

•  Reduced peak demand charges.  

•  Downsizing HVAC equipment (reduced first cost).  

•  Reduced HVAC operating costs.  

•  Lower maintenance costs.  

•  Productivity improvements.  

Lighting also affects other building loads, especially HVAC. The 

usual “rule of thumb” is that every watt saved in lighting saves an 

additional 1/4 watt in avoided HVAC energy [8]. 



 18

Most controls require commissioning to ensure that they operate 

according to design intent and are properly adapted to local conditions. 

With occupancy sensors, the time delay and sensitivity should be adjusted 

for each workspace. With automatic daylighting controls, the sensitivity to 

changes in daylight must be set for local room conditions. Initial 

commissioning may be done by a professional or by the facility 

management staff, but for best performance, occupants should be involved 

in fine-tuning control system operation according to their preference [9]. 

2.3.2  Control selection guidelines  

This section provides an overview of general control strategies and 

devices, as well as several useful tables to evaluate which strategies and 

devices are appropriate for various space types.  

There are several general strategies for using lighting controls to 

reduce operating costs and improve lighting system functionality: 

1. Occupancy Sensing: Turning lights on and off according to occupancy 

as detected with occupancy sensors. Appropriate for unpredictable 

occupancy patterns.  

2. Scheduling: Turning lights off according to program using 

programmable relays, timers and other time clock devices. Appropriate 

for predictable occupancy patterns.  

3. Tuning: Reducing power to electric lights in accordance with the user 

needs at the time. Tuning may be accomplished with dimming devices, 

but bi-level switching of overhead lighting should also be considered, 

especially when daylight is available.  



 19

4. Daylighting: Reducing power to electric lights or turning lights off in 

the presence of daylight from side lighting or top lighting. Daylighting 

controls typically employ a photo sensor, linked to a switching or 

dimming unit that varies electric light output in response to available 

daylight. Bi-level switching should be considered if dimming is not 

economically justified.  

5. Demand Limiting: Reducing electric lighting power during or in 

anticipation of power curtailment emergencies. During Emergency 

Alerts periods lighting loads can be shed either through voluntary 

curtailment or automatically by the facilities manager or utility service 

provider.  

6. Lumen Maintenance: Compensating for lamp lumen depreciation using 

a photocell. This strategy is generally deprecated today, as the lamp 

lumen depreciation from modern building lighting systems is too small 

to make lumen maintenance economically viable. 

7. Integrated system: Integrated lighting controls provide all necessary 

control adjustments and inputs at one location, where several control 

strategies can be applied at once. Although integrated controls are 

somewhat more expensive, the convenience of having one accessible 

location for performing all system commissioning can reduce setup and 

maintenance costs.  

2.3.2.1 Control devices  

The above control strategies define what the lighting controls do. 

The control devices are the physical equipment that is installed to 



 20

implement the desired control strategies in a particular application. The 

needs of both the lighting users and the facility manager must be 

considered when developing the lighting control program.   

Control selection should consider the building’s expected electric 

load profile as shown in table 2.1. For example, daylighting control may 

be very attractive for a building with peak loads during daylight hours, to 

reduce demand charges, but not interesting for a building with most of its 

electric use at night. For this application, adaptive compensation may be a 

more cost-effective strategy [10]. 

Table (2.1): Selecting control devices based on expected lighting load 
profile [10] 

Lighting use profile Selection Devices 

 

Typical work hours 
8 to 5 with 

limited weekend use 

Select controls 
that reduce peak 

demand 

Occupancy sensors and photo sensors 
for tenant spaces 

 
Time clock devices for public areas 

 

 
Extended hours 

 

Select controls 
that reduce 

unpredictable use 

 
Occupancy sensors 

Manual dimming/multilevel 
 

switching for adaptive compensation 

 

 
24-hour 

 

Select controls 
that reduce 

lighting day and 
night 

 
Photo sensors 

 
Manual dimming/multilevel switching 

for adaptive compensation 

 

Event-oriented 
operation 

Manual controls 
work best 

Manual dimming 
 

Multilevel switching 

2.3.2.2 Occupancy sensors  

Occupancy sensors are switching devices that respond to the 

presence and absence of people in the sensor’s field of view. The 

occupancy sensor system is usually made up of one or more components, 

which include a motion detector and a control unit consisting of a 



 21

transformer for power supply and a relay for load switching, sometimes 

called a power pack. The sensor sends a signal to the control unit that 

switches lights on and off. Most sensors include manual and/or automatic 

controls to adjust sensitivity to motion and to provide a time delay for 

shut-off of lights upon vacancy.   

The relationship between the power supply, relay, controller and 

motion detector is shown in figure 2.1.  

 
 

Figure (2.1): Occupancy sensor control system [7] 

Figure 2.2 provides a flow diagram to help decide whether 

Ultrasonic, PIR, or Dual-technology occupancy sensors are more 

appropriate for a particular application.    

 
 
 



 22

Figure (2.2): Selecting occupancy sensor types [7] 



 23

2.3.3  Daylighting controls   

Daylighting controls are devices that regulate the level of 

illumination provided by electric lights in response to the presence of 

daylight. They usually consist of a sensing device (photocell or photo 

sensor) that monitors either the total light level in the space or the 

available daylight level at the daylight aperture, and a control module that 

then switches or dims the electric lighting to maintain the needed 

illumination with minimal energy use.   

Since daylight may be present in large areas of commercial 

buildings for many hours of the day, automatic photo electrically 

controlled lighting systems can easily save 10–50% of the annual lighting 

energy [11], reducing both building operating costs and consumption of 

natural resources. Equally important, since daylight availability usually 

coincides with the utility’s peak demand profile, daylight controls can also 

reduce peak demand charges.  

2.3.4  Building controls integration  

There are many benefits to integrating the operation of the building 

lighting with other electrical loads in a building, especially if the overhead 

lighting is dimmable. Even in facilities without dimmable lighting 

systems, there are economies from combining switching control of lighting 

circuits with other building electric loads. Scheduling controls require 

commissioning the operation of many lighting zones in a complex, and this 

is best accomplished from one facility. As lighting averages 37% of a 

typical commercial building’s total electrical demand, reducing power to a 



 24

building’s dimmable lighting system by 25% (hardly noticeable in terms of 

light output) would reduce a building’s electric demand by 10% [7]. With 

dimmable lighting, it is even possible to adjust lighting power according to 

the hourly price of energy or other utility pricing signal.  

2.3.4.1 Protocols  

Integrating lighting control with other building equipment requires 

consideration of the protocols used to allow communications between 

control products from different equipment vendors. The development and 

acceptance of open-protocol communications standards for building 

equipment controls and the pervasiveness of the Internet are creating new 

opportunities for building owners and operators. BACnet (Building 

Automation Communications network) is an open-protocol standard 

(ASHRAE/ANSI standard) for intermediating BAS transactions, as is 

LonMark, which is based on LonWorks from the Echelon Corp [7]. Both 

protocols integrate control networks from different vendors with the 

Internet. Both protocols use the Internet (or TCP/IP) as the 

communications medium between control networks. Most modern 

buildings already have wiring to support their computer networks; this 

“road” serves as well for building equipment communications as it does 

for enterprise computing. Comparisons between LonMark and BACnet are 

beyond the scope of these guidelines, but any modern building using BAS 

controls will probably elect to use a hybrid system with some equipment 

running LonMark and other control networks running BACnet as shown in 

figure2.3. Gateways between LonMark and BACnet are straightforward.  



