Advanced AI-powered monitoring and predictive analytics for critical power infrastructure. Detect grid instabilities before they cascade into blackouts.
Real-time data from IEEE 9-bus test system • Updates every second
Monitor frequency deviations, RoCoF, and grid health in real-time
Automatic detection of critical events and anomalies
Dashboard refreshes every second with latest PMU measurements
Interactive visualization of the power grid network
Voltage: 1.04 p.u.
Frequency: 60.0 Hz
Status: Normal
3 generators and 6 load buses interconnected
Hover over nodes to see live measurements
30 Hz synchrophasor measurements at every bus
Watch how our system detects and responds to grid events in real-time
See how the system automatically detects frequency drops, voltage sags, and generator trips
Watch real-time charts update with PMU measurements and EKF state estimates
Experience AI-powered predictions warning of potential stability issues
Built for utilities, grid operators, and energy companies
Real-time phasor measurement data at 30 Hz (every 33ms) for precise grid state awareness
Advanced state estimation with intelligent filtering for accurate grid parameter tracking
AI-powered insights for proactive grid management and event prediction
Intuitive web interface with real-time visualizations and interactive topology
Modern FastAPI backend for seamless integration with existing systems
Enterprise-grade architecture designed for critical infrastructure
Advanced engineering for mission-critical power systems
stream_pmu.py
ekf_service.py
web_api.py
dashboard_enhanced.html
| PMU Latency | < 35ms |
| EKF Processing Time | < 50ms |
| API Response Time | < 10ms |
| Dashboard Refresh Rate | 1 Hz |
| Memory Footprint | ~50 MB |
| CPU Usage | < 5% |
Based on the WSCC 9-bus test case, a standard benchmark for power system analysis:
Transform grid operations with data-driven intelligence
in operational costs through:
Enhanced grid reliability through:
Incident response with:
Monitor transmission and distribution networks, detect voltage instabilities, and optimize load balancing
Real-time situational awareness, inter-area oscillation detection, and frequency regulation
Manage grid stability with high penetration of solar, wind, and battery storage systems
Monitor critical facilities, data centers, and manufacturing plants with dedicated power systems
Power systems research, EKF algorithm development, and grid dynamics education
Grid modernization projects, SCADA upgrades, and smart grid implementations
Get started in minutes with our streamlined deployment process
git clone https://github.com/hushare1/GRIDSENSE-STREAM-AI.git
cd GRIDSENSE-STREAM-AI
python3 -m venv venv && source venv/bin/activate
pip install -r requirements.txtpython3 run_integrated.pyStarts PMU streaming, EKF service, and web dashboard at http://localhost:8001
http://localhost:8001http://localhost:8001/docsGET /api/latestExtend the system with custom events, integrate with your SCADA/EMS, or deploy to production infrastructure
Connect to existing SCADA infrastructure via OPC UA, Modbus, or DNP3 protocols
Integrate with EMS platforms for advanced grid optimization and control
Store historical data in OSIsoft PI, Wonderware, or time-series databases
Trigger alerts via email, SMS, Slack, PagerDuty, or custom webhooks
Comprehensive guides, API references, and tutorials
On-site or remote training for your engineering team
Tailored features and integrations for your needs
Enterprise SLA with dedicated support team
Transform your grid operations with GridSense-AI Pro