The course covers various aspects of optimization with a focus on applications to energy networks. Throughout the course, concepts from optimization theory are introduced followed by practical applications of the discussed approaches.
Learning objective
After this class, the students should have a good handle on how to approach a research question which involves optimization and implement and solve the resulting optimization problem by choosing appropriate tools.
Content
In our everyday’s life, we always try to take the decision which results in the best outcome. But how do we know what the best outcome will be? What are the actions leading to this optimal outcome? What are the constraints? These questions also have to be answered when controlling a system such as energy systems. Optimization theory provides the opportunity to find the answers by using mathematical formulation and solution of an optimization problem. The course covers various aspects of optimization with a focus on applications to energy networks. Throughout the course, concepts from optimization theory are introduced followed by practical applications of the discussed approaches. The applications are focused on the Optimal Power Flow problem which is formulated and solved to find optimal device settings in the electric power grid and other relevant energy scheduling problems. On the theoretical side, the formulation and solving of unconstrained and constrained optimization problems, multi-time step optimization, stochastic optimization including probabilistic constraints and decomposed optimization (Lagrangian and Benders decomposition) are discussed.
Performance assessment
Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course