Navigation

13M021MID - Monitoring and Diagnostics of High Voltage Substations

Course specification
Course title Monitoring and Diagnostics of High Voltage Substations
Acronym 13M021MID
Study programme Electrical Engineering and Computing
Module
Type of study master academic studies
Lecturer (for classes)
Lecturer/Associate (for practice)
Lecturer/Associate (for OTC)
    ESPB 6.0 Status elective
    Condition No
    The goal Introducing the students to the most important methods of monitoring and diagnostics of the high voltage substations elements. Comparison of existing and newly established procedures for monitoring and diagnostics.
    The outcome Training the students to select appropriate methods and techniques for determining the real condition of high voltage equipment and systems necessary for their reliable operation and asset management.
    Contents
    URL to the subject page http://ees.etf.bg.ac.rs/predmet.php?Id=20#fajlovi
    Contents of lectures Introduction. Review of the condition monitoring. Benefit from the condition monitoring. Monitoring of high voltage equipment: the selection of the parameters for monitoring? Continuous or periodic monitoring. Information necessary for the reliable operation of high-voltage equipment and asset management. Thermal imaging process.
    Contents of exercises Examples of measurement of the partial discharges. Intelligent systems for the monitoring and diagnostics. Characteristics. Examples. Advanced diagnostic methods, software tools and examples of application in condition monitoring and diagnostics of overhead power lines.
    Literature
    1. H.M.Ryan, “High voltage engineering and testing”, 2nd Edition, IEE Publishing London, p.728, 2001. (Original title)
    2. A. Haddad and D.F. Warne, “Advances in high voltage engineering”, IEE Publishing London, p.647, 2004. (Original title)
    3. CIGRE Brochure No.167, Working Group 13.09, “User guide for the application of monitoring and diagnostic techniques for switching equipment for rated voltages of 72.5 kV and above”, Paris, 2000. (Original title)
    4. Žarković M. and Stojković Z. (2017) : Analysis of artificial intelligence expert systems for power transformer condition monitoring and diagnostics, Electric Power Systems Research, 149, pp. 125 - 136, 0378-7796, 10.1016/j.epsr.2017.04.025, Aug2017.
    5. Žarković M., Stojković Z. (2015) : Artificial intelligence based thermographic approach for high voltage substations risk assessment; IET Generation, Transmission & Distribution Vol. 9, Issue 14, November 2015, p. 1935-1945.
    Number of hours per week during the semester/trimester/year
    Lectures Exercises OTC Study and Research Other classes
    3 1
    Methods of teaching Classic lectures and lectures in electronic form. Exercises include solving problems, measurements in the laboratory or in the field, as well as the numerical simulations.
    Knowledge score (maximum points 100)
    Pre obligations Points Final exam Points
    Activites during lectures 10 Test paper 60
    Practical lessons 10 Oral examination 0
    Projects 0
    Colloquia 0
    Seminars 20