ESE 595 - Advanced Data Analytics in Modern Energy Systems

This course will cover a broad spectrum of cutting-edge topics of data analytics in modern energy systems. These include behind the meter data analytics, net load forecasting, prediction of network congestion and critical contingencies in power system operation, predictive maintenance of important assets in energy systems, outage and fault location, stability margin estimation in power systems, reinforcement learning for energy storage control and dynamic pricing, and learning-based transient dynamics prediction and simulation. Students will engage extensively in hands-on projects, supported by comprehensive real-world data.

3 credits

Prerequisite(s): ESE 588 and ESE 577 or ESE 589 or ESE 590

Grading Letter graded (A, A-, B+, etc.)