The applications of artificial intelligence based methods for solving hydrothermal scheduling problems

MINISTRY OF EDUCATION AND TRAINING 
HCMC UNIVERSITY OF TECHNOLOGY AND EDUCATION 
DISSERTATION 
THE APPLICATIONS OF ARTIFICIAL INTELLIGENCE 
BASED METHODS FOR SOLVING HYDROTHERMAL 
SCHEDULING PROBLEMS 
ELECTRICAL ENGINEERING 
62520202 
PhD Candidate: 
THANG TRUNG NGUYEN 
Supervisors: 
 Assoc. Prof. DIEU NGOC VO 
 Assoc. Prof. ANH VIET TRUONG 
HCM city, February 2017
i 
BIOGRAPHY 
1. Personal details 
Full name Nguyễn Trung Thắng Year of birth 06/08/1985 
Academic title PhD Candidate Sex Male 
Administrative position Lecturer ID number 260953419 
Faculty Electrical & Electronic engineering 
Institution Ton Duc Thang University 
Address No. 19, Nguyen Huu Tho 
street, District 7, HCMC 
City Ho Chi Minh 
Email address trungthangttt@gmail.com 
2. Qualification 
No Years Cademic institutions Major/ Specialty Academic 
degree 
1 2003-2008 HCMC University of 
technical education 
Electrical engineering Engineer 
2 2008-2010 HCMC University of 
technical education 
Electrical engineering Master 
3 2013-Now HCMC University of 
technical education 
Electrical engineering PhD Candidate 
3. Professional experience 
No Years Institutions Professional address Position 
1 2008-
2009 
Cao Thang 
technology College 
No. 65, Huynh Thuc Khang 
street, District 1, HCMC 
Lecturer 
2 2009-
Now 
Ton Duc Thang 
University 
No. 19, Nguyen Huu Tho 
street, District 7, HCMC 
Lecturer 
4. English Language 
Ability Reading Writing Speaking 
Fair Fair Fair 
Level Toeic 650 
 HCM city, 06 / 10 /2017 
 PhD Candidate 
 Thang Trung Nguyen 
ii 
CERTIFICATE 
I hereby certify that the work which is being presented in the study entitled, “The 
applications of artificial intelligence based methods for solving hydrothermal 
scheduling problems” in partial fulfillment of the requirements for the award of 
degree of Doctor of engineering in electrical engineering, is an authentic record of my 
own work carried out under the supervision of Assoc. Prof. Dieu Ngoc Vo and Assoc. 
Prof. Anh Viet Truong. 
The matter presented in the study has not been submitted elsewhere for the award of 
any other degree. 
 HCM city, 06 /10 /2017 
PhD Candidate 
Thang Trung Nguyen 
iii 
ACKNOWLEDGEMENTS 
After a long hard working period of time to finish the dissertation, I could not forget 
the people who have helped and supported me over the years. I could not have 
completed my dissertation without these people. 
First of all, I would like to express my deeply attitude to my Program Examination 
Committee Chairperson, Assoc. Prof. Dieu Ngoc Vo who has given me very valuable 
guidance, suggestions and comments toward the completion of the study. He is very 
patient in giving me appropriate advices so that I can complete my dissertation. I really 
appreciate his supervision and supports during my research. Besides, Assoc. Prof. Anh 
Viet Truong is also a very enthusiastic Program Examination Committee Member, 
who always give me useful suggestions that can make my study more perfect and more 
realistic. I really appreciate his contribution to my study. I could not forget good 
knowledge that Prof. Anh Huy Quyen taught me when I was a university student and 
his comments on the study as well as his friendly behavior and his encouragement in 
my study. 
Special thanks are extended to my wife, Tam Thi Nguyen, has encouraged me to 
overcome the hard times during my study. 
I could not forget the help from my special partners, the head of electrical engineering 
department, Dr. Bach Hoang Dinh and the Dean of electrical and electronics 
engineering faculty, Dr. Duy Hoang Vo, who gave me good conditions to focus on my 
study and encouraged me to overcome drawbacks during the study. Thanks are due to 
my friend, Mr Ly Huu Pham, who supported me many things in teaching and 
administrative works and went to coffee shop with me for writing my study. Besides, I 
also thank Mr Au Ngoc Nguyen and Mr Tho Quang Tran, who are my classmates and 
encouraged me when I coped with disappointment. 