 25

 
Figure (2.3): Control network running LonMark and BACnet [7] 

2.3.4.2 Integrated controls  

With integrated controls, more than one lighting control strategy is 

implemented at a time with the same lighting hardware. For example, 

integrated controls for a classroom application might exploit daylighting, 

tuning, and scheduling all with the same hardware.   

By combining more than one strategy, more energy can potentially 

be saved and the greatest economic benefit extracted from the investment 

in controls. Combining several strategies increases the economic benefits 

if the marginal cost of adding additional strategies onto one base strategy 

is small. While integrated controls offer the potential of greater energy 

savings and more highly responsive lighting systems, they also run the 

risks inherent in any complex system: more complexity in design and more 

difficulty in diagnosing failure. These trade-offs should be carefully 

considered in the design of a system [7].   



 26

2.3.5 Energy savings  

 Lighting controls reduce building operation costs. Properly operated 

lighting controls reduce lighting energy when lighting is unnecessary and 

reduce lighting demand when and where possible. 

Occupancy sensors reduce the time of lighting operation. Time 

switches and programmable relay systems also reduce hours. Dimming 

controls, such as daylighting, reduce or eliminate lighting power 

throughout the day even in occupied areas. Reducing energy use during 

peak periods may also reduce lighting demand and related peak demand 

charges.   

Since every building is different, it is difficult to know how much 

energy lighting controls are likely to save in any given application. In large 

part, the energy savings from controls depend on how the building lighting 

was operated before the controls were installed. If building occupants are 

conscientious with lighting, then energy savings would be modest. 

However, many buildings enclose spaces where automatic controls can 

significantly reduce wasted lighting energy by eliminating lighting during 

unoccupied times or reducing electric light levels where adequate daylight 

is available [7]. 

Table 2.2 presents estimates of the maximum yearly energy savings 

that would be expected per controlled circuit according to control type, 

space type and typical hours of operation. The energy savings values listed 

are the maximum expected values, not the average, and assume that the 

control devices are properly specified, installed, and commissioned.  



 27
Table (2.2): Lighting control energy savings examples by application 
and control type. [7]  

Space type Controls type Maximum expected 
yearly energy savings 

Private 
Office 

Occupancy sensor 45% 
Side lighting w/photo sensor 35% 
Manual dimming or multilevel switching 30% 

Laboratory 
Side lighting w/photo sensor 40% 
Occupancy sensor 35% 

Classroom 
Multilevel switching 15% 
Side lighting w/photo sensor 40% 
Occupancy sensor 25% 

2.4 Previous Studies 

Energy management is becoming a major concern on university 

campuses. The university’s facilities are an eclectic mix of building styles 

and construction, including research facilities, libraries, offices, 

auditoriums, dormitories, classrooms, dining halls, a central steam-heating 

plant, individual building chillers for air conditioning, thousands of lighting 

fixtures and exit lights.  

The Duke University Board of trustees had been approved  of  $ 3.5 

million loan , in September 1996. After 8 years, definitely in June 2004, the 

energy management program has saved over $4.7 billion in directly 

metered utilities [12]. 

Initially the university focused on projects that were relatively easy 

to implement and that produced immediate savings. The initial projects fell 

into the general categories of steam trap maintenance, lighting 

improvements, and HVAC repair and replacement. The sample of saving in 

the period of FY 96/97 are illustrated in the next table: 



 28
Table (2.3): FY 96/97 savings & cost avoidance [12] 

Efficiency 
measure Detail 

First 
Cost 
($) 

Estimated 
annual 
saving 

Simple 
payback 
(years) 

Steam Traps Trap maintenance pilot 
program. 12,472 $10,393 1.2 

Compact 
Fluorescent Lamps 

Energy efficient replacement 
for incandescent lamps. 
Consume less energy and 
have longer life. 

83,622 $25,340 3.3 

LED Exit Signs 
Consume much less energy 
than incandescent signs and 
last many times longer. 

58,464 $12,180 4.8 

Motion Sensors 
Save energy by automatically 
turning off lights during 
unoccupied periods. 

2,565 $1,166 2.2 

HVAC Controls 
Replacement of pneumatic 
controls by DDC enabled 
more efficient operation of 
buildings. 

59,400 $11,000 5.4 
 

University of New Brunswick has two campuses, one in Fredericton 

and the other in Saint John. The university has been investing in energy 

conservation measures for three decades. These investments have enabled 

the university to control the rate at which its utility costs have increased, 

and students have profited by an improved learning environment. 

During the energy crisis of the 1970s, the university installed an 

automated energy management system that utilized Honeywell Delta 1000 

panels and was monitored by a central computer located in the Services 

Building. The system introduced, for the first time, occupancy scheduling 

and monitoring of heating, ventilation and air-conditioning systems. 

In 1991 the front end of the Automated Energy Management System 

was upgraded to a Honeywell Graphic Central System. The Graphic 

Central System was accessible from one work station utilizing a Dell 425E 

computer. The upgraded system was user friendly and it dramatically 

increased the capacity of the automation system. Occupancy scheduling 



 29

and monitoring of 50 heating, ventilation and air-conditioning systems in 

11 facilities was provided by the system [13]. 

In 1996, the university's Board of Governors approved an energy 

management program for the Fredericton campus. The program calls for an 

investment in energy conservation projects of up to $1,900,000. Projected 

annual cost avoidance of all projects was $436,000, resulting in a simple 

payback of 4.36 years [14]. 

Elizabethtown College in Pennsylvania, has recently started a ‘Green 

Lights Program’ in which all regular light switches in common areas (i.e. 

social rooms, laundry facilities, and bathrooms) will be replaced with 

occupancy sensors. Green Mountain College in Poultney, Virginia has 

begun to use the EPA’s Energy Star™ program to replace inefficient light 

fixtures and switches in order to cut energy costs while improving building 

conditions and helping the environment [15].  

Large universities, on the other hand, have engaged in much more 

extensive audits and programs for obvious reasons.  Princeton University, 

for example, has the most thorough online environmental audit regarding 

energy use. Princeton has installed motion and daylight sensors in 

classrooms, auditoriums, and hallways.  According to their research, these 

sensors result in an approximate 50% reduction in classroom lighting and a 

20-25% reduction in hallway lighting demands [16].  Princeton’s 

Environmental Audit Team has made further recommendations that motion 

and daylight sensors be installed in dormitory bathrooms to reduce 

electrical waste because lights in dormitory bathrooms are rarely, if ever, 

switched off. 



 30

Brown University is also worth mentioning here because a project 

team recently researched lighting efficiency at Brown University as part of 

an environmental geology course. The goal of the lighting efficiency 

project at Brown was to determine whether or not timers and/or motion 

sensors should be installed in dormitory and office hallways to reduce 

energy consumption and expenditures. Their findings, however, showed 

that sensors may not be the most energy efficient method of reducing 

lightening in hallways at night.  Dimming hallway lights seems to be a 

much better option, according to the students who conducted this audit 

[16]. In addition, they recommend that installing motion sensors in on-

campus bathrooms would not be a feasible option for Brown University.  
 
