universiti putra malaysia an improved leader particle ...psasir.upm.edu.my/48250/1/fk 2014...

UNIVERSITI PUTRA MALAYSIA

AHMAD REZAEE JORDEHI

FK 2014 58

AN IMPROVED LEADER PARTICLE SWARM OPTIMISATION ALGORITHM FOR SOLVING FLEXIBLE AC TRANSMISSION SYSTEMS OPTIMISATION PROBLEM IN POWER SYSTEM

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AN IMPROVED LEADER PARTICLE SWARM OPTIMISATION

ALGORITHM FOR SOLVING FLEXIBLE AC TRANSMISSION SYSTEMS

OPTIMISATION PROBLEM IN POWER SYSTEM

By


Thesis Submitted to the School of Graduate Studies, Universiti Putra Malaysia,

in Fulfilment of the Requirement for the Degree of Doctor of Philosophy

January 2014

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Dedicated to my dear mother, caring father, kind wife, lovely brothers and sister

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Abstract of thesis presented to the senate of Universiti Putra Malaysia in

fulfilment of requirement of the degree of Doctor of Philosophy

AN IMPROVED LEADER PARTICLE SWARM OPTIMISATION ALGORITHM

FOR SOLVING FLEXIBLE AC TRANSMISSION SYSTEMS OPTIMISATION

PROBLEM IN POWER SYSTEM

By


January 2014

Chairman: Jasronita Jasni, PhD

Faculty: Engineering

Line outage contingencies in power systems are likely to result in overloads in branches,

voltage deviations in buses and excessive power losses. The most common approach for

alleviating such consequences is using flexible AC transmission systems (FACTS) devices.

Since overloads are the main concern in line outage contingencies and thyristor-controlled

series compensator (TCSC) has proved to be effective in power flow control, it is used for

mitigating consequences of line outage contingencies. When FACTS devices are utilised in a

power system, they should be allocated optimally.

From the optimisation perspective, optimal allocation of FACTS devices is a very complex

optimisation problem. Heuristic approaches are the most common approaches for solving

FACTS allocation problems. Among heuristics, particle swarm optimisation (PSO) has some

advantages which make it popular in solving FACTS allocation problems.Despite all PSO

advantages, it suffers from premature convergence.Due to PSO’s premature convergence, in

TCSC allocation problem during contingency, it is not able to find near-global solution.

Therefore, considerable amounts of overloads, voltage deviations and power losses are

obtained.

Although existing approaches mitigatePSO’s premature convergence to some extent, they

have some shortcomings that should be addressed carefully.Their explorative capability is not

decreased during the run.In most cases, the mutated object is transferred to new position

either it leads to lower objective value or not. In most of cases, the mutations are applied to

positions or velocities of particles, while applying mutation to the leader may enhance the

leader and push all particles toward better regions of search space.They also do not provide

any mechanism for jumping out particles after stagnation.

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The aim of this research is to develop a new PSO variant called improved leader PSO

(ILPSO) by addressing the mentioned shortcomings of existing premature convergence

mitigation strategies. It should efficiently mitigate premature convergence problem and result

in lower amounts of overloads, voltage deviations and power losses (than existing

algorithms) in D-TCSC allocation problem during line outage contingencies.

The proposed PSO variant features a five-staged successive mutation strategy. The security

enhancement problem is formulated as a multi-objective optimisation problem while its

objectives are minimising overpowerflows, voltage deviations, power losses and also

maximising line utilisation factors. The results of applying improved leader PSO to IEEE 14

bus power system shows its significant outperformance over six other optimisation

algorithms including conventional PSO, mutated PSO, enhanced PSO, harmony search,

genetic algorithm and gravitational search algorithm. Improved leader PSO leads to lower

amount of overpowerflows and power losses with respect to other algorithms, whileit also

results in low values of voltage deviation.ILPSO has also been applied to Malaysian 87 bus

power system (TNB), wherein overloads and power losses are reduced significantly.

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Abstrak tesis yang dikemukakan kepada Senat Universiti Putra Malaysia sebagai memenuhi

keperluan untuk ijazah Doktor Falsafah

ALGORITMA PENAMBAHBAIKAN KETUA PENGOPTIMUMAN KUMPULAN

ZARAH SEBAGAI PENYELESAIAN MASALAH PENGOPTIMUMAN SISTEM

PENGHANTARAN AC FLEKSIBEL DALAM SISTEM KUASA

Oleh


Januari 2014

Pengerusi: Jasronita Jasni, PhD

Fakulti: Kejuruteraan

Putusan talian luar jangkaan dalam sistem kuasa mungkin menyebabkan lebihan beban di

cabang, pelencongan voltan dalam bas dan kehilangan kuasa yang berlebihan. Pendekatan

yang paling biasa dalam menangani kesan-kesan tersebut ialah dengan menggunakan peranti

penghantaran AC fleksibel (FACTS). Oleh kerana lebihan beban adalah kebimbangan utama

dalam putusan talian luar jangkaan dan penggunaan pemampas siri kawalan-thyristor telah

terbukti berkesan dalam kawalan aliran kuasa, ia digunakan untuk menangani kesan-kesan

putusan talian luar jangkaan. Apabila peranti FACTS digunakan dalam sistem kuasa, ia harus

diperuntukkan secara optimum.

