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Information
| Unit | INSTITUTE OF NATURAL AND APPLIED SCIENCES |
| ELECTRICAL-ELECTRONICS ENGINEERING (MASTER) (WITH THESIS) (ENGLISH) | |
| Code | EE514 |
| Name | Enerji Sistemlerinde Dijital İkiz ve Veri Odaklı Modelleme |
| Term | 2026-2027 Academic Year |
| Term | Spring |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Belirsiz |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. MEHMET TÜMAY |
| Course Instructor |
The current term course schedule has not been prepared yet.
|
Course Goal / Objective
This course covers the concept of digital twins in energy systems, data-driven modeling techniques, and the integration of these two approaches. The aim is to create virtual representations of physical systems, develop models fed by real-time data, and use them in optimization/decision support processes.
Course Content
The concept of digital twins and their role in energy systems Physical modeling vs. data-driven modeling Hybrid modeling approaches Data collection infrastructures and sensor technologies Time series data analysis Fundamentals of machine learning: Regression, classification Deep learning (LSTM, RNN) Predictive maintenance Anomaly detection and fault diagnosis Digital twin applications in energy systems: Smart grids EV charging stations Energy storage systems Real-time data processing (stream processing: Spark, Flink) IoT and communication protocols (MQTT, OPC-UA) Cloud and edge computing architectures Digital twin platforms (FIWARE, etc.) Security, data integrity and standardization
Course Precondition
Prerequisites Basic programming (Python/MATLAB) Linear algebra and statistics Introduction to energy systems
Resources
Digital Twin: Enabling Technologies - Fuller et al. Digital Twin Driven Smart Manufacturing - Tao & Zhang
Notes
Recent IEEE, Elsevier (Applied Energy, IEEE TSG, Energy AI) makaleleri FIWARE teknik dokümantasyonları - Apache Spark
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Analyzing the Concept of Digital Twin |
| LO02 | Managing Data Collection and Communication Infrastructures |
| LO03 | Processes and analyzes time series data. |
| LO04 | Develops Machine and Deep Learning Models |
| LO05 | Develops applications in energy systems. |
| LO06 | Ensures system security and standardization. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Being able to specialize in at least one of the branches that form the foundations of electrical-electronic engineering by increasing the level of knowledge beyond the undergraduate level. | |
| PLO02 | Bilgi - Kuramsal, Olgusal | To comprehend the integrity of all the subjects included in the field of specialization. | |
| PLO03 | Bilgi - Kuramsal, Olgusal | Knowing and following the current scientific literature in the field of specialization | |
| PLO04 | Bilgi - Kuramsal, Olgusal | To be able to comprehend the interdisciplinary interaction of the field with other related branches. | 5 |
| PLO05 | Bilgi - Kuramsal, Olgusal | Ability to do theoretical and experimental work | |
| PLO06 | Bilgi - Kuramsal, Olgusal | To create a complete scientific text by compiling the information obtained from the research. | |
| PLO07 | Bilgi - Kuramsal, Olgusal | To work on the thesis topic programmatically, following the logical integrity required by the subject within the framework determined by the advisor. | |
| PLO08 | Bilgi - Kuramsal, Olgusal | To search for literature in scientific databases, particularly the ability to correctly and accurately scan databases and evaluate and categorize listed items. | |
| PLO09 | Bilgi - Kuramsal, Olgusal | Knowledge of English at a level that can easily read and understand a scientific text written in English in the field of specialization | |
| PLO10 | Bilgi - Kuramsal, Olgusal | Compile information on his/her expertise in a presentation format and present it understandably and effectively. | |
| PLO11 | Bilgi - Kuramsal, Olgusal | Ability to write a computer program in a familiar programming language, generally for a specific purpose, specifically related to the field of expertise. | |
| PLO12 | Bilgi - Kuramsal, Olgusal | Being able to guide and take the initiative in environments that require solving problems related to the field | |
| PLO13 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Ability to communicate with people in an appropriate language | |
| PLO14 | Yetkinlikler - Öğrenme Yetkinliği | To be able to produce projects, policies, and processes in the field of expertise and to evaluate these elements | 4 |
| PLO15 | Yetkinlikler - Öğrenme Yetkinliği | Ability to research new topics based on existing research experience |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Introduction to Digital Twin | Introduction to Digital Twin | Öğretim Yöntemleri: Anlatım |
| 2 | Modeling Approaches | Modeling Approaches | Öğretim Yöntemleri: Anlatım |
| 3 | Data Acquisition and IoT | Data Acquisition and IoT | Öğretim Yöntemleri: Anlatım |
| 4 | Time Series Analysis | Time Series Analysis | Öğretim Yöntemleri: Anlatım |
| 5 | Machine Learning - I | Machine Learning - I | Öğretim Yöntemleri: Anlatım |
| 6 | Machine Learning - II | Machine Learning - II | Öğretim Yöntemleri: Anlatım |
| 7 | Fundamentals of Deep Learning | Fundamentals of Deep Learning | Öğretim Yöntemleri: Anlatım |
| 8 | Mid-Term Exam | Ölçme Yöntemleri: Ödev, Proje / Tasarım, Performans Değerlendirmesi |
|
| 9 | Predictive Maintenance | Predictive Maintenance | Öğretim Yöntemleri: Anlatım |
| 10 | Applications in Energy Systems | Applications in Energy Systems | Öğretim Yöntemleri: Anlatım |
| 11 | Energy Storage and Digital Twin | Energy Storage and Digital Twin | Öğretim Yöntemleri: Anlatım |
| 12 | Big Data and Processing | Big Data and Processing | Öğretim Yöntemleri: Anlatım |
| 13 | Architectures and Platforms | Architectures and Platforms | Öğretim Yöntemleri: Anlatım |
| 14 | Security and Standardization | Security and Standardization | Öğretim Yöntemleri: Anlatım |
| 15 | Project Presentations | Project Presentations | Öğretim Yöntemleri: Anlatım |
| 16 | Term Exams | Ölçme Yöntemleri: Ödev, Proje / Tasarım, Performans Değerlendirmesi |
|
| 17 | Term Exams | Ölçme Yöntemleri: Yazılı Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 17 | 3 | 51 |
| Out of Class Study (Preliminary Work, Practice) | 6 | 12 | 72 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 6 | 3 | 18 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 2 | 2 |
| Final Exam | 1 | 2 | 2 |
| Total Workload (Hour) | 145 | ||
| Total Workload / 25 (h) | 5,80 | ||
| ECTS | 6 ECTS | ||