2019-10 investigation and minimization of power loss and

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Power Systems Engineering Thesis

2019-10

Investigation and Minimization of Power

Loss and Voltage Profile Enhancement

Using Unified Power Flow Controller

(Case Study: North Western Region of

Ethiopia 230 Kv and 400 Kv

Transmission Systems)

Tsehay, Asresahegn

http://hdl.handle.net/123456789/10959

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BAHIR DAR UNIVERSITY

BAHIR DAR INSTITUTE OF TECHNOLOGY

SCHOOL OF RESEARCH AND POSTGRADUATE STUDIES

FACULTY OF ELECTRICAL AND COMPUTER ENGINEERING

INVESTIGATION AND MINIMIZATION OF POWER LOSS AND

VOLTAGE PROFILE ENHANCEMENT USING UNIFIED

POWER FLOW CONTROLLER (CASE STUDY: NORTH

WESTERN REGION OF ETHIOPIA 230 kV AND 400 kV

TRANSMISSION SYSTEM)

ASRESAHEGN TSEHAY YEMIDRALEM

Bahir Dar, Ethiopia

October, 2019

MSc Thesis By Asresahegn T. ii

INVESTIGATION AND MINIMIZATION OF POWER LOSS AND VOLTAGE

PROFILE ENHANCEMENT USING UNIFIED POWER FLOW CONTROLLER

(CASE STUDY: NORTH WESTERN REGION OF ETHIOPIA 230 kV AND 400

kV TRANSMISSION SYSTEM)


A thesis submitted to the school of Research and Graduate Studies of Bahir Dar Institute

of Technology in partial fulfillment of the requirements for the degree of Master of

Science in the Power Systems Engineering in the Faculty of Electrical and Computer

Engineering.

Advisor:

Dr.-Ing. Belachew Bantyirga

Bahir Dar, Ethiopia

October, 2019

MSc Thesis By Asresahegn T. iii

DECLARATION

I, the undersigned, declare that the work, which is being presented in the thesis, entitled

on “Investigation and Minimization of Power Loss and Voltage Profile Enhancement

Using Unified Power Flow Controller (Case Study: North Western Region of Ethiopia

230 kV and 400 kV Transmission System)’’, submitted to Bahir Dar University in

partial fulfillment of the requirements for the degree of Master of Science in Power

Systems Engineering is the result of my own research carried out under the supervision

of Dr.-Ing. Belachew Bantyirga. All the material used and reproduced has been properly

referenced.

Signature: ---------------------

Name of Candidate: Asresahegn Tsehay Yemidralem

Date: ----------------------------

This is to declare that the above statement made by the candidate is correct and true to

the best of my knowledge.

Signature: -----------------------

Advisor: Dr.-Ing. Belachew Bantyirga

Date: ------------------------------

MSc Thesis By Asresahegn T. iv

© 2019


ALL RIGHTS RESERVED

MSc Thesis By Asresahegn T. v

MSc Thesis By Asresahegn T. vi

Dedicated to my beloved friend Zenebech Adane and my parents.

MSc Thesis By Asresahegn T. vii

ACKNOWLEDGMENT

First of all, I would like to acknowledge my greats debt in this work to my Merciful

God who supported me with patience and strength to complete this thesis.

Cordial thanks and deep gratitude are offered to my advisor Dr.-Ing. Belachew

Bantyirga, for his systematic guidance, supervision, valuable advice and constant

encouragement throughout this thesis work.

My sincere thanks is to Bahir Dar substation II EEU employees for their support on

giving data used for conducting my research.

My special thanks is also to Debre Tabor University for sponsoring my MSc program

in the field of Electrical Power Systems Engineering at Bahir Dar University.

At the last, but not least, my deepest thanks also go to my family and my best friends.

May God bless us all!

MSc Thesis By Asresahegn T. viii

ABSTRACT

Power transmission system plays a vital role in transmitting the electric power

generated at the generation station to the distribution system. When the power

transmission system operates with heavily loaded lines resulting in power losses and

higher voltage deviation, which may lead to mal operation of power system and

eventually collapse of the system. Growth in customer demand for electrical power is

one of the causes for power loss and voltage deviation. Currently transmission line loss

minimization in a power system is an important issue and it can be achieved by means

of installation of flexible AC transmission system (FACTS) device. The purpose of this

thesis is to minimize the transmission power loss and voltage profile enhancement for

the Ethiopian North Western Region Transmission System network by using Unified

Power Flow Controller (UPFC), which is one of the FACTS devices. The power flow

analysis by Newton Raphson algorithm in MATLAB environment is used and particle

swarm optimization techniques is adopted for optimal sizing of the device. The result

implied that: - within proper placement and optimal setting of the UPFC the active

power loss is improved by 21.2%, 29.57%, 37.4% and 47.52% at base load demand,

25%, 50% and 75% load demand increment respectively. The reactive power loss is

also improved by 37.3%, 35.4%, 39.54% and 47.85% during base load demand, 25%,

50% and 75% load demand increment respectively. The weak buses voltage

magnitudes are improved after the inclusion of UPFC. The lowest bus voltage

magnitude during 75% load demand increment is 0.9608 pu, which is above the

permissible bus voltage magnitude. Using the payback period and net present value

methods of finical measures, the cost benefit analysis is done. Thus, this thesis definitely

addressed the mechanism regarding voltage profile enhancement and power loss

minimization of transmission line by incorporating the UPFC to the system.

Key words: - Power loss minimization, PSO, UPFC, Voltage profile enhancement.

MSc Thesis By Asresahegn T. ix

TABLE OF CONTENTS

DECLARATION ..........................................................................................................iii

ACKNOWLEDGMENT.............................................................................................. vii

ABSTRACT ................................................................................................................viii

LIST OF ABBREVIATIONS ...................................................................................... xii

LIST OF FIGURES .................................................................................................... xiv

LIST OF TABLES ....................................................................................................... xv

LIST OF SYMBOLS .................................................................................................. xvi

CHAPTER ONE ............................................................................................................ 1

1. INTRODUCTION .................................................................................................. 1

1.1. Background ..................................................................................................... 1

1.2. Statement of the Problem ................................................................................ 3

1.3. Objective of the Thesis .................................................................................... 4

1.3.1. General Objective .................................................................................... 4

1.3.2. Specific Objectives .................................................................................. 4

1.4. Scope of the Study........................................................................................... 4

1.5. Significance of the Study ................................................................................ 5

1.6. Organization of the Thesis .............................................................................. 5

CHAPTER TWO ........................................................................................................... 6

2. LITERATURE REVIEW AND THEORETICAL BACKGROUND.................... 6

2.1. Cited Literature ............................................................................................... 6

2.2. Overview of FACTS Controllers .................................................................. 12

2.3. Unified Power Flow Controller (UPFC) ....................................................... 15

2.3.1. Basic UPFC Structure ............................................................................ 15

2.3.2. Operation of UPFC ................................................................................ 16

2.3.3. Controlling mechanism in UPFC ........................................................... 18

CHAPTER THREE ..................................................................................................... 21

MSc Thesis By Asresahegn T. x

3. METHODOLOGY ............................................................................................... 21

3.1. Power Flow Analysis .................................................................................... 25

3.1.1. Formulation of Load Flow Problem ...................................................... 25

3.1.2. Node Power Equations ........................................................................... 27

3.1.3. Load Flow Solution by Newton Method ............................................... 28

3.1.4. Modeling of UPFC ................................................................................. 31

3.2. Particle Swarm Optimization ........................................................................ 33

3.3. Problem Formulation..................................................................................... 36

3.3.1. Objective Function ................................................................................. 36

3.3.2. Constraints ............................................................................................. 37

CHAPTER FOUR ........................................................................................................ 40

4. RESULT AND DISCUSSION ............................................................................. 40

4.1. Case 1: Load Flow Analysis before Installing UPFC Device in the System 40

4.1.1. Bus Voltage Profile ................................................................................ 40

4.1.2. Active Power Loss and Reactive Power Loss........................................ 44

4.2. Case 2: Load Flow Analysis after Installing UPFC Device in the System ... 45

4.2.1. Optimal Placement and Rating of UPFC ............................................... 45

4.2.2. Bus Voltage Profile ................................................................................ 45

4.2.3. Comparison of Bus Voltage Profile ....................................................... 50

4.2.4. Active Power and Reactive Power Loss ................................................ 53

4.2.5. Comparison of Transmission Power Loss ............................................. 54

4.3. Financial Losses Analysis ............................................................................. 56

CHAPTER FIVE ......................................................................................................... 68

5. CONCLUSION AND RECOMMENDATION ................................................... 68

5.1. Conclusion ..................................................................................................... 68

5.2. Recommendation ........................................................................................... 69

REFERENCE ............................................................................................................... 70

MSc Thesis By Asresahegn T. xi

APPENDICES ............................................................................................................. 74

Appendix A: Variation of Active and Reactive Power Demand ............................. 74

Appendix B: Transmission line power flows during different loading conditions

without UPFC device ............................................................................................... 74

Appendix C: Transmission line power flows during different loading conditions

with UPFC device .................................................................................................... 77

Appendix D: MATLAB code of PSO for determining variables of the UPFC device

.................................................................................................................................. 80

MSc Thesis By Asresahegn T. xii

LIST OF ABBREVIATIONS

AC Alternating Current

AGC Automatic Generation Control

DC Direct Current

DE Differential Evolution

DIgSILENT Digital Simulation and Electrical Network Calculation

EEP Ethiopian Electric Power

FACTS Flexible Alternating Current Transmission System

GA Genetic Algorithm

GTO Gate Turn Off

HVDC High Voltage Direct Current

IEEE International Electrical and Electronics Engineering

IPFC Interline Power Flow Controller

MATLAB Matrix Laboratory

MOORPF Multi Objective Optimal Reactive Power Flow

NWRTS North Western Region Transmission System

PSO Particle Swarm Optimization

pu per unit

SGA Simple Genetic Algorithm

SPSO Simple Particle Swarm Optimization

SSSC Static Synchronous Series Compensator

STATCOM Static Compensator

SVC Static VAR Compensator

MSc Thesis By Asresahegn T. xiii

TCPST Thyristor Controlled Phase Shifting Transformer

TCR Thyristor Controlled Reactor

TCSC Thyristors Controller Series Compensator

TSC Thyristor Switched Capacitor

TVAC Time Varying Acceleration Coefficient

UPFC Unified Power Flow Controller

VAR Voltage Ampere Reactive

VSC Voltage Source Converter

MSc Thesis By Asresahegn T. xiv

LIST OF FIGURES

Figure 2.1 Over view of power flow controller devices [8] ........................................ 13

Figure 2.2 UPFC connected in a transmission line between two buses [30] ............... 16

Figure 2.3 Functional capabilities of UPFC [30] ......................................................... 17

Figure 3.1 Flow chart of overall methodology of the thesis ........................................ 21

Figure 3.2 The North Western Region Transmission System single line diagram ...... 24

Figure 3.3 Flowchart of the Newton Raphson load flow method ................................ 30

Figure 3.4 Voltage source equivalent circuit of UPFC [33] ........................................ 31

Figure 3.5 Flow chart of particle swarm optimization ................................................. 35

Figure 3.6 Flow chart of the PSO based UPFC sizing ................................................. 38

Figure 3.7 Convergence Characteristics of PSO algorithm ......................................... 39

Figure 4.1 Bus voltage result at base load demand. ..................................................... 41

Figure 4.2 Bus voltage result at 25% load demand increment. ................................... 42



Figure 4.5 Bus voltage result at base load demand post UPFC. .................................. 46

Figure 4.6 Bus voltage result at 25% load demand increment post UPFC. ................. 47



Figure 4.9 Comparison of bus voltage at base load demand ....................................... 51

Figure 4.10 Comparison of voltage profile at 25% load demand increment ............... 52



Figure 4.13 Comparison on active power loss pre and post UPFC ............................. 54

Figure 4.14 Comparison on reactive power loss pre and post UPFC .......................... 55

Figure 4.15 NPV analysis of installation UPFC for scenario 1 ................................... 62




MSc Thesis By Asresahegn T. xv

LIST OF TABLES

Table 1.1 Load demand increment for three years ........................................................ 4

Table 3.1 Generation Stations ...................................................................................... 22

Table 3.2 Load bus ....................................................................................................... 22

Table 3.3 Transmission line parameters ...................................................................... 23

Table 3.4 PSO parameters for general problems ......................................................... 36

Table 4.1 Bus voltage result at base load demand. ...................................................... 40

Table 4.2 Bus voltage result at 25% load demand increment ...................................... 41

Table 4.3 Bus voltage result at 50% load demand increment. ..................................... 42

Table 4.4 Bus voltage result at 75% load demand increment. ..................................... 43

Table 4.5 The effect of load demand increment on transmission power loss .............. 45

Table 4.6 UPFC variables at base load demand .......................................................... 46

Table 4.7 Bus voltage result at base load demand post UPFC. ................................... 46

Table 4.8 UPFC variables at 25% load demand increment ......................................... 47

Table 4.9 Bus voltage result at 25% load demand increment post UPFC ................... 47

Table 4.10 UPFC variables at 50% load demand increment ....................................... 48

Table 4.11 Bus voltage result at 50% load demand increment post UPFC ................. 48

Table 4.12 UPFC variables at 75% load demand increment ....................................... 49

Table 4.13 Bus voltage result at 75% load demand increment post UPFC ................. 49

Table 4.14 Comparison of bus voltage profile pre and post UPFC device.................. 50

Table 4.15 Transmission power loss post UPFC. ........................................................ 54

Table 4.16 Comparison of transmission power loss pre and post UPFC..................... 54

Table 4.17 Cost comparison of different FACTS controller ....................................... 57

Table 4.18 Cost of UPFC in the four scenarios ........................................................... 57

Table 4.19 Cost comparison pre and post UPFC ......................................................... 59

Table 4.20 NPV analysis of installation UPFC for scenario 1 .................................... 61




Table 4.24 Economic Analysis of Installation of UPFC based on Payback period and

NPV` ............................................................................................................................ 67

MSc Thesis By Asresahegn T. xvi

LIST OF SYMBOLS

C1, C2 Acceleration Factors

Gbest Global Best

km kilometer

kV kilovolt

MVA Mega Volt Ampere

MVAR Mega Volt Ampere Reactive

MW Mega Watt

Pbest Personal Best

Pd Active Power Demand

Pg Generated Active Power of Generator

Pmax Maximum Active Power

Pmin Minimum Active Power

Qd Reactive Power Demand

Qg Generated Reactive Power of Generator

Qmax Maximum Reactive Power

Qmin Minimum Reactive Power

R1, R2 Random Values

cr Angle of Series Voltage of UPFC

vr Angle of Shunt Voltage of UPFC

Vcr Series Voltage of UPFC

Vvr Shunt Voltage of UPFC

W Inertia Weight Factor

MSc Thesis By Asresahegn T. 1

CHAPTER ONE

1. INTRODUCTION

1.1. Background

Electric power system basically consists power generation system, power transmission

system, power distribution system and loads or end users. The electric power generation

system is a power station where the electricity is generated from various available energy

sources. The generated power is stepped up and enters to the power transmission system.

The electric power transmission system is the one in which the bulk power is transmitted

through a long distance to the electric distribution system. The distribution system stepped

down the voltage and distribute to the customers.

