Power Engineering and Project Management – 2022

ObjectivesLearning outcomesIIIIIIIVVVIVIIVIIIElective Courses

Study Programme
Power Engineering and Project Management

Degree Programme
First cycle degree programme

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

Occupational Profiles of Graduates
Graduates from this study curriculum are capable to create their own business or to be emplyed in some of the companies that are dealing with: generating electricity by clasical or renewable sources; trading; power distribution and transmission companies; management, design, protection, automation and control of electric power facilities; consulting services in project management studies and techno-econimic analysis; energy efficiency and environment etc.

The Programme Learning Outcomes
Study programme Power engineering and Management follows the needs of the companies in power engineering area in order to create modern educated engineer that will have professional knowledge in power engineering, information and communication technologies, as well as, competence and knowledge for managing complex technical projects in a new market oriented business environment. In this study programme the students are studying technologies for power generation from clasical and renewable sources; substation and control systems in power systems; modern software tools for solving engineering tasks; methods for efficient usage of electricity, as well as, managerial skills and techniques of project management.

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.
  • Demonstrates knowledge and understanding of research, development, engineering design in industrial processes and power engineering and management.
  • 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 engineering and management.
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 engineering and management of power plants.
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 the ability to evaluate and use modern software development 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
4ФЕИТ04З017 Project management 6 3+2+0+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
4ФЕИТ04Л011 Management and engineering economy 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
4ФЕИТ04З003 Power Plants 6 3+2+0+0
4ФЕИТ10З014 Communication technologies and protocols in power engineering 6 3+1+1+0
4ФЕИТ09З018 Transmission and Distribution Power Systems 6 3+2+0+0
4ФЕИТ04З021 Electrical Substations 6 3+2+0+0
Elective course 1 6
Elective course 1
Code Title ECTS No of classes per week
4ФЕИТ04З005 Energy Efficiency and Environment 6 3+2+0+0
4ФЕИТ09З022 High Voltage 1 6 3+1+1+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
4ФЕИТ04Л002 Power Plant and System Operation 6 3+2+0+0
4ФЕИТ04Л013 Renewable Energy Sources for Electricity Generation 6 3+2+0+0
4ФЕИТ04Л022 Power System Protection 6 2+2+1+0
Elective course 1 6
Elective course 2 6
Elective course 1 & 2
Code Title ECTS No of classes per week
4ФЕИТ03Л002 Electrical Measurements of Non-electrical Quantities 6 3+1+1+0
4ФЕИТ04Л009 Communication skills 6 3+1+1+0
4ФЕИТ09Л013 Low Voltage Electrical Installations and Lighting 6 2+2+1+0
4ФЕИТ04Л012 Nuclear Power Plants 6 3+2+0+0
4ФЕИТ04Л023 Software tools in Power Engeenering 6 3+1+1+0
4ФЕИТ04Л025 Photovoltaic Systems 6 3+1+1+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
4ФЕИТ04З006 Grounding, professional risk and safety in power plants аnd substations 6 3+2+0+0
4ФЕИТ04З024 Power Plant and Substation Control Systems 6 3+2+0+0
Elective course 1 6
Elective course 2 6
Elective course 3 6
Elective course 1, 2 & 3
Code Title ECTS No of classes per week
4ФЕИТ04З001 Wind Power Plants 6 3+2+0+0
4ФЕИТ04З007 Cogeneration Plants 6 3+2+0+0
4ФЕИТ04З010 Small Hydro Power Plants 6 3+2+0+0
4ФЕИТ09З012 Overhead lines and cables 6 3+2+0+0
4ФЕИТ04З015 Electric Power Plants Planning and Operation 6 3+2+0+0
4ФЕИТ04З019 Design and Integration of Renewable Energy Sources in Power Systems 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
4ФЕИТ04Л020 Power Plants and Substation Design 6 3+2+0+0
4ФЕИТ04Л008 Computer-based Modeling in Power Engineering 6 3+2+0+0
4ФЕИТ12Л011 Internship 3
Elective course 1 6
Elective course 1
Code Title ECTS No of classes per week
4ФЕИТ04Л016 Entrepreneurship and business for engineers 6 3+2+0+0
4ФЕИТ03Л008 Principles of Quality Management 6 3+2+0+0
4ФЕИТ09Л020 Regulation in Electricity Sector 6 3+2+0+0
4ФЕИТ08Л014 Technological Innovations 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
L E
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 4ФЕИТ07З013 Operating Systems V 2 2+1 6 FEIT
6 4ФЕИТ12З009 Introduction to WEB programming V 2 2+1 6 FEIT
7 4ФЕИТ08З013 Statistical Data Analysis V 3 1+1 6 FEIT
8 4ФЕИТ12Л001 WEB Applications VI 2 2+1 6 FEIT
9 4ФЕИТ03Л001 Virtual Instrumentation in LabVIEW VI 2 2+1 6 FEIT
10 4ФЕИТ09Л009 Smart Grids VI 3 2+0 6 FEIT
11 4ФЕИТ01Л005 Inteligent Control Systems VI 2 2+1 6 FEIT
12 4ФЕИТ08Л006 Computer-supported Geometric Modeling VI 3 2+1 6 FEIT
13 4ФЕИТ01Л006 Computer Process Control VI 2 2+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 4ФЕИТ01З007 Machine Learning VII 2 2+1 6 FEIT
24 4ФЕИТ01З011 Operations Research VII 2 2+1 6 FEIT
25 4ФЕИТ12З010 Development of Server-based WEB Applications 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