Power Systems – 2022

ObjectivesLearning outcomesIIIIIIIVVVIVIIVIIIElective Courses

Study Programme
Power Systems

Degree Programme
First cycle degree programme

Level of qualification
Bachelor of Science in Electrical Engineering and Information Technologies, in Power Systems

Occupational Profiles of Graduates
Graduates from this programme will have unique opportunity to become a part of the Power Industry, which is one of the most stabile industries and continuously employs a number of young engineers for many decades now. The field of Power Systems offers chances for successful career and well payed job in transmission and distribution companies, electricity trading and supply, as well as, in the public sector, consultancy, installation design and equipment production companies. Following the implementation of the emerging technologies and market practices in the Power Systems, adequate specialists are urgently required in the country and worldwide, where our diploma is recognized without limitations.

The Programme Learning Outcomes
The study programme in Power Systems enables students to acquire know-how and skills in three out of four main activities of Power Industry: electricity transmission, distribution and supply. The teaching process includes use of state-of-the-art software tools for simulation and analyses of Power Systems operation, as well as, for in-deep study of Power Systems planning and control, Electricity Markets, High Voltage Engineering, Low Voltage Installations, Lighting and Quality of Supply. Quite a few Lab exercises in Faculty’s Laboratories provide additional opportunities for students to gain pratical knowledge in the area of power engineering. The theoretical and practical knowledge acquired during this programme qualify its students for resolving a spectrum of technical problems they may encounter in their careers.

International Accreditation
The first cycle study programs at FEEIT are accredited by the German Accreditation Agency for Study Programmes in Engineering, Informatics, Natural Sciences and Mathematics (ASIIN), which is a world leader in quality assurance in higher education. This accreditation confirms that the study programs satisfies the criteria for Bachelor degree programs specified in EUR-ACE Framework standards for the accreditation of engineering programs and the content studied are relevant to areas covered in study programs.

General Learning Outcomes

Knowledge and understanding
  • Demonstrate knowledge and understanding in the scientific field of electrical engineering, based on education and training, including knowledge of theoretical, practical, conceptual, comparative, and critical perspectives in the scientific field according to the appropriate methodology.
Application of knowledge and understanding
  • Demonstrate the ability to apply acquired knowledge and understanding in a professional manner.
  • An ability to identify, analyze and solve complex engineering problems by selecting an appropriate method.
Ability to assess
  • An ability to collect, analyze, evaluate and present information, ideas, and concepts based on relevant data.
  • Making an appropriate assessment taking into account personal, social, scientific and ethical aspects.
Communication skills
  • An ability to communicate effectively in both verbal and written forms with professional and non-professional audiences.
  • An ability to work effectively as an individual or as a member of a team taking shared responsibility for collective results.
  • Ability to participate independently, in a professional manner, in regards to scientific and interdisciplinary discussions.
Learning skills
  • Commitment to the professional development and lifelong learning achieved through higher education, technical training, membership in professional societies, and other activities in order to update already acquired knowledge in the relevant field to achieve continuous professional growth.
  • An ability to acquire and apply new knowledge as needed using appropriate learning strategies.


Specific Learning Outcomes

Knowledge and understanding
  • Demonstrate knowledge and understanding in the scientific field of electrical engineering, based on education and training, including knowledge of theoretical, practical, conceptual, comparative, and critical perspectives in the scientific field according to the appropriate methodology.
  • Demonstrate knowledge and understanding of research, development and engineering design in industrial processes and power systems.
  • Understanding and knowledge of current issues related to scientific research and new sources of knowledge.
Application of knowledge and understanding
  • An ability to identify, analyze and solve complex engineering problems.
  • An ability to apply knowledge and understanding in a way that demonstrates professionalism to the relevant field or profession.
  • An ability to identify, analyze and solve problems related to power systems.
Ability to assess
  • An ability to collect, analyze, evaluate and present information, ideas, and concepts from relevant data.
  • Making an appropriate assessment taking into account personal, social, scientific and ethical aspects.
  • An ability to provide answers to both theoretical and practical issues, in order to give explanations and choose the appropriate solution.
  • An ability to analyze, evaluate and present information, ideas, and concepts based on relevant data in the field of power systems.
Communication skills
  • An ability to communicate effectively in both verbal and written forms with professional and non-professional audiences.
  • An ability to work effectively as an individual or as a member of a team taking shared responsibility for collective results.
  • An ability to participate independently and professionally in specific, scientific and interdisciplinary discussions.
Learning skills
  • Commitment to professional development and lifelong learning through higher education, technical training, membership in professional societies, and other activities in order to update already acquired knowledge in the field and to achieve continuous professional growth.
  • An ability to acquire and apply new knowledge as needed using appropriate learning strategies.
  • Demonstrate a high degree of independence initiative for learning and professional development.
  • Understanding the need for learning and ability for continuous professional development, through the use of professional and scientific literature, professional training, continuing formal education, membership in professional organizations, etc.
  • Awareness of new technologies and an ability to evaluate and use modern software tools.
  • An ability to use information technologies for distance and e-learning.
  • Skills for cooperative, competitive and individual learning.
  • Applying active teaching and learning techniques.