The power transmission system connects the generation station to distribution or load

centers. The load demand increment of the customer connected to distribution system

affects the transmission system. Due to the reactive power unbalances which is caused by

load increment and power transfer limitation, voltage deviation and power loss in

transmission system increases [1]. Because few problems could appear with the power

flows through the existing electric transmission networks, the increment of load demand

should be monitored [2]. If this situation fails to be controlled, some lines located on the

particular paths might become overloaded. Due to the overloaded conditions, the

transmission lines will have to be driven close to or even beyond their transfer capacities

[3]. In addition, voltage profile will decrease below the allowable limit and the transmission

power loss will increase. This will finally lead to total collapse of the system.

Building a new transmission line will not be an efficient way to solve the above problems

since it is complicated and due to economical reason [3]. Therefore, the best way to

overcome this major problem is by developing a new way of transmitting more efficiently

using the existing transmission lines. In couple of years, the electromechanical equipment

was used for solving the problems. The equipment was switched inductors or capacitors

banks and phase-shifting transformer. However, all this equipment is not reliable or not

efficiently enough due to the certain problems related to this equipment. They are not only

relatively slow but also they can’t be switched frequently because they tend to wear out


quickly [4]. In this context, one possible solution to improve the system operation is the

use of Flexible AC Transmission Systems (FACTS) technologies [5]. It opens up new

opportunities for controlling the power, decreasing the losses and enhancing the capacity

of existing transmission lines [6]. Using FACTS devices has two inherent advantages over

the more conventional switched capacitor and reactor-based compensators. Firstly, the

power electronics-based voltage sources can internally generate and absorb reactive power.

Secondly, they can facilitate both reactive and real power compensation and thereby can

provide independent control for real and reactive power flow. However, not all FACTS

devices can provide the above functions and it is very important to select the type of devices

in order to achieve the desired purpose.

The IEEE [7] defines the FACTS device as: “alternating current transmission systems

incorporating power electronic-based and other static controllers to enhance and increase

power transfer capability”. The FACTS controller can be also defined as “a power

electronic based system and other static equipment that provide control of one or more AC

transmission system parameters” [8].

In practical uses of FACTS in the power system, there are three common requirements

which are listed as follows: -

What Kinds of FACTS devices should be installed?

Where in the system should be placed?

How much capacity should it have?

Power system losses can be divided into two categories: technical losses and non-technical

losses. Technical losses are due to current flowing in the electrical network. It generates

the following types of losses: - (i) Copper losses: - these are due to I2R losses that are

inherent in all conductors because of their finite resistance. This is sometimes called

conductor loss or conductor heating loss and is simply a real power loss. (ii) Dielectric

losses: - these are losses due to the heating effect on the dielectric material between

conductors. (iii) Induction and radiation losses: - these are produced by the electromagnetic

fields surrounding conductors. Technical losses are caused by well-known physical

electricity effects such as harmonics distortion, long single-phase line, unbalanced loading,


losses due to overloading and low voltage, loss due to aging and poor standard of

equipment [9].

In the North Western Region Transmission System (NWRTS) network there are basically

two electric power generation stations. These are: - Tis Abay II hydro power plant and

Beles hydro power plant. Tis Abay II hydro power plant consists of two generating unit

having a total maximum generating capacity of 72 MW and it is 28.96 km far from Bahir

Dar town. The transmission voltage level from this power plant to Bahir Dar substation II

is 132 kV. The Beles hydro power plant consists of four generating unit having a total

maximum generating capacity of 468 MW and it is 62.84 km far from Bahir Dar town. The

transmission voltage level from this power plant to Bahir Dar Substation II is 400 kV.

This thesis deals with the application of UPFC device for power loss minimization and

voltage profile enhancement in the existing NWRTS network. The 230/400 kV NWRTS

network to be analyzed in this thesis consists of the following transmission lines: - Tis

Abay II to Bahir Dar, Beles hydro power plant to Bahir Dar, Bahir Dar to Debre Markos,

Debre Markos to Gebre-Guracha, Bahir Dar to Mota, Mota to Debre Markos, Bahir Dar to

Alamata, Bahir Dar to Gondar, Gondar to Metema, Gondar to Humera, and Humera to

Endasilasie.

1.2. Statement of the Problem

Electrical energy is generated and transported from remote generating stations to the load

centers or customers through transmission lines. The increment of the power demand for

customers drives the system to experience stressed conditions. This leads to voltage

deviation and thereby transmission power loss. Thus, the transmission lines are susceptible

to losses, which have a great negative impact on delivering the required amount of power

generated at generation station to the receiving end. The transmission power loss is also a

considerable cost for utility.

The load demand increment of NWRTS network can be known by the increased amount

of power transferred in the transmission line i.e. if the load demand increases, the power to

be transferred to the load should also increase. The load demand increment of the NWRTS

network, taken from Bahir Dar Substation II, is shown in Table 1.1. The average power


transferred at peak load shown in Table 1.1 below is the sum of the power transferred to

all of the transmission lines in the case study area for three consecutive years.

Table 1.1 Load demand increment for three years

No Year (E.C) Average power transferred at

peak load (MW)

1 2008 552.4

2 2009 673.5833

3 2010 766.9167

As indicated in the Table 1.1, the load demand is increasing year to year.

Therefore, by incorporating UPFC devices for the Ethiopia North Western Region

Transmission System (NWRTS) network, this thesis address the minimization of power

loss and voltage profile enhancement caused by load demand increment.

1.3. Objective of the Thesis

1.3.1. General Objective

The general objective of this thesis is to minimize transmission line power loss and to

enhance the bus voltage profile using UPFC device (for the case of Ethiopia North-Western

Region Transmission System).

1.3.2. Specific Objectives

The specific objectives of this thesis include the following: -

To evaluate the power loss and voltage profile of the existing transmission network

To model and design UPFC device used to minimize the system loss and enhance

the voltage profile

To study the effects on system loss minimization and voltage profile enhancement

with and without installing the UPFC device

1.4. Scope of the Study

Even though there are different methods of power loss minimization and voltage profile

improvement in transmission line, the study will mainly focus on application of UPFC


devise on loss minimization and voltage profile enhancement at steady state condition. And

also, the implementation of the study is limited on the computer simulation.

1.5. Significance of the Study

Since the power system loss will cause a considerable cost for electric utility, its evaluation

and reduction are very important aspect. The decrease in voltage profile of a certain buses

out of the acceptable limit will cause in total collapse of the system. Therefore, this thesis

has significance on avoiding such conditions on the selected power system as a case study.

1.6. Organization of the Thesis

This thesis work is organized into five chapters.

Chapter one is an introduction. The system power loss reduction phenomenon and the

voltage profile improvement aspect are discussed in this chapter. The North Western

Region Transmission System networks are introduced in general. This chapter also covers

the problem statement, the objectives, the scope, the significance and the organization of

the thesis.

Chapter two is about the theoretical background and literature reviews. It mainly covers

the basic theories of FACTS devices with their description and the publications related to

this thesis.

Chapter three deals with the methodology how this thesis has been done. The general idea

of load flow analysis by using Newton Raphson is briefly discussed in this chapter. The

choice of optimization techniques and the reasons behind the selection is also analyzed.

Chapter four presents the results and discussions made based on the simulation. Taking

different scenario in the case study, the advantage of using UPFC device is clearly

examined.

Chapter five states the conclusion made from the overall thesis work. Finally, the

recommendation is also presented.


CHAPTER TWO

2. LITERATURE REVIEW AND THEORETICAL BACKGROUND

2.1. Cited Literature

Researchers have proposed various ways for solving the problem of voltage profile

improvement and power loss minimization in transmission systems. The most related

works done by the researchers are presented below.

Stéphane Gerbex et al. [10] suggested on optimal location of multi-type FACTS devices in

a power system by means of genetic algorithms. The paper presented a genetic algorithm

to seek the optimal location of multi-type FACTS device in a power system. The

optimizations are performed on three parameters: the location of the devices, their types

and their values. The system load-ability is applied as measure of power system

performance. Four different kinds of FACTS controllers are used and modeled for steady-

state studies: TCSC, TCPST, TCVR and SVC. Simulations were done on a 118-bus power

system for several numbers of devices. Results showed that, there is efficiency difference

on the devices used for system load-ability. It also showed that, the simultaneous use of

several kinds of controllers is the most efficient solution to increase the load-ability of the

system.

Shaheen et al. [11] presented the optimal location for a unified power flow controller based

on evolutionary optimization techniques. In this study, FACTS devices basically the UPFC

have been proposed as an effective solution for controlling power flow and regulating bus

voltage in electrical power systems, resulting in an increased transfer capability, low

system losses, and improved stability. Two evolutionary programming i.e. genetic

algorithm and particle swarm optimization techniques are used for checking the proposed

idea. The IEEE-14 bus case study was taken as the case study in this paper. The result

implied that, unified power flow controller (UPFC) is one of the most important and useful

FACTS devices for controlling the power flow in the system.

Lu et al. [12] investigated a novel method of optimal location for FACTS devices with a

Bacterial Swarming Algorithm (BSA) for reactive power planning. The IEEE-30 and


IEEE-118 bus study cases were analyzed for this study. Four types of FACTS devices i.e.

Thyristor Controlled Series Capacitor (TCSC), which permits the modification of

transmission line reactance is the first device. The second is Thyristor Controlled Phase

Shifting Transformer (TCPST), which controls the phase-angle between the bus voltages

at the two ends of a branch. Thyristor Controlled Voltage Regulator (TCVR) is taken as

the third device which acts principally on the magnitude difference between the bus

voltages at the two ends of a branch. Static Var Compensator (SVC) is used as the fourth

type of FACTS devices to absorb or inject reactive power at the bus which is chosen to

place an SVC. The simulation results implied, with BSA applied, it is possible for utility

to place multi-type FACTS devices in a transmission system such that the optimal reactive

power planning can be achieved and the system real power loss can be minimized.

Rashed et al. [13] suggested on evolutionary optimization techniques for optimal location

and parameter setting of the TCSC under single line contingency. In this regard, two

evolutionary techniques, the GA and the PSO algorithm, are implemented to find the

optimal allocation for FACTS devices in power networks. Simulation has been carried out

on the IEEE-6 bus and IEEE-14 bus systems. The result achieved shows that FACTS can

improve sharply the security of a power system by minimizing the overloading of

transmission lines and voltage deviation. Both algorithms found the same place to allocate

the FACTS devices. The PSO algorithm is much faster than the GA technique and this is

because in the GA there are features such as selection, mutation and crossover and the PSO

does not have these features.

Valle et al. [14] presented the enhanced particle swarm optimizer for power system

application. In this study, the case study is part of the Brazilian power network with 45

bus-bars and 10 machines. The study has been optimized with the PSO technique and the

related results are compared with other techniques such as the BFA and the GA. In terms

of success ratio, both algorithms achieved a feasible and suitable solution. In the case of

global optimality, PSO was able to reach and find a global solution while the BFA was

able to find a near optimal solution. In terms of global optimality, PSO was better and had

a smaller value of the objective function and a much higher accuracy than the BFA. The


results proved that the PSO technique is able to find reasonable and optimal places to

allocate FACTS devices with a high speed of convergence.

Sharifzadeh et al. [15] proposed on optimal reactive power dispatch based on particle

swarm optimization considering FACTS devices. The study analyzed the IEEE-14 bus

system and IEEE-30 bus system as a case study. In this case, the PSO algorithm has been

deployed in the system and related results are compared with other techniques such as the

GA and differential evolution (DE). Simulation results illustrated the capability of PSO for

finding the solution to the problem. In addition, comparing the results from these

algorithms proved the greater robustness of the PSO technique over the GA and differential

evolution algorithms.

Sheeba et al. [16] presented the optimal location of an SVC using artificial intelligence

techniques. In this study, a static var compensator was used. The paper stated that SVC

device has been used widely in power networks because of the lower cost and high system

enhancement. The device also supports the voltage, and if installed in the optimum place

it can reduce power losses. The size of the compensator on SVC indicates the amount of

reactive power connected to the bus-bar with a voltage of 1 p.u. A positive value indicates

that the SVC generates reactive power and injects into the network and a negative value

shows that the SVC absorbs reactive power from the network.

Ch. Rambabu et al. [17] proposed on the improvement of voltage profile and reduction on

power system losses by using multi type FACTS devices. In this paper the ability of

FACTS devices to regulate both active and reactive power control and voltage-magnitude

control is presented. The paper mathematically models the FACT devices basically SVC,

TCSC and UPFC. Having a simulation with five different scenarios on standard IEEE 5

bus power system, system loss minimization and the voltage profile improvement was

checked by inserting FACTS devices. The work used a systematic method i.e.

interchanging the placement of the devices among the entire bus which is time and energy

consuming for a system having more than 5 buses.

Jumaat et al. [18] proposed on transmission loss minimization using SVC based on particle

swarm optimization. The paper deals about optimal sizing of static VAR compensator


(SVC) for loss minimization. The technique used to optimize the size of SVC was particle

swarm optimization technique. Having five different loading conditions on standard IEEE

26 bus reliability test system, the work showed that the active power loss can be minimized

by installing SVC. In addition, the effectiveness of particle swarm optimization technique

(PSO) is showed as compared to bee algorithm (BA) technique. But the work didn’t

consider about the voltage profile and the reactive power compensation. `

Mondal et al. [19] investigated PSO-based location and parameter setting of advance SVC

controller in comparison to the genetic algorithm in mitigating small signal oscillations.

The IEEE-14 bus case study was analyzed as a case study with maximize the damping ratio

as an objective function. The optimization problem mentioned here is to search for the

optimal location and the optimal set of SVC parameters using the PSO and GA algorithms.

It can be said that the SVC controller is designed to minimize small signal oscillations in

the power system after a disturbance, thereby leading to improve stability. The ability and

performance of the PSO- and GA-based FACTS devices have been compared in relation

to power system disturbances: for instance, changing the load and transmission line power

outage. The study showed that the PSO-based optimization technique has a high accuracy

and convergence rate and this technique is basically free from computational complexity

unlike the GA technique.

N. Mancer et al. [20] investigated on multi objective optimal reactive power flow using

modified PSO considering TCSC. This paper presents a new variant of particle swarm

algorithm with time varying acceleration coefficients (TVAC) to solve multi objective

optimal reactive power flow (MOORPF) i.e. power loss minimization and voltage

deviation. The proposed algorithm is used to adjust dynamically the parameters setting of

Thyristor controlled series capacitor (TCSC) in coordination with voltages of generating

units. This study was implemented on the standard IEEE 30-Bus system and the results

were compared with other evolutionary programs such as simple genetic algorithm (SGA)

and the simple particle swarm algorithm (SPSO). Simulation results confirmed about the

robustness of this new variant based PSO in term of solution quality and convergence time.


Esmaeil et al. [21] proposed on optimal placement of multiple type facts devices to

maximize power system load-ability using a generic graphical user interface(GUI). The

paper presents a GUI based on a genetic algorithm (GA) which able to find the optimal

locations and sizing the parameters of multi-type FACTS devices in large power systems.

Five different FACTS devices are implemented: SVC, TCSC, TCVR, TCPST and UPFC.

The simulation results on IEEE test networks with up to 300 buses show that the FACTS

placement toolbox is effective and flexible enough for analyzing a large number of

scenarios with mixed types of FACTS to be optimally sited at multiple locations

simultaneously.

