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 | Engineering Knowledge: Knowledge in mathematics, science, fundamental engineering, computational science, and related engineering disciplines; the ability to apply this knowledge to solve complex engineering problems. | X | ||||
| 2 | Problem Analysis: The ability to identify, formulate, and analyze complex engineering problems using fundamental science, mathematics, and engineering knowledge, while keeping in mind the relevant UN Sustainable Development Goals. | |||||
| 3 | Engineering Design: The ability to design creative solutions to complex engineering problems; the ability to design complex systems, processes, devices, or products to meet current and future requirements, taking into account realistic constraints and conditions. | |||||
| 4 | Techniques and Tool Usage: The ability to select and use appropriate techniques, resources, and modern engineering and information tools, including estimation and modeling, for the analysis and solution of complex engineering problems, while being aware of their limitations. | |||||
| 5 | Research and Investigation: The ability to use research methods, including literature review, experimental design, experiment execution, data collection, analysis and interpretation of results, for the investigation of complex engineering problems. | |||||
| 6 | Global Impact of Engineering Applications: Information about the impacts of engineering applications on society, health and safety, the economy, sustainability and the environment within the framework of the UN Sustainable Development Goals; awareness of the legal consequences of engineering solutions. | X | ||||
| 7 | Engineering Ethics: Awareness of ethical responsibility and adherence to engineering professional principles; impartiality and inclusivity without discrimination. | |||||
| 8 | Individual and Teamwork: The ability to work effectively individually and as a team member or leader in interdisciplinary and multidisciplinary teams (face-to-face, remote, or mixed). | |||||
| 9 | Oral and Written Communication: The ability to communicate effectively orally and in writing on technical topics, taking into account the diverse differences of the target audience (education, language, profession, etc.). | |||||
| 10 | Project Management: Knowledge of business practices such as project management and economic feasibility analysis; awareness of entrepreneurship and innovation. | |||||
| 11 | Lifelong Learning: Lifelong learning skills encompassing the ability to learn independently and continuously, adapt to new and emerging technologies, and think critically about technological changes. | |||||
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 | ||