Semester 1
Mandatory courses
Code Title ECTS No of classes per week
4ФЕИТ08З007 Mathematics 1 8 4+3+0+0
4ФЕИТ08З015 Physics 1 7 3+2+1+0
4ФЕИТ06З006 Fundamentals of Electrical Engineering 8 3+3+1+0
4ФЕИТ07З019 Programming and Algorithms 7 2+2+2+0

Semester 2
Mandatory courses
Code Title ECTS No of classes per week
4ФЕИТ03Л003 Electrical Materials 3 2+0+1+0
4ФЕИТ06Л005 Fundamentals of Electric Circuits 7 3+2+1+0
4ФЕИТ08Л008 Mathematics 2 7 3+3+0+0
4ФЕИТ07Л018 Data Structures and Programming 6 2+2+2+0
4ФЕИТ08Л016 Physics 2 7 3+2+1+0

Semester 3
Mandatory courses
Code Title ECTS No of classes per week
4ФЕИТ08З009 Mathematics 3 6 3+3+0+0
4ФЕИТ03З006 Electrical Measurements 6 3+1+1+0
4ФЕИТ05З033 Signals and Systems 6 3+2+0+0
4ФЕИТ05З017 Electronics 6 2+2+1+0
4ФЕИТ09З019 Design of Low Voltage Electrical Installations 6 2+2+1+0

 

During studying, the student may choose up to 4 courses from the faculty list of electives

Semester 4
Mandatory courses
Code Title ECTS No of classes per week
4ФЕИТ02Л006 Electric Machines and Transformers 6 3+1+1+0
4ФЕИТ09Л006 Power Networks 6 3+2+0+0
4ФЕИТ05Л014 Electromagnetics 6 3+2+0+0
4ФЕИТ01Л019 Control systems 6 2+2+1+0
4ФЕИТ08Л010 Mathematics 4 6 3+3+0+0

 

During studying, the student may choose up to 4 courses from the faculty list of electives

Semester 5
Mandatory courses
Code Title ECTS No of classes per week
4ФЕИТ09З002 High Voltage Transmission Networks and Systems 6 3+2+0+0
4ФЕИТ09З003 Power Distribution System 6 3+1+1+0
4ФЕИТ09З022 High Voltage 1 6 3+1+1+0
4ФЕИТ10З014 Communication technologies and protocols in power engineering 6 3+1+1+0
  Elective course 1 6  
Elective course 1
4ФЕИТ09З001 Computer Applications in Power Systems 6 3+0+2+0
4ФЕИТ09З012 Overhead lines and cables 6 3+2+0+0

 

During studying, the student may choose up to 4 courses from the faculty list of electives

Semester 6
Mandatory courses
Code Title ECTS No of classes per week
4ФЕИТ04Л004 Power Plants and Substation 6 3+2+0+0
4ФЕИТ09Л011 Computer Methods for Power Systems Analysis 6 3+1+1+0
4ФЕИТ09Л014 Fundamental Economics for the Power Sector 6 3+2+0+0
Elective course 1 6
Elective course 2 6
Elective course 1 & 2
Code Title ECTS No of classes per week
4ФЕИТ09Л009 Smart Grids 6 3+2+0+0
4ФЕИТ09Л010 Power Quality 6 3+1+1+0
4ФЕИТ03Л005 Power Systems Measurements 6 3+1+1+0
4ФЕИТ09Л023 High Voltage 2 6 3+2+0+0

 

During studying, the student may choose up to 4 courses from the faculty list of electives

Semester 7
Mandatory courses
Code Title ECTS No of classes per week
4ФЕИТ09З016 Electricity Markets 6 3+2+0+0
4ФЕИТ09З021 Power System Operation 6 3+2+0+0
4ФЕИТ09З024 Power Systems Control and Dispatching 6 3+2+0+0
Elective course 1 6
Elective course 2 6
Elective course 1 & 2
Code Title ECTS No of classes per week
4ФЕИТ09З004 Power System Reliability 6 3+2+0+0
4ФЕИТ09З007 Electrical Lighting 6 3+1+1+0
4ФЕИТ09З008 Groundings and Grounding Systems in Power Networks 6 3+2+0+0
4ФЕИТ02З018 Fundamentals of Renewable Energy Sources 6 3+1+1+0

