TÜRKÇE
ENGLISH
Information
| Code | EE0014 |
| Name | Energy Analytics |
| Term | 2023-2024 Academic Year |
| Term | Spring |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | İngilizce |
| Level | Doktora Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | |
| Course Instructor |
1 |
Course Goal / Objective
This course aims to teach theoretical and practical aspects of energy analytics by covering major electric power system applications of predictive analytics.
Course Content
An Overview of Turkish Electric Power System and Electricity Market, Digitalisation of Energy, Internet of Energy, Introduction to Energy Analytics, Basics of R Programming Language, Preparation and Wrangling of Energy Data, Visualisation of Energy Data, Exploratory Data Analysis for Energy Analytics, Introduction to Energy Forecasting, Electric Load Forecasting, Building Electrical Energy Consumption Forecasting, Reactive Power Forecasting, Renewable Energy Forecasting: Solar and Wind Energy Forecasting, and Electricity Price Forecasting.
Course Precondition
No Preparation
Resources
[1] Market Operations in Electric Power Systems: Forecasting, Scheduling, and Risk Management, M. Shahidehpour & H. Yamin & Z. Li [2] Spatial Electric Load Forecasting, H. L. Willis [3] R for Data Science: Import, Tidy, Transform, Visualize, and Model Data, H. Wickham & G. Grolemund [4] Forecasting: Principles and Practice, R. J. Hyndman & G. Athanasopoulos
Notes
[1] Energy Time Series Forecasting: Efficient and Accurate Forecasting of Evolving Time Series from the Energy Domain, L. Dannecker
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Understand basic concepts of predictive analytics in the energy industry |
| LO02 | Ability to use R programming language for energy analytics |
| LO03 | Know how to prepare, wrangle, and visualize energy data |
| LO04 | The basics of energy analytics were understood. |
| LO05 | Projects related to energy analytics were understood. |
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 and Electronics Engineering by increasing the level of knowledge beyond the master's level | 5 |
| PLO02 | Bilgi - Kuramsal, Olgusal | To comprehend the integrity of all the subjects included in the field of specialization. | 4 |
| PLO03 | Bilgi - Kuramsal, Olgusal | Having knowledge of the current scientific literature in the field of specialization to analyze the literature critically | 5 |
| PLO04 | Bilgi - Kuramsal, Olgusal | To comprehend the interdisciplinary interaction of the field with other related branches, to suggest similar interactions. | 3 |
| PLO05 | Bilgi - Kuramsal, Olgusal | Ability to do theoretical and experimental work | 2 |
| PLO06 | Bilgi - Kuramsal, Olgusal | To create a complete scientific text by compiling the information obtained from the research | 4 |
| 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. | 4 |
| 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. | 4 |
| PLO09 | Bilgi - Kuramsal, Olgusal | Having a command of English and related English jargon at a level that can easily read and understand a scientific text written in English in the field of specialization and write a similar text | 4 |
| PLO10 | 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. | 5 |
| PLO11 | Bilgi - Kuramsal, Olgusal | Ability to plan and teach lessons related to the field of specialization or related fields | 3 |
| PLO12 | Bilgi - Kuramsal, Olgusal | Being able to guide and take the initiative in environments that require solving problems related to the field | |
| PLO13 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Ability to communicate with people in an appropriate language | |
| PLO14 | Yetkinlikler - Öğrenme Yetkinliği | Adopting the ethical values required by both education and research aspects of academician | |
| PLO15 | Yetkinlikler - Öğrenme Yetkinliği | To be able to produce projects, policies, and processes in the field of expertise and to evaluate these elements | |
| PLO16 | Yetkinlikler - Öğrenme Yetkinliği | Ability to research new topics based on existing research experience | 3 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Course Introduction and Scope | No Preparation | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Proje Temelli Öğrenme |
| 2 | An Overview of Turkish Electric Power System and Electricity Market | Review of previous lecture | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Proje Temelli Öğrenme |
| 3 | Darting a Glance at Digitalisation of Energy and Internet of Energy Concepts | Review of previous lecture | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Proje Temelli Öğrenme |
| 4 | Introduction to Energy Analytics and Basics of R Programming Language | Review of previous lecture | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Proje Temelli Öğrenme |
| 5 | Preparation and Wrangling of Energy Data | Review of previous lecture | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Proje Temelli Öğrenme |
| 6 | Visualization of Energy Data | Review of previous lecture | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Proje Temelli Öğrenme |
| 7 | Visualization of Energy Data | Review of previous lecture | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Proje Temelli Öğrenme |
| 8 | Mid-Term Exam | Ölçme Yöntemleri: Ödev, Sözlü Sınav |
|
| 9 | Introduction to Energy Forecasting and Electric Load Forecasting | Review of previous lecture | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Proje Temelli Öğrenme |
| 10 | Building Electrical Energy Consumption Forecasting | Review of previous lecture | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Proje Temelli Öğrenme |
| 11 | Reactive Power Forecasting | Review of previous lecture | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Proje Temelli Öğrenme |
| 12 | Renewable Energy Forecasting: Solar Energy | Review of previous lecture | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Proje Temelli Öğrenme |
| 13 | Renewable Energy Forecasting: Wind Energy | Review of previous lecture | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Proje Temelli Öğrenme |
| 14 | Electricity Price Forecasting | Review of previous lecture | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Proje Temelli Öğrenme |
| 15 | Student Presentations for Project Work | Review of previous lecture | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Proje Temelli Öğrenme |
| 16 | Term Exams | Ölçme Yöntemleri: Ödev, Sözlü Sınav |
|
| 17 | Term Exams | Ölçme Yöntemleri: Ödev, Sözlü Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 5 | 70 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
| Final Exam | 1 | 30 | 30 |
| Total Workload (Hour) | 157 | ||
| Total Workload / 25 (h) | 6,28 | ||
| ECTS | 6 ECTS | ||