 
 
 



 31

 

 

 

 

 

 

 

CHAPTER THREE 

 DESCRIPTION OF THE AUDITED 
UNIVERSITY  

  



 32

Chapter Three 
Description of the Audited University 

3.1 Introduction 

An-Najah National University is recognized as Palestine's leader in 

higher education.  In almost 90 years of teaching, the university has been 

playing a leading part in the development of modern higher education in 

Palestine. The university is one of the pioneering and well-established 

universities in Palestine.  Students from different parts of the country attend 

the university in pursuit of learning, knowledge and personal development.  

The university has four campuses distributed between the cities of 

Nablus and Tulkarm.  There are three campuses in Nablus: the Old 

Campus, the New Juneid Campus, and Hisham Hijawi College of 

Technology Campus.  The fourth Campus is Khudouri which is located in 

the city of Tulkarm. 

An energy conservation study was performed for An-Najah National 

University in Nablus. The study objective was to obtain an overview of 

existing building energy consuming systems related to the lighting, Heating 

Ventilating and Air Conditioning (HVAC), and building control. In order 

to determine the energy consumed by this buildings, daytime walk-through 

were performed, building occupants were questioned as to equipment and 

building usage schedules. Most building characteristics and systems were 

also discussed. 



 33

3.2 New Campus Description 

The new campus of An-Najah National University is constituted by 

four different poles (buildings) located at 121,000m2 land in the west 

region of Nablus city, named building of Fine Arts which consists of: 

School of Arts, Faculty of Graduate Studies, College of Law and Theater 

building, building of Science and IT which consists of: Faculty of Science, 

Faculty of Optometry and Faculty of IT, Pharmacy & Medicine building 

and building of Engineering College. The description of the main faculties  

and its operating schedules could be seen in table 3.1. 

Table (3.1): The main faculties and its operating schedules in the 
university 

Faculty Area (m2) 
Working hours / day 

From To 
Engineering  12.795 8 AM 5 PM 
Pharmacy & Medicine  7.700 8 AM 5 PM 
Science, IT and Optometry 19,250 8 AM 5 PM 
Fine Arts, Graduate Studies and Law 12.185 8 AM 5 PM 

  

3.3 University Layout 

The general layout of the university and the location of the main 

faculties is shown in figure 3.1. 

 

 
 
 
 
 
 
 
 
 



 34
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure (3.1): New campus layout 

ÇáãÓ
ÑÍ



 35
3.4 University Faculties 

3.4.1 Building description 

Table 3.2 shows the general description of the buildings, which   

may give some of the no cost opportunities to reduce energy consumption. 
 

Table (3.2): Buildings description 
Faculty of Engineering 

Gross area (m2) X Ceiling height (m) = Volume (m3) 
12,795 X 3 = 38385 

Conditioned floor area (if different than gross floor area) (m2) 1270 m2 
Total southern exterior glass area (m2) 134 m2 

Single panes (m2) 134 m2 Double panes (m2) 0.0 
Other general building descriptions 

Faculties of Science, IT and Optometry
Gross area (m2) X Ceiling height (m) = Volume (m3) 

19,250 X 3 = 57750 
Conditioned floor area (if different than gross floor area) (m2) 763 m2 

Total southern exterior glass area (m2) 222 m2 
Single panes (m2) 222 m2 Double panes (m2) 0.0 

Other general building descriptions 
Faculties of Fine Arts, Graduate Studies and Law

Gross area (m2) X Ceiling height (m) = Volume (m3) 
12,185 X 3 = 36555 

Conditioned floor area (if different than gross floor area) (m2) 2,185 m2 
Total southern exterior glass area (m2) 84 m2 

Single panes (m2) 84 m2 Double panes (m2) 0.0 
Other general building descriptions 

Faculties of Pharmacy and Medicine  
Gross area (m2) X Ceiling height (m) = Volume (m3) 

7,700 X 3 = 23,100
Conditioned floor area (if different than gross floor area) (m2) 298 m2 

Total southern exterior glass area (m2) 50 m2 
Single panes (m2) 50 m2 Double panes (m2) 0.0 

Other general building descriptions 
• Not all the faculties southern windows have curtains (shutters). 

3.4.2 Major energy consuming equipment 

Table 3.3 lists the major energy consuming systems and equipments in 

the university faculties. 



 36

Table (3.3): Major energy consuming equipments 

Equipment / System 
Faculty of Engineering Faculties of Science, IT 

and Optometry 
Faculties of Fine Arts, 

Graduate Studies and Law 
Faculties of Pharmacy 

and Medicine 
Number 
of units 

Nameplate 
rating per unit 

Number 
of units 

Nameplate 
rating per unit 

Number 
of units 

Nameplate rating 
per unit 

Number 
of units 

Nameplate 
rating per unit 

A. Hot water 
Space Heating Diesel 

Boilers 3 415-1364 kW 3 420 kW 2 990 kW 2 590 kW 

Electrical Boilers 15 3 kW 18 3 kW 6 3 kW - - 

B. Lighting 
Fluorescent Lamps 1,711 18-36 W 1,943 18-36 W 1,141 18-36 W 746 18-36 W 
Emergency Lamps 88 16 W 72 8 W 44 8 W 40 8 W 

C. Air Conditioning 
Chillers 1 11 kW 2 7.5 kW 3 187 kW 2 11,27 kW 

Split Units 36 2   kW 35 3.5 kW 3 3.5 kW 8 3.5 kW 

D. Hot water Pumps 
 14 1.1-3 kW 9 4-7.5 kW 24 0.75-11 kW 10 0.2-0.6 kW 

E. Compressors 
 1 4 kW 1 4 kW - - 1  4 kW 

F. Refrigerators 
 13 300 W 18 300 W 8 300 W 12 300 kW 

G. Elevators 
 2 11 kW 4 8 kW 2 11 kW 3 75 kW 

 



 37

3.4.3 Electricity bills 

The university receives its electric utility service from Nablus Municipality. Table 3.4 shows how the electrical 

energy consumption is varied with months, and the energy utilization index (EUI); dividing the  kWh by the faculties 

areas. 

Table (3.4): Electrical energy use and cost for the university faculties 

Month 
Faculty of Engineering Faculties of Science, and IT Faculty of Fine Arts Faculty of Pharmacy 

Consump. 
(kWh) 

Cost 
(NIS) 

EUI 
(kWh/m2) 

Consump. 
(kWh) 

Cost 
(NIS) 

EUI 
(kWh/m2) 

Consump. 
(kWh) 

Cost 
(NIS) 

EUI 
(kWh/m2) 

Consump. 
(kWh) 

Cost 
(NIS) 

EUI 
(kWh/m2) 

January 14500 9669 1.13 42500 28345 2.2 24000 16006 1.96 6720 4480 0.87 
February 20500 13671 1.60 46000 30680 2.38 29000 19341 2.38 9120 6081 1.18 
March 29000 20298 2.26 57000 39898 2.96 39500 27648 3.24 12480 8734 1.62 
April 26000 18198 2.03 55500 38848 2.88 30500 21348 2.5 11520 8062 1.49 
May 22000 16055 1.72 45000 32845 2.33 25500 18610 2.09 8400 6127 1.09 
June 20500 14960 1.60 45000 32845 2.33 40500 29560 3.32 8880 6477 1.15 
July 25000 18245 1.95 59000 43065 3.06 32000 23355 2.62 9120 6652 1.18 
August 21000 15325 1.64 47500 34670 2.46 26500 19340 2.17 9840 7178 1.27 
September 26000 18975 2.03 46500 33940 2.41 29500 21530 2.42 8640 6302 1.12 
October 21000 15325 1.64 58500 42700 3.03 27000 19705 2.21 11760 8580 1.52 
November 24500 17880 1.91 58500 42700 3.03 29000 21165 2.38 10800 7879 1.4 
December 21500 15690 1.68 41000 29925 2.13 27500 20070 2.25 9840 7183 1.3 
Total 271,500 194,291  602,000 430,461 360,500 257,678 117,120 83,735 

  



 38

Figure 3.2 shows the  electrical energy consumption in kWh 

variations with respect to time in months, for the university faculties. 