Aborisade et al. [22] proposed on a comparison of the voltage enhancement and loss

reduction capabilities of STATCOM and SSSC FACTS controllers. In this work, the

Newton Raphson iterative algorithm was adopted. Simulation of power flow solutions

without any Flexible Alternating Current Transmission System (FACTS) device

(STATCOM and SSSC) and with STATCOM and SSSC were done using a MATLAB

based program. The paper showed that even though STATCOM and SSSC provided

approximately the same effect on the voltage, SSSC gives a higher reduction in losses

compared to STATCOM.

Kumar R. et al. [23] has proposed on optimal placement of unified power flow controller

for minimization of power transmission line losses. The work used a genetic algorithm-

based method for finding the optimal location of UPFC to be installed in a power system,

for the minimization of the system losses and at the same time meeting the operational

constraints on line flows and bus voltages. Newton Raphson load flow algorithm was used

in the determination of the bus voltages, power injections at all the buses and power flows

though the transmission network for a specified load demand at various buses in the system.

The simulation results clearly showed that installing the UPFC in the power system will

minimize the power loss and improve the voltage profile.

Bhatti, Engr. M.et al. [24] presented on electric power transmission and distribution losses

overview and minimization in Pakistan. This paper briefly described the different types

and main causes of transmission and distribution loss and proposed that, new technologies

should be implemented to reduce losses i.e. advance metering, HVDC and gas-insulated


substations. But there is no clear method presented in the paper on how the new

technologies listed there have to be implemented.

R. Kalaivani and S. K. Dheebika [25] done on the enhancement of voltage stability and

reduction of power loss using genetic algorithm through optimal location of SVC, TCSC

and UPFC. The work was focusing on the multi objective optimization problem that can

be solved by the proposed GA. The proposed approach employs the GA for the optimal

placement and ratings of FACTS devices based on minimization of voltage stability index,

generation cost and real power loss function and tested on standard IEEE 14 and IEEE 57

bus test systems. The result implied that, the optimal location and their ratings were found

and the objectives; voltage stability index, generation fuel cost, and power losses were

minimized.

Mehedi H. et al. [26] proposed on static voltage stability assessment and power loss

minimization of power systems with FACTS devices. The analysis is carried out on the

Western System Coordinating Council (WSCC) 9-bus test system. Two FACTS devices

i.e. static var compensator (SVC) and a static synchronous compensator (STATCOM) are

used in the analysis and comparison was done between these two devices. The result

showed that a STATCOM provides higher voltage stability margin than SVC. However,

the reactive power support from the FACTS devices depends on the proper placement of

the FACTS devices in the network. The power loss of the system is also improved when

FACTS devices are used in the appropriate location. As the weakest bus requires highest

reactive power, the proposed approach suggests placing the FACTS device at the weakest

bus of the network. It has been concluded that, to reduce the possibility of voltage collapse

and power loss, the weakest bus is the best choice to install an expensive FACTS device.

Nur Ashida Salim et al. [27] presented on the application of evolutionary programming for

the placement of TCSC and UPFC for minimization of transmission losses and

improvement of voltage profile. The paper presented the evolutional programming

technique used to optimize the fitness and Static Voltage Stability Index method to

determine the optimal location of the FACTS devices tested on standard IEEE 14 bus. The

weakest bus which has highest value of voltage stability index was selected and the FACTS


devices were installed. The obtained result compares the performance of TCSC and UPFC

on loss minimization and voltage profile improvement and concluded that UPFC has a

better performance.

From the above reviewed literature, it is clear that the FACTS device can minimize the

power loss and improve the voltage profile of the transmission system. But it is very crucial

on the selection of FACTS device to be used for the given power system and the way how

to install those devices. Therefore, in this study the FACTS device required to minimize

the power loss and improve voltage profile is identified and the particle swarm optimization

technique is used for the optimal sizing of the UPFC device as optimization technique for

the North Western Region Transmission System network.

2.2. Overview of FACTS Controllers

The two categories of power flow control devices are the conventional (mechanically

switched) and power electronics-based devices. Regarding the mode of placement of this

technology in the network; we have shunt, series, and combined as shown in Figure 2.1.


Figure 2.1 Over view of power flow controller devices [8]

Depending on the arrangement to be installed in the transmission line, FACTS controllers

can be classified into four categories [8]:

Series Controllers

Shunt Controllers

Combined series-series Controllers

Combined series-shunt Controllers

Series Controllers: The series controller could be a variable impedance, such as capacitor,

reactor, etc., or a power electronics based variable source of main frequency, sub-

synchronous and harmonic frequencies (or a combination) to serve the desired need. In

principle, all series controllers inject voltage in series with the line. The variable impedance

multiplied by the current flow through it, represents an injected series voltage in the line.

As long as the voltage is in phase quadrature with the line current, the series controller only

FACTS Devices

Voltage Source

Converter (VSC)

Shunt and

Series Devices

Shunt and

Series D.

Series

Devices

Shunt

Devices

Variable

impendence

Static Var

Compensator (SVC)

Thyristor Controlled

Series Compensator

(TCSC)

HVDC VSC Back to

Back

Unified/Interline

Power Flow Controller

(UPFC/IPFC)

Dynamic Flow

Convertor

(DFC)

Static Synchronous

Series Compensator

(SSSC)

HVDC Back to

Back

Static Synchronous

Compensator

(STATCOM)

Conventional

(manually switched)

L, C, Transformer

Switched Shunt

Compensation (L, C)

Switched Series

Compensation (L, C)

Phase Shifting

Transformer


supplies or consumes variable reactive power [28]. Any other phase relationship will

involve handling of real power as well.

Shunt Controllers: As in the case of series controllers, the shunt controllers may be

variable impedance, variable source, or a combination of these. In principle, all shunt

controllers inject current into the system at the point of connection. The variable shunt

impedance connected to the line voltage causes a variable current flow and hence

represents injection of current into the line. As long as the injected current is in phase

quadrature with the line voltage, the shunt controller only supplies or consumes variable

reactive power. Any other phase relationship will involve handling of real power as well

[29].

Combined series-series Controllers: This could be a combination of separate series

controllers, which are controlled in a coordinated manner, in a multiline transmission

system. Or it could be a unified controller, in which series controllers provide independent

series reactive compensation for each line but also transfer real power among the lines via

the power link [29]. The real power transfer capability of the unified series-series

controller, referred to as Interline Power Flow Controller, makes it possible to balance both

the real and reactive power flow in the lines and thereby maximizes the utilization of the

transmission system.

Combined series-shunt Controllers: This could be a combination of separate shunt and

series controllers, which are controlled in a coordinated manner or a Unified Power Flow

Controller with series and shunt elements [30]. In principle, combined shunt and series

controllers inject current into the system with the shunt part of the controller and voltage

in series in the line with the series part of the controller. However, when the shunt and

series controllers are unified, there can be a real power exchange between the series and

shunt controllers via the power link.

Depending on the power electronic devices used in the control, the FACTS controllers can

be also classified as [8]:-

i. Variable impedance type

ii. Voltage Source Converter (VSC) based.


The variable impedance type controllers include:- Static Var Compensator (SVC) (shunt

connected), Thyristor Controlled Series Capacitor or compensator (TCSC) (series

connected), Thyristor Controlled Phase Shifting Transformer (TCPST) of Static and PST

(combined shunt and series). The VSC based FACTS controllers are:- Static Synchronous

Compensator (STATCOM) (shunt connected), Static Synchronous Series Compensator

(SSSC) (series connected), Interline Power Flow Controller (IPFC) (combined series-

series) and Unified Power Flow Controller (UPFC) (combined shunt series).

The FACTS controllers based on VSC have advantages over the variable impedance type.

For example, STATCOM is much more compact than SVC for similar rating and is

technically superior [8]. It can supply required reactive current even at low values of the

bus voltage and can be designed to have in-built short-term overload capability. Also, a

STATCOM can supply active power if it has an energy source or large energy storage at

its DC terminals.

2.3. Unified Power Flow Controller (UPFC)

2.3.1. Basic UPFC Structure

UPFC device consists of two three-phase switching converters employing GTOs, a shunt-

connected transformer connecting converter 1 to the transmission line in shunt, a series-

connected transformer connecting converter 2 to the transmission line in series and a DC

link provided by a DC storage capacitor. The main function of the converter is to change a

DC input voltage to a symmetrical AC output voltage of desired magnitude, frequency and

phase shift with respect to a selected reference phase. The functions of the coupling

transformers are to isolate UPFC and the transmission line and to match the voltage levels

between the line and the voltage produced by the converters [30].

Series converter inserts a voltage of controllable magnitude and controllable phase angle

in series with the transmission line via series-connected transformer, thereby provides the

control of real and reactive power flow on the transmission line. The real power injected

into the system by the series branch must be taken from the parallel branch and transmitted

to the series branch over DC link. With this respect, series branch provides the main

function by injecting an AC voltage, Vse at system frequency with variable magnitude and


phase angle. The basic schematic diagram of a UPFC connected to the transmission line is

shown in Figure 2.2.

Figure 2.2 UPFC connected in a transmission line between two buses [30]

2.3.2. Operation of UPFC

During operation, Vse is added to the AC system terminal voltage, Vs by the series

connected coupling transformer. Transmission line current IL flows through voltage source,

Vse resulting in real and reactive power exchange between UPFC and the power system.

Figure 2.10 shows conceptual series power injection into system by the series branch.

Phase angle of output voltage of converter 2, can be chosen independently of the phase

angle of IL; which means that output voltage of series branch, Vse can be independently

controlled without any restriction. This enables free flowing of real power in either

direction between AC terminals of the two converters, as illustrated in figure 2.10. The

shunt converter exchanges a current with the power system; in this manner it can generate

or absorb controllable reactive power and provide shunt reactive power compensation. This

arrangement makes UPFC an ideal AC-to-AC power converter. The DC link capacitor is

designed to provide a path for the real power exchange between converters and also provide


a proper DC voltage required by both converters to control reactive power circulated

internally.

With its operational flexibility, UPFC might be used for the purposes of terminal voltage

regulation, series compensation, and transmission angle regulation. Figure 2.3 depicts the

concerned phasor relationships of these operating modes.

Figure 2.3 Functional capabilities of UPFC [30]

Terminal voltage regulation is similar to that obtainable with a transformer tap-changer

having infinitely small steps is shown in Figure 2.3 (a). The series voltage Vse is injected

either in-phase or counter-phase with sending end voltage Vs, namely Vse=±∆Vo. Series

reactive compensation is shown schematically in Figure 2.3 (b). The series voltage Vse is

injected either 90° lagging or 90° leading with the transmission line current IL. In this case

Vse= ±Vc. The phase shifting is shown schematically in Figure 2.3 (c). The series voltage,

Vse is injected with an angular relationship with respect to Vs so that the desired phase shift

(leading or lagging) without any change in magnitude is achieved. In this mode Vse= ±Vr.

In multi-function control mode, the injected series voltage Vse can be controlled to meet


simultaneous terminal voltage regulation, series compensation, and phase shifting. In this

multi-function mode, Vse = ∆Vo + Vc + Vr. The resulting voltage phasors can be observed

in Figure 2.3 d.

2.3.3. Controlling mechanism in UPFC

So far in the above sections we have seen the basic structure and operation of UPFC having

two converters (series converter and shunt converter) coupled with common DC side. The

detailed controlling mechanism is discussed below [30].

Shunt converter control mechanism

The shunt converter takes a controlled current from the network. This current has two

component i.e Ip and Iq. The first component of this current is Ip, which is automatically

calculated by the requirement to balance the active power gone to the series converter by

the DC link. This balancing of power is commanded through regulating the voltage of the

DC capacitor via feedback controlling. The other part of the current in the shunt converter

is the reactive current, Iq that can be controlled with the same method as in a STATCOM.

There are two modes of the operating control for the shunt converter (STATCOM) which

are: -

i. Reactive Power (VAR) Control Mode: - In reactive power control mode the

reference input is an inductive or capacitive VAR request. The shunt converter

control translates the VAR reference into a corresponding shunt current request

and adjusts the gating of the converter to establish the desired current.

ii. Automatic Voltage Control Mode: - In voltage control mode (which is normally

used in practical applications), the shunt converter reactive current is

automatically regulated to maintain the transmission line voltage to a reference

value at the point of connection.

Series converter control mechanism

The series converter controls the magnitude and angle of the injected voltage, Vse in series

with the line. This voltage injection is directly or indirectly intended to influence the flow

of power on the line. However, Vse is dependent on the operating mode selected for the


UPFC to control power flow. The principal operating modes are as follows in the next

subsections.

i. Direct Voltage Injection Mode: - the series converter simply generates the voltage

vector, Vse with the magnitude and phase angle requested by the reference input.

This operating mode may be advantageous when a separate system optimization

control coordinates the operation of the UPFC and other FACTS controllers

employed in the transmission system. Special functional cases of direct voltage

injection include those having dedicated control objectives, for example, when the

injected voltage vector, Vse is kept in phase with the system voltage for voltage

magnitude control, or in quadrature with it for controlled quadrature boosting, or in

quadrature with the line current vector, IL to provide controllable reactive series

compensation.

ii. Line Impedance Compensation Mode: - the magnitude of the injected voltage

vector, Vse is controlled in proportion to the magnitude of the line current, IL so that

the series insertion emulates impedance when viewed from the line. The desired

impedance is specified by reference input and in general it may be complex

impedance with resistive and reactive components of either polarity. A special case

of impedance compensation occurs when the injected voltage is kept in quadrature

with respect to the line current to emulate purely reactive (capacitive or inductive)

compensation. This operating mode may be selected to match existing series

capacitive line compensation in the system.

iii. Phase Angle Regulation Mode: - the injected voltage vector, Vse is controlled with

respect to the input bus voltage vector, Vs so that the output bus voltage vector, Vo

is phase shifted without any magnitude change. One special case of phase shifting

occurs when Vse is kept in quadrature with Vs to emulate the quadrature booster.

iv. Automatic Power Flow Control Mode: - the magnitude and angle of the injected

voltage vector, Vse is controlled so as to force such a line current vector that results

in the desired real and reactive power flow in the line. In automatic power flow

control mode, the series injected voltage is determined automatically and

continuously by a closed-loop control system to ensure that the desired P and Q are

maintained despite power system changes. The transmission line containing the


UPFC thus appears to the rest of the power system as a high impedance power

source or sink. This operating mode, which is not achievable with conventional line

compensating equipment, has far reaching possibilities for power flow scheduling

and management. The mathematical modeling of the UPFC will be discussed in

section 3.1.4

From the different FACTS controllers discussed so far, in this thesis the UPFC is selected

for loss minimization and voltage profile enhancement of the NWRTS network. The main

reasons for choosing UPFC are: -

i. It provides simultaneous or individual controls of basic transmission system

parameters such as transmission voltage, impedance and phase angle [23].

ii. It has a unique capability to control real and reactive power flow and also

regulate the bus voltage.

iii. It can perform the function of STATCOM and SSSC.

iv. It provides an additional flexibility by combining some of the function of

STATCOM and SSSC.


CHAPTER THREE

3. METHODOLOGY

This thesis work had basically three specific objectives. It began with a Newton Raphson

power flow analysis on the selected case study in order to assess the currently existing

power system conditions. Depending on the power flow result, the optimal placement of

the UPFC device is identified. The particle swarm optimization technique is developed to

determine the parameters of the UPFC device which determine its rating. The overall

methodology of this thesis is summarized in the Figure 3.1 below.

Figure 3.1 Flow chart of overall methodology of the thesis

Data collection and analysis

The recent and necessary data for the transmission network is collected from the Ethiopian

Electric Power through their recorded technical data regarding the transmission network.

