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Content and learning outcomes
This course is about utilizing quantitative methods to analyze and prevent risks of failure in electrical power systems, and shows on practical examples.
The lectures are concentrated to three parts, and a final seminar. The course parts includes the following areas of attention:
- Models; basic methods and techniques
- Analysis; input data, approximative methods and tools.
- Results; cost efficient strategies and economic incentives
The following activities are part of the course
- Work with project assignment individually or in pairs. The problem formulation should relate to a real situation and preferably connected to your area of work/studies, written report.
- Lectures presenting different methods for reliability analysis in electric power engineering.
- Guest lectures with speakers from the industry, showing on results of reliability analysis.
- Computer laborations that exercise the application of methods and tools that are presented in the course.
- Written examination, testing reached knowledge and abilities in the methods taught in the course, one examination in classroom and one home exam.
- Seminar with oral presentation of projects as well as opposition to projects. Participation is mandatory.
Intended learning outcomes
After completed course the students should be able to use reliability assessment as a tool for decision support for planning and operation of the electric power system. After the course is completed, the participants have gained knowledge to:
-Describe the fundamental definitions and concepts for reliability assessment
-Analyze a system and its components using the following techniques for reliability assessment:
- Network modelling
- Component importance techniques
- Markov modelling
- Lifetime models
-Analyze an electrical distribution system with the above described methods tools such as NEPLAN
-Describe how reliability is treated in the regulation.
-Formulate an Life cycle cost model (LCC)
-Formulate a reliability centred maintenance plan following fundamentals of RCM and knowledge in more advanced methods like RCAM.
The course is offered in three main blocks, with each block consisting of a number of consecutive with lectures, online teaching and/or computer laborations. Between the blocks there are breaks for selfstudies. The course ends with a seminar day and final adjustments of reports.
Literature and preparations
Completed course SF1920 Probability Theory and Statistics, or equivalent course of at least 5 credits.
Completed course of at least 6 credits in electrical engineering, eg EG2100 Power System Analysis, EG2200 Power Generation Operation and Planning, EH2741 Communication and Control in Electric Power Systems, EI2436 Power Grid Technology and Substation Design, EJ2301 Power Electronics or EJ2201 Electrical Machines and Drives, or equivalent experience.
Mathematics from year 1-3.
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C. J. Wallnerström, P. Hilber, Reliability Analysis and Asset Management Applied to Power Distribution, March 2014.
Examination and completion
If the course is discontinued, students may request to be examined during the following two academic years.
A, B, C, D, E, FX, F
- PRO1 - Project work, 4.5 credits, grading scale: P, F
- TEN1 - Exam, 3.0 credits, grading scale: A, B, C, D, E, FX, F
Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.
The examiner may apply another examination format when re-examining individual students.
Other requirements for final grade
For passing grade in the course the following is required:
PRO1, 4.5 credits:
- Approved project assignment, written and oral presentations.
- Approved laboratory work, including attending laboratory exercises and written laboration reports.
TEN1, 3 credits:
- Approved examination, divided into two occasions.
Opportunity to complete the requirements via supplementary examination
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Opportunity to raise an approved grade via renewed examination
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- All members of a group are responsible for the group's work.
- In any assessment, every student shall honestly disclose any help received and sources used.
- In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.
Further information about the course can be found on the Course web at the link below. Information on the Course web will later be moved to this site.Course web EI2452
Main field of study
EI270X Master thesis at EME/QED
Sanja Duvnjak Zarkovic email@example.com
The course provides students with a good opportunity to formulate a problem area for their master thesis project and also to initiate contacts in the industry.
In this course, the EECS code of honor applies, see: http://www.kth.se/en/eecs/utbildning/hederskodex.