The BRADLEY DEPARTMENT of ELECTRICAL and COMPUTER ENGINEERING

Graduate PROGRAMS

Course Information

Description

This course is designed to introduce various linear and nonlinear program based optimization algorithms that are specially suited for the design, analysis and operation of electric power systems, power processing devices, machines and transformers.

Why take this course?

Various technical areas within power engineering routinely use large scale optimization techniques. These areas include generation expansion planning, bulk power supply systems, hydro-thermal scheduling, power converter design optimization and transformer design. Optimization and computational techniques and algorithms to be discussed in this course will give the student the necessary tools to analyze the design problems listed above.

Prerequisites

5324

This course requires a thorough understanding of principles of power system analysis including generation planning, production costing, reliability and stability analysis. This material is covered in EE 5324.

Major Measurable Learning Objectives

    The course should help the student understand the tools required to analyze and evaluate electric power apparatus and systems. In addition the student should also be able to compare the accuracy of results and solution times with respect to the complexity of the algorithms for studying electric power problems.

Course Topics

Topic

Percentage of Course

Power system models 15%
Power processing device models 15%
Transformer models 15%
Electric machine models 10%
Linear programming applications 15%
Quadratic programming applications 10%
Generalized reduced gradient applications 10%
Single and multivariable constrained method applications 10%