Ja
nu

ar
y

Fe
br

ua
ry

M
ar

ch
Ap

ril
M

ay
Ju

ne
Ju

ly
Au

gu
st

Se
pt

em
pe

r

O
ct

ob
er

N
ov

em
be

r

D
ec

em
be

r

Science0

10000

20000

30000

40000

50000

60000

Months

KW
h/

ye
ar

Electrical Energy Consumption

Science Fine Arts Engineering Pharmacy
 

Figure (3.2): Electrical energy consumption for the university faculties 

Then another type of energy which is consumed by the faculties, is 

the diesel burned in boilers to produce hot water for space heating in 

winter, table 3.5 shows the  diesel consumption around the months. 

Table (3.5): Diesel consumption and cost for the university faculties 
 Faculty of 

Engineering 
Faculty of 

Science 
Faculty of 
Fine Arts 

Faculty of 
Pharmacy 

Fuel type Diesel Diesel Diesel Diesel 
Total cost  
(winter season) 198,000 NIS 247,500 NIS 222,750 NIS 198,000 NIS 

Number of  
consumed liters 36,000 liters 45,000 liters 40,500 liters 36,000 liters 

Figure 3.3 Illustrates the percentage of energy cost distribution for 

electricity and fuel as a source of energy, for the university faculties. 

 

kW
h/

m
on

th
  



 39

 
Figure (3.3): Energy cost distribution (elect. vs. fuel)   

3.4.4 Weekly load curve 

The relationship of power supplied to the time of occurrence, 

illustrates the varying magnitude of the load during one week called weekly 

load curve. The weekly load curve is good tool for load management to 

achieve many benefits: 

1. Demonstrates load distribution in a facility during one week. 

2. Facility management can redistribute load to suit transformers and 

cables capacities. 

3. Facility management can redistribute load to avoid maximum demand 

penalty, which is charged for monthly maximum load occurs during 

system peak load period. 

The weekly load curves for the university faculties were measured 

by using the Energy Analyzer apparatus, as shown in the next figures 3.4, 

3.5, 3.6, and 3.7, referred to appendix 3. 

 

56%

44%

70%

30%

60%

40%

36%

64%

0%
20%
40%
60%
80%

100%

Engineering Science Fine Arts Pharmacy

Energy Cost Distribution (Elect. Vs. Fuel) 

Diesel
Electricity



 40

Faculty of Engineering

0
20000
40000
60000
80000

100000
120000
140000
160000
180000

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3:

08
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P
M

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M

Time (One Week)

W
,V

A
,V

A
R

St/Avg (VA) Pt/Avg (W) Qt/ Avg (VAR)  
Figure (3.4): Weekly load curve for the faculty of Engineering 

Faculties of Science, IT and Optometry

0

50000

100000

150000

200000

250000

300000

  1
0:

45
:0

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AM

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PM

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AM

Time (One Week)

W
,V

A
,V

A
R

St/ Avg (VA) Pt/ Avg (W) Qt / Avg (VAR)  
 Figure (3.5): Weekly load curve for the faculty of Science 

Faculties of Fine Arts, Graduate Studies and Law

0
20000
40000
60000
80000

100000
120000
140000

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0:

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AM

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PM

Time (One Week)

W
,V

A
,V

A
R

St/ Avg (VA) Pt/ Avg (W) Qt / Avg (VAR)  
Figure (3.6): Weekly load curve for the faculty of  Fine Arts 

Faculties of Pharmacy and Medicine

0
10000
20000
30000
40000
50000
60000
70000
80000

  1
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Time (One Week)

W
,V

A
,V

A
R

St/ Avg (VA) Pt/ Avg (W) Qt / Avg (VAR)  
Figure (3.7): Weekly load curve for the faculty of Pharmacy 



 41

3.4.5 Data collection 

3.4.5.1 Boilers 

There are ten boilers in the university, with different capacities, used 

for space heating in winter season, three of them is out of service. In order 

to determine the efficiency of these boilers we used the apparatus called 

Combustion Analyzer, and the measured data from the exhausted flue gas 

in the stack is illustrated in table 3.6. 

Table (3.6): Boilers flue gas data measured at university faculties 
 Faculty of 

Engineering 
Faculties of Science, 
IT and Optometry 

Faculty 
of Fine 

Arts 

Faculty of 
Pharmacy 

Boiler 
1 

Boiler 
2 

Boiler 
1 

Boiler 
2 

Boiler 
3 Boiler Boiler 

Temperature 
(oF) 413 304 260 252 224 386 264 

O2% 6.9 4.4 4 9.1 7.4 10.9 6.2 
CO2% 10 12.3 8.2 7.7 9.8 6.5 11 
CO% 9 2 6 2 52 8 4 
Excess air % 45 24 21 72 49 98 39 
Losses% 15.8 4.6 10.6 12.2 10.5 18.8 11.5 
NOx (ppm) 60 85 99 60 68 40 65 
SOx (ppm) 0 0 0 0 0 0 0 
Efficiency % 84.2 88.4 89.4 87.8 89.5 81.2 88.5 

3.4.5.2 HVAC distribution system 

The university faculties uses an electrical chillers for space cooling 

in some areas, these chillers consists of an indoor unit and an outdoor unit, 

the outdoor unit contains a compressor, condenser, fans, and motors; the 

indoor unit consists of an evaporator and a flow control device, the chillers 

specifications are illustrated in tables 3.7, and 3.8.  

 



 42
Table (3.7) Chillers nameplate 

Faculty of Engineering 

Compressor Motor 
Qty Volt Hz Ph LRA.EA Amp.EA 

4 380 50 3 130 29 

Condition Fan Motor 
Qty Volt Hz Ph kW.Ea FLA.EA 

2 380 50 3 11 3 
Coil Test Pressure 450 Psig
Refrigerant R-22 

Faculties of Science, IT and Optometry 

Compressor Motor 
Qty Volt Hz Ph LRA.EA Amp.EA 

1 380 50 3 145 32 

Condition Fan Motor 
Qty Volt Hz Ph kW.Ea FLA.EA 

1 380 50 3 75 2      3 
Coil Test Pressure 450 Psig 
Refrigerant R-22 

Faculties of Pharmacy and Medicine 

Compressor Motor 
Qty Volt Hz Ph LRA.EA Amp.EA 

3 380 50 3 145 32 

Condition Fan Motor 
Qty Volt Hz Ph kW.Ea FLA.EA 

2 380 50 3 11 3 
Coil Test Pressure 450 Psig 
Refrigerant R-22 

 

Table (3.8) Chillers nameplate (other types) 

