Powering the Future of Energy with Edge Intelligence
AI‑ready, standards‑based data infrastructure powering resilient, decentralized energy systems
Edge-Native Operational Intelligence for Distributed Energy
IOTech’s AI‑ready edge data platforms enable providers of Battery Energy Storage Systems, solar, wind, EV charging, and other DER assets to transform high‑volume data into real‑time operational intelligence.
By normalizing equipment data from diverse protocols and executing analytics directly at the point of control, IOTech delivers the scalable, secure infrastructure needed to operate DER fleets at commercial scale. This edge‑native approach unlocks safer, more efficient, and more cost‑effective energy solutions, driving innovation, accelerating product differentiation, and helping vendors compete in an increasingly decentralized, software‑defined energy market.
The Operational Challenges Facing DER Vendors and Operators
As DER deployments scale, vendors and operators face growing challenges in integration, data management, real-time control, and security. These complexities make it harder to operate efficiently and scale to fleet-level operations.
Heterogeneous Devices and Protocols
DER fleets span BESS, solar, wind, EV charging, meters, and site controllers—all using different protocols and data models. This fragmentation slows integration, raises cost, and hinders creating consistent, analytics‑ready data.
High‑Volume, High‑Frequency Data
DERs generate continuous telemetry and events that are too costly and slow to centralize in the cloud. Operators need insight and action at the edge, not delays from the cloud.
Real‑Time Response Requirements
Grid‑connected assets must react to frequency, voltage, and dispatch signals in milliseconds. Cloud‑only architectures can’t meet these latency or reliability demands, making local, deterministic control essential.
Expanding Security Risks
Distributed assets increase the attack surface. Operators must secure thousands of remote endpoints and protect data from device to edge to cloud under zero‑trust principles.
Scaling to Fleet‑Level Operations
Growing deployments require consistent onboarding, configuration, monitoring, and lifecycle management. Manual, site‑by‑site engineering doesn’t scale and slows commercial growth.
Readiness for AI and Autonomy
AI‑driven forecasting, optimization, and predictive maintenance depend on high‑quality, standardized data, real‑time feature extraction, and local execution environments—capabilities many DER operators lack today.
Enabling the AI‑Ready Edge for a Decentralized, Software‑Defined Grid
IOTech’s AI‑ready edge data platforms provide DER Vendors and Operators with ability to create a massively scalable, federated architecture capable of normalizing and aggregating huge data volumes while still delivering real‑time performance for control and AI.
How IOTech addresses the data, scale, and interoperability challenges of modern energy systems:
Unified data integration across all DER assets
Standardizes data from any device or protocol into a consistent data layer without custom engineering. Deploys on low-cost edge hardware while maintaining high-performance acquisition for cost-effective scaling.
Real‑time intelligence at the edge
Executes analytics and control locally for millisecond-level responses, ensuring safe and stable operation under grid events and high-frequency telemetry conditions.
Massively scalable, federated architecture
Aggregates millions of data points from thousands of assets with deterministic performance for control and AI. Employs MQTT / Sparkplug for efficient, interoperable data sharing.
AI‑ready infrastructure for fleet‑scale operations
Delivers high-quality, time-aligned data and local compute for forecasting, optimization, anomaly detection, and autonomous control across distributed fleets.
Simplified integration and interoperability
Enables real-time data access for applications and third-party systems via secure, standards-based APIs (OPC UA, MQTT), with seamless access to historical data.
Secure, software‑defined deployment at scale
Delivers zero‑trust security, containerized deployment, and centralized fleet management to scale from pilot to thousands of sites with minimal OPEX.
Customer Use Case: Powering a 500 MW Grid‑Scale Battery with Real‑Time Edge Intelligence
A major 500 MW / 1,000 MWh grid-forming Battery Energy Storage System (BESS) is transforming a former fossil-fuel site into a renewable energy hub. This requires real-time control, high data throughput, and integration across thousands of devices.
IOTech’s AI-ready edge data platform provides a unified, real-time data layer that enables grid-forming control, predictive maintenance, and automated market optimization at scale.
The result: Improved grid stability, reduced integration complexity, and optimized asset performance.
