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 Area Elective 3 0 0 3 5
Pre-requisite Course(s)
N/A
Course Language English
Course Type Technical Elective Courses
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

Sources

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 Adequate knowledge of mathematics, physical sciences and the subjects specific to engineering disciplines; the ability to apply theoretical and practical knowledge of these areas in the solution of complex engineering problems. X
2 The ability to define, formulate, and solve complex engineering problems; the ability to select and apply proper analysis and modeling methods for this purpose. X
3 The ability to design a complex system, process, device or product under realistic constraints and conditions in such a way as to meet the specific requirements; the ability to apply modern design methods for this purpose.
4 The ability to select, and use modern techniques and tools needed to analyze and solve complex problems encountered in engineering practices; the ability to use information technologies effectively. X
5 The ability to design experiments, conduct experiments, gather data, and analyze and interpret results for investigating complex engineering problems or research areas specific to engineering disciplines. X
6 The ability to work efficiently in inter-, intra-, and multi-disciplinary teams; the ability to work individually.
7 Effective oral and written communication skills; The knowledge of, at least, one foreign language; the ability to write a report properly, understand previously written reports, prepare design and manufacturing reports, deliver influential presentations, give unequivocal instructions, and carry out the instructions properly.
8 Recognition of the need for lifelong learning; the ability to access information, follow developments in science and technology, and adapt and excel oneself continuously.
9 Acting in conformity with the ethical principles; professional and ethical responsibility and knowledge of the standards employed in engineering applications.
10 Knowledge of business practices such as project management, risk management, and change management; awareness of entrepreneurship and innovation; knowledge of sustainable development.
11 Knowledge of the global and social effects of engineering practices on health, environment, and safety issues, and knowledge of the contemporary issues in engineering areas; awareness of the possible legal consequences of engineering practices.
12 Ability to work in the fields of both thermal and mechanical systems including the design and production steps of these systems.

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 14 2 28
Presentation/Seminar Prepration
Project 1 20 20
Report
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