Chiller specifications Faculties of Pharmacy 
and Medicine 

Faculties of Fine Arts, 
Graduate Studies and Law 

Model HAE 251 PH 100 
V / Ph / Hz 400 / 3 / 50 400 / 3 / 50 
Max Absorption 44 322 
Power 27 kW 187 kW 
Refrigerant R-22 R-22 
Refrigerant Pressure 26 BAR 28 BAR 
Water Pressure 6 Bar 10 Bar 
Water Temperature 65 ºC 90 ºC 

3.4.5.3 Power factor improvement 

The average power factor measured by Energy Analyzer for one 

week was 0.96, for all faculties of the university. Thus, there is no required 

action for power factor improvement. Figure 3.8, 3.9, 3.10, and 3.11 

illustrates the existed average power factor for each faculty, referred to 

appendix 3 



 43

Power Factor Analysis

0
0.2
0.4
0.6
0.8

1
1.2

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3:

08
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PM

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M

Time (One Week)

P.
F

Pft+ Avg ()

Power Factor Analysis

0.86
0.88
0.9

0.92
0.94
0.96
0.98

  1
0:
45

:0
0 
AM

  0
3:
45

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PM

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45

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45

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PM

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45

:0
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AM

Time (One Week)

P.
F

Pfti+ Avg ()

Power Factor Analysis

0.84
0.86
0.88

0.9
0.92
0.94
0.96
0.98

1

  1
0:
09

:0
0 
AM

  0
6:
09

:0
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PM

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2:
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AM

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09

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09

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09

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09

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09

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:0
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09

:0
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Time (One Week)

P.
F

Pfti+ Avg ()

Power Factor Analysis

0.88

0.9
0.92

0.94
0.96

0.98
1

1.02

  1
1:
26

:0
0 
AM

  0
3:
06

:0
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PM

  1
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Time (One Week)

P.
F

Pfti+ Avg ()

 

 

 

 

[ 

 

Figure (3.8): Average power factor measured at the Engineering faculty 

 

 
 
 

 

 

 

Figure (3.9): Average power factor measured at the Science faculty 

 

 

 

 

 

 

Figure (3.10): Average power factor measured at the Fine Arts faculty 

 
 
 
 
 
 
 

 
 
 
Figure (3.11): Average power factor measured at the Pharmacy faculty 



 44

3.4.5.4 Lighting system 

A lighting system is an integral part of a building’s architectural 

design, and interacts with the shape of each room, its furnishings, and the 

level of natural light. There is great potential for saving electricity, 

reducing the emission of greenhouse gases associated with electricity 

production, and reducing consumer energy costs through the use of more 

efficient lighting technologies as well as advanced lighting design 

practices.  

Lighting averages 45% of the university building's total electrical 

demand. Lighting at the university according to the measurements taken by 

the Extech Data logging light meter, and comparing them with the 

standards (appendix 1) are very excessive in many areas. Appendix 2 

illustrates the existing lighting system, the luminance in each area in the 

university, and the recommended conditions for each area are also 

presented.  

 

 

 
 
 
 
 
 
 
 
 
 
 

 



 45

 

 

 

 

 

 

 

 

 

CHAPTER FOUR 

ENERGY AUDIT IN DIFFERENT 
FACULTIES OF THE UNIVERSITY 

 

  



 46

Chapter Four 

Energy Audit in Different Faculties of the University 

4.1 Introduction 

As mentioned in the previous chapter, four faculties were audited 

and analyzed in this study. The data were collected using measurement 

instrumentation and through effective estimation based on sound 

engineering  judgment.  

The measurements instruments used for measuring and collecting 

data were: 

• The energy analyzer equipment: It was installed on each electrical board 

of the facility for power measurements and energy consumed and for 

determination of the power factor. 

• Combustion analyzer equipment: It was used on the boiler's chimney for 

determination of the combustion efficiency, excess air percentage, flue 

gas temperature, O2 and CO2. 

• Thermometer: For temperatures measurement. 

• Lux meter: For lighting illumination measurements. 

Evaluation of alternative energy conservation measures based on the 

evaluation of energy use pattern of the buildings, several energy 

conservation measures (ECMs) were analyzed. Energy conservation 

measures were studied in different energy systems; lighting system, cooling 

system, and heating system. Also they were classified into the three 

categories of: 



 47

• No cost measures (low return): These are measures that can be 

implemented through operational and behavioral means without the 

need for system or building alterations and, therefore, do not require 

extra cost for their implementation.  

• Low cost measures (medium return): These are measures that can be 

implemented for building alterations or modifications and thus, extra 

but low cost is required for their implementation. 

• Major investment measures (high return): These measures require major 

financial investment for their implementation. They can be implemented 

through system renovation or retrofitting to the building or for new 

similar projects. 

4.2 Heating System Saving Opportunities 

A large fraction of a facility’s total energy usage begins in the boiler 

plant. The cost of boiler fuel is typically the largest energy cost of a 

facility, or the second largest. For this reason, a relatively small efficiency 

improvement in the boiler plant may produce greater overall savings than 

much larger efficiency improvements in individual end users of energy. 

Also, most boiler plants offer significant opportunities for improving 

efficiency [17]. 

The main efficiency measures is to reduce boiler excess air. Excess 

air is the extra air supplied to the burner beyond the air required for 

complete combustion. Excess air is supplied to the burner because a boiler 

firing without sufficient air or "fuel rich" is operating in a potentially 



 48

dangerous condition. Therefore, excess air is supplied to the burner to 

provide a safety factor above the actual air required for combustion. 

The more air is used to burn the fuel, the more heat is wasted in 

heating this air rather than in producing steam. Air slightly in excess of the 

ideal stochiometric fuel/air ratio is required for safety, and to reduce NOx 

emissions, but approximately 15% is adequate [17]. Poorly maintained 

boilers can have up to 140% excess air, but this is rare. Reducing this boiler 

back down to 15% even without continuous automatic monitoring would 

save 8% of total fuel use. A rule of thumb often used is that boiler 

efficiency can be increased by 1% for each 15% reduction in excess air or 

40°F (22°C) reduction in stack gas temperature [17]. 

The apparatus used to measure the boilers combustion efficiency was 

"Combustion Analyzer" as mentioned before, in tables 3.6. The boiler 

efficiency and excess air before and after controlling the excess air are 

illustrated in tables 4.1, 4.2, 4.3, and 4.4: 

Table (4.1): Excess air and efficiency for the faculty of Engineering 
boilers 

Engineering faculty Before controlling After controlling  
Boiler (1) 

Excess Air (%) 45 11 
Efficiency (%) 84.2 87.2 

Boiler (2) 
Excess Air (%) 24 10 
Efficiency (%) 88.4 89.2 

 
 
 
 
 
 
 



 49
Table (4.2): Excess air and efficiency for the faculty of Science boilers 

Science faculty Before controlling After controlling  
Boiler (1) 

Excess Air (%) 21 10 
Efficiency (%) 89.4 90.4 

Boiler (2) 
Excess Air (%) 72 12 
Efficiency (%) 87.8 90.1 

Boiler (3) 
Excess Air (%) 49 11 
Efficiency (%) 89.5 91 

 

Table (4.3): Excess air and efficiency for the faculty of Fine Arts 
boilers 

Fine Arts faculty Before controlling After controlling  
Boiler 

Excess Air (%) 98 13 
Efficiency (%) 81.2 87.5 

 
 

Table (4.4): Excess air and efficiency for the faculty of Pharmacy 
boilers 

Pharmacy faculty Before controlling After controlling  
Boiler 

Excess Air (%) 39 10 
Efficiency (%) 88.5 89.9 

Figure 4.4 support the previous tests, and shows the relation between 

the percent of  the flue gas oxygen, the percent of excess air and the 

combustion efficiency. 
 