Dari perspektif pengoptimuman, pengagihan optimum bagi peranti FACTS merupakan

masalah pengoptimuman yang sangat kompleks. Pendekatan heuristik adalah pendekatan

yang paling biasa bagi menyelesaikan masalah pengagihan FACTS. Di kalangan heuristic,

pengoptimuman kumpulan zarah (PSO) mempunyai kelebihan yang menjadikannya popular

dalam menyelesaikan masalah pengagihan FACTS. Walaubagaimanapun, PSO mengalami

penumpuan pramatang. Disebabkan penumpuan pramatang PSO, penyelesaian hampir-

sejagat dalam masalah pengagihan TCSC semasa luar jangkaan tidak dapat dikenalpasti. Oleh

yang demikian, sejumlah besar lebihan beban, pelencongan voltan dan kehilangan kuasa

dapat diperolehi.

Walaupun pendekatan yang sedia ada dapat menangani penumpuan pramatang PSO hingga

ke suatu tahap tertentu,ia mempunyai beberapa kelemahan yang harus ditangani secara teliti.

Keupayaan ia yang menjelajah tidak berkurangan semasa dikendalikan. Dalam kebanyakan

kes, objek yang bermutasi dipindah ke kedudukan baru samaada ia membawa kepada nilai

objektif yang lebih rendah atau tidak. Dalam kebanyakan kes,mutasi digunakan pada

kedudukan atau halajuzarah, manakala penggunaan mutasi boleh memperbaiki ketua dan

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menolak kesemua zarah ke arah kawasan ruang carian yang lebih baik. Ianya juga tidak

memberikan apa-apa mekanisme untuk zarah loncatan keluar selepas penggenangan.

Tujuan kajian ini adalah untuk membangunkan satu varian PSO baru yang dikenali sebagai

penambahbaikan ketua PSO (ILPSO) dengan menangani kelemahan yang disebut sebagai

strategi pengurangan penumpuan pramatang yang sedia ada. Ia secara efisiennya dapat

menangani masalah penumpuan pramatang dan menghasilkan jumlah yang rendah pada

lebihan beban, pelencongan voltan dan kehilangan kuasa (berbanding algoritma yang sedia

ada) dalam masalah pengagihan D-TCSC ketika gangguan luar jangkaan pada talian.

Varian PSO yang dicadangkan mempunyai strategi mutasi berturutan lima-peringkat.

Masalah peningkatan keselamatan dirumuskan sebagai masalah pengoptimuman pelbagai

objektif dimana objektifnya adalah meminimumkan lebihan aliran kuasa, pelencongan voltan,

kehilangan kuasadan juga memaksimumkan faktor penggunaan talian. Penggunaan

penambahbaikan ketua PSO pada sistem kuasa 14 bas IEEE menunjukkan prestasi cemerlang

yang ketara ke atas enam algoritma pengoptimuman lain termasuk PSO konvensional, PSO

bermutasi, PSO dipertingkat, carian harmoni, algoritma genetik dan algoritma carian graviti.

Penambahbaikan ketua PSO membawa kepada lebihan aliran kuasa dan kehilangankuasa

yang lebih rendah berbanding lain-lain algoritma, ia juga menghasilkan nilai pelencongan

voltan yang rendah. ILPSO juga telah digunakan pada sistem kuasa 87 bas Malaysia (TNB),

di mana lebihan beban dan kehilangan kuasa dikurangkan dengan ketara.

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ACKNOWLEDGEMENTS

First, I would like to express my gratitude to the creator deity of the universe, for helping me

to complete this thesis.

It has been an honour and pleasure to have Dr. Jasronita Jasni as my supervisor. I am grateful

to her, for the time given to me, for her valued suggestions and encourage. I enjoyed her

support and patience during the very tough moments of the research work and writing of the

thesis.

I would like to express deepest thanks and admiration to Dr. Noor Izzri b. Abd. Wahab and

Prof. Mohd Zainal Abidin b. Ab. Kadir, for their valued helps, discussion and comments. I

would like to express special thanks to my dear mother, father, wife and family for their

everlasting support.

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I certify that a Thesis Examination Committee has met on January 10, 2014 to conduct the final examination of Ahmad Rezaee Jordehi on his thesis entitled "An

improved leader particle swarm optimisation algorithm for solving flexible AC transmission

systems (FACTS) optimisation problem in power system" in accordance with the Universities and University Colleges Act 1971 and the Constitution of the Universiti Putra Malaysia [P.U.(A) 106] 15 March 1998. The Committee recommends that the student be awarded the relevant degree of Doctor of Philosophy.