The data collected includes: -

The transmission line parameters.

The peak load demand of the North Western Region Transmission System network

The generation capacity of the power plants.

Data Collection

Data Analysis

Optimal placement and sizing of the

UPFC using PSO

UPFC Modeling and Design

Load flow analysis without

UPFC

Load flow analysis with UPFC


The collected data are analyzed and presented in Table 3.1 - Table 3.3.

1. Generation station

Table 3.1 Generation Stations

No Generation Name Pg

(MW/unit)

Pmax

(MW

(total))

Pmin

(MW)

Qg

(Mvar)

Qmax

(Mvar)

Qmin

(Mvar)

1 Tis Abay II Hydro

Power Plant

29.173 72 0 2.978 42.2 -25

2 Beles Hydro Power

Plant

184.04 468 0 109.2 280.4 -166

2. Load buses

Table 3.2 Load bus

Bus

No

Load bus name

Peak Load

Pd(MW) Qd(Mvar)

3 Bahir Dar 230 65.53 30.76

8 Debre Markos 230 16.12 8.220

9 Mota 230 3.450 1.700

10 Alamata 230 17.85 8.080

11 Gondar 230 37.00 11.80

12 Metema 230 4.000 1.960

13 Humera 230 17.94 8.690

14 Endasilasie 230 13.36 6.460


3. Transmission line parameters in pu

Table 3.3 Transmission line parameters

TL

No

From bus To bus R(pu) X(pu) B(pu)

1 Tis Abay 132 Bahir Dar 132 0.035482 0.070505 0.01381

2 Beles 400 Bahir Dar 400 0.000958 0.012159 0.37713

3 Bahir Dar 400 D. Markos 400 0.002997 0.03986 1.10239

4 D. Markos 400 G.Guracha 400 0.001400 0.01800 0.49790

5 Bahir Dar 230 Mota 230 0.012781 0.066429 0.120060

6 Mota 230 D. Markos 230 0.017209 0.089447 0.161660

7 Bahir Dar 230 Alamata 230 0.025643 0.083875 0.245986

8 Bahir Dar 230 Gondar 230 0.029325 0.084425 0.255224

9 Gondar 230 Metema 230 0.033358 0.098995 0.317930

10 Gondar 230 Humera 230 0.034659 0.106534 0.378560

11 Humera 230 Endasilasie 230 0.046434 0.137799 0.442560

The North Western Region Transmission System network single line diagram is drawn

using DIgSILENT power factory software as shown in the figure below. The DIgSILENT

power factory software is used in this thesis for only drawing purpose because it has a good

feature to show all of the power system components. The power flow analysis is done by

using MATLAB software.


Figure 3.2 The North Western Region Transmission System single line diagram

External grid 1, External grid 2, External grid 3, and External grid 4 in Figure 3.2 represents

the remaining transmission network from Gebre-Guracha side, Debre Markos side,

Alamata side and Endasilasie side respectively. The external grids are provided with

parameters taken from the actual EEP grid used to show the power exchange between the

case study system and the portions of omitted part of the Ethiopian transmission system.

This external grid network however needs to be represented as an equivalent generator for

purpose of the studies to reflect the influence of the external grid network on the portion

of the network for which studies are being carried out. For the analysis done on the

MATLAB in this thesis, the external grids are represented by generator bus.


3.1. Power Flow Analysis

Load flow analysis is the most important and essential approach to investigate problems in

power system operating and planning [31]. Based on a specified generating state and

transmission network structure, load flow analysis solves the steady operation state with

node voltages and branch power flow in the power system. Load flow analysis can provide

a balanced steady operation state of the power system, without considering system transient

processes. Hence, the mathematic model of load flow problem is a nonlinear algebraic

equation system without differential equations.

3.1.1. Formulation of Load Flow Problem

Classification of Node Types

An electric power system is composed of generators, transformers, transmission lines and

loads. In the process of power system analysis, the static components, such as transformers,

transmission lines, shunt capacitors and reactors, are represented by their equivalent

circuits consisting of R, L, C elements. Therefore, the network formed by these static

components can be considered as a linear network and represented by the corresponding

admittance matrix or impedance matrix. In load flow calculation, the generators and loads

are treated as nonlinear components.

The relationship between node current and voltage in the linear network can be described

by equation (3.1) and (3.2).

I YV (3.1)

1

ˆ ˆ (i 1,2,...... )n

i ij j

j

I Y V n

(3.2)

Where iI and jV are the injected current at bus i and voltage at bus j respectively, Yij is an

element of the admittance matrix, n is the total number of nodes in the system.

To solve the load flow equation, the relation of node power with current should be used.

*ˆ (i 1,2,...... )i ii

i

P jQI n

V

(3.3)

*1

ˆ (i 1,2,...... )n

i iij j

i j

P jQY V n

V

(3.4)


Where Pi, Qi are the injected active and reactive power at node i, respectively. If node i is

a load node, then Pi and Qi should take negative values. In equation (3.3), Vi* is the

conjugate of the voltage vector at node i. Substituting equation (3.3) to equation (3.2), we

have,

* *

1

(i 1,2,...... )ˆ

ni i

ij j

i j

P jQY V n

V

(3.5)

There are n nonlinear complex equations in equation (3.5). They are the principal equations

in load flow calculation. In power system load flow problem, the variables are nodal

complex voltages with its angle and complex powers: V, θ, P, Q. If there are n nodes in a

power system, the total number of variables is 4n.

As mentioned above, there are n complex equations or 2n real equations defined in

principal by equation (3.5), thus only 2n variables can be solved from these equations,

while the other 2n variables should be specified as original data. Usually, two variables at

each node are assumed known, while the other two variables are treated as state variables

to be resolved.

According to the original data given, the bus in power systems can be classified into three

types [32]:

i. Slack Bus: In load flow studies, there should be one and only one slack node specified

in the power system, which is specified by a voltage, constant in magnitude and phase

angle. Therefore, V and θ are given as known variables at the slack node, while the

active power P and reactive power Q are the variables to be solved. The effective

generator at this node supplies the losses to the network. This is necessary because the

magnitude of losses will not be known until the calculation of currents is complete, and

this cannot be achieved unless one node has no power constraint and can feed the

required losses into the system. The location of the slack node can influence the

complexity of the calculations; the node most closely approaching a large AGC power

station should be used.

ii. PQ Bus: For PQ nodes, the active and reactive power (P, Q) are specified as known

parameters, and the complex voltage (V, θ) is to be resolved. Usually, substation nodes


are taken as PQ nodes where the load powers are given constants. When output P and

Q are fixed in some power plants, these nodes can also be taken as PQ node. Most

nodes in power systems belong to the PQ type in load flow calculation.

iii. PV Bus: For PV nodes, active power P and voltage magnitude V are specified as known

variables, while reactive power Q and voltage angle θ are to be resolved. Usually, PV

nodes should have some controllable reactive power sources and can thus maintain

node voltage magnitude at a desirable value. Generally speaking, the buses of power

plants can be taken as PV nodes, because voltages at these buses can be controlled with

reactive power capacity of their generators. Some substations can also be considered

as PV nodes when they have enough reactive power compensation devices to control

the voltage.

3.1.2. Node Power Equations

Power system load flow calculations can be roughly considered as the problem of solving

the node voltage phasor for each node when the injecting complex power is specified. If

the complex power can be represented by equations of complex voltages, then a nonlinear

equation solving method, such as the Newton Raphson method, can be used to solve the

node voltage phasors. In this section, node power equations are deduced first.

The complex node voltage has two representation forms: - the polar form and the

rectangular form. Accordingly, the node power equations also have two forms. From

equation (3.5), the node power equations can be expressed as

* *ˆ (i 1,2,...... )i i i ij j

j i

P jQ V Y V n

(3.6)

Where j i means the node j should be directly connected with node i, including j = i. As

we know, the admittance matrix is a sparse matrix, and the terms in summation are

correspondingly few. If the voltage vector of equation (3.6) adopts polar form,

i ij

V V e

(3.7)

Where Vi, θi are the magnitude and phase angle of voltage at node i. The elements of

admittance matrix can be expressed as:


ij ij ijY G jB (3.8)

Hence equation (3.6) can be rewritten as:

( ) 1,2,...,j ji i i ij ij j

j i

P jQ V e G jB V e i n

(3.8)

Combining the exponential items of above equation and using the relationship:

cos sinje j (3.9)

We have,

( ) (cos sin ) 1,2,...,ji i i ij ij ij ij

j i

P jQ V e G jB Vj j i n

(3.10)

Where θij =θi - θj is the voltage phase angle difference between node i and j.

Dividing equation (3.10) into real and imaginary parts,

( cos sin )

( 1,2,..., )( sin cos )

i j ij ij ij ijij i

i j ij ij ij ijij i

P V V G B

i nQ V V G B

(3.11)

They are usually expressed as the following forms as mathematical models of the load flow

problem:

( cos sin )

( 1,2,..., )( sin cos )

i i j ij ij ij ijisj i

i i j ij ij ij ijisj i

P P V V G B

i nQ Q V V G B

(3.12)

Where Pi, Qi, Pis, Qis are the mismatch active power, mismatch reactive power, the

specified active power and reactive powers at node i respectively.

3.1.3. Load Flow Solution by Newton Method

Load flow solution by Newton’s method is mathematically superior to the Gauss-Seidel

method and it is less prone to divergence with ill-conditioned problems. The number of

iteration required to obtain a solution is independent of the system size. It has also quadratic

convergence. Therefore, for this thesis load flow solution by Newton’s method is selected.

Assume that total number of system nodes is n, the number of PV nodes is r. For

convenience, let the slack bus be the last node, i.e., node n. Therefore, we have n -1 active


power equations and n - r -1 reactive power equations as described in equation (3.13) and

equation (3.14).

1 1 1 1 1 1 1

2 2 2 2 2 2 2

1 1 1 1 1 1 1

( cos sin )

( cos sin )( 1,2,..., )

( cos sin )

j j j j j

j i

j j j j j

j i

n n n j n j n j n j n j

j i

P P s V V G B

P P s V V G Bi n

P P s V V G B

M

(3.13)

1 1 1 1 1 1 1

2 2 2 2 2 2 2

1 1 1 1 1 1 1

( sin cos )

( sin cos )( 1,2,..., )

( sin cos )

j j j j j

j i

j j j j j

j i

n n n j n j n j n j n j

j i

Q Q s V V G B

Q Q s V V G Bi n

Q Q s V V G B

M

(3.14)

In equation (3.13) and (3.14), node voltage angle θi and magnitude Vi are the variables to

be resolved. Here the number of θi is n - 1 and the number of Vi is n - r - 1. There are 2n -

r - 2 unknown variables in total and they can be solved by the above 2n - r - 2 equations.

The concise form of equations (3.13) and (3.14) is:-

P H N

Q J L V

(3.15)

Taking partial derivations of equation (3.13), and (3.14), and noting that both Pis, Qis are

constants, we can obtain the elements of the Jacobian matrix as,

( cos sin )i

i j ij ij ij ijij

j

PH V V G B j i

(3.16)

( sin cos )i

i j ij ij ij ijiij iij i

PH V V G B i j

(3.17)

( cos sin )i

i j ij ij ij ijij

j

PN V V G B j i

V

(3.18)

2( cos sin ) 2

ii j ij ij ij ijii i ii

j iij i

PN V V G B V G i j

V

(3.19)


( cos sin )i

i j ij ij ij ijij

j

QJ V V G B j i

(3.20)

( cos sin )

ii j ij ij ij ijii

j ijj i

QJ V V G B i j

(3.21)

( sin sin )i

i j ij ij ij ijij

j

QL V V G B j i

V

(3.22)

2( sin cos ) 2

ii j ij ij ij ijii i ii

j iij i

QL V V G B V B i j

V

(3.23)

The flowchart of the Newton Raphson load flow method is shown in Figure 3.3.

Yes

No

Figure 3.3 Flowchart of the Newton Raphson load flow method

Set all voltage to

starting values

Calculate all ∆P and

∆Q save the max

Calculate the Jacobian

Matrix

Is max ∆P

and ∆Q<ε

Solve for ∆Vi and ∆θi using

Jacobian inverse

Update the bus

voltage and angle

Calculate the line flow,

line loss, mismatch

power

Print Results


3.1.4. Modeling of UPFC

In chapter two of this thesis the basic schematic diagram of the UPFC with its operating

characteristics was discussed. So now in this section the voltage source model of UPFC

which used to incorporate the UPFC to the Newton Raphson load flow analysis is derived

from its equivalent circuit diagram as shown below.

Figure 3.4 Voltage source equivalent circuit of UPFC [33]

As shown in the equivalent circuit in Figure 3.4, the series converter of the UPFC which is

connected in series with the transmission line is represented by series voltage source, VcR

and the shut converter of UPFC which is connected to the transmission line by the coupling

transformer is represented by the shunt voltage source, VvR.

The UPFC voltage sources are:

(cos sin )cR cR cR cRE V j (3.24)

(cos sin )vR vRvR vRE V j (3.25)

Where VcR and δcR are within the controllable magnitude (VcRmin ≤ VcR ≤ VcR

max) and phase

angle (0 ≤ δcR≤ 2*pi) of the voltage source representing the series converter. The

magnitude VvR and phase angle δvR of the voltage source representing the shunt converter

are controlled between limits (VvRmin ≤ VvR ≤ VvR

max) and (0 ≤ δvR ≤ 2*pi), respectively.


Based on the equivalent circuit shown in Figure 3.4 and equations (3.24) and (3.25), the

active and reactive power equations are [33]: -

At bus k:

2 [ cos( ) sin( )]

[ cos( ) sin( )]

[ cos( ) sin( )]

m m mk k kk k km k km k

cR cR cRk km k km k

vR vR vR vR vRk k k

P V G V V G B

V V G B

V V G B

(3.26)

2 [ sin( ) cos( )]

[ sin( ) cos( )]

[ sin( ) cos( )]

m m mk k kk k km k km k

cR cR cRk km k km k

vR vR vR vR vRk k k

Q V B V V G B

V V G B

V V G B

(3.27)

At bus m:

2 [ cos( ) sin( )]

[ cos( ) sin( )]

m m mm m m mk mk k mk k

m mm m mcR cR cRmk

P V G V V G B

V V G B

(3.28)

2 [ sin( ) cos( )]

[ sin( ) cos( )]

m m mm m m mk mk k mk k

m mm m mm mcR cR cR

Q V B V V G B

V V G B

(3.29)

At series converter:

2 [ cos( ) sin( )]

[ cos( ) sin( )]

mmcR cR cR cR cRk km k km k

m mm m mm mcR cR cR

P V G V V G B

V V G B

(3.30)

2 [ sin( ) cos( )]

[ sin( ) cos( )]

mmcR cR cR cR cRk km k km k

m mm m mm mcR cR cR

Q V B V V G B

V V G B

(3.31)

At shunt converter:

2 [ cos( ) sin( )]vR vR vR cR vR vR vR vRk k kP V G V V G B (3.32)

2 [ sin( ) cos( )]vR vR vR vR vR vR vR vRk k kQ V B V V G B (3.33)

Assuming the loss on the converters is negligible, the active and reactive power supplied

to the shunt converter, PvR equals the active power demand by the series converter, PcR; i.e.

0vR cRP P (3.34)

Furthermore, if the coupling transformers are assumed to contain no resistance then the

active power at bus k matches the active power at bus m.