 



 50

 
Figure (4.1):  Combustion efficiency chart for #6 fuel oil 

To compute the saving achieved by this efficiency improvement, the 

fuel consumption should be known, based on the faculties diesel bills the 

yearly consumption cost is known, then the next equation could be used to 

estimate the saving: 

Saving = k × [1- (η before /η after )]………………….4.1  

Where: 

k = annual fuel usage by boiler, liters/yr. 

η1 = combustion efficiency before improvement. 

η2 = combustion efficiency after improvement. 

So by using equation 4.1, and taking the engineering faculty as an 

example  to compute the saving we obtain that: 

Saving = k × [1- (η before /η after )]                               



 51

            = 36,000 × [1- (84.2 /87.2 )]                               

            = 36,000 × (0.0344) 

            = 1,238.4 (liters/year). 

Knowing that each liter of diesel costs 5.5 NIS of energy, and 

approximately 10.5 kWh, we can compute the saving in (NIS/year), 

(kWh/year) respectively. 

Saving in NIS/year = 1,238.4 Liter × 5.5 (NIS/Liter)  

                                  = 6,811.2 (NIS/year)  

By applying the previous equation on the other boiler in the 

engineering faculty we can achieve additional saving equal to 1,775.78 

NIS, so the total saving are: 

                                     8,586.98 (NIS/year) 

Applying the previous scenario, and by using equation 4.1, we can 

calculate the saving in the other faculties.  

Table (4.5) Boilers saving for the university faculties 

Faculty Saving (kWh/year) Saving (NIS/year)  
Engineering 16,393.3 8,586.98 
Pharmacy 5,886.6 3,083.45 
Fine Arts 30,618 16,038 
Science 25,076.8 13,135.46 
Total 77,974.7 40,843.89 

 



 52

4.3 Cooling System Saving Opportunities 

The space cooling system in the university works by electrical 

energy; it covers about half of the total volume. 

The energy consumption by this system could be estimated by taking 

the total load for each faculty multiply by the total hours operating in the 

summer season. 

Total load = 36 unit × 1.8 kW + 1 chiller × 10.5 kW = 75 kW 

In diagnostic phase it was noticed that the temperature of the chiller 

were set on 9oC and it's too low, in the other hand the temperature of the 

cooled space were about 21oC, this means that there is a large amount of air 

leakage in the building because of opened windows or doors. 

Saving could be achieved by increasing the temperature that the chiller 

is set on, percentage of saving is calculated as follows: 

Percentage saving = [(Tout - Texisting) – (Tout - Tsuggested)]/(Tout - Texisting)….4.2

Where: 

Tout: before cooling the space (30 oC) 

Texisting: the temperature in the room (21 oC)  

Tsuggested: suggested room temperature (24 oC) 

Percentage saving = [(30 – 21) – (30 – 24)] / (30 – 21) 

                         = 33% 



 53

Energy consumption saving = 0.33 × 75 kW × 600 h/year                                        

                                                         = 14,850 (kWh/year) 

Cost reduction = 0.73 × 14,850 = 10,840.5 (NIS/year) 

Table (4.6): HVAC saving for the university faculties 
Faculty Saving (kWh/year) Saving (NIS/year)  

Engineering 14,850 10,840.5 
Pharmacy 19,764 14,427.7 
Fine Arts 23,490 17,147.7 
Science 31,135 22,728.5 
Total 89,239 65,144.4 

This energy saving opportunity is very attractive because it could be 

done without any initial investment cost, and the SPBP is immediately. 

4.4 Lighting System Saving Opportunities 

By having an understanding of the lamps, ballasts, fixtures and 

control option available today as well as the techniques used to develop 

efficient lighting. Lighting can be produced that is energy efficient cost 

effective and yields a higher quality of light. Improvements in lighting 

efficiency can be obtained in the following areas: 

ECM # 1: Extra-lamps removal (no cost measure) 

According to illumination measurements shown in Appendix 2, it 

was found that values, which were measured at some areas, exceeds the 

standard illumination required for the certain areas or places as shown in 

Appendix 1. So removing extra lamps is recommended for the areas 

specified in Appendix 2. 



 54

In order to calculate the optimum number of fixtures and reducing the 

number of excessive lamps equation 4.3 was used: 

mu KK   n 
A  E  N
××Φ×

×
=  ………………….4.3 

 

Where: 

N: number of units, E: illumination lm/m² (lux), A: area in m², n: number of 

lamps in the unit, Φ: luminous flux in lumen, K u: reflectance factor , and Km: 

maintenance factor. 

Table 4.7 illustrates the annual energy saving achieved upon the 

removal of the lamps specified in Appendix 2. 

Table (4.7): Annual energy saving achieved upon lamps removal 
specified in appendix 2 

Lamp 
type 

# 
of lamps 

Saved 
demand kW 

Saved energy 
(kWh) 

Fluorescent 4677 110.939 157,418 

With reference to Appendix 2, it is expected to achieve an annual 

energy saving of approximately 157,418 KWh upon removal of the 

specified lamps. The corresponding savings in electricity bills are 

calculated as shown in table 4.8, knowing that lamp removal doesn’t incur 

any costs from the university:  

Table (4.8): Annual cost saving achieved upon lamps removal specified 
in appendix 2 

Energy 
saving 

Electric 
tariff 

Total saving in 
electricity bill Investment S.P.B.P 

157,418 
kWh/year 

0.73 
NIS/kWh 

114,915 
NIS/year 0 Immediate 



 55

ECM # 2: Installing reflectors in lamp fixture (medium cost measure) 

Reflectors are mirror-like devices that can be mounted inside 

existing fluorescent fixture to direct light out of the fixture more efficiently. 

These reflectors approximately double the light output of the lamp fixture. 

By installing reflectors in the fixtures, one lamp in every two lamp fixture 

can be disconnected [19]. 

Reducing the number of lamps will not appreciably decrease the 

light levels in the university. Ballast consumes energy whether the lamps 

are working or not, reducing the number of lamps by installing reflectors 

this will reduce the number of ballast used. 

Table 4.9 showing the energy savings results when installing 

reflectors. The following formula is used to calculate the energy used 

(kWh/year): 

Energy used = [wattage from lamps] × [wattage from ballasts] 

Energy used = (# of lamps × w/lamp × oper. hours/year)/1000 + 0.2 × 
                        (# of lamps × w/lamp × oper. hours/year)/1000....4.4 [18]

 

Table (4.9): Annual energy savings results when installing reflectors 

Existing system Recommended system 

Lamp 
type watt # of 

lamps 
# of 

ballast 
Oper 
time 

Energy 
used 

kWh/y 

# of 
lamps 

# of 
ballast 

Energy 
used 

kWh/y 

Energy 
savings 
kWh/y 

FL 36 2*1766 3532 1500 288,87 1*1766 1766 114437 114437 

From table 4.9, it is expected to achieve an annual energy saving of 

approximately 114,437 kWh upon installing reflectors in lamp fixtures in 

specified lamps. The corresponding savings are calculated as shown in 

table 4.10. 