Members of the Thesis Examination Committee were as follows:

Mohd. Nizar b. Hamidon, PhD

Associate Professor

Faculty of Engineering

Universiti Putra Malaysia

(Chairman) Hashim. b. Hizam, PhD

Associate Professor



(Internal Examiner) Chandima Gomes, PhD

Professor



(Internal Examiner) Mohammad Shahidehpour, PhD

Professor


Illinois Institute of Technology

(External Examiner)

NORITAH OMAR, PhD Associate Professor and Deputy Dean

School of Graduate Studies Universiti Putra Malaysia Date:

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This thesis submitted to senate of Universiti Putra Malaysia and has been accepted as

fulfilment of requirement for degree of Doctor of Philosophy. Members of the Supervisory

Committee were follows:

Jasronita Jasni, PhD

Senior Lecturer



(Chairman)

Noor Izzri b. Abd. Wahab, PhD

Senior Lecturer



(Member)

Mohd Zainal Abidin b. Ab. Kadir, PhD

Professor



(Member)

_______________________________

BUJANG BIN KIM HUAT, PhD

Professor and Dean

School of Graduate Studies


Date:

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Declaration by graduate student

I hereby confirm that:

this thesis is my original work;

quotations, illustrations and citations have been duly referenced;

this thesis has not been submitted previously or concurrently for any other degree at any

other institutions;

intellectual property from the thesis and copyright of thesis are fully-owned by Universiti

Putra Malaysia, as according to the Universiti Putra Malaysia (Research)Rules 2012;

written permission must be obtained from supervisor and the office of Deputy Vice

Chancellor (Research and Innovation) before thesis is published in book form;

there is no plagiarism or data falsification/fabrication in the thesis, and scholarly integrity

is upheld as to the Universiti Putra Malaysia (Graduate Studies) Rules 2003 (Revision

2012-2013) and the Universiti Putra Malaysia (Research) Rules 2012. The thesis has

undergone plagiarism detection software.

Signature: Date:

Name and Matric No.:

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Declaration by Members of Supervisory Committee

This is to confirm that:

the research conducted and the writing of this thesis was under our supervision;

supervision responsibilities as stated in the Universiti Putra Malaysia (Graduate Studies)

Rules 2003 (Revision 2012-2013) are adhered to.

Signature:

Name of

Chairman of

Supervisory

Committee:

Signature:

Name of

Member of

Supervisory

Committee:

Signature:

Name of

Member of

Supervisory

Committee:

Signature:

Name of

Member of

Supervisory

Committee:

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TABLE OF CONTENTS

Page

DEDICATION ii

ABSTRACT iii

ABSTRAK v

ACKNOWLEDGEMENTS vii

APPROVAL viii

DECLARATION x

LIST OF TABLES xiii

LIST OF FIGURES xvi

CHAPTER

I INTRODUCTION 1

1.1 Overview 1

1.2 Problem Statement 3

1.3 Aim and Objectives 3

1.4 Scope and Limitations 3

1.5 Contribution 3

1.6 Organisation of chapters 3

II THEORETICAL BACKGROUND 4

2.1 An Overview of FACTS Devices 6

2.2 Introduction of FACTS Allocation Problem 6

2.3 Approaches for Solving FACTS Allocation Problem 6

2.3.1 Classical Optimization Methods 6

2.3.2 Approaches based on technical criteria 7

2.3.3 Heuristic approaches 8

2.4 An Overview of PSO 9

2.4.1 Primary version 9

2.4.2 Inertia weight PSO 10

2.5 PSO Applications on FACTS allocation Problem 11

2.6 Premature convergence problem in PSO 18

2.6.1 Self Organised Criticality 19

2.6.2 Prey and predator strategy 19

2.6.3 Charged PSO 20

2.6.4 Using mutation operators 21

III METHODOLOGY 25

3.1 Introduction 25

3.2 Improved leader PSO 28

3.3 Application of ILPSO to D-TCSC allocation problem 29

3.3.1 Problem formulation 29

3.3.2 Algorithms for comparison

31

IV RESULTS AND ANALYSIS 35

4.1 Introduction 35

4.2 Results and Analysis for IEEE 14 bus test system 35

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4.2.1 Introduction of IEEE 14 bus test system 35

. 4.2.2 Contingency analysis and ranking for IEEE 14 bus

power system

36

4.2.3 Finding appropriate weights 37

4.2.4 Results of D-TCSC allocation for the four most

severe contingencies

38

4.2.5 Overall results on IEEE 14 bus power system 59

4.3 Results and analysis of results for Malaysian 87 bus power

system

61

4.3.1 Introduction of Malaysian 87 bus power system 61

4.3.2 Contingency ranking of Malaysian 87 bus power

system

63

4.3.3 Optimisation of Malaysian 87 bus power system by

ILPSO

63

V CONCLUSIONS AND FUTURE RESEARCH DIRECTIONS 69

5.1 Conclusion 69

5.2 Future Research Directions 69

REFERENCES

70

APPENDICES 78

A. Data of test systems 78

B. Pseudocodes and flowcharts 85

C. Contingency ranking of Malaysian 87 bus power system 91

BIODATA OF STUDENT 92

LIST OF PUBLICATIONS 93

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