iv 
ABSTRACT 
The study presents the application of several artificial interlligence based methods for 
solving short-term hydrothermal scheduling problem. The objective of these problems 
is mainly to minimize total electricity generation fuel cost at thermal plants while 
neglecting the cost at hydropower plants so that all equality and inequality constraints 
of the system including power balance constraint considering transmission line, upper 
and lower limits on power generated by thermal and hydro plants, and hydraulic 
constraints at hydropower plants such as boundaries of water discharge, boundaries of 
reservoir volume, avaialbe water, initial volume as well as end volume. In addition, 
constraints in transmission lines such as transmission capacity of lines, voltage at 
buses, tap setting, etc are also taken into consideration. The complicated level of the 
considered constraints is increased and ranged from the first problem to the final 
problem. Augmented Lagrange Hopfield Network and three other methods such as 
conventional Cuckoo Search algorithm (CCSA), Modified Cuckoo Search algorithm 
(MCSA) and Adaptive Selective Cuckoo Search algorithm (ASCSA) are applied for 
solving the problems in the study. Among the applied Cuckoo Search algorithms, 
CCSA is the original one which has been successfully applied for recent years since it 
was first developed in 2009 meanwhile MCSA has been developed based on the 
original one and ASCSA is first introduced in the study. In addition, ALHN is also a 
strong method which has been developed and successfully applied for solving 
electrical engineering problems.The performance of these methods are tested on 
several systems according to each kind of problem and there is a fact that not every 
applied method is applied for solving all considered problems because their different 
effcciency on the considered problems. In fact, the three Cuckoo Search algorithms are 
run on all the problems but ALHN is only applied for the first two problems where 
water head of reservoir is fixed and reservoir volume constraints are not taken into 
account. As a result, the comparisons among these methods with many existing 
methods indicate that the methods are effecitve and robust for solving the short-term 
hydrothermal scheduling problem because they obtain better solution quality and 
shorter execution time than most methods available in the report. Among the methods, 
ALHN is very effective for the first two problems where valve point loading effects of 
thermal units are not considered but it must stop working when the effects are taken 
into account. On the contrary, the three Cuckoo Search algorithms become more 
effective for the problems with valve point loading effects. Among the three Cuckoo 
Search algorithms, ASCSA is the most efficient method whereas the effectiveness 
between CCSA and MCSA has a trade-off for different problems. In fact, MCSA is 
more effective than conventional Cuckoo Search for the first and the final problems; 
however, the figure is opposite for the rest of the problems. Compared to other 
methods in other studies, the four methods are better than nearly all methods in terms 
of quality of solutions and fast convergence speed. 
iv 
TÓM TẮT 
 Luận án trình bày ứng dụng các phương pháp thông minh nhân tạo giải các bài 
toán phối hợp tối ưu hệ thống thủy nhiệt điện. Mục tiêu của các bài toán là cực tiểu chi 
phí phát điện tại các nhà máy nhiệt điện trong khi đó không xét đến chi phí phát điện 
tại các nhà máy thủy điện sao cho các ràng buộc cân bằng và bất cân bằng của hệ 
thống như ràng buộc cân bằng công suất có xét đến tổn hao truyền tải đường dây, các 
giới hạn công suất phát của nhà máy thủy điện và nhiệt điện và các ràng buộc từ hồ 
thủy điện như thể tích hồ chưa, lưu lượng xả, thể tích nước cho phép sử dụng phải 
được thỏa mãn. Ngoài ra, ràng buộc trên lưới truyền tải như khả năng truyền tải 
đường dây, điện áp tại các nút, cài đặt đầu phân áp, chọn công suất tụ bù cũng được 
xét đến. Mức độ phức tạp của các ràng buộc được tăng dần từ bài toán thứ nhất đến bài 
toán cuối cùng. 
 Ba phương pháp cuckoo Search như cuckoo Search cổ điển (CCSA), Cuckoo 
Search cải biên (MCSA) và Cuckoo Search chọn lọc thi nghi (ASCSA), và phương 
pháp mạng Hopfield Lagrange tăng cường (ALHN) đã được áp dụng để giải các bài 
toán trên. CCSA là phương pháp Cuckoo Search đầu tiên được xây dựng năm 2009 
trong khi đó MCSA được phát triển dựa trên CCSA vào năm 2011. ALHN cũng là một 
phương pháp được phát triển từ phương pháp Hopfield Neural Network và đã được áp 
dụng trong lĩnh vực kỹ thuật điện. Khác với ba phương pháp này, ASCSA chưa được 
áp dụng cho bất cứ bài toán nào trước đây vì ASCSA là phương pháp được phát triển 
đầu tiên trong luận này dựa trên các cải biên từ CCSA. 
