View
216
Download
0
Category
Preview:
Citation preview
7/29/2019 Rupinder File
1/11
i
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.
7/29/2019 Rupinder File
2/11
ii
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.
7/29/2019 Rupinder File
3/11
iii
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
7/29/2019 Rupinder File
4/11
iv
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
5.2 Conflicting nature of objectives (for PD = 175MW) 44
5.3 Conflicting nature of objectives (for PD = 200MW) 48
5.4 Conflicting nature of objectives (for PD = 225MW) 52
5.5 Conflicting nature of objectives (for PD = 250MW) 56
7/29/2019 Rupinder File
5/11
v
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
for power demand (PD) = 150MW 39
5.7 , cost, emission, (F1),(F2), of 6 unit system
for power demand (PD) = 175MW 41
5.8 Economic dispatch in Rs/h for values of w1 and w2 42
5.9 Generation schedules of six unit system
for power demand (PD) = 175MW 43
5.10 , cost, emission, (F1),(F2), of 6 unit system
for power demand (PD) = 200MW 45
5.11 Economic dispatch in Rs/h for values of w1 and w2 47
5.12 Generation schedules of six unit system
for power demand (PD) = 200MW 48
5.13 , cost, emission, (F1),(F2), of 6 unit system
7/29/2019 Rupinder File
6/11
vi
for power demand (PD) = 225MW 49
5.14 Economic dispatch in Rs/h for values of w1 and w2 50
5.15 Generation schedules of six unit system
for power demand (PD) = 225MW 51
5.16 , cost, emission, (F1),(F2), of 6 unit system
for power demand (PD) = 250MW 53
5.17 Economic dispatch in Rs/h for values of w1 and w2 55
5.18 Generation schedules of six unit system
for power demand (PD) = 250MW 55
5.19 Comparison of CEED fuel cost ($/h) of 6 unit system 57
7/29/2019 Rupinder File
7/11
vii
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
7/29/2019 Rupinder File
8/11
viii
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
7/29/2019 Rupinder File
9/11
ix
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
7/29/2019 Rupinder File
10/11
x
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
5.2 Multiobjective economic emission dispatch (CEED) of 6 unit system
for Power demand PD = 175MW 41
5.3Multiobjective economic emission dispatch (CEED) of 6 unit system
for Power demand PD = 200MW 45
5.4 Multiobjective economic emission dispatch (CEED) of 6 unit system
for Power demand PD = 225MW 49
5.5 Multiobjective economic emission dispatch (CEED) of 6 unit system
for Power demand PD = 250MW 53
5.6 Comparison with different techniques 57
7/29/2019 Rupinder File
11/11
xi
CHAPTER 6: CONCLUSION AND FUTURE SCOPE 59-60
6.1Conclusion 596.2Future Scope 60REFERENCES
Recommended