The electric power industry has undergone extensive changes over the past several decades and become substantially more complex, dynamic, and uncertain as new market rules, regulatory policies, and technologies have been adopted. This includes the adoption of more distributed, variable generation which introduces new dynamic and stochastic behaviors on the grid. Along with the introduction of shale gas, the generation mix is significantly being altered creating operational challenges for utilities. The availability of more detailed data about system conditions from devices, such as phasor measurement units for wide area visibility and advanced meter infrastructure for dynamic pricing and demand response, can be a great benefit for electric system reliability and flexibility. However, this large volume (and variety) of data poses its own challenges.
Shifting operational data analytics from a traditionally off-line environment to real-time situational awareness (e.g., visibility) to measurement-based, fast control will require significant advancements in algorithms and computational approaches. The goal is to leverage scientific research in mathematics for application to power system models and software tools.
- Frequency responsive demand modeling
- Renewables integration
- VERDE – visualizing electric grid
- Grideye – wide-area grid monitoring network
- Management & Optimization of VARs for Future Transmission Infrastructure (MOVARTI)