Time Schedule:
Daniel Sadi Kirschen
E E 554
Seattle Campus
Deals with problems whose solution depends upon the inversion of sparse matrices that occur in the planning and operational studies of large interconnected energy systems. Application studies include system model development, state estimation, and load flow. Prerequisite: E E 456 or permission of instructor.
Class description
This course will cover computational methods for the analysis of large power systems: solution of systems of linear equations, solutions of systems of non-linear equations, applications to the power flow problem, sparsity techniques, least square estimation, application to state estimation in power systems, introduction to the optimal power flow problem.
Student learning goals
Define and discuss the major problems in steady state power system analysis
Design, develop and test computer programs for solving the power flow and state estimation problems
Data structures and programming techniques to take advantage of sparsity
Purpose and implementation of the optimal power flow
General method of instruction
Lectures, group discussions, programming assignments, reading of scientific papers
Recommended preparation
An introductory course in power system analysis Experience with programming in any scientific computing language
Class assignments and grading
Over the course of the quarter, you will be given 5 or 6 programming assignments. You will work on these assignments in groups of 2 and both partners will receive the same mark for the assignment. I will decide on the composition of the groups and will change it for each assignment.
Programming assignments: 70% Final oral examination: 30%
The final exam will be an oral examination where you will give a short presentation on a paper selected from the litterature and will then be asked questions about the various topics that will have been covered in the course. The date and time of this exam will be arranged with each student individually.