3.2. Particle Swarm Optimization

Particle Swarm Optimization (PSO) was developed by J. Kennedy and R. Eberhart in 1995

[34]. It was originally used for solving continuous nonlinear functions. The idea of PSO

comes from a simplified social system like bird flocking or fish schooling.

Imagine a group of birds is searching for food in an n-dimension area (n equals the number

of control variables). None of these birds knows where the food is. However, they know

which bird is nearest to the food (assume the closest bird to the food is Bird A). The best

strategy for the rest of birds to find the food is following Bird A and searching its

neighboring area.

In PSO, each single solution (particle) can be viewed as a bird. The position of each particle

can be expressed as 𝑥𝑖 = (𝑥𝑖1, 𝑥𝑖2, …, 𝑥𝑖n). The initial solutions in PSO are randomly selected

and then PSO will continually search for optimal value by updating the solutions in each

iteration. The fitness value of the particle is related to the objective function. And the

velocity of the particles 𝑣𝑖= (𝑣𝑖1, 𝑣𝑖2, …, 𝑣𝑖n) is related to its pervious velocity, global best-

known position, and local best-known position. The velocity indicates the directions of all

the particles in the next iteration. The local best-known position is the best solution that

achieved by each particle so far. The global best-known position is the best solution among

all the achieved solutions. The inertia velocity part, local best-known position part, and

global best-known position part of the velocity reflect the cooperation and competition

mechanism in PSO.

PSO starts with a group of randomly generated solutions and updates the solutions in each

iteration. The behavior of all the particles appears to be managed by a control center. The

principle of the PSO algorithm is quite straightforward as described in equation (3.35) and

(3.36).

1 d 1 1 best d

2 2 best d

*(W*V . *(P X )

. (G x ))

dV k C R

C R

(3.35)

1 1d d dX X V (3.36)

Where: - W is the inertia weight factor

C1 and C2 are acceleration factors


R1 and R2 are random values between 0 and 1

k is the constriction factor

The acceleration factors handle the step sizes of the particles in the next iteration. If the

acceleration factors are too small, the particles may not have enough velocity to reach the

target regions. If the acceleration factors are too big, the particles may fly over the optimal

value. Appropriate selection of acceleration factors could avoid trapping into local minimal

and reduce the computation time.

The advantages of PSO over the other artificial intelligence are: -

1. PSO choose the directions of next step by cooperation and competition.

2. Fewer parameters need to be set compared to Simulated Annealing method and

Genetic Algorithm method.

3. The computation speed of PSO is less sensitive to the complexity of the objective

functions.

4. It has efficient global search algorithm.

5. It is also derivative free.

The pseudo code for particle swarm optimization is: -

For each particle

Initialize particle

End

Do

For each particle

Calculate fitness value

If the fitness value is better than the best fitness value (Pbest) in history

Set current value as the new Pbest

End

Choose the particle with the best fitness value of all the particles as the Gbest

For each particle

Calculate particle velocity

Update particle position

End

While maximum iterations or minimum error criteria is not attained


The flow chart for PSO in shown in the Figure 3.5.

Yes

No

Figure 3.5 Flow chart of particle swarm optimization

Initialize the parameters (W, C1, C2)

Set iteration count iter = 1

Start

Update velocity and position of each particle

Evaluate fitness of each particle and update the Pbest and Gbest

Is

iter ≤ itermax?

Print the optimum values of Gbest

Stop

Evaluate initial fattiness of each particle and select Pbest and Gbest

Initialize the particles with random Position(X) and velocity (V)

iter=iter+1


PSO Parameters

The selection of the PSO parameters for general problems is listed in Table 3.4. Some of

these parameters may change based on different problems formulated by the users [35].

Table 3.4 PSO parameters for general problems

Parameters Conditions

1.Population size 20-40 works well for most of the optimization problem.

2.Dimension of particle Equals the number of control variables

3.Domains of particles Depends on the upper and lower bound of constraints

4.Acceleration factor 2 ≤ C1 = C2 ≤ 4

5.Stopping criteria

Iteration number

Difference between the current and previous best solution

If there is no improvement after a certain number of

iterations

3.3. Problem Formulation

3.3.1. Objective Function

The objective function considered in this thesis is minimizing the real power loss to find

the optimal rating of UPFC.

Minimize F=Ploss

The real power loss of the system equals the sum of the real power loss on each branch,

and it can be described as:

2 2: ( 2 cos )

Nl

loss ij i j i j ij

i j

F P G V V V V

(3.37)

Where: - Nl is the number of the branches,

G𝑖j is the conductance of the branch between bus i and bus j,


𝑉𝑖 is the voltage magnitude of bus i,

𝑉𝑗 is the voltage magnitude of bus j,

𝜃𝑖j is the difference of phase angle between bus i and bus j.

3.3.2. Constraints

The optimization problem has both equality constraints and inequality constraints to be

processed.

Equality Constraints

The equality constraints are the power balance equations, which can be described by the

equations (3.38).

1

1

( cos sin ) 0

( sin cos ) 0

PQ

PQ

N

gi di i j ij ij ij ij

k

N

gi di i j ij ij ij ij

k

P P V V G B

Q Q V V G B

(3.38)

Where Pgi is the real power generation at bus i,

Pdi is the real power demand at bus i,

Qgi is the reactive power generation at bus i,

Qdi is the reactive power demand at bus i.

Inequality Constraints

The inequality constraints are the ranges of the bus voltage magnitudes, reactive power

injection and the variables of the UPFC device.

i. min max

i i iV V V

ii. min max

gi gi giQ Q Q

iii. The UPFC constraints

a. 0.001 0.2cRV

b. 0.9 1.1vRV

c. 0 2*cR pi

d. 0 2*cR pi


The flow chart of PSO based UPFC sizing is shown in the Figure 3.6.

Yes

No

No

Figure 3.6 Flow chart of the PSO based UPFC sizing

Initialize the particles with random position(X) and velocity (V)

Input line, bus, and UPFC data

Is iter ≤ itermax?

The optimal size of the UPFC = Gbest particle

Start

Update the position and velocity of each particles

Stop

Input PSO parameters

iter =1

NR power flow analysis

Execute the objective function for each particle

Determine the Pbest, Gbest and save their values for all particles

iter=iter+1


Convergence Characteristics of PSO

The convergence characteristics of PSO algorithm can be shown in Figure 3.7 by using a

simple test function. The objective function is minimization of F(X) described in equation

(3.39) with its constraint in equations (3.40) and (3.41).

2 2 21 2 3(X) 10*(X 1) 20*(X 2) 30*(X 3)F (3.39)

31 2 5X XX (3.40)

21 2 32*X 0X X (3.41)

Figure 3.7 Convergence Characteristics of PSO algorithm

As shown in Figure 3.7, the PSO algorithm convergence after 100 iterations which implies

PSO has fast convergence characteristics. The best fitness function value were 9.3941 and

the best values for the variable X1, X2 and X3 were 0.43875, 1.4563 and 3.105 respectively.


CHAPTER FOUR

4. RESULT AND DISCUSSION

The power flow analysis for the network has two cases with four different scenarios. The

first case is power system network simulation under varying load demand without UPFC

and the second case is power system network simulation including UPFC under the same

varying load demand as first case. In both cases the bus voltage profile and total system

losses are recorded.

4.1. Case 1: Load Flow Analysis before Installing UPFC Device in the

System

Newton Raphson load flow analysis method is applied to find the bus voltage magnitudes

and power flows through the transmission lines. The load demand is varied from base load

demand by a step of 25% up to 75% (i.e. 25%, 50% and 75% above the base load demand).

4.1.1. Bus Voltage Profile

Scenario 1: Newton Raphson power flow simulation at base load demand.

The base load demand simulation is done to analyze the existing status of the power system

network. During the base load demand conditions, the Newton Raphson power flow

analysis was converged at the fifth iteration and the simulation result is presented in the

Table 4.1.

Table 4.1 Bus voltage result at base load demand.

Bus No Bus voltage (pu)

1 1.0300

2 0.9991

3 0.9918

4 1.0200

5 0.9744

6 0.9959

7 1.0000


8 1.0000

9 0.9967

10 1.0000

11 0.9649

12 0.9573

13 0.9664

14 1.0000


Figure 4.1 Bus voltage result at base load demand.

As we can observe from Figure 4.1 above, the bus voltage magnitude of bus 12 and bus 11

are the smallest voltage values as compared to all of the other bus voltage magnitudes and

therefore these two buses (bus 12 and 11) are the weak buses on the existing power system.

Scenario 2: Newton Raphson power flow at 25% load demand increment.

In this scenario the active and reactive power demand is increased by 25% and the

simulation result is tabulated in Table 4.2.

Table 4.2 Bus voltage result at 25% load demand increment


1 1.0300

2 0.9818

3 0.9783

4 1.0200

5 0.9617

6 0.9937

7 1.0000


8 1.0000

9 0.9854

10 1.0000

11 0.9454*

12 0.9355*

13 0.9502

14 1.0000

0.92

0.94

0.96

0.98

1

1.02

1.04

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Bus

Volt

age

mag

nit

ude

(pu)

Bus Number


Figure 4.2 Bus voltage result at 25% load demand increment.

During the 25% load demand increment, bus 11 and 12 have a voltage magnitude of 0.9454

pu and 0.9355 pu respectively (showed in bold face with * symbol in Table 4.2). These

voltage magnitudes are below the permissible voltage value (0.95 pu according to IEEE

standard).

Scenario 3: Newton Raphson power flow at 50% load demand increment.

Now in this scenario the load demand is increased by 50%. The Newton Raphson load flow

analysis result is presented in Table 4.3.

Table 4.3 Bus voltage result at 50% load demand increment.


1 1.0300

2 0.9567

3 0.9580

4 1.0200

5 0.9461*

6 0.9908

7 1.0000


8 1.0000

9 0.9687

10 1.0000

11 0.9195*

12 0.9072*

13 0.9294*

14 1.0000

0.88

0.9

0.92

0.94

0.96

0.98

1

1.02

1.04

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Bus

Volt

age

Mag

nit

ude

(pu)

Bus Number



During this scenario, four buses i.e. bus 5 having bus voltage value of 0.9461 pu, bus 11

having bus voltage value of 0.9195 pu, bus 12 having bus voltage value of 0.9072 pu and

bus 13 having bus voltage value of 0.9294 pu are out of the permissible voltage deviation

limit due to the increment of the load demand by 50%.

Scenario 4: Newton Raphson power flow simulation at 75% load demand increment.

Table 4.4 Bus voltage result at 75% load demand increment.


1 1.0300

2 0.9153*

3 0.9229*

4 1.0200

5 0.9245*

6 0.9869

7 1.0000


8 1.0000

9 0.9405*

10 1.0000

11 0.8800*

12 0.8648*

13 0.8990*

14 1.0000

0.84

0.86

0.88

0.9

0.92

0.94

0.96

0.98

1

1.02

1.04

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Bu

s V

otl

age

Mag

nit

ud

e (p

u)

Bus Number



During this scenario, most of the bus voltage magnitudes are below the permissible voltage

deviation limit.

From the Newton Raphson power flow simulation results in all of the above various

scenarios, we can observe that when the load demand of the customers is increased, the bus

voltage magnitude of the system is decreased. Thus, we can conclude that load demand

increment causes a decrease in voltage profile.

4.1.2. Active Power Loss and Reactive Power Loss

So far, we have recognized that, the increment of the load demand affects the bus voltage

profile. But this is not the only case. The increment of the load demand also affects the

power loss in the transmission line. The detail transmission lines power flow pre and post

of installing the UPFC device is presented in appendix B and C respectively.

0.75

0.8

0.85

0.9

0.95

1

1.05

1 2 3 4 5 6 7 8 9 10 11 12 13 14Bus

Volt

age

Mag

nit

ude

(pu)

Bus Number


Table 4.5 The effect of load demand increment on transmission power loss

System Condition Active Power Loss

(MW)

Reactive Power Loss

(MVAR)

At base load demand 7.6569 13.2002

At 25% load demand increment 13.9021 52.3995



As we can observe from Table 4.5 the load demand increment increases the transmission

power loss.

4.2. Case 2: Load Flow Analysis after Installing UPFC Device in the System

4.2.1. Optimal Placement and Rating of UPFC

Before installing the UPFC device, two basic questions should be answered here. The first

one is: - at what transmission line does the UPFC device should be placed? The UPFC

device should be placed at a transmission line were the bus voltage magnitude is smallest

i.e. between the weak buses [26, 27]. As we have observed before in the power flow

simulation results, the weakest buses in all of the four scenarios are bus 11 and bus 12.

Therefore, the UPFC device is installed between bus 11 and bus 12. Here one additional

bus (bus 15) is required in order to connect the UPFC between bus 11 and bus 12 and hence

the total number of buses will be 15 when the UPFC is added to the system. The second

basic question is: - what should be the rating of the UPFC device going to be installed in

the system? The rating of the UPFC devices going to be installed in the system is

determined by the particle swarm optimization techniques. As we have seen before on the

section dealing with modeling of the UPFC, there are four basic variables (series voltage

injected to the system, VcR, the angle of the series injected voltage, cR, shunt voltage, VvR

and the angle of the shunt voltage, vR) whose magnitude is tuned by PSO. Depending on

these values the rating of the UPFC device is determined.

4.2.2. Bus Voltage Profile

Scenario 1: Newton Raphson power flow simulation at base load demand.


During this scenario, the four variables of UPFC that are determined by the PSO have the

following magnitudes as indicated in Table 4.6.

Table 4.6 UPFC variables at base load demand

Variables VcR (pu) cR (degree) VvR (pu) vR (degree)

Magnitude 0.03953 107.43 1.035 17.843

Depending of these variables, the rating of the UPFC is determined to be 35 MVAR since

the UPFC PQ sending have a magnitude of 33.1≅ 35 MVAR.

Table 4.7 Bus voltage result at base load demand post UPFC.


1 1.0300

2 1.0111

3 1.0050

4 1.0200

5 0.9838

6 0.9981

7 1.0000

8 1.0000


9 1.0023

10 1.0000

11 1.0000

12 0.9979

13 0.9922

14 1.0000

15 0.9985

Figure 4.5 Bus voltage result at base load demand post UPFC.

0.96

0.97

0.98

0.99

1

1.01

1.02

1.03

1.04

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Bus

Volt

age

Mag

nit

ude

(pu)

Bus Number


Scenario 2: Newton Raphson power flow simulation result at 25% load demand

increment.



Table 4.8 UPFC variables at 25% load demand increment


Magnitude 0.033208 112.12 1.0501 23.839


the UPFC PQ sending have a magnitude of 48.19 MVAR ≅ 50 MVAR.

Table 4.9 Bus voltage result at 25% load demand increment post UPFC


1 1.0300

2 1.0041

3 1.0004

4 1.0200

5 0.9772

6 0.9971

7 1.0000

8 1.0000


9 1.0013

10 1.0000

11 1.0000

12 0.9971

13 0.9899

14 1.0000

15 0.9979

Figure 4.6 Bus voltage result at 25% load demand increment post UPFC.

0.95

0.96

0.97

0.98

0.99

1

1.01

1.02

1.03

1.04

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

BuS

Volt

age

Mag

nit

ude

(pu)

Bus Number



increment.








