Rupinder File

7/29/2019 Rupinder File

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CANDIDATES DECLARATION

I hereby certify that the work which is being presented in the thesis entitled

MULTIOBJECTIVE OPTIMIZATION FOR THERMAL GENERATION by RUPINDER

KAUR in partial fulfillment of requirements for the award of degree of M.Tech. (Power

Engineering) submitted in the Department of Electrical Engineering at GURU NANAK DEV

ENGINEERING COLLEGE, LUDHIANA under PUNJAB TECHNICAL UNVERSITY,

JALANDHAR is an authentic record of my own work carried out during a period from Jan

2012 to Sept. 2013 under the supervision of Dr. YADWINDER SINGH BRAR, Professor,

Department of Electrical Engineering, GNDEC Ludhiana. The matter presented in this thesis

has not been submitted by me in any other University / Institute for the award

of M.Tech Degree.

Signature of the Student

This is to certify that the above statement made by the candidate is correct to the best of my/ourknowledge.

Signature of the Supervisor

The M.Tech Viva Voce Examination of RUPINDER KAUR has been held on

____________ and accepted.

Signature of Supervisor Signature of External Examiner

Signature of H.O.D.


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ABSTRACT

A major objective for the thermal power generation is to minimize fuel consumption by

allocating optimal power generation to each unit (Economic Dispatch) and to maintain

emissions within the environmental license limit (Emission Dispatch) subject to equality and

inequality constraints. The economic dispatch problem minimizes the total operating cost of a

power system while meeting the total demand plus transmission losses within generator limits.

The emission of NOx, SO2, and CO2 gases from thermal power plant cause detrimental effects

on human beings and considered as an objectives in optimization problem. But the

improvement of one objective can be achieved only at the expense of another. Due to

conflicting nature of economy and emission objectives, problem becomes multiobjective in

nature. In this research work weighting method is applied to convert multiobjective

optimization into scalar optimization. The weighting method assigns different weights to each

objective function based on its importance. The Lagranges multiplier method is applied to

convert constraint scalar optimization problem into unconstraint scalar optimization problem.

Fuzzy approach is used to achieve the one best compromised solution. The best solution

attains maximum satisfaction level from the membership functions of the participating

objectives. In order to show the effectiveness of this technique, the proposed approach is

applied to a test system with six number of generating units. The numerical results obtained are

compared with other techniques such as min-max and max-max price penalty factor by taking

different power demands and are found satisfactory.


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ACKNOWLEDGEMENT

Firstly, I would like to express my sincere thanks and deep sense of gratitude to my supervisor,

Dr. Yadwinder Singh Brar, Professor, Department of Electrical Engineering, GNDEC,

Ludhiana. His knowledge, valuable guidance and unlimited patience inspired me in the

completion of the thesis. Thanks sir for all your moral support and ideas.

I would also like to thanks Er. Jaswinder Singh, Head, Department of Electrical

Engineering, Guru Nanak Dev Engineering College, Ludhiana, for providing the necessary

infrastructure, various facilities and opportunities, which lead to successful completion of this

thesis work.

I also express my gratitude to other faculty members of the department for their

intellectual support throughout the course of this work.

Last but not least, thanks God for giving me a great family and great teachers in all

respect of life, for allowing me to share all these experiences with them and for helping me

remember the essential things in a life. I would like to express my gratitude and appreciation to

all those who helped and inspired me in various ways for successful completion of my thesis

work.

Rupinder Kaur


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LIST OF FIGURES

Figure No. Figure Title Page No.

1.1 A simple model of a steam turbine unit 5

1.2 Operating cost of a thermal unit 6

1.3 Heat rate curve of steam turbine generator 7

1.4 Incremental cost curve steam turbine generator 7

5.1 Conflicting nature of objectives (for PD = 150MW) 40






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LIST OF TABLES

Table No. Table Title Page No.

5.1 Input data for fuel cost coefficients 35

5.2 Input data for NOx emission coefficients 36

5.3 B-Coefficients for six generator units 36

5.4 , cost, emission, (F1),(F2), of 6 unit system

for power demand (PD) = 150MW 37

5.5 Economic dispatch in Rs/h for values of w1 and w2 38

5.6 Generation schedules of six unit system














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5.19 Comparison of CEED fuel cost ($/h) of 6 unit system 57


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NOMENCLATURE

CEED Combined Economic Emission Dispatch

FT CEED fuel cost

CO2 Carbon-dioxide

Convergence tolerance

$/h Dollar per hour

DM Decision Maker

ELD Economic Load Dispatch

EED Economic Emission Dispatch

F(Pi) Fuel cost of ith generator

ai, bi and ci Fuel cost coefficients

GA Genetic Algorithm

Kg/h kilogram per hour

MW Mega watt

MOOP MultiObjective Optimization Problem

MWh Megawatt hour

NOx Oxides of nitrogen

SO2 Sulphur dioxide

PD Power Demand

Pi Real power generation of unit i Lower limit of generator output

Upper limit of generator output

Lagranges multiplier

Step length

n No. of generators

di, ei, andfi NOx emission coefficients


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F1 Total Fuel Cost

F2 Total NOx emission

Summation

IT No. of iterations

ITMAX Maximum no. of iterations

PG Power generation of the system

PL Transmission losses

,B0i,B00 Transmission loss coefficients

M No. of objectives

w1 and w2 Weighting coefficients

(F1) Membership function of fuel cost

(F2) Membership function of emission

Rs/h Rupees per hour


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CONTENTS

Candidates Declaration i

Abstract ii

Acknowledgement iii

List of Figures iv

List of Tables v

Nomenclature vi

CHAPTER1: INTRODUCTION 1-13

1.1Overview 11.2Thermal Power Plant 41.3Economic Load Dispatch 51.4Emission Dispatch 81.5Combined Economic Emission Dispatch 8

1.5.1 Fuel Cost Objective 9

1.5.2 Emission Objective 9

1.5.3 Equality constraints 10

1.5.4 Inequality constraints 10

1.6Weighted Sum Method 111.7Outline of Thesis 12CHAPTER 2: LITERATURE REVIEW 14-19

CHAPTER 3: PROBLEM FORMULATION 20-22

CHAPTER 4: PRESENT WORK 23-34


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4.1Introduction 234.2Multiobjective Dispatch Problem 234.3 Calculating 274.4Stopping Criterion 284.5Updating 284.6Best Compromise Solution 294.7Algorithm of Problem 304.8 Flowchart of the Problem 32

CHAPTER 5: RESULTS AND DISCUSSION 35-57

5.1 Multiobjective economic emission dispatch (CEED) of 6 unit system

for Power demand PD = 150MW 36



5.3Multiobjective economic emission dispatch (CEED) of 6 unit system






5.6 Comparison with different techniques 57


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CHAPTER 6: CONCLUSION AND FUTURE SCOPE 59-60

6.1Conclusion 596.2Future Scope 60REFERENCES

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