Electric Grid Dynamics and Stability | February 24 – 26, 2026
The goal of this course is to present how issues associated with the dynamics and stability affect the design and operation of large-scale electric grids. The analysis of electric grids is often divided into issues that affect their steady-state operations and issues that affect their dynamics and ultimate stability. Steady-state issues, such as power flow, are usually covered in undergraduate electric power classes. Dynamic considerations, however, are often considered at only a cursory level or skipped entirely. Yet with the recent changes in electricity systems, such as the integration of large amounts of renewable generation and the deployment of large numbers of phasor measurement units, dynamics are more important than ever.
The purpose of this three-day short course is to put electric grid dynamics into a proper perspective by providing a comprehensive coverage of how dynamics impact the design and operation of the grid, the models and tools used for their assessment, and case study examples. The course philosophy is to provide in-depth coverage of the topics, but to do so using a practical, hands-on approach with abundant examples. For example, the course provides a detailed consideration of what is needed to do and contains an interactive, real-time simulation of a large-scale electric grid during a variety of different events that involve electric grid dynamics. Throughout the course, concepts will be illustrated using common industrial tools including PowerWorld Simulator. Collectively the four course instructors have wide experience in this area doing electric power system studies, software tool development, research and engineering education (Hours: CEU 2.1, PDH 21).
Introduction of Artificial Intelligence in Power Systems | April 7-9, 2026
The course is designed to provide introductory coverage of data science and machine learning that is tailored for power engineering applications. The electricity industry is transforming itself from a hierarchical, passive, and sparsely-sensed engineering system into a flat, active, and ubiquitously-sensed cyber-physical system. The emerging multi-scale data from synchrophasors, smart meters, weather, and electricity markets offers tremendous opportunities as well as challenges for the industry to dynamically learn and adaptively control a smart grid. This training introduces the foundation of high-dimensional spaces and data analytical tools necessary to model and operate a modern power system. We will introduce a suite of tools for statistical time series analysis and dimensionality reduction. We will discuss the differences between first-principle models and data-driven models in real-time operations. Discussions and computer-based simulation projects will prepare the participants to better understand how to integrate data-driven and physics-based reasoning in modern power systems.
Printed Circuit Board Design Fundamentals
In this course, learners will explore key concepts related to printed circuit board (PCB) design and manufacturing. Participants will gain hands-on experience with the Allegro X System Capture Schematic Editor, where they will learn to create schematic parts, develop both flat and hierarchical schematics, design variants, and produce netlists. Also, the course will cover the Allegro X PCB Editor layout design, enabling learners to apply design constraints, effectively place and route their designs, and create essential manufacturing outputs. Finally, participants will use Allegro X DesignTrue DFM to develop and implement a new set of design for manufacturing (DFM) constraints, ensuring their designs meet industry standards for manufacturability.