 

During studying, the student may choose up to 4 courses from the faculty list of electives

Semester 8
Mandatory courses
Code Title ECTS No of classes per week
4ФЕИТ12Л006 Final Thesis 9
4ФЕИТ09Л017 Power System Planning 6 3+2+0+0
4ФЕИТ12Л011 Internship 3
Elective course 1 6
Elective course 2 6
Elective course 1
Code Title ECTS No of classes per week
4ФЕИТ09Л005 Engineering Economics 6 3+2+0+0
4ФЕИТ04Л016 Entrepreneurship and business for engineers 6 3+2+0+0
4ФЕИТ04Л018 Project management and Ethics in Engineering 6 3+2+0+0
4ФЕИТ09Л020 Regulation in the Electricity Sector 6 3+2+0+0
Elective course 2
Code Title ECTS No of classes per week
4ФЕИТ03Л001 Virtual Instrumentation in LabVIEW 6 2+2+1+0
4ФЕИТ06Л002 Electric Vehicles 6 3+2+0+0
4ФЕИТ04Л022 Power System Protection 6 2+2+1+0

 

During studying, the student may choose up to 4 courses from the faculty list of electives

No. Code Title Semester No of classes per week ECTS Faculty
1 4ФЕИТ06З004 Energy and Sustainable Dеvelopment III 3+2+0 6 FEIT
2 4ФЕИТ05З011 Digital Signal Processing V 3+1+1 6 FEIT
3 4ФЕИТ08З003 Discrete Mathematics V 3+3+0 6 FEIT
4 4ФЕИТ08З004 Electrooptics V 2+2+1 6 FEIT
5 4ФЕИТ04З005 Energy Efficiency and Environment V 3+2+0 6 FEIT
6 4ФЕИТ07З013 Operating Systems V 2+2+1 6 FEIT
7 4ФЕИТ12З009 Introduction to WEB programming V 2+2+1 6 FEIT
8 4ФЕИТ08З013 Statistical Data Analysis V 3+1+1 6 FEIT
9 4ФЕИТ12Л001 WEB Applications VI 2+2+1 6 FEIT
10 4ФЕИТ01Л005 Inteligent Control Systems VI 2+2+1 6 FEIT
11 4ФЕИТ08Л006 Computer-supported Geometric Modeling VI 3+2+0 6 FEIT
12 4ФЕИТ01Л006 Computer Process Control VI 2+2+1 6 FEIT
13 4ФЕИТ04Л025 Photovoltaic Systems VI 3+1+1 6 FEIT
14 4ФЕИТ08Л011 Numerical Methods VI 3+0+2 6 FEIT
15 4ФЕИТ07Л016 Data Science and Data Analysis VI 2+2+1 6 FEIT
16 4ФЕИТ01Л017 Robotics 1 VI 2+2+1 6 FEIT
17 4ФЕИТ05З001 VLSI Design with PLD and FPGA Components VII 3+1+1 6 FEIT
18 4ФЕИТ05З007 Embedded Systems VII 3+1+1 6 FEIT
19 4ФЕИТ08З002 Introduction to nanomaterials and nanotechnologies VII 2+2+1 6 FEIT
20 4ФЕИТ10З005 Digital Currencies VII 3+1+1 6 FEIT
21 4ФЕИТ05З012 Digital Image Processing VII 3+1+1 6 FEIT
22 4ФЕИТ02З014 Small and Special Electrical Machines VII 3+0+2 6 FEIT
23 4ФЕИТ12З010 Development of Server-based WEB Applications VII 2+2+1 6 FEIT
24 4ФЕИТ01З007 Machine Learning VII 2+2+1 6 FEIT
25 4ФЕИТ01З011 Operations Research VII 2+2+1 6 FEIT
26 4ФЕИТ08З012 Fundamentals of Convex Optimization with Applications VII 3+2+0 6 FEIT
27 4ФЕИТ10З030 Network Forensics VII 3+1+1 6 FEIT
28 4ФЕИТ05Л023 Machine Vision VIII 3+1+1 6 FEIT
29 4ФЕИТ05Л005 Biomedical Electronics VIII 3+1+1 6 FEIT
30 4ФЕИТ03Л010 Measurement Systems and Data Acquision VIII 3+1+1 6 FEIT