 Tính hiệu quả của các phương pháp được kiểm tra trên các hệ thống khác nhau 
với năm bài toán khác nhau. Kết quả được so sanh giữa bốn phương pháp với nhau và 
giữa bốn phương pháp với các phương pháp đã được nghiên cứu trước đây để đưa ra 
nhận xét về tính hiệu quả của bốn phương pháp này so với các phương pháp khác và 
tìm ra phương pháp hiệu quả nhất trong bốn phương pháp cũng như đề xuất khả năng 
áp dụng của từng phương pháp cho từng bài toán cụ thể. Kết quả đánh giá cho thấy 
ALHN chỉ hiệu quả cho hai bài toán đầu tiên với chiều cao cột nước cố định bỏ qua 
thể tích hồ chứa và bỏ qua hiệu ứng xả van tại các nhà máy nhiệt điện. Trong khi đó, 
phương pháp được đề xuất ASCSA tỏ ra hiệu quả hơn CCSA và MCSA cho tất cả các 
hệ thống ở năm bài toán này và hiệu quả hơn ALHN cho ba bài toán còn lại. MCSA 
hiệu quả hơn CCSA ở hai bài toán đầu tiên và bài toán cuối nhưng kém hiệu quả hơn ở 
bài toán thứ ba và thứ tư. So với các phương pháp trước đây, bốn phương pháp áp 
dụng được đánh giá khá hiệu quả khi hầu hết nổi trội hơn các phương pháp khác về 
chất lượng lời giải tối ưu với tốc độ hội tụ nhanh. 
v 
TABLE OF CONTENTS 
Title Page 
Acceptance Decision 
Biography i 
Certificate ii 
Acknowledgements iii 
Abstract iv 
Table of Contents v 
List of Abbreviations vi 
List of Figures vii 
List of Tables viii 
Nomenclature ix 
CHAPTER 1: INTRODUCTION 
1.1. Background ........................................................................................................... 1 
1.2. Statement of the problem ...................................................................................... 1 
1.3. Objectives of the research ..................................................................................... 4 
1.4. Contributions ......................................................................................................... 4 
1.5. Scope and limitation .............................................................................................. 4 
1.6. Organization of the dissertation ............................................................................ 5 
CHAPTER 2: LITERATURE REVIEW 
2.1. Introduction ........................................................................................................... 6 
2.2. Fixed-head short-term hydrothermal scheduling problem neglecting reservoir 
volume constraints ....................................................................................................... 6 
2.3. Fixed-head short-term hydrothermal scheduling problem considering reservoir 
volume........................................................................................................................ 10 
2.4. Variable-head short-term hydrothermal scheduling problem ............................. 13 
2.5. Multi-objective fixed head short-term hydrothermal scheduling problem ......... 18 
2.6. Hydrothermal optimal power problem ................................................................ 20 
2.7. Summary ............................................................................................................. 21 
CHAPTER 3: CUCKOO SEARCH ALGORITHMS AND AUGMENTED 
LAGRANGE HOPFIELD NETWORK 
3.1. Introduction ......................................................................................................... 22 
3.2. Conventional Cuckoo Search algorithm (CCSA) ............................................... 23 
v 
3.3. Modified Cuckoo Search Algorithm (MCSA) .................................................... 29 
3.4. Adaptive Selective Cuckoo Search Algorithm (ASCSA) ................................... 32 
3.5. Augmented Lagrange Hopfield Network (ALHN) ............................................. 43 
3.6. Summary ............................................................................................................. 45 
CHAPTER 4: ARTIFICIAL INTELLIGENCE BASED METHODS FOR 
FIXED-HEAD SHORT-TERM HYDROTHERMAL SCHEDULING PROBLEM 
NEGLECTING RESERVOIR VOLUME CONSTRAINTS 
4.1. Introduction ......................................................................................................... 46 
4.2. Problem formulation ........................................................................................... 47 
4.3. Calculation of power output for slack thermal and hydro units .......................... 51 
4.4. Conventional Cuckoo Search Algorithm for the problem .................................. 53 
4.5. Modified Cuckoo Search Algorithm for the problem ......................................... 57 
4.6. Adaptive Selective Cuckoo Search Algorithm for the problem ......................... 61 
4.7. Augmented Lagrange Hopfield Network for the problem. ................................. 63 
4.8. Determining the best compromise solution by for multiobjective problem ....... 69 
