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Cyprus International University
TR

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
-
Keywords

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

  1. 01 Edwin K. P. Chong, Stanislav H. Zak, An Introduction to Optimization, John Wiley and Sons, 2008.
  2. 02 David G. Luenberger, Yinyu Ye, Linear and Nonlinear Programming, 3rd Edition, Springer, 2008.
  3. 03 John W. Chinneck, Practical Optimization: a Gentle Introduction, 2000.
  4. 04 Stefan Waner,Steven Costenoble, Finite Math and Applied Calculus, Cengage Learning, 2010.

Learning Outcomes

No learning outcomes have been defined.

Program Outcomes

  1. Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledgein these areas in complex engineering problems
  2. Ability to identify, formulate, and solve complex environmental problems; ability to select and apply proper analysis and modeling methods for this purpose.
  3. Ability to design and conduct experiments, gather data, analyze and interpret results for investigating environmental problems or discipline specific research questions.
  4. Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
  5. Ability to communicate effectively in English, both orally and in writing; knowledge of a minimum of one foreign language
  6. Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
  7. Consciousness to behave according to ethical principles and professional and ethical responsibility; knowledge on standards used in engineering practice.
  8. Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about sustainable development.
  9. Knowledge about the global and social effects of engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions.

Po-Lo Matrix

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