Atlas Edge

A Physics-First Distributed EMS for Modern Grids

Modern energy systems are becoming more complex than traditional control architectures can handle. Atlas Edge brings a new idea to the grid: spectral geometry as a control system.

One platform that replaces fragmented SCADA + EMS + DERMS stacks with a single physics-first control layer.

One Platform. Complete Grid Intelligence.

We combine capabilities that traditionally require multiple vendors:

⚡
EMS-Level Control
📊
SCADA Telemetry
🔄
DERMS Coordination
🛠ïļ
Predictive Maintenance
🌐
Edge Autonomy
ðŸŽŊ
Spectral Physics
7
Asset Types
20+
HMI Views
50+
Features
5–10 ξs
Spectral Compute

The Challenge

⚡

Renewable Variability

Wind and solar oscillate unpredictably, stressing grid stability

🔋

Massive Battery Fleets

Each with different dynamics, constraints, and degradation curves

🌀

Interacting Control Loops

Thermal, storage, and renewables chase each other in unstable feedback

📉

Aging Equipment

Failures are nonlinear and hard to forecast with traditional methods

📋

Compliance Load

NERC CIP, FERC, and regulatory requirements grow each year

📈

Exploding Data Volume

More SCADA points per asset than control rooms can process

Traditional EMS and SCADA systems respond with more software on top of more software.

More layers, more tuning, more brittleness.

Atlas Edge takes a physics-first route.

How Atlas Edge Works

Atlas Edge treats the entire grid as a coupled spectral field.

1

Universal Spectral Embedding

All telemetry and control signals are mapped into a shared phase-space using a universal spectral operator. Only minimal semantic mapping per asset type (no custom models per site).

2

Geometric Coherence Measurement

Instantly measure how in-sync or out-of-sync each asset is with the fleet. Kuramoto-based fleet coherence scoring across the entire system.

3

Distributed Stabilization

Grow the modes that add stability. Dampen the modes that add oscillation. Hold the modes that are neutral. Works across assets, technologies, and time scales.

What's Inside Atlas Edge

Not just analytics — a full SCADA + EMS + DERMS stack with a spectral control core.

ðŸ”đ

Complete SCADA Layer

  • ✓Modbus TCP, DNP3, IEC-104, OPC-UA protocols
  • ✓Historian (TimescaleDB) with A/B redundancy
  • ✓20+ HMI pages for complete operations
  • ✓Alarms, SOE, logbook, work orders
  • ✓Historical replay, trends, compliance reporting
ðŸ”đ

Full EMS / DERMS Architecture

  • ✓AGC (Automatic Generation Control)
  • ✓Economic dispatch with Îŧ-iteration
  • ✓State estimation (WLS-based)
  • ✓Fleet-level coherence (Kuramoto order parameter)
  • ✓Mixed fleet control: thermal + renewable + storage
ðŸ”đ

Predictive Maintenance, Built In

  • ✓J-lag wear accumulator for fatigue tracking
  • ✓Battery monotonic stability (45° attractor)
  • ✓Turbine and generator health scoring
  • ✓Spectral drift forecasting
ðŸ”đ

Distributed Edge Compute

  • ✓91/9 autonomy architecture
  • ✓Local fallback during network loss
  • ✓Only escalates unusual patterns
  • ✓Reduces cloud cost and latency
ðŸ”đ

Universal Asset Layer

Supported assets with semantic mappings + spectral control models:

🌎ïļ
Wind
☀ïļ
Solar
🔋
Battery
💧
Hydro
ðŸ”Ĩ
Gas
⮛
Coal
⚛ïļ
Nuclear

Use Cases

🌎ïļ

Renewable Stabilization

Dampen oscillations, reduce chasing behavior, improve ramp smoothness across wind and solar fleets.

🔋

Battery EMS

Coordinated fleet charging/discharging without central optimizer brittleness.

🌀

Oscillation Dampening

Instant detection and suppression of hidden cross-asset feedback loops.

⚙ïļ

Mixed-Fleet Coordination

Thermal + renewable + storage working together instead of against each other.

🛠ïļ

Predictive Maintenance

Early detection of mechanical or electrical degradation through spectral drift.

📋

NERC CIP Compliance

Built-in audit logging, CIP-007 exports, and security controls.

Why Spectral Geometry?

Traditional control systems fight complexity with more tuning, more nested PI loops, more ML models, more heuristics.

Atlas Edge fights complexity with geometry.

ðŸŽŊ

Zero Manual Tuning

The system continuously adapts using universal physics. No parameter adjustment per site or asset.

🔍

Transparent

Based on mathematical invariants, not opaque ML. Every decision is traceable.

🔄

Cross-Asset

Works on every class of device, because physics does. Wind, solar, batteries, thermal — one framework.

⚡

Microsecond Fast

~5-10 Ξs spectral computation. 926× faster than equivalent Python. Real-time stability decisions.

Stability emerges from the structure of the spectral field itself —
not from thousands of hand-tuned parameters.

Current Status

✓

Physics kernel implemented — Spectral engine integrated into the platform

✓

50+ production features implemented across control, visualization, compliance

✓

Full SCADA + EMS + DERMS integration in single platform

✓

7 asset controllers with semantic mappings operational

✓

Pilot plans defined for wind, solar, and battery sites

◐

Looking for pilot partners for controlled field deployments

○

Preparing for field deployment validation

For utilities, operators, and OEMs:

Atlas Automations LLC â€Ē Physics-first algorithms for complex systems

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