4.9. Numerical results ................................................................................................ 70 
4.10. Summary ........................................................................................................ 103 
CHAPTER 5: CUCKOO SEARCH ALGORITHMS FOR FIXED-HEAD 
SHORT-TERM HYDROTHERMAL SCHEDULING PROBLEM 
CONSIDERING RESERVOIR VOLUME CONSTRAINTS 
5.1. Introduction ....................................................................................................... 106 
5.2. Problem formulation ......................................................................................... 106 
5.3. Calculation of power output for slack thermal and hydro units ........................ 107 
5.4. Cuckoo Search Algorithm for the problem ....................................................... 108 
5.5. Modified Cuckoo Search Algorithm for the problem ....................................... 112 
5.6. Adaptive Selective Cuckoo Search Algorithm for the problem ....................... 114 
5.7. Numerical results .............................................................................................. 11 ...  and 
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PUBLICATIONS RELATED TO THE STUDY 
CHAPTER 4 
1. TT Nguyen, DN Vo, AV Truong, “Cuckoo search algorithm for short-term 
hydrothermal scheduling”, Applied Energy (2014) 132, 276-287 (SCI) 
2. TT Nguyen, DN Vo, “Multi-objective short-term fixed head hydrothermal 
scheduling using augmented lagrange hopfield network”, Journal of Electrical 
Engineering and Technology (2014) 9 (6), 1882-1890 (SCIE) 
3. TT Nguyen, DN Vo, “Modified Cuckoo Search algorithm for short-term 
hydrothermal scheduling”, International Journal of Electrical Power & Energy 
Systems (2015) 65, 271-281 (SCIE) 
4. TT Nguyen, DN Vo, AV Truong, LD Ho, “An Efficient Cuckoo-Inspired Meta-
Heuristic Algorithm for Multiobjective Short-Term Hydrothermal Scheduling”, 
Advances in Electrical and Electronic Engineering (2016)14 (1), 18-28 
(Scopus) 
5. LH Pham, TT Nguyen, DN Vo, BH Dinh, “Optimal Generation Coordination of 
Hydrothermal System”, International Journal of Hybrid Information 
Technology (2016) 9 (5), 13-20 (Scopus) 
6. TT Nguyen, DN Vo, “Cuckoo Search Algorithm for Hydrothermal Scheduling 
Problem”, Handbook of Research on Modern Optimization Algorithms and 
Applications in Engineering and Economics, publisher: IGI Global (2015) 
(Book chapter) 
7. TT Nguyen, AV Truong, HP Trieu. “Adaptive selective cuckoo search 
algorithm for multi-objective short-term hydrothermal scheduling”, Journal of 
Technical Education Science (2017) 41, 7-14 
8. TT Nguyen, DN Vo, “Modified Cuckoo Search Algorithm for Multiobjective 
Short-Term Hydrothermal Scheduling”. Swarm and evolutionary computation. 
(SCIE-Article in press). 
9. TT Nguyen, DN Vo, AV Truong, BH Dinh, “Adaptive selective Cuckoo Search 
algorithm for short-term hydrothermal scheduling problem”, Applied soft 
computing. (SCIE- under review round 3) 
CHAPTER 5 
10. BH Dinh, TT Nguyen, DN Vo, “Adaptive Cuckoo Search Algorithm for Short-
Term Fixed-Head Hydrothermal Scheduling Problem with Reservoir Volume 
Constraints”, International Journal of Grid and Distributed Computing (2016) 9 
(5), 191-20 (ISI) 
11. TT Nguyen, DN Vo, BH Dinh, “Cuckoo Search Algorithm Using Different 
Distributions for Short-Term Hydrothermal Scheduling with Reservoir Volume 
 219 
Constraint”, International Journal on Electrical Engineering and Informatics 
(2016) 8 (1), 76-92 (Scopus) 
CHAPTER 6 
12. TT Nguyen, DN Vo, “An efficient cuckoo bird inspired meta-heuristic 
algorithm for short-term combined economic emission hydrothermal 
scheduling”, Ain Shams Engineering Journal (2016), Article in press (Elsevier) 
(ISI-Article in Press). 
13. TT Nguyen, DN Vo, “Solving Short-Term Cascaded Hydrothermal Scheduling 
Problem Using Modified Cuckoo Search Algorithm”, International Journal of 
Grid and Distributed Computing (2016) 9 (1), 67-78 (ISI). 
14. TT Nguyen, DN Vo, AV Truong, BH Dinh, A cuckoo bird-inspired meta-
heuristic algorithm for optimal short-term hydrothermal generation 
cooperation. Cogent engineering, (2016) 3(1):1-9. (ISI) 
15. TT Nguyen, DN Vo, AV Truong, PT Ha, LD Ho, “An Effectively Enhanced 
Cuckoo Search Algorithm for Variable Head Short-Term Hydrothermal 
Scheduling”, GMSARN International Journal, (2016) 10 (4):157 – 162. 
CHAPTER 7 
16. TT Nguyen, DN Vo, AV Truong, LD Ho, “Meta-Heuristic Algorithms for 
Solving Hydrothermal System Scheduling Problem Considering Constraints in 
Transmission Lines”, Global Journal of Technology and Optimization (2016) 7 
(1): 1-6 
17. TT Nguyen, DN Vo, AV Truong, BH Dinh“An effective novel optimal algorithm 
for solving hydrothermal optimal power flow problem”, Cogent Engineering (ISI-
under review)