Software Defined
Grid Intelligence

Enabling flexible interconnection agreements that reduce grid upgrade costs by 60-80% while accelerating electrification deployment timelines from years to months.

Read the Research

The Grid Interconnection Crisis

The U.S. grid interconnection queue has reached 2,000 GW—more than double the existing grid capacity. Traditional utility approaches require $2.1 Billion in infrastructure upgrades to meet 2030 electrification goals. Source

Flexible interconnection agreements represent a paradigm shift: managing demand dynamically rather than building excess capacity. This approach can reduce infrastructure costs by 60-80% while maintaining grid reliability.

Grid Intelligence Solutions

A Software Defined approach to grid management delivers measurable improvements in capacity utilization, interconnection speed, and cost efficiency by leveraging real-time data, predictive analytics, and automated processes to reduce time and cost for utilties to connect new services to the grid.

Dynamic Capacity Management

Real-time grid modeling and automated load balancing enable utilities to safely maximize existing infrastructure capacity.

Capacity Utilization 90%+
N-1 Compliance 100%
Response Time ~800ms

Flexible Interconnection

Automated agreement generation and smart contract enforcement streamline the interconnection process for new grid connections.

Timeline Reduction 78%
Processing Time 8 weeks
Success Rate 96%

Predictive Analytics

Machine learning algorithms analyze historical patterns and real-time data to forecast grid demand with exceptional accuracy.

Forecast Accuracy 92%+
Prediction Horizons 48 hours
Model Updates Real-time

Technology Architecture

We’re building a platform that streamlines load studies and interconnection by leveraging software simulations to reduce the time, cost, and complexity utilities face when managing new connection requests.

Core Components

High-throughput data ingestion helps utilities verify and trust load simulations before interconnection.

A processing engine that handles billions of data poinst from, smart meters, and IoT sensors across the grid infrastructure to ensure simulation match reality.

  • Real-Time Event Processing: Continuously ingests grid data to detect constraints and load issues early
  • Grid Data Integration: Combines historical and live data to support load study automation and interconnection impact analysis
  • Instant Response Tools: Sub-second alerts and analytics for operators and planners
  • Built for Grid Planning: Stores time-series data to analyze trends and forecast future load scenarios

Advanced algorithms for demand forecasting, fault detection, and capacity optimization.

Machine learning models trained on 10+ years of grid data to predict demand patterns, equipment failures, and optimal capacity allocation.

  • Demand Forecasting: LSTM neural networks with 94%+ accuracy
  • Fault Detection: Anomaly detection using isolation forests
  • Capacity Optimization: Genetic algorithms for resource allocation
  • Model Updates: Continuous learning with online training pipelines

Forecast load impacts and streamline interconnection reviews with grid-proven data models.

Our forecasting engine uses over a decade of operational grid data to simulate how new loads or projects will affect local capacity, helping reduce costly surprises and accelerate approvals.

  • Load Impact Forecasting: Anticipate how new connections will affect feeders, substations, and local constraints
  • Early Fault Warnings: Identify unusual behavior in the system before it becomes a failure
  • Capacity Planning: Recommend least-cost upgrades or defer them with smart load shifting strategies
  • Always Up to Date: Continuously adapts as new interconnections and grid data come online

Accelerate interconnection reviews with real-time impact modeling and scenario planning.

Our simulation engine creates a live digital model of the grid, helping utilities evaluate new interconnection requests faster by forecasting system impacts and identifying potential constraints before they cause delays or require costly upgrades.

  • Load Flow Modeling: Analyze how proposed connections affect local voltage, capacity, and stability
  • Reliability Planning: Simulate N-1 events to ensure new loads won’t compromise grid performance
  • What-If Scenarios: Run interconnection simulations instantly to test upgrade options or alternative locations
  • Fast Results: Designed for speed, so planners can evaluate more scenarios without bottlenecks

System Architecture

Data Layer

SCADA • AMI • Weather • Market

Processing Layer

Stream Processing • ML Pipeline

Intelligence Layer

Optimization • Prediction • Control

Interface Layer

APIs • Dashboard • Automation

Research & Insights

After several months of research, it’s clear that software-defined grid intelligence has the potential to significantly improve utility operations and speed up clean energy deployment.

By combining accurate grid simulation with machine learning and large language models, utilities can streamline flexible interconnections, enable real-time enforcement, and use the resulting data to prioritize infrastructure upgrades and long-term planning.

Key Research Findings

Cost Reduction

60-80%

Reduction in grid upgrade costs through intelligent capacity management

Timeline Acceleration

78%

Faster interconnection processing with automated agreement generation

Capacity Utilization

95%+

Safe utilization of existing infrastructure without compromising reliability

Queue Backlog

2,000 GW

Total capacity in interconnection queues that could be accelerated

Research Methodology

Grid Simulation Studies

Using two years of historical utility data and sensor network inputs, we build a digital twin of grid operations to streamline interconnection impact analysis and support grid reliability.

Cut Grid Upgrade Costs

Current data indicated that ~$3B in unnecessary infrastructure cost savings by managing capacity with software, not steel..

Accelerate Interconnections

Reduce approval timelines from 18–24 months to weeks with automated load studies and real-time simulations.

Protect Grid Reliability

Enforce flexible load limits instantly using UL-1741 and UL 3141 compliant hardware and APIs—no more guesswork or manual monitoring.