Real-Time Contingency Management
Advanced grid management that leverages real-time data collection, predictive analytics, and AI-driven responses for optimal capacity expansion and seamless renewable integration
Challenges
- Unplanned outages cost the U.S. economy $150 billion annually (U.S. Department of Energy)
- The average cost of critical infrastructure failure for utilities is $100,000 per hour (NOAA)
- The average weather/climate disasters per year (1980-2023): 8.5. Recent five years (2019-2023) saw a significant increase to 20.4 events per year. (NOAA)
- Between 2019 and 2022, Renewable consumption grew on average 6% YoY. (EIA)
- Reserve margins can't accurately reflect the variability introduced by renewables.
- Transmission congestion costs for RTOs surged has grown over 3x between 2020 and 2022, reaching $12 billion (Grid Strategies LLC)
Solutions
- Aggregate real-time data from substations, transmission lines, and weather stations.
- Generate a precise real-time model of the grid's status, factoring in load, generation capacity, and environmental conditions.
- Simulate various contingencies, using predictive analytics to anticipate their effects on grid stability.
- Continuously monitor live data against predictive models.
- Calculate optimal responses, such as adjusting power flows or production levels, to mitigate risk.
- Translate responses into control commands for swift reactions to maintain stability.
- Learn from events to enhance models and algorithms for better future performance.