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 | 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 Lecturer(s) |
|
| 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;
|
| 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 | 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 | Gains adequate knowledge in mathematics, science, and relevant engineering disciplines and acquires the ability to use theoretical and applied knowledge in these fields to solve complex engineering problems. | X | ||||
| 2 | Gains the ability to identify, formulate, and solve complex engineering problems and the ability to select and apply appropriate analysis and modeling methods for this purpose. | |||||
| 3 | Gains the ability to design a complex system, process, device, or product under realistic constraints and conditions to meet specific requirements and to apply modern design methods for this purpose. | |||||
| 4 | Gains the ability to select and use modern techniques and tools necessary for the analysis and solution of complex engineering problems encountered in engineering applications and the ability to use information technologies effectively. | |||||
| 5 | Gains the ability to design experiments, conduct experiments, collect data, analyze results, and interpret findings for investigating complex engineering problems or discipline specific research questions. | |||||
| 6 | Gains the ability to work effectively in intra-disciplinary and multi-disciplinary teams and the ability to work individually. | X | ||||
| 7 | a) Gains the ability to communicate effectively in written and oral form, b) Gains acquires proficiency in at least one foreign language, the ability to write effective reports and understand written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions. | |||||
| 8 | Gains awareness of the need for lifelong learning and the ability to access information, follow developments in science and technology, and to continue to educate him/herself | |||||
| 9 | a)Gains the ability to behave according to ethical principles, awareness of professional and ethical responsibility. b) Gains knowledge of the standards utilized in energy systems engineering applications. | |||||
| 10 | Gains knowledge on business practices such as project management, risk management and change management; awareness about entrepreneurship, innovation; knowledge on sustainable development. | |||||
| 11 | a) Gain awareness of the effects of Energy Systems Engineering applications on health, environment and safety in universal and societal dimensions. b) Gain knowledge of the problems of the era reflected in the field of engineering; gain 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 |
| 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 | ||