Stochastic Processes In Power Systems
Electrical Engineering
Institute of Natural and Applied Sciences
Third Cycle (Doctorate Degree)
| Course Unit Title | Course Unit Code | Type of Course Unit | Level of Course Unit | Year of Study | Semester | ECTS Credits |
|---|---|---|---|---|---|---|
| Stochastic Processes In Power Systems | MEL604 | Elective | Doctorate degree | 1 | Spring | 8 |
Name of Lecturer(s)
Prof. Dr. Nurettin ABUT
Prof. Dr. Semra ÖZTÜRK
Associate Prof. Dr. Hasbi İSMAİLOĞLU
Learning Outcomes of the Course Unit
1) Interpret the probability and random variables
2) Apply the distribution and density functions
3) Comprehend the stochastic processes
4) Distinguish the Markov processes
5) Calculate the reliability level of a system
Program Competencies-Learning Outcomes Relation
| Program Competencies | |||||||||||
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | ||
| Learning Outcomes | |||||||||||
| 1 | Middle | Middle | Low | No relation | Middle | Middle | No relation | Low | No relation | Middle | |
| 2 | High | Middle | Low | No relation | Middle | No relation | Low | Middle | No relation | Low | |
| 3 | Middle | High | Low | No relation | Middle | No relation | Low | Middle | Low | Low | |
| 4 | Middle | High | Middle | No relation | Middle | No relation | Middle | Middle | Low | Middle | |
| 5 | High | Middle | Middle | No relation | Middle | No relation | Middle | Middle | Middle | Low | |
Mode of Delivery
Face to Face
Prerequisites and Co-Requisites
None
Recommended Optional Programme Components
Probability Theory
Course Contents
Introduction. Trials events. Conditional probability and Bayes' Theorem. Random variable, the mean value, variance and moments. Distribution and density functions. Two-dimensional random variables. Stochastic processes, stationary processes. Concepts of correlation and power spectrum . Markov and Poisson processes.
Weekly Schedule
1) Introduction2) Trials, events,
3) Conditional probability and Bayes' Theorem
4) Random variable and the mean value
5) Variance and moments
6) Distribution and density functions
7) Distribution and density functions
8) Midterm examination/Assessment
9) Two-dimensional random variables
10) Stochastic processes
11) Stationary processes
12) The concepts of self-correlation and cross-correlation
13) The concept of the power spectrum
14) Markov processes
15) Poisson processes
16) Final examination
Recommended or Required Reading
Planned Learning Activities and Teaching Methods
Assessment Methods and Criteria
Language of Instruction
Turkish
Work Placement(s)
Not Required