 56
Table (4.10): Annual cost saving achieved upon the installing reflectors 
in lamp fixtures in specified lamps  

Energy 
saving 

Electric 
tariff 

Total saving in 
electricity bill

# of 
fixtures

Reflector 
cost Investment S.P.B.P 

114,437 
kWh/year 

0.73 
NIS/kWh 

83,539 
NIS/year 1766 100 

NIS 
176,600 

NIS 
2.1 

Years 

ECM # 3: Installing high-efficiency lamps and ballasts (medium cost 

measure) 

The efficiency and output of fluorescent lamps varies depending on 

both the lamps itself and ballast installed. New ballast has been developed 

that has superior qualities over conventional wound choke ballast's 

(magnetic ballast). 

Electronic ballast offer some advantages such as, 20-30% energy 

reduction compared with conventional ballast, 50% longer service life of 

lamps, net power factor of  95%-99%, reduction in weight, cool operation, 

eliminates the annoying problems of light flicker and noise and this lead to 

an improvement in the quality of lighting [18]. 

The high efficient lamps (HOT5), 24W offer some  advantages such 

as, longer life time  20,000 hours, 10-40% more light output than standard 

T8 lamps, and 2,700 out put lumen [18]. 

This opportunity recommends that if the university starts to phase 

out inefficient lighting lamps and ballast by replacing the lamps that bum 

out with high efficiency lamps, also replacing the magnetic ballasts that 

burn out with electronic ballasts. 

The power consumption by ballasts at the building can be reduced by 

8 watt per 2-lamp fixture. Each ballast serves one lamp (36w). And saves 



 57

12 watt by one lamp. Tables 4.11, 4.12 shows the annual energy savings 

results due to replacing the ballasts and lamps.  

Table (4.11): Annual energy savings by installing high-efficiency 
electronic ballasts 

Fixture 
type 

# of 
fixtures 

# of 
ballasts

Wattage 
reduction/ballast

Oper. 
hours/yr 

Energy 
saved 

(kWh/yr) 
Faculty of Engineering 
FL/36/2 906 453 4 1800 3,261.6 
Faculties of Science, IT and Optometry 
FL/36/2 1,436 718 4 1800 5,169.6 
Faculties of Fine Arts, Graduate Studies and Law
FL/36/2 786 393 4 1800 2,829.6 
Faculties of Pharmacy and Medicine 
FL/36/2 404 202 4 1800 1,454.4 

Total Energy Saved 12,715.2 

Table (4.12): Annual energy saving achieved upon the replacement of 
the specified lamps 

Replaced 
lamp type  

Replace 
with 

# of 
Lamps 

Saved 
demand 

kW 

Annual 
operation 

hours 

Saved 
energy 

(kWh/year) 

FL 36 W HOT5 
24 W 1,766 21.192 1800 38,145.6 

With reference to tables 4.11 and 4.112, it is expected to achieve an 

annual energy saving of 50,860.8 kWh upon installing high-efficiency 

electronic ballasts, and high efficiency lamps. The corresponding savings 

are calculated as shown in table 4.13. 

Table (4.13): Annual cost saving achieved upon installing electronic 
ballasts, and high efficiency lamps 

Energy 
saving 

Total saving 
in electricity 

bill 

Price difference 
(elec. Pallast -
mag. Ballast ) 

Price difference 
(24W lamp -36W 

lamp ) 
Investment S.P.B.P 

50,860.8 
kWh/y 

37,128.4 
NIS/year 

(80-10) = 70 
NIS 

(15-5) = 10 
NIS 

141,280  
NIS 

3.8 
years 



 58

ECM # 4: Domino Effect savings (no cost measure) 

In addition to the direct savings that results from the previous  

ECO's; an additional saving occurs through reduced air-conditioning 

demand; lower wattage means less heat, so the air conditioning units do 

less work to cool the conditioned areas. The air conditioning savings have 

been called the Domino Effect; it can be calculated using the Rundquist 

Method [18]. 

According to our local climate and the operating time in the building 

the air conditioning is used only in summer season about 14 weeks per 

year.  

year  theof 27%%100
year /  weeks52

 weeks14
=×  

In this opportunity the air conditioned areas is computer labs, 

conference rooms, and head of department rooms, the Domino Effect 

Energy Savings (DEES) can be calculated in each of the previous ECO's as 

follows: 

(DEES) = (Fraction of year in cooling season × 0.33× total energy saving 
                from the previous ECO's in the conditioned areas)…...4.5 [18]

Table 4.14 shows the Domino Effect Energy Savings (DEES), for 

the conditioned areas that mentioned before. 

 

 



 59
Table (4.14): Domino Effect energy savings (DEES) 

Area 
# ECO's 

Energy 
saved 

kWh/yr

Fraction 
of cooling 

season 

DEES 
kWh/yr 

Faculty of Engineering 
G0030 ECO#1 9,690 0.27 863.379
Faculties of Science, IT and Optometry 
G360 ECO#1 7580.2 0.27 699.453 

Faculties of Fine Arts, Graduate Studies and Law 
20 ECO#1 870.4 0.27 77.552 

Faculties of Pharmacy and Medicine 
G0030 ECO#1 3,450 0.27 207.395 

Total Energy Saved 1,847.78 

From table 4.14, it is expected to achieve an annual energy saving of 

approximately 1,847.78 kWh upon Domino Effect Energy Savings (DEES). 

The corresponding savings are calculated as shown in table 4.15. 

Table (4.15): Domino Effect cost savings (DECS) 
Energy 
saving 

Electricity 
tariff 

Total saving in 
electricity bill Investment S.P.B.P 

1,847.78 
kWh/year 

0.73 
NIS/kWh 

1,348.88 
NIS/year 0 Immediate 

4.5 Summary of the Saving Opportunities 

Table 4.16 illustrates the saving opportunities summary for 

An_Najah National University, that includes the annual saving in kWh, the 

annual cost saving, the annual Co2 reduction, and the simple payback 

period for each energy conservation measure. 

 



 60

Table (4.16): Summary of the saving opportunities  

 

 

Opportunity Description 
Energy 
saved 

(kWh/year) 

Cost 
reduction 
(NIS/year) 

Opportunity 
implementation 

cost (NIS) 

Equivalent 
kg of CO2 
reduction 

S.P.B.P 

Boiler combustion 
efficiency 

Increasing boiler combustion 
efficiency by controlling the 
amount of excess air. 

77,974.7 40,843.89 No cost 84,212.67 Immediately

Space cooling 
system 

Saving could be achieved by 
changing the temperature that 
the system is set on. 

89,239 65,144.4 No cost 96,378.12 Immediately

Lamps removal Saving could be achieved by 
removing unnecessary lamps. 157,418 114,915 No cost 170,011.44 Immediately

Lamp reflectors Saving could be achieved by 
installing reflectors for fixtures. 114,437 83,539 176,600 123,591.96 2.1 years 

High-Efficiency 
lamps and ballasts 

Saving could be achieved by 
replacing old lamps with high 
efficient lamps, and magnetic 
ballasts with electronic ballasts. 

50,860.8 37,128.4 141,280 54,929.66 3.8 years 

Domino Effect 
Saving could be achieved by 
reducing the air-conditioning 
demand. 

1,847.78 1,348.88 No cost 1,995.60 Immediately

Total 491,777.28 342,919.57 317,880 531,119.45  



 61

The energy cost before and after improvements which obtained from 

table 4.16 are illustrated in figure 4.2, also the percentage of energy saving 

for each energy conservation measures shown in figure 4.3. 

