In this course, classical and modern optimization techniques are covered in sufficient detail to allow students to use them in almost any engineering and non-engineering areas. The focus of the course is on electrical power systems applications. Electrical power industry is going through a major transformation and relies on optimal planning and operations to increase energy efficiency, lower energy cost and address environmental concerns. During the semester various optimization methods are studied and applied to standard power system problems such as optimal power flow, unit commitment, state estimation, short and long term planning, and frequency and voltage control. The course will cover classical methods including linear programming, non-linear programming, dynamic programming, relaxation methods, mixed integer programming and modern algorithms such as genetic algorithm, neural networks, simulated annealing and others. These algorithms will be mastered from both the theoretical and implementation point of view.
Completion of 18-372 is recommended but not required.
Course format: Online
Check the original course description for the most recent information.