19D021VIE - Artificial Intelligence in power engineering

Course specification
Course title Artificial Intelligence in power engineering
Acronym 19D021VIE
Study programme Electrical Engineering and Computing
Type of study doctoral studies
Lecturer (for classes)
Lecturer/Associate (for practice)
    Lecturer/Associate (for OTC)
      ESPB 9.0 Status elective
      The goal Introducing students with the basic concepts of artificial intelligence and perception of how to apply in the electric power industry. Training students to independently use neuronal networks, fuzzy expert system, classification, and clustering algorithms for engineering applications in power engineering.
      The outcome Students will be able to independently analyze and synthesize different types of artificial intelligence that can be applied in many fields of power engineering. Empowering to apply different algorithms for the design of artificial intelligence systems and systems using fuzzy logic using appropriate software tools.
      Contents of lectures Solving problems in power engineering using artificial intelligence. Methodology for the application of artificial intelligence in the field of: calculation of power and reliability flows, diagnostics of elements of the power electrical systems, relay protection, renewable energy sources, smart grids and prediction of the price of electricity, load, production, and consumption of electricity.
      Contents of exercises Practical classes include exercising on the computer. Formation of algorithms and a program code that simulates the work of unsupervised machine learning, neural networks, and fuzzy logic.Application of artificial intelligence algorithms to adequate power industry database within potential seminary paper or research paper.
      1. Computational Intelligence Applications to Power Systems, Yong-Hua Song, Allan Johns, Raj Aggarwal,Springer Science & Business Media, 1996. (Original title)
      2. Artificial intelligence in power system optimization, Ongsakul, Weerakorn, Vo, Dieu Ngoc, CRC Press, Taylor & Francis, 2012. (Original title)
      3. Artificial Intelligence Techniques in Power Systems, K. Warwick, Arthur Ekwue, Raj Aggarwal, Institution of Electrical Engineers IET, 1997. (Original title)
      Number of hours per week during the semester/trimester/year
      Lectures Exercises OTC Study and Research Other classes
      Methods of teaching Classes are held on the board using the projector. Work is planned at the Computer Center.
      Knowledge score (maximum points 100)
      Pre obligations Points Final exam Points
      Activites during lectures 0 Test paper 0
      Practical lessons 20 Oral examination 30
      Projects 0
      Colloquia 0
      Seminars 50