0

200000

400000

600000

800000

1000000

Co
st

 (N
IS

)

Heating System Lighting System Cooling System

Energy Cost Before and After Improvements

Energy Cost After Improvements Actual Energy Cost
 

Figure (4.2): Energy cost before and after improvements 

 

Percentage of Energy Cost Saving by ECM

12%

19%

34%

24%

11% 0%

Boiler Efficiency Saving Space Cooling Saving
Lamps Removal Saving Lamps Reflector Saving
High Efficiency Lamps and Ballasts Saving Domino Effect Saving

 
Figure (4.3): Percentage of energy cost saving by ECM 

 



 62

 
 

 

 

 

 

 

CHAPTER FIVE 

 ENERGY CONSERVATION 
SOFTWARE DEVELOPMENT  

 



 63

Chapter Five 
Energy Conservation Software Development 

5.1 Introduction  

In the previous chapter, we had illustrated the methods employed in 

energy conservation, transforming them into mathematical models, which 

used to find the total energy saving from each opportunity in our study, and 

crowning that in this chapter, by designing a software in which all energy 

conservation calculations are accomplished on universities or any other 

facilities, printing the outcome in specific tables, with each study per se, in 

addition to a list of final consequences that indicates all forms of energy 

saving in our study. 

Utilizing the computer softwares instead of manual calculations has 

numerous beneficial effects, including: 

- Tabulating large quantities of energy use data. 

- Minimizes calculation errors. 

- Provides reliable and neatly organized data for use in analysis and post-

retrofit troubleshooting. 

- Pro-rating the data so as to provide calendar-month consumption 

figures (as opposed to varying-length billing periods). 

- Showing recent trends in energy use accounting for savings achieved 

by an energy retrofit program, including documenting and adjusting for 

the effects of weather and other independent variables. 



 64

5.2 Software Components 

The energy conservation software in universities, includes a set of 

partial programs to certain study cases illustrated in chapter four. It 

includes lighting, air-conditioning, improving the power factor, raise the 

boilers efficiency and recover the expense of capital. The main data screen 

is shown in figure 5.1. 

 
Figure (5.1): Energy management program main data screen display 

The list design block diagram of the main data screen display is 

shown in figure 5.2. Since they are available in the user interface for 

choosing any process to be implemented. It is needless to say that it is not 

crucial to process all the cases in each study. On the contrary we could 

choose any case study independently according to subject matter.  



 65

  

Figure (5.2): Block diagram of the main data screen display 



 66

5.3 Software Language 

In designing and programming this software we use Microsoft Office 

Excel 2007, which is one of the strongest softwares, used to create and 

format spreadsheets, analyze and share information to make more informed 

decisions. With the Microsoft Office Fluent user interface, rich data 

visualization, and Pivot table views, professional-looking charts are easier 

to create and use.  

Microsoft Office Excel 2007, combined with Excel Services, a new 

technology provides significant improvements for sharing data with greater 

security. We can share sensitive information more broadly with enhanced 

security with other partners. By sharing a spreadsheet using Office Excel 

2007 and Excel Services, we can navigate, sort, filter, input parameters, 

and interact with Pivot table views directly on the web browser [20]. 

A valuable aspect of Excel is the ability to write code using the 

programming language Visual Basic for Applications (VBA). With this 

code any function or subroutine that can be set up in a Basic or like 

language can be run using input taken from the spreadsheet proper, and the 

results of the code are instantaneously written to the spreadsheet or 

displayed on charts [20]. 

5.4 Energy Conservation Measures Flow Charts 

We are going to transform the most important methods of energy 

conservation in universities which we illustrated in chapter four, into 

mathematical models to put its flow charts. so we can implement the case 

study on our facility and others in general.  



 67

We recall that the process of modeling on all issues that can be 

formulated in the form of mathematical calculations. There remains some 

issues that are on the suggestions and advice can be implemented purely 

administrative procedures. We note here that the method of modeling is to 

turn every issue into two parts, one containing various kinds of  

information available (nominal, measured, extracted from the tables, and  

virtual), and the second contains the accounts according to the model 

mathematical formulas for each issue. 

5.4.1 Lighting system (Lumen Method) 

This method is based upon utilization factor, which is used to 

determine and calculate the number of fixtures necessary to achieve an 

average luminance. It is also a quick method to get an overview of the 

necessary number of fixtures in the room to have a good opportunity to 

reduce number of fixtures. 

Lumen Method calculation input requirements: 

- Physical characteristics of the room, including length, width, and height. 

- Ceiling, wall, and floor reflectance's (% of light reflected by the room 

surface). 

- Work plane height (i.e. desk height or height above the floor at which 

the visual work is to be performed). 

- Distance from the work plane to the fixtures. 



 68

- Coefficient of utilization (Cu) of the fixtures: This value depends on the 

design of the fixtures and the characteristics of the space where the 

fixtures is located. 

- Maintenance factor (Km): May be either recoverable due to 

maintenance of lighting system and room surfaces, lamp depreciation, 

ballasts factors, and thermal application effect. The overall of 

maintenance factor range from 0.65-0.85 for ballasted lighting systems 

and from 0.75-0.95 for most incandescent systems.     

The flow chart of the lumen Method main function is shown in  

figure 5.3. 



 69

 
 

Figure (5.3): Flow chart of Lumen Method function 



 70
Also the Lighting Distribution is shown in figure 5.4. 

 

Figure (5.4): Flow chart of Lumen Method lighting distribution 



 71

5.4.2 Heating system 

This method is based mainly upon the boiler  efficiency and its fuel 

consumption. The measures used is controlling the excess air which is the 

most important tool for managing the energy efficiency and atmospheric 

emissions of a boiler system. 

Heating system calculation input requirements: 

- Physical characteristics of the building, including area, number of 

floors, floors area and height, and building envelop. 

- Exterior doors and windows, types and orientation. 

- Boilers annual fuel consumption, fuel type and price.  

- Boiler stack gases characteristics, temperature, percent of oxygen and 

excess air, combustion efficiency and losses. 

- Combustion efficiency after improvements (controlling excess air). 

The flow chart of the heating system main function in figure 5.5, 

illustrates all steps required for calculating the saving and the simple 

payback period. 

 

 



 72

 
 

Figure (5.5): Flow chart of heating system function 



 73

5.4.3 Cooling system 

This method is based upon the number of air conditions, chillers and 

their set point temperatures. The measures used is to controlling the set 

point temperature of the air condition and the chiller systems to suit the 

indoor climate, depending upon the ambient temperature, and the seasonal 

operation hours.  

Cooling system calculation input requirements: 

- Physical characteristics of the building, including area, number of 

floors, floors area and height, and building envelop. 

- Exterior doors and windows, types and orientation. 

- Number of Air conditions, chillers, and their rated power.  

- Indoor, ambient, and set point temperatures . 

- Seasonal operation hours . 

- Electric tariff rate. 

The flow chart of the cooling system main function in figure 5.6, 

illustrates all steps required for calculating the saving and the simple 

payback period. 

 



 74

 
 

Figure (5.6): Flow chart of cooling system function 



 75

5.4.4 Power factor improvement 

This method is based upon measuring power factor in the facility to 

make sure that is equal or more than 92%. Because low power factor is 

expensive and inefficient, and also reduces the electrical system’s 

distribution capacity by increasing current flow and causing voltage drops. 

Power factor improvement calculation input requir