EE674 COMPUTATION.TECH. IN POWER SYS. ANALYSIS
Course Code: | 5670674 |
METU Credit (Theoretical-Laboratory hours/week): | 3 (3.00 - 0.00) |
ECTS Credit: | 8.0 |
Department: | Electrical and Electronics Engineering |
Language of Instruction: | English |
Level of Study: | Graduate |
Course Coordinator: | Prof.Dr. MURAT GÖL |
Offered Semester: | Fall Semesters. |
Course Objectives
At the end of this course, the student will learn:
- basic computational techniques employed in power system analysis
- solving linear equations efficiently in computataional environment
- modifying solution of a linear equation
- basic concepts of parallel processing
Course Content
Power system modeling; sparse data structures; computational issues for various power system problems; solution of large sparse linear systems: factorization, ordering, inverse factors, sparse vector methods, compensation, partial matrix refactorization, applications; vector processing and parallel processing: implementation issues and applications in power.
Course Learning Outcomes
Student, who passed the course satisfactorily will be able to:
- build system matrices to model a given power system using sparse storage techniques
- use computational techniques to implement a compuattionally efficient power system analysis tool
Program Outcomes Matrix
Contribution | |||||
# | Program Outcomes | No | Yes | ||
1 | Depth: Our graduates acquire in depth knowledge in one of the various specialization areas of Electrical and Electronics Engineering, they are informed about current scientific research topics and they implement innovative methods. | ✔ | |||
2 | Breadth: Our graduates get familiarized in other subspecialty areas related to their specialization in Electrical and Electronics engineering and/or relevant areas in other disciplines. | ✔ | |||
3 | Research: Our graduates acquire the skills to conduct and to complete scientific research by accessing contemporary knowledge in their specialty areas. | ✔ | |||
4 | Life-long learning: Our graduates develop their life-long learning habits. | ✔ | |||
5 | Communication skills: Our graduates concisely communicate their ideas and work related results in written and oral form. | ✔ | |||
6 | Ethics: Our graduates internalize rules of research and publication ethics as well as professional ethics. | ✔ |