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 X
Major Area Courses
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 Adequate knowledge in mathematics, science and subjects specific to the energy systems engineering discipline; the ability to apply theoretical and practical knowledge of these areas to complex engineering problems. X
2 The ability to identify, define, formulate and solve complex engineering problems; selecting and applying proper analysis and modeling techniques for this purpose.
3 The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose.
4 The ability to develop, select and utilize modern techniques and tools essential for the analysis and determination of complex problems in energy systems engineering applications; the ability to utilize information technologies effectively.
5 The ability to design experiments, conduct experiments, gather data, analyze and interpret results for the investigation of complex engineering problems or research topics specific to the energy systems engineering discipline.
6 The ability to work effectively in inter/inner disciplinary teams, the ability to work individually. X
7 a)Effective oral and writen communication skills in Turkish; the ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and to receive clear and understandable instructions. b)The knowledge of at least one foreign language; the ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and to receive clear and understandable instructions.
8 Recognition of the need for lifelong learning; the ability to access information, to follow recent developments in science and technology.
9 a)The ability to behave according to ethical principles, awareness of professional and ethical responsibility; b)knowledge of the standards utilized in energy systems engineering applications.
10 Knowledge on business practices such as project management, risk management and change management; awareness about entrepreneurship, innovation; knowledge on sustainable development.
11 a) Knowledge on the effects of energy systems engineering applications on the universal and social dimensions of health, environment and safety; b) and awareness of the legal consequences of engineering solutions.

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