Computational Methods For Power System Analysis

Catalog description

System modeling of power networks. Description of modern electricity markets. Analysis of the economic dispatch problem using optimality conditions. Planning of distributed energy resources. Smart grid applications. Machine learning applications to power systems (forecasting, demand-side management, and fault detection). Assigned projects will involve implementing some of the methods using realistic power system models. Course Learning Outcomes 1. Explain how electricity markets work and how various computational methods are used in power system operations and planning. 2. Understand formulation and solution techniques applied to normal operation of large power systems. 3. Implement existing optimization packages to solve power system problems. 4. Use machine learning methods to answer questions about power system operations. View Class Schedule