1 1.0300

2 0.9966

3 1.0200

4 1.0200

5 0.9696

6 0.9959

7 1.0000

8 1.0000


9 0.99995

10 1.0000

11 1.0000

12 0.9963

13 0.9877

14 1.0000

15 0.9973


0.94

0.95

0.96

0.97

0.98

0.99

1

1.01

1.02

1.03

1.04

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Bus

Volt

age

Mag

nit

ude

(pu)

Bus Number


Magnitude 0.031483 117.09 1.0674 30.21



increment.

For this scenario, the four variables of UPFC that are determined by the PSO have the







1 1.0300

2 0.9886

3 0.9848

4 1.0200

5 0.9608

6 0.9945

7 1.0000

8 1.0000


9 0.9980

10 1.0000

11 1.0000

12 0.9955

13 0.9853

14 1.0000

15 0.9966


0.92

0.94

0.96

0.98

1

1.02

1.04

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Bus

Volt

age

mag

nit

ude

(pu)

Bus Number


Magnitude 0.029781 122.29 1.0872 37.11


4.2.3. Comparison of Bus Voltage Profile

Table 4.14 Comparison of bus voltage profile pre and post UPFC device

Bus

No.

Bus Voltage Magnitude (pu)

At base load

demand

At 25% load demand

increment

At 50% load

demand increment

At 75% load

demand increment

Pre

UPFC

Post

UPFC

Pre

UPFC

Post

UPFC

Pre

UPFC

Post

UPFC

Pre

UPFC

Post

UPFC

1 1.0300 1.0300 1.0300 1.0300 1.0300 1.0300 1.0300 1.0300

2 0.9991 1.0111 0.9818 1.0041 0.9567 0.9966 0.9153* 0.9886

3 0.9918 1.005 0.9783 1.0004 0.9580 0.9938 0.9229* 0.9848

4 1.0200 1.0200 1.0200 1.0200 1.0200 1.0200 1.0200 1.0200

5 0.9744 0.9838 0.9617 0.9772 0.9461* 0.9696 0.9245* 0.9608

6 0.9959 0.9981 0.9937 0.9971 0.9908 0.9959 0.9869 0.9945

7 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000

8 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000

9 0.9967 1.0023 0.9854 1.0013 0.9687 0.9999 0.9405* 0.9980

10 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000

11 0.9649 1.0000 0.9454* 1.0000 0.9195* 1.0000 0.8800* 1.0000

12 0.9573 0.9979 0.9355* 0.9971 0.9072* 0.9963 0.8648* 0.9955

13 0.9664 0.9922 0.9502 0.9899 0.9294* 0.9877 0.8990* 0.9853

14 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000

As clearly shown in Table 4.14 above, all of the bus voltages are within the permissible

voltage deviation limit when the UPFC is added to the system.


At Base load demand: -

Figure 4.9 Comparison of bus voltage at base load demand

After the inclusion of 35 MVAR UPFC device within the system, the bus voltages

magnitudes are improved. Specially, the voltage magnitude of bus 5 is improved from

0.9744 pu to 0.9838pu, the voltage magnitude of bus 11 is improved from 0.9649 pu to

1.00 pu bus, the voltage magnitude of bus 12 is improved from 0.9573 pu to 0.9979 pu and

the voltage magnitude of bus 13 is improved from 0.9664 pu to 0.9922 pu.

0.92

0.94

0.96

0.98

1

1.02

1.04

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Bus

Volt

age

Mag

nit

ude

(pu)

Bus Number

Pre UPFC

Post UPFC


At 25% load demand increment: -

Figure 4.10 Comparison of voltage profile at 25% load demand increment

When 50 MVAR UPFC device is incorporated to the system, almost all of the bus voltages

are improved as shown in Figure 4.10. Specially, the voltage magnitude of bus 5 is

improved from 0.9617 pu to 0.9772 pu, the voltage magnitude of bus 11 is improved from

0.9454 pu to 1.00 pu bus, the voltage magnitude of bus 12 is improved from 0.9355 pu to

0.9971 pu and the voltage magnitude of bus 13 is improved from 0.9502 pu to 0.9899 pu.

At 50% load demand increment: -


0.88

0.9

0.92

0.94

0.96

0.98

1

1.02

1.04

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Bus

Volt

age

Mag

nit

ude

(pu)

Bus Number

Pre UPFCPost UPFC

0.8

0.85

0.9

0.95

1

1.05

1 2 3 4 5 6 7 8 9 10 11 12 13 14Bus

Volt

age

Mag

nit

ude

(pu)

Bus Number

Pre UPFC

Post UPFC


After the inclusion of 65 MVAR UPFC device within the system almost all of the bus

voltages are improved as shown in Figure 4.11. Specially, the voltage magnitude of bus 5

is improved from 0.9461 pu to 0.9696 pu, the voltage magnitude of bus 11 is improved

from 0.9195 pu to 1.00 pu bus, the voltage magnitude of bus 12 is improved from 0.9072

pu to 0.9963 pu and the voltage magnitude of bus 13 is improved from 0.9294 pu to 0.9877

pu.

At 75 % load demand increment: -


After the inclusion of 85 MVAR UPFC device within the system almost all of the bus

voltages are improved as shown in Figure 4.12. Specially, the voltage magnitude of bus 2

is improved from 0.9153 pu to 0.9886 pu, the voltage magnitude of bus 3 is improved from

0.9229 pu to 0.9848 pu, the voltage magnitude of bus 5 is improved from 0.9245 pu to

0.9608pu, the voltage magnitude of bus 11 is improved from 0.8800 pu to 1.00 pu bus, the

voltage magnitude of bus 12 is improved from 0.8648 pu to 0.9955 pu and the voltage

magnitude of bus 13 is improved from 0.8990 pu to 0.9853 pu.

4.2.4. Active Power and Reactive Power Loss

The active and reactive power loss of the system at different scenario when the UPFC

incorporated to the system is shown in Table 4.15.

0.75

0.8

0.85

0.9

0.95

1

1.05

1 2 3 4 5 6 7 8 9 10 11 12 13 14Bus

Vlo

ltag

e M

agnit

ude

(pu)

Bus Number

Pre UPFC

Post UPFC


Table 4.15 Transmission power loss post UPFC.

System Condition Active Power Loss

(MW)

Reactive Power Loss

(MVAR)

At base load demand 6.0335 8.2773




4.2.5. Comparison of Transmission Power Loss

Table 4.16 Comparison of transmission power loss pre and post UPFC.

System Condition

Active Power Loss

(MW)

Reactive Power Loss

(MVAR)

Pre

UPFC

Post

UPFC

Pre

UPFC

Post

UPFC

At base load demand 7.6569 6.0335 13.2002 8.2773

At 25% load demand increment 13.9021 9.7919 52.3995 33.822



Figure 4.13 Comparison on active power loss with and without UPFC

7.6569

13.9021

23.8557

41.4896

6.0335

9.7919

14.925

21.773

0

5

10

15

20

25

30

35

40

45

Base load 25% 50% 75%

Act

ive

Po

wer

(M

W)

Load Demand Increment

Active Power Loss

Pre UPFC

Post UPFC


As we can observe from Figure 4.13 after the inclusion of the UPFC device with its optimal

place and rating, the active power loss is decreased from 7.6569 MW to 6.0335 MW (i.e.

it is improved by 21.2% at base load demand). At 25% load demand increment the active

power loss is decreased from 13.9021 MW to 9.7919 MW (i.e. it is improved by 29.57%).

At 50% load demand increment the active power loss is decreased from 23.8557 MW to

14.925 MW (i.e. it is improved by 37.44%). At 75% load demand increment the active

power loss is decreased from 41.4896 MW to 21.773 MW (i.e. it is improved by 47.52%).

Figure 4.14 Comparison on reactive power loss pre and post UPFC

Figure 4.14 indicates, after the inclusion of the UPFC device with its optimal place and

rating the reactive power loss is improved by 37.3% at base load demand, improved by

35.45% at 25% load demand increment, improved by 39.54% at 50% load demand

increment and improved by 47.85% at 75% load demand increment.

The percentage improvement of the reactive power loss is higher than that of the active

power loss in all of the above four scenarios. That is why the voltage profile of all buses

are improved since the reactive power have a great impact on the bus voltage profile.

13.2002

52.3995

114.2284

222.7013

8.2773

33.822

69.056

116.13

0

50

100

150

200

250

Base Load 25% 50% 75%

Rea

ctiv

e P

ow

er (

MW

)

Load Demand Increment

Reactive Power Loss

Pre UPFC

Post UPFC


4.3. Financial Losses Analysis

The annual energy of power loss for the four scenarios evaluated in this study can be

estimated as follows:

Case 1: Financial Losses of the system pre installation of UPFC

Scenario 1: Annual MWh loss for 7.6569 MW

= (peak loss in MW) * 8760 h

=7.6569*8760=67092.84 MWh=67.076 GWh



= 13.9021*8760=121782.39 MWh=121.78 GWh



= 23.8557*8760=208975.93 MWh=208.98 GWh



=41.4896*8760=363448.89 MWh=363.45 GWh

Case 2: Financial Losses of the system post installation of UPFC



=6.0335*8760=52866.6 MWh=52.87 GWh


= (peak loss in MW)* 8760 h

= 9.7919*8760=85777.04 MWh=85.78 GWH




=14.925*8760=130743 MWh=130.74 GWh



=21.773*8760=190731.48 MWh=190.73 GWh

Cost of UPFC Rating

Although FACTS controllers can offer high-speed control for enhancing electric power

system, one significant disadvantage of power electronic based controllers is more expense

per unit of rating than that of similar conventional equipment. Table 4.17 shows the costs

of the various FACTS controllers [36].

Table 4.17 Cost comparison of different FACTS controller

FACTS Controller Expense (US $)

DSTATCOM $34 per kVAR

SVC $26 per kVAR

TCSC $47 per kVAR

UPFC $37 per kVAR

Based on Table 4.17 and the exchange rate of Commercial Bank of Ethiopia on December

12, 2018 G.C one US Dollar =27.22 Ethiopian Birr (ETB), the costs for UPFC in the four

scenarios are tabulated in Table 4.18.

Table 4.18 Cost of UPFC in the four scenarios

Scenarios Rating

(MVAR)

Cost per

kVAR

Total cost

($)

Total cost (ETB)

Scenario 1 35 $37 1295000 35.2499 million





Cost Implication

The cost evaluation is based on the ETB/kWh energy rates for Ethiopian Electric Utility,

under the new power tariff. The cost of energy is rated at 0.55 ETB/kWh or 550 ETB/MWh,

by taking the average of all the tariff class energy unit costs (ETB/kWh). Using the 550

ETB/MWh, the total amount of annual financial loss due to power loss in each scenario is

estimated as follows:

Case 1: Cost implication of the system pre installation of UPFC

For scenario 1: the annual financial loss for a year is 67092.84 MWh *550 ETB/MWH i.e.

36901062 ETB; approximately amounted to 36.9011 million ETB.

For scenario 2: the annual financial loss for a year is 121782.39 MWh *550 ETB/MWH

i.e. 66980314.5 ETB; approximately amounted to 66.9803 million ETB.





Case 2: Cost implication of the system post installation of UPFC

For scenario 1: the annual financial loss for a year is 52866.6 MWh *550 ETB/MWh i.e.




For scenario 3: the annual financial loss for a year is 130743 MWh *550 ETB/MWh i.e.





Table 4.19 Cost comparison pre and post UPFC

Scenario Cost pre

UPFC

(ETB/year)

A

Cost post

UPFC

(ETB/year)

B

Saving

(ETB/year)

(A – B)

Cost of

UPFC

(ETB/year)

1 36901062 29076630 7824432 35249900

2 66980314.5 47177372 19802942.5 50357000

3 114936761.5 71908650 43028111.5 65464100

4 199896889.5 104902314 94994575.5 85606900

Methods of financial losses analysis

The economic analysis in this study used standard financial measures, such as the Payback

Period and Net Present Value (NPV) [37].

i. Payback Period

The Payback Period is the number of months of benefits required for the project to

breakeven point. The payback time can be estimated by the following equation.

Payback Period (Months) = (Net investment/Net annual return) *12

This method determines the period after which the initial investment is recovered. A project

is only carried out if the payback time is lower than a certain threshold defined by the

company. Typically used thresholds for the payback time vary between 2 to 4 years.

However it is inferior to the NPV method, as it takes into account any cash flows after the

payback time.

Therefore, referring the above table the cost benefit analysis using Payback Period method

is presented as follows:

Payback Period for scenario 1= Cost of UPFC/Saving =35249900/7824432= 4.5 years

Payback Period for scenario 2= Cost of UPFC/Saving =50357000/19802942.5= 2.5 years

Payback Period for scenario 3= Cost of UPFC/Saving =65464100/43028111.5= 1.5 years


Payback Period for scenario 4= Cost of UPFC/Saving =85606900/949945575.5= 0.9 year

ii. Net Present Value (NPV) method

Net Present Value (NPV) is the value of all future cash flows (positive and negative) over

the entire life of an investment discounted to the present.

In the NPV method, all marginal cash flows of a project are taken into account during its

entire lifetime. Cash flows in upcoming years are discounted to t = 0 by using an

appropriate rate called the Opportunity Cost of Capital (OCC), hurdle rate, discount rate or

required rate of return, which results in the present value of these cash flows. The NPV

method is typically used for large capital projects.

The Net Present Value of these cash flows (if the salvage value of the equipment is assumed

to be negligible) is calculated by:

0

( )(1 r)

n

tt

CFtPV

(4.1)

0 – NPV PV C (4.2)

Where,

CFt =the net cash flow at time t

C0 = the initial investment

r = the cost of capital (discount rate) = 12%

t = the number of years = 0, 1, 2, 3, …, n

n = the life time of the investment = 20 years

Therefore, the cost benefit analysis using Net Present Value (NPV) method for the four

various scenarios are presented in Table 4.20 - Table 4.23.


For scenario 1:

Table 4.20 NPV analysis of installation UPFC for scenario 1

Ye

ars

Financial loss

without UPFC (in

millions ETB)

A

Financial loss

with UPFC (in

millions ETB)

B

Net cash flow

(CFt) (in

millions ETB)

A - B

PV (in

millions

ETB)

NPV (in

millions

ETB)

0 36.9011 29.0766 7.8244 -35.2499 -35.2499

1 36.9011 29.0766 7.8244 6.9861 -28.2638

2 36.9011 29.0766 7.8244 6.2376 -22.0262

3 36.9011 29.0766 7.8244 5.5693 -21.4569

4 36.9011 29.0766 7.8244 4.9726 -16.4844

5 36.9011 29.0766 7.8244 4.4398 -12.0446

6 36.9011 29.0766 7.8244 3.9641 -8.0805

7 36.9011 29.0766 7.8244 3.5394 -4.5411

8 36.9011 29.0766 7.8244 3.1602 -1.3809

9 36.9011 29.0766 7.8244 2.8216 1.4406

10 36.9011 29.0766 7.8244 2.5193 3.9599

11 36.9011 29.0766 7.8244 2.2493 6.2092

12 36.9011 29.0766 7.8244 2.0083 8.2176

13 36.9011 29.0766 7.8244 1.7932 10.01072

14 36.9011 29.0766 7.8244 1.6010 11.6118

15 36.9011 29.0766 7.8244 1.4295 13.0412

16 36.9011 29.0766 7.8244 1.2763 14.3176

17 36.9011 29.0766 7.8244 1.1396 14.4572

18 36.9011 29.0766 7.8244 1.0175 15.4747

19 36.9011 29.0766 7.8244 0.9085 16.3831

20 36.9011 29.0766 7.8244 0.8111 17.1943


Figure 4.15 NPV analysis of installation UPFC for scenario 1

As we can observe from Figure 4.15 above, the UPFC rating in this scenario are capable

of providing positive cash flows after nine years of service but funds accumulated after the

end of years of service, is 17.1943 million ETB.

