ECTS - Optimization in Energy Systems

Optimization in Energy Systems (ENE422) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Optimization in Energy Systems ENE422 3 0 0 3 5
Pre-requisite Course(s)
Course Language English
Course Type N/A
Course Level Bachelor’s Degree (First Cycle)
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture, Discussion, Question and Answer, Drill and Practice, Team/Group, Brain Storming, Project Design/Management.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives This course is designed to introduce the basic concepts of optimization, optimization techniques and applications in energy systems engineering
Course Learning Outcomes The students who succeeded in this course;
  • Have a firm understanding of optimization concepts (problem formulation, mathematical modeling, search procedure, solution methods)
  • Be able to use MATLAB programming for the numerical solution to optimization problems.
  • Be aware of the optimization techniques and their application
  • Be able to apply optimization tools in the analysis of and the solution to problems related to energy systems engineering.
  • Gain an ability to identify, formulate, and solve energy systems engineering problems.
  • Be able to use the optimization tools in the design, analysis, control, and improvement of energy systems
Course Content Fundamentals of optimization, graphical optimization, linear and nonlinear programming, unconstrained and constrained optimization, global optimization, MATLAB applications, case studies in energy systems engineering.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introduction to Optimization
2 Introduction to Optimization
3 Graphical Optimization
4 Linear Programming
5 Nonlinear Programming
6 Numerical Techniques
7 Unconstrained Optimization
8 Constrained Optimization
9 Midterm Exam
10 Global Optimization
11 Optimization Toolbox from MATLAB
12 Analysis of Optimization Problems in Energy Systems Engineering
13 Analysis of Optimization Problems in Energy Systems Engineering
14 Solution of Optimization Problems in Energy Systems Engineering
15 Solution of Optimization Problems in Energy Systems Engineering
16 Final Exam


Other Sources 1. EngineerinOptimization Methods and Applications, A. Ravindran, K.M. Ragsdell, G.V. Rektaitis, 2nd Edition, 2006, Wiley
2. Multidiscipline Design Optimization, G. N. Vanderplaats, VR&D, Inc., Monterey CA, 2007 0-944956-04-1
3. Energy Systems: Optimization, Modeling, Simulation, and Economic Aspects, Journal, Springer, ISSN: 1868-3967
4. Applied Optimization with MATLAB Programming, Wiley, by P. Venkataraman (2002).
5. Practical Optimization (Algorithms and Engineering Applications), (Springer) by Antoniou, Andreas and Lu, Wu-Sheng (2007).
6. Numerical Optimization (Springer) by Jorge Nocedal and Stephen Wright (2006).

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation 1 10
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments 6 20
Presentation - -
Project 1 30
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 40
Final Exam/Final Jury 1 30
Toplam 10 130
Percentage of Semester Work 70
Percentage of Final Work 30
Total 100

Course Category

Core Courses
Major Area Courses X
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 An ability to apply knowledge of mathematics, science, and engineering. X
2 An ability to design and conduct experiments, as well as to analyze and interpret data. X
3 An ability to design a system, component, or process to meet desired needs. X
4 An ability to function on multi-disciplinary teams. X
5 An ability to identify, formulate, and solve engineering problems. X
6 An understanding of professional and ethical responsibility. X
7 An ability to communicate effectively. X
8 The broad education necessary to understand the impact of engineering solutions in a global and societal context. X
9 Recognition of the need for, and an ability to engage in life-long learning. X
10 Knowledge of contemporary issues. X
11 An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice. X
12 Skills in project management and recognition of international standards and methodologies

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Special Course Internship
Field Work
Study Hours Out of Class 14 2 28
Presentation/Seminar Prepration
Project 1 20 20
Homework Assignments 3 3 9
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 1 10 10
Prepration of Final Exams/Final Jury 1 10 10
Total Workload 125