Current Situation
The grid is managed through power flow and the effect that load and source have on the grid based on day-ahead planning and worst-case demand scenarios.
Goals and Objectives
Use predictive analytics and access to multiple data sources to predict grid performance and use a more “just in time” approach to power management. It will allow the ISOs to significantly reduce back and ancillary generation sources.
Technology Deployed
DERMS, smart grid components, grid analytics, cognitive, cloud, artificial intelligence, machine learning
Use Case Summary
Real-time control of grid through analytics and predictive performance to better account for supply and demand on the grid.