FUNDAMENTALS OF ENERGY SYSTEMS OPTIMIZATION
- Course
- ENRE533 - FUNDAMENTALS OF ENERGY SYSTEMS OPTIMIZATION
- Department
- Energy Systems Engineering - English - Master
- Course Type
- Course
- Status
- Required
- Language
- English
- Credit
- 3
- ECTS
- 8
- T+P+L
- 3 + 0 + 0
- Course Coordinator(s)
- Asst. Prof. Dr. Neyre TEKBIYIK ERSOY
- Prerequisite
- -
Course Description
This course introduces the basic concepts of optimization and optimization systems. Students learn how to formulate typical optimization problems, especially in the energy field. The course starts with a detailed introduction to optimization, and continues with the modeling, objective functions, maxima and minima, necessary and sufficient conditions for an unconstrained minimum. One dimensional and multidimensional optimization methods are also within the scope of this course.
FUNDAMENTALS OF ENERGY SYSTEMS OPTIMIZATION
Evaluation Tools (Active Term)
| Item | Type | Weight (%) |
|---|---|---|
| Midterm | Midterm | 25 |
| Final Exam | Final | 35 |
| Project | Project | 15 |
| Project Presentation | Presentation | 10 |
| Assignment | Assignment | 15 |
| Total | 100 | |
Course outcomes
No course outcomes have been defined yet.
Course Syllabus
| Week | Topic |
|---|---|
| Week 1 | Introduction to the course |
| Week 2 | Introduction to optimization; vectors, matrices, eigenvalues, eigenvectors |
| Week 3 | Formulation of optimization problems, Unconstrained optimization |
| Week 4 | Local extrema and optimality conditions |
| Week 5 | Convexity, concavity, energy systems related optimization |
| Week 6 | National Holiday |
| Week 7 | Unconstrained optimization algorithms |
| Week 8 | MIDTERM EXAM WEEK |
| Week 9 | MIDTERM EXAM WEEK |
| Week 10 | Solving unconstrained optimization problems by using Matlab |
| Week 11 | Solving unconstrained optimization problems by using Matlab (cont'd) |
| Week 12 | Constrained optimization |
| Week 13 | Solving constrained optimization problems by using Matlab |
| Week 14 | PROJECT PRESENTATIONS |
| Week 15 | - |
Reference Books & Course Materials
- 01 Edwin K. P. Chong, Stanislav H. Zak, An Introduction to Optimization, John Wiley and Sons, 2008.
- 02 David G. Luenberger, Yinyu Ye, Linear and Nonlinear Programming, 3rd Edition, Springer, 2008.
- 03 John W. Chinneck, Practical Optimization: a Gentle Introduction, 2000.
- 04 Stefan Waner,Steven Costenoble, Finite Math and Applied Calculus, Cengage Learning, 2010.
Learning Outcomes
No learning outcomes have been defined.
Program Outcomes
No program outcomes have been defined.
Po-Lo Matrix
The PO-LO matrix has not been populated yet.