For scenario 2:


Yea

rs

Financial loss pre

UPFC (in

millions ETB)

A

Financial loss

post UPFC (in

millions ETB)

B

Net cash flow

(CFt) (in

millions ETB)

A - B

PV (in

millions

ETB)

NPV (in

millions

ETB)

0 66.9803 47.1773 19.8029 -50.3570 -50.3570

1 66.9803 47.1773 19.8029 17.6812 -32.6758

2 66.9803 47.1773 19.8029 15.7869 -16.8889

3 66.9803 47.1773 19.8029 14.0953 -2.7936

4 66.9803 47.1773 19.8029 12.5851 9.7915

5 66.9803 47.1773 19.8029 11.2367 21.0282

-40

-30

-20

-10

0

10

20

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

NP

V (

mil

lio

n E

TB

)

Years


6 66.9803 47.1773 19.8029 10.0328 31.0610

7 66.9803 47.1773 19.8029 8.9578 40.0188

8 66.9803 47.1773 19.8029 7.9981 48.0169

9 66.9803 47.1773 19.8029 7.1411 55.1540

10 66.9803 47.1773 19.8029 6.3760 61.5340

11 66.9803 47.1773 19.8029 5.6929 67.2269

12 66.9803 47.1773 19.8029 5.0829 72.3098

13 66.9803 47.1773 19.8029 4.5383 76.8481

14 66.9803 47.1773 19.8029 4.0521 80.9002

15 66.9803 47.1773 19.8029 3.6179 84.5181

16 66.9803 47.1773 19.8029 3.2303 87.7484

17 66.9803 47.1773 19.8029 2.8842 90.6326

18 66.9803 47.1773 19.8029 2.5752 93.2078

19 66.9803 47.1773 19.8029 2.2993 95.5071

20 66.9803 47.1773 19.8029 2.0529 97.3401



As we can observe from Figure 4.16, the UPFC rating in this scenario are capable of

providing positive cash flows after four years of service and funds accumulated after the


For scenario 3:


Ye

ars

Financial loss pre

UPFC (in

millions ETB)

A

Financial loss

post UPFC (in

millions ETB)

B

Net cash flow

(CFt) (in

millions ETB)

A - B

PV (in

millions

ETB)

NPV (in

millions

ETB)

0 114.9368 71.9086 43.0281 -65.4641 -65.4641

1 114.9368 71.9086 43.0281 38.4180 -27.0461

2 114.9368 71.9086 43.0281 34.3017 7.2556

3 114.9368 71.9086 43.0281 30.6266 10.3183

4 114.9368 71.9086 43.0281 27.3451 37.6634

5 114.9368 71.9086 43.0281 24.4153 62.0787

6 114.9368 71.9086 43.0281 21.7994 83.8781

7 114.9368 71.9086 43.0281 19.4637 103.3418

8 114.9368 71.9086 43.0281 17.3783 120.7202

-60

-40

-20

0

20

40

60

80

100

120

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

NP

V (

mil

lio

n E

TB

)

Years


9 114.9368 71.9086 43.0281 15.5164 136.2365

10 114.9368 71.9086 43.0281 13.8539 150.0904

11 114.9368 71.9086 43.0281 12.3696 161.1347

12 114.9368 71.9086 43.0281 11.0442 172.1789

13 114.9368 71.9086 43.0281 9.8609 182.0398

14 114.9368 71.9086 43.0281 8.8044 190.8443

15 114.9368 71.9086 43.0281 7.8611 198.7053

16 114.9368 71.9086 43.0281 7.0188 205.7241

17 114.9368 71.9086 43.0281 6.2668 211.9909

18 114.9368 71.9086 43.0281 5.5954 217.5863

19 114.9368 71.9086 43.0281 4.9959 218.0862

20 114.9368 71.9086 43.0281 4.4606 222.5467


As we can observe from Figure 4.17 above, the UPFC rating in this scenario are capable

of providing positive cash flows after two years of service and funds accumulated after the


-100

-50

0

50

100

150

200

250

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

NP

V (

mil

lio

n E

TB

)

Years


For scenario 4:


Ye

ars

Financial loss pre

UPFC (in

millions ETB)

A

Financial loss

post UPFC (in

millions ETB)

B

Net cash flow

(CFt) (in

millions ETB)

A - B

PV (in

millions

ETB)

NPV (in

millions

ETB)

0 199.8969 104.9023 94.9946 -85.6069 -85.6069

1 199.8969 104.9023 94.9946 84.8166 -0.7903

2 199.8969 104.9023 94.9946 67.6153 66.8249

3 199.8969 104.9023 94.9946 60.3708 127.1957

4 199.8969 104.9023 94.9946 53.9025 181.0982

5 199.8969 104.9023 94.9946 48.1272 229.2254

6 199.8969 104.9023 94.9946 42.9707 272.1961

7 199.8969 104.9023 94.9946 38.3667 310.5628

8 199.8969 104.9023 94.9946 34.2560 344.8188

9 199.8969 104.9023 94.9946 30.5857 375.4045

10 199.8969 104.9023 94.9946 27.3087 402.7132

11 199.8969 104.9023 94.9946 24.3827 427.0960

12 199.8969 104.9023 94.9946 21.7703 448.8663

13 199.8969 104.9023 94.9946 19.4378 468.3040

14 199.8969 104.9023 94.9946 17.3552 485.6592

15 199.8969 104.9023 94.9946 15.4957 501.1549

16 199.8969 104.9023 94.9946 13.8354 514.9903

17 199.8969 104.9023 94.9946 12.3531 527.3433

18 199.8969 104.9023 94.9946 11.0296 528.4729

19 199.8969 104.9023 94.9946 9.8478 538.3207

20 199.8969 104.9023 94.9946 8.7927 547.1133



As we can observe from Figure 4.18, the UPFC rating in this scenario are capable of

providing positive cash flows after one years of service and funds accumulated after the


Table 4.24 Economic Analysis of Installation of UPFC based on Payback period and NPV`

Scenarios Payback Period

(In Years)

NPV

(In Million ETB)

1 4.5 17.1943

2 2.5 97.3401

3 1.5 222.5467

4 0.9 547.1133

From Table 4.24 above, it is clearly observed that the payback periods are 4.5, 2.5, 1.5 and

0.9 years for scenario 1, 2, 3 and 4 respectively. Therefore, the installed UPFC rating in

the 4th scenario provides early recovery of installation cost and implies that the UPFC

installation is most efficient during the 75% load demand increment since the power loss

improvement in this case is greater than all of the other scenarios.

-200

-100

0

100

200

300

400

500

600

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

NP

V (

mil

lio

n E

TB

)

Years


CHAPTER FIVE

5. CONCLUSION AND RECOMMENDATION

5.1. Conclusion

This thesis aimed to minimize the transmission line power loss and enhancement of the bus

voltage profile for the Ethiopian North Western Region Transmission System network. The

power flow analysis by using Newton Raphson method was adopted. From the power flow

analysis, it was clearly identified that bus 11 and 12 were the weak buses on the existing

power system. Therefore, the optimal place for the UPFC device was between bus 11 and

12 and its optimal rating was determined by particle swarm optimization technique. The

result has confirmed that: - a 3.51% and 2.17% enhancement at base load demand, 5.46%

and 6.21% enhancement at 25% load demand increment, 8.05% and 8.9% enhancement at

50% load demand increment and 12% and 13.09% enhancement at 75% load demand

increment was achieved for bus 11 and 12 respectively. A 21.2%, 29.57%, 37.44% and

47.52% improvement was achieved on active power loss minimization at base load

demand, 25%, 50% and 75% load demand increment respectively. In addition, a 37.3%,

35.4%, 39.54% and 47.85% improvement was achieved on reactive power loss

minimization at base load demand, 25%, 50% and 75% load demand increment

respectively. The payback period and net present value methods of financial measures are

adopted and those methods implied that the UPFC is cost effective if it is installed in the

case study area.

Since the voltage profile in the system has a relation with power loss, the enhancement of

the voltage profile minimizes the power loss of the system. Therefore, installing the UPFC

in a power transmission system has a great advantage on improving the system condition

and enhances the voltage profile as a result it improves the performance of the system.


5.2. Recommendation

UPFC device in general has a high cost compared to classical power flow controller devices

due to the great technology improvement involved on it. But its cost can be compromised

by its unique properties which can controls all the transmission line parameters. This fact

is taken in to account in this thesis. Therefore, the researcher recommends the utility to

install the UPFC at the specified place with its optimal rating.

Further studies can be done on the application of UPFC for loss minimization and voltage

profile enhancement on the full Ethiopian transmission power system network and for other

countries power system also.

This study was focused only on the steady state power system condition. Therefore, further

research can be done on capability of UPFC on power loss minimization and voltage profile

improvement during transient condition of a power system.


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APPENDICES

Appendix A: Variation of Active and Reactive Power Demand

Bus

No.

Active and Reactive Power Demand (MW and MVAR)

At base load

demand

At 25% load

demand increment

At 50% load

demand increment

At 75% load

demand increment

Pd Qd Pd Qd Pd Qd Pd Qd

3 65.53 30.76 81.912 8.4500 98.295 46.14 114.68 53.830

8 16.12 8.220 20.150 10.275 24.180 12.33 28.210 4.3850

9 3.450 1.700 4.3125 2.1250 5.1750 2.550 6.0375 2.9750

10 17.85 8.080 22.313 10.100 26.775 12.12 31.238 14.140

11 37.00 11.80 46.250 14.750 55.500 17.70 64.750 20.650

12 4.000 1.960 5.0000 2.4500 6.0000 2.940 7.0000 3.4300

13 17.94 8.690 22.425 10.862 26.910 13.035 31.395 15.208

14 13.36 6.460 16.700 8.0750 20.040 9.690 23.380 11.305

Appendix B: Transmission line power flows during different loading

conditions without UPFC device

Appendix B1: Transmission line power flows at base load demand

TL No. PQ sending (pu) PQ receiving (pu) PQ Loss (pu)

