Summer Course at Aalto University on Condition Monitoring and Diagnostics of Power Assets

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Our chapter together with Aalto University is offering an intensive 5-day 4-credit course on the Condition Monitoring and Diagnostics of Power Assets taught by Dr. Murtaza Hashmi, a recognized Condition Monitoring Expert at Power Systems. The assessment of the course will be based on attendance, active participation in the discussions, and performance in Group Work and Home Work activities. It is worth mentioning that the course is free for our IEEE Members. Please note that we only have 6 places available for this course.

Please find the additional information as follows.  

Course General Information:

This course will address state-of-the-art condition monitoring techniques used for different assets in electrical power systems. A brief overview of condition monitoring and diagnostics, associated monitoring parameters, and tools for analysis will be discussed. Special focus will be given on understanding advanced diagnostics technique of Partial Discharge (PD), its types and characteristic, detection principles and methods, analysis criteria and standards, PD signals propagation and attenuation, and calibration technique. The advanced condition monitoring and diagnostics techniques will be described for transformers, switchgears, power cables, and other electrical equipment installed in the substation including the details of pilot projects, case studies and real-time measurements. An overview of smart sensing infrastructure, its application for digital transformation, and digital substations will be carried out which build the basis of Industry 4.0 for advanced condition monitoring, diagnostics, and predictive maintenance applications in power systems.

Learning Outcomes:

Upon successful completion of this course, students will be able to:

  • Explain the meaning of condition monitoring & diagnostics and its applications
  • Explain PD monitoring techniques and standards, limits and advantages and disadvantages of online and offline PD monitoring, associated sensors, PD data analysis and interpretation for the condition assessment of electrical equipment.
  • Explain different advanced condition monitoring & diagnostics systems for transformers, switchgears, power cables, and other electrical equipment installed in the substation.
  • Develop condition monitoring plan to install advanced systems for the diagnostics and predictive maintenance of electrical power assets
  • Explain elements of smart sensing infrastructure and develop strategy to implement it in power systems under Industry 4.0 initiative

Learning Resources:

A set of course presentation slides, and supporting materials based on publications, white papers, case studies, and technology brochures will be available.

Learning and Teaching Activities:

This course relies on lectures and interactive discussions as the primary delivery mechanism. A Group Work will be assigned to the students in the classroom to reinforce the theoretical concepts encountered in lectures and deliver brief presentation by each Group. In addition, a Home Work will be assigned to the students in the form of writing an essay to summaries the details of advanced condition monitoring systems for power assets to gauge their progress and understanding.

Assessment:

The assessment of the course will be based on the attendance, active participation in the discussions, and performance in Group Work and Home Work activities.

Language:

The working language of the course is English.



  Date and Time

  Location

  Hosts

  Registration



  • Start time: 15 Aug 2022 08:30 AM
  • End time: 19 Aug 2022 03:30 PM
  • All times are (UTC+02:00) Helsinki
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  • Aalto University
  • Otaniemi
  • Espoo, Sodra Finlands Lan
  • Finland
  • Building: Maarintie 8
  • Room Number: 2103
  • Click here for Map

  • Co-sponsored by Aalto University
  • Starts 05 May 2022 02:30 PM
  • Ends 05 August 2022 11:59 PM
  • All times are (UTC+02:00) Helsinki
  • 2 spaces left!
  • No Admission Charge


  Speakers

Murtaza Hashmi Murtaza Hashmi

Topic:

Condition Monitoring and Diagnostics of Power Assets

This course will address state-of-the-art condition monitoring techniques used for different assets in electrical power systems. A brief overview of condition monitoring and diagnostics, associated monitoring parameters, and tools for analysis will be discussed. Special focus will be given on understanding advanced diagnostics technique of Partial Discharge (PD), its types and characteristic, detection principles and methods, analysis criteria and standards, PD signals propagation and attenuation, and calibration technique. The advanced condition monitoring and diagnostics techniques will be described for transformers, switchgears, power cables, and other electrical equipment installed in the substation including the details of pilot projects, case studies and real-time measurements. An overview of smart sensing infrastructure, its application for digital transformation, and digital substations will be carried out which build the basis of Industry 4.0 for advanced condition monitoring, diagnostics, and predictive maintenance applications in power systems.

Biography:

Murtaza Hashmi received Master’s Degree in electric power engineering from the Royal Institute of Technology (KTH) Stockholm, Sweden in 2001, and D.Sc. (Tech.) in condition monitoring and asset management from Aalto University, Finland in 2008. He worked as Power Distribution Specialist at ABB Oy for two years. From 2010-2013, he worked as Senior Scientist with Energy Systems Knowledge Centre at VTT Technical Research Centre of Finland. Currently, he is working as Condition Monitoring Expert at Power Systems, Saudi Aramco. His major interests are implementing online advanced condition monitoring technologies for substation equipment, conducting Partial Discharge (PD) measurements for insulation diagnostics of electrical equipment, power systems transients, and insulation coordination. He has published more than fifty research articles in reputed refereed international journals and conferences. He is member of IEEE and GCC CIGRE.





Agenda

Course Agenda (15 – 19th August 2022, Timing 08:30 – 15:30):

Day 1, August 15, (PD Monitoring & Diagnostics in Electrical Equipment)

  • Understanding condition monitoring & diagnostics, its significance, associated parameters, and advanced tools for analysis.
  • Partial Discharge (PD), its types & characteristic, detection principles & methods, analysis criteria and standards.
  • PD signals propagation and attenuation, different types of noises or interferences and their elimination.
  • Calibration of online PD monitoring system

Day 2, August 16, (Condition Monitoring & Diagnostics of Transformers)

  • Online Dissolved Gas Analysis (DGA) monitoring system
  • Online drying & dehydrating breather systems
  • Bushing monitoring system for bushing and winding health condition assessment
  • Other monitoring systems based on PD measurements using ultrasonic and high frequency sensors

Day 3, August 17, (Condition Monitoring & Diagnostics of Switchgears and Power Cables)

  • Online PD monitoring system for Gas Insulated Substations (GIS)
  • Online asset monitoring systems for Air Insulated Substations (AIS)
  • Condition monitoring systems for power cables
  • PD monitoring & diagnostics case studies

Day 4, August 18, (Condition Monitoring of Other Electrical Equipment)

  • PD monitoring in rotating machines
  • Room-Temperature Vulcanizing (RTV) silicon rubber coating assessment for insulators, bushings and surge arresters
  • Fault detection & localization system for overhead distribution lines
  • Condition monitoring and predictive maintenance using advanced UV, optical and infrared imaging techniques

Day 5, August 19, (Smart Sensing Infrastructure and Smart Grids)

  • Components of Industry 4.0 and its application in digital transformation
  • Smart sensing infrastructure for smart grids
  • Digital substations with advanced sensing technologies
  • Group Work: Important elements of CM system – Sensors, data communication, data analysis, decision-making
  • Explanation of Home Work: An essay on advanced condition monitoring systems for transformers, switchgears, and power cables – Technology, implications, and challenges for implementation!