1-2 1.115600 - 0.148050i -1.0916 + 0.083067i 0.023968 - 0.064985i

2-3 1.0797 - 0.13464i -1.0797 - 0.062222i 2.2204e-16 - 0.19686i

4-5 0.400000 - 0.126010i -0.3897 + 0.115i 0.010300 - 0.011002i

5-3 -0.21108 + 0.13593i 0.21108 - 0.14569i 0.00000 - 0.0097691i

5-6 -0.036725 + 0.17014i 0.037902 - 0.1591i 0.0011763 + 0.011032i

6-7 0.000178 + 0.14294i 3.1017e-15 - 0.1235i 0.00017836 + 0.019385i

6-8 -0.054421 + 0.020028i 0.054421 +0.004197i 6.9389e-18 + 0.024225i

8-9 -0.038198 + 0.007817i 0.038228 + 0.02118i 3.0216e-05 + 0.028995i

3-9 0.038437 + 0.045273i -0.038228 - 0.02118i 0.00020862 + 0.024087i

3-10 0.163400 + 0.1062i -0.1612 - 0.092953i 0.0021951 + 0.013251i

3-11 0.645540 - 0.017673i -0.62857 + 0.002863i 0.016978 - 0.01481i


11-12 0.178810 - 0.068973i -0.178 + 0.0808i 0.00081084 + 0.011827i

11-13 0.415260 + 0.08311i -0.41334 - 0.077836i 0.0019108 + 0.0052733i

13-14 0.043345 + 0.25784i -0.04 - 0.24303i 0.0033447 + 0.014809i

Appendix B2: Transmission line power flows at 25% load demand increment


1-2 1.5378 - 0.3052i -1.4912 + 0.14948i 0.046524 - 0.15572i

2-3 1.4932 - 0.20744i -1.4932 - 0.24511i -2.2204e-16 - 0.45255i

4-5 0.4000 - 0.19663i -0.3883 + 0.18119i 0.011699 - 0.015445i

5-3 -0.37131 + 0.046562i 0.37131 - 0.073387i 0.000000 - 0.026825i

5-6 -0.06164 + 0.24256i 0.064205 - 0.23591i 0.0025653 + 0.0066461i

6-7 0.00044469 + 0.2194i 7.494e-16 - 0.20088i 0.00044469 + 0.01854i

6-8 -0.060527 + 0.01928i 0.060527 - 0.020262i 0.000000 - 0.00097776i

8-9 -0.06499 - 0.012836i 0.06509 + 0.039402i 9.997e-05 + 0.026566i

3-9 0.065657 + 0.0618i -0.06509 - 0.039402i 0.00056791 + 0.02239i

3-10 0.2062 + 0.18957i -0.2015 - 0.18409i 0.0046963 + 0.0054824i

3-11 0.81787 - 0.012414i -0.7899 - 0.025028i 0.027975 - 0.037441i

11-12 0.22384 - 0.09107i -0.2225 + 0.101i 0.0013351 + 0.00993i

11-13 0.52294 + 0.13735i -0.51969 - 0.14209i 0.0032441 - 0.0047419i

13-14 0.057192 + 0 .36709i -0.05 - 0.36344i 0.0071915 + 0.0036502i



1-2 1.9971 - 0.56846i -1.9154 + 0.27161i 0.081624 - 0.29685i

2-3 1.9152 - 0.35008i -1.9152 - 0.44839i 0.000000 - 0.79848i

4-5 0.4000 - 0.28367i -0.38579 + 0.26038i 0.014214 - 0.023289i

5-3 -0.51471 - 0.012635i 0.51471 - 0.039469i 0.000000 - 0.052103i

5-6 -0.087777 + 0.33016i 0.092797 - 0.33114i 0.0050197 - 0.0009831i

6-7 0.0009377 + 0.31323i -1.305e-15 - 0.29623i 0.00093775 + 0.017004i

6-8 -0.084405 + 0.027475i 0.084405 - 0.029393i 0.000000 - 0.0019172i


8-9 -0.094453 - 0.043251i 0.094699 + 0.064937i 0.00024629 + 0.021686i

3-9 0.095965 + 0.08434i -0.094699 - 0.064937i 0.0012657 + 0.019403i

3-10 0.25167 + 0.30528i -0.2418 - 0.31572i 0.0098738 - 0.010445i

3-11 0.99877 + 0.0028597i -0.95529 - 0.072194i 0.043483 - 0.069335i

11-12 0.26905 - 0.11382i -0.267 + 0.1212i 0.002054 + 0.0073783i

11-13 0.63449 + 0.21152i -0.62924 - 0.23117i 0.0052493 - 0.019652i

13-14 0.074237 + 0.50117i -0.06 - 0.51774i 0.014237 - 0.016567i



1-2 2.5331 - 1.048i -2.3908 + 0.50727i 0.14231 - 0.54076i

2-3 2.3972 - 0.62792i -2.3972 - 0.80299i 0.00000 - 1.4309i

4-5 0.4000 - 0.40385i -0.38088 + 0.36543i 0.019124 - 0.03842i

5-3 -0.66026 - 0.13526i 0.66026 + 0.042416i 0.00000 - 0.092844i

5-6 -0.11615 + 0.448i 0.12591 - 0.46355i 0.0097568 - 0.015556i

6-7 0.0019177 + 0.4419i -1.471e-15 - 0.42791i 0.0019177 + 0.013986i

6-8 -0.11005 + 0.03996i 0.11005 - 0.043319i 0.000000 - 0.0033569i

8-9 -0.12918 - 0.094059i 0.12975 + 0.10518i 0.0005716 + 0.011121i

3-9 0.13249 + 0.11865i -0.12975 - 0.10518i 0.0027443 + 0.013471i

3-10 0.30458 + 0.48435i -0.2821 - 0.53329i 0.022485 - 0.048937i

3-11 1.1973 + 0.039496i -1.1299 - 0.15797i 0.067366 - 0.11847i

11-12 0.31459 - 0.1377i -0.3115 + 0.1414i 0.0030878 + 0.0036979i

11-13 0.75497 + 0.32542i -0.74631 - 0.37024i 0.0086634 - 0.044818i

13-14 0.098806 + 0.68524i -0.07 - 0.74329i 0.028806 - 0.058056i


Appendix C: Transmission line power flows during different loading

conditions with UPFC device

Appendix C1: Transmission line power flows at base load demand


1-2 1.0993 - 0.11031i -1.0797 + 0.13464i 0.019621 + 0.024324i

2-3 1.0797 - 0.13464i -1.0797 - 0.062222i 2.2204e-16 - 0.19686i

4-5 0.4000 - 0.073909i -0.39036 + 0.06508i 0.0096372 -0.0088293i

5-3 -0.21108 + 0.13593i 0.21108 - 0.14569i 0.000000 -0.0097691i

5-6 -0.053853 + 0.10659i 0.05438 - 0.093447i 0.00052768 +0.013147i

6-7 4.0423e-05 + 0.07342i 6.5919e-16 -0.05358i 4.0423e-05 +0.01984i

6-8 -0.054421 + 0.020028i 0.054421 + 0.004197i 6.9389e-18 +0.024225i

8-9 -0.054421 + 0.035226i 0.054488 -0.005358i 6.7414e-05 +0.029867i

3-9 0.054729 + 0.019103i -0.054488 +0.00536i 0.00024055 +0.02446i

3-10 0.16281 + 0.033711i -0.1612 - 0.018434i 0.0016076 + 0.015278i

3-11 0.65109 + 0.1551i -0.62466 - 0.21429i 0.026431 - 0.059191i

11-15 -0.122 -0.051443i 0.122 + 0.051017i -1.3878e-17 – 0.00426i

15-12 -0.122 - 0.051017i 0.122 + 0.0608i 0.000000 + 0.0097829i

11-13 0.41216 - 0.048329i -0.41043 + 0.056044i 0.0017328 + 0.007715i

13-14 0.04043 + 0.12396i -0.04 - 0.1003i 0.00042969 + 0.02366i

Appendix C2: Transmission line power flows at 25% load demand increment


1-2 1.4967 - 0.18708i -1.4601 + 0.20522i 0.036555 + 0.018136i

2-3 1.4601 - 0.20522i -1.4601 - 0.16134i 0.000000 - 0.36655i

4-5 0.4000 - 0.11076i -0.38993 + 0.10049i 0.010074 - 0.010269i

5-3 -0.34597 + 0.14231i 0.34597 - 0.16429i 0.000000 - 0.021985i

5-6 -0.083231 + 0.1417i 0.08428 - 0.13023i 0.0010485 + 0.011472i

6-7 9.3939e-05 +0.1066i 4.486e-15 - 0.086922i 9.3939e-05 + 0.01966i

6-8 -0.084374 +0.02365i 0.084374 - 0.000470i 1.3878e-17 + 0.023179i


8-9 -0.084374 +0.00898i 0.084517 + 0.02062i 0.0001431 + 0.029611i

3-9 0.085175 + 0.04369i -0.084517 - 0.02062i 0.00065762 + 0.02307i

3-10 0.20423 + 0.071272i -0.2015 - 0.059441i 0.0027255 + 0.011832i

3-11 0.82475 + 0.21067i -0.78155 - 0.32024i 0.043193 - 0.10957i

11-15 -0.0775 - 0.071402i 0.0775 + 0.071169i 1.3878e-17 - 0.000233i

15-12 -0.0775 - 0.071169i 0.0775 + 0.0810i 0.000000 + 0.0098311i

11-13 0.51593 - 0.068987i -0.5132 + 0.069717i 0.0027242 + 0.0007303i

13-14 0.050705 + 0.15528i -0.0500 - 0.13241i 0.000705 + 0.02287i



1-2 1.9077 - 0.3077i -1.8478 + 0.31733i 0.059998 + 0.0096372i

2-3 1.8478 - 0.31733i -1.8478 - 0.28423i 0.000000 - 0.60156i

4-5 0.4000 - 0.15293i -0.38923 + 0.1404i 0.010766 - 0.012492i

5-3 -0.48129 + 0.13869i 0.48129 - 0.17872i 0.000000 - 0.04003i

5-6 -0.11243 + 0.18228i 0.11427 - 0.17332i 0.0018443 + 0.008956i

6-7 0.000185 + 0.14555i 1.936e-15 - 0.12619i 0.000185 + 0.01936i

6-8 -0.11446 + 0.02777i 0.11446 - 0.0060986i -1.3878e-17 + 0.02167i

8-9 -0.11446 - 0.02445i 0.11475 + 0.053569i 0.0002931 + 0.029119i

3-9 0.11615 + 0.074205i -0.11475 - 0.053569i 0.0014027 + 0.020636i

3-10 0.2462 + 0.11885i -0.2418 - 0.11218i 0.004404 + 0.006665i

3-11 1.0041 + 0.2699i -0.93875 - 0.44609i 0.065356 - 0.17619i

11-15 -0.033 - 0.091553i 0.033 + 0.091369i 1.3878e-17 - 0.0001847i

15-12 -0.033 - 0.091369i 0.033 + 0.1012i -2.0817e-17 + 0.00983i

11-13 0.62 - 0.090913i -0.61605 + 0.083047i 0.0039458 - 0.0078664i

13-14 0.061054 + 0.18695i -0.06 - 0.16507i 0.0010539 + 0.021883i



1-2 2.336 - 0.48194i -2.2446 + 0.48025i 0.091412 - 0.0016909i


2-3 2.2446 - 0.48025i -2.2446 - 0.43629i 4.4409e-16 - 0.91653i

4-5 0.4000 - 0.20159i -0.38818 + 0.18577i 0.011819 - 0.015821i

5-3 -0.61717 + 0.12317i 0.61717 - 0.18752i 0.000000 - 0.064354i

5-6 -0.14143 + 0.22936i 0.14444 - 0.22405i 0.00301 + 0.0053106i

6-7 0.0003335 + 0.19152i 1.2768e-15 -0.17263i 0.00033353 + 0.01889i

6-8 -0.14477 + 0.03253i 0.14477 - 0.012851i 0.0000000 + 0.019679i

8-9 -0.14477 - 0.066876i 0.14532 + 0.095157i 0.0005532+ 0.028281i

3-9 0.14795 + 0.11185i -0.14532 - 0.09516i 0.0026262 + 0.016695i

3-10 0.28903 + 0.17844i -0.2821 - 0.17954i 0.0069303 - 0.001093i

3-11 1.1904 + 0.33352i -1.0963 - 0.59631i 0.094163 - 0.26279i

11-15 0.0115 - 0.1119i -0.0115 + 0.11162i 6.9389e-18 - 0.0002803i

15-12 0.0115 - 0.11162i -0.0115 + 0.1214i 0.0000000 + 0.0097831i

11-13 0.72438 - 0.11413i -0.71898 + 0.09603i 0.0054014 - 0.018101i

13-14 0.07148 + 0.21897i -0.07 - 0.19828i 0.0014799 + 0.020689i


Appendix D: MATLAB code of PSO for determining variables of the UPFC

device

% POWER LOSS MINIMIZATION AND VOLTAGE PROFILE IMPROVEMENT

% FOR THE CASE OF ETHIOPIAN NWRTS NETWORK

%=========MSc THESIS PERPARED BY ASRESAHEGN T.===========

clc

clear

tic

iter=0;

iteration=200;

nvars = 4; %Number of variables to be optimized

N = 50; %Number of Particles or Swarm size

% Acceleration constants

c1 = 2;

c2 = 2;

% Inertia Weight

w_max=0.9;

w_min=0.4;

w_temp(1)=w_max;

busdata; %Loading the data for bus14

% Initialization of Swarm & velocity

Swarm=[unifrnd(0.001,0.2,N,1),unifrnd(0,2*pi,N,1),unifrnd(0.9,1.1,N,1),

unifrnd(0,2*pi,N,1)];

% Initialize velocity

Velocity =[unifrnd(-0.003,0.003,N,1),unifrnd(-0.003,0.003,N,1),

unifrnd(-0.003,0.003,N,1), unifrnd(-0.003,0.003,N,1)];

for i=1:N

Vcr=Swarm(i,1);

sourse(1,1)=Vcr;

Tcr=Swarm(i,2);

sourse(1,2)=Tcr;

Vvr=Swarm(i,3);

sourse(1,3)=Vvr;

Tvr=Swarm(i,4);

sourse(1,4)=Tvr;

eval(['initial_results_',num2str(i),'=finalNRrun14']);

% Penalty for bus voltage violation

bus_inf=VM;

for bus_num=1:14

if bus_inf1(bus_num)>1.10

penalty_Vl(bus_num)=10000*(bus_inf1(bus_num)-1.10)^2;

elseif bus_inf1(bus_num)<0.95


else

penalty_Vl(bus_num)=0;

end

end

penalty_Vl_violation=sum(penalty_Vl);

% penality for UPFC parameters (Vcr)

bus_inf2=source(1,1);

for bus_num=1,1


penalty_Vcr(bus_num)=10000*(bus_inf2(bus_num)-0.20)^2;




else

penalty_Vcr(bus_num)=0;

end

end

penalty_Vcr_violation=sum(penalty_Vcr);

% penality for UPFC parameters (Tcr)


for bus_num=1,2

if bus_inf3(bus_num)>2*pi

penalty_Tcr(bus_num)=10000*(bus_inf3(bus_num)-2*pi)^2;


penalty_Tcr(bus_num)=10000*(bus_inf3(bus_num)-0.0)^2;

else

penalty_Tcr(bus_num)=0;

end

end

penalty_Tcr_violation=sum(penalty_Tcr);

% penality for UPFC parameters (Vvr)


for bus_num=1,3


penalty_Vvr(bus_num)=10000*(bus_inf4(bus_num)-1.1)^2;



else

penalty_Vvr(bus_num)=0;

end

end

penalty_Vvr_violation=sum(penalty_Vcr);

% penality for UPFC parameters (Tvr)


for bus_num=1,4


penalty_Tvr(bus_num)=10000*(bus_inf5(bus_num)-2*pi)^2;

elseif bos_inf(bus_num)<0.0

penalty_Tvr(bus_num)=10000*(bus_inf5(bus_num)-0.0)^2;

else

penalty_Tvr(bus_num)=0;

end

end

penalty_Tvr_violation=sum(penalty_Tvr);

losses(i)=PLoss_initial;

Obj_fun_initial=losses(i)+penalty_Vl_violation+penalty_Vcr_violation+pe

nalty_Vvr_violation+penalty_Tvr_violation;

end

%% Initialize best position (Pbest) and global best postion (Gbest)

matrix

Pbest=Swarm;

Val_Pbest=Obj_fun_initial;

% finding best particle in initial population

[Val_Gbest,m]=min(Val_Pbest);

Gbest=Swarm(m,:); %used to keep track of the best particle ever

Gbest_calc=repmat(Swarm(m,:),N,1);

%% STARRTING THE PSO LOOP

for iter=1:iteration

% Update the value of the inertia weight w


if iter <= iteration

w_temp(iter)=w_max + (((w_min-w_max)/iteration)*iter); %

Change inertia weight

end

% generate random numbers

R1=rand(N,nvars);

R2=rand(N,nvars);

Velocity=(w_temp(iter)*Velocity+c1*R1.*(Pbest-

Swarm)+c2*R2.*(Gbest_calc-Swarm));

for v_iter=1:nvars

if v_iter==nvars

Outstep=Velocity(:,v_iter)>0.003;

Velocity(find(Outstep),v_iter)=0.003;

Outstep=Velocity(:,v_iter)<-0.003;

Velocity(find(Outstep),v_iter)=-0.003;

else

Outstep=Velocity(:,v_iter)>0.01;

Velocity(find(Outstep),v_iter)=0.01;

Outstep=Velocity(:,v_iter)<-0.01;

Velocity(find(Outstep),v_iter)=-0.01;

end

end

% update positions of particles

Swarm=Swarm+Velocity; % evaluate a new swarm

for k=1:N

Vcr=Swarm(k,1);

sourse(1,1)=Vcr;

Tcr=Swarm(k,2);

sourse(1,2)=Tcr;

Vvr=Swarm(k,3);

sourse(1,3)=Vvr;

Tvr=Swarm(k,4);

sourse(1,4)=Tvr;

eval(['final_results_',num2str(k),'=finalrunupfc14']);

% Penalty for bus voltage violation

bus_inf=VM;

for bus_num=1:14





else

penalty_Vl(bus_num)=0;

end

end

penalty_Vl_violation=sum(penalty_Vl);

% penality for UPFC parameters (Vcr)


for bus_num=1,1





else

penalty_Vcr(bus_num)=0;

end

end


penalty_Vcr_violation=sum(penalty_Vcr);

% penality for UPFC parameters (Tcr)


for bus_num=1,2


penalty_Tcr(bus_num)=10000*(bus_inf3(bus_num)-2*pi)^2;


penalty_Tcr(bus_num)=10000*(bus_inf3(bus_num)-0.0)^2;

else

penalty_Tcr(bus_num)=0;

end

end

penalty_Tcr_violation=sum(penalty_Tcr);

% penality for UPFC parameters (Vvr)


for bus_num=1,3





else

penalty_Vvr(bus_num)=0;

end

end

penalty_Vvr_violation=sum(penalty_Vcr);

% penality for UPFC parameters (Tvr)


for bus_num=1,4


penalty_Tvr(bus_num)=10000*(bus_inf5(bus_num)-2*pi)^2;

elseif bos_inf(bus_num)<0.0

penalty_Tvr(bus_num)=10000*(bus_inf5(bus_num)-0.0)^2;

else

penalty_Tvr(bus_num)=0;

end

end

penalty_Tvr_violation=sum(penalty_Tvr);

losses_temp(k)=PLoss_final;

Obj_fun_temp=losses_temp(k)+penalty_Vl_violation+penalty_Vcr_violation+

penalty_Tcr_violation+penalty_Vvr_violation+penalty_Tvr_violation;

% Final Evaluation

Val_Pbest_temp=Obj_fun_temp;

end

if Val_Pbest_temp<Val_Pbest

losses=losses_temp;

Val_Pbest=Val_Pbest_temp;

Pbest=Swarm;

end

[Val_Gbest_temp,n]=min(Val_Pbest);

if Val_Gbest_temp<Val_Gbest

Val_Gbest=Val_Gbest_temp;

Gbest=Swarm(n,:);

Gbest_calc=repmat(Swarm(n,:),N,1);

end

Val_Gbest_rec(iter)=Val_Gbest;

toc

end

2019-10 investigation and minimization of power loss and

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