Overview

The power grid is evolving to accommodate electric vehicles (EVs), distributed energy resources (DERs), renewable energy, and increasing demand for sustainability and resilience. Traditional grids, with centralized control and one-way energy flow, are insufficient for modern needs. This briefing outlines a next-generation grid edge solution powered by edge AI and IoT, designed to optimize operations for power utilities.

Key Challenges and Solutions

Challenges

Centralized control and minimal automation can't quickly address local demand fluctuations, causing energy imbalances and inefficient grid use. These issues lead to wasted energy, higher operational costs, and grid instability. As energy demands evolve, relying on outdated systems becomes impractical, highlighting the need for more dynamic, intelligent solutions.

Solutions

Edge AI positions computational power and real-time monitoring closer to areas with significant demand fluctuations. This enables decentralized decision-making and efficient automated load balance through local DER orchestration, enhancing system reliability. It also supports resilient microgrids, ensuring they operate independently and maintain stability during disruptions. Implementing edge AI results in a more adaptable, responsive, and reliable energy infrastructure.

Solution Architecture

EdgeIQ Low-Voltage Platform

Deployed under service transformers to provide localized grid management. Includes:

• EdgeIQ AI Director: Central intelligence for real-time decision-making and resource orchestration, optimizing grid operations and DERs.

• EdgeIQ IoT Terminal: Collects and processes data from sensors, smart meters, and DERs, providing localized insights and seamless device integration.

• Rogowski Coils and Current Transformers (CTs): Measure alternating currents accurately for real-time monitoring and analysis, integrating seamlessly with the IoT ecosystem.

• Other Open Standard IoT Devices: Leverage open IoT protocols for seamless communication, such as temperature sensors for predictive maintenance.

FeederIQ Mid-Voltage Platform

A distributed AI solution along primary feeders, with components such as:

• FeederIQ AI Director: Centralized intelligence for resource orchestration and real-time decision-making at substations.

• FeederIQ AI Nodes: Distributed processing nodes connecting EdgeIQ IoT Terminals with the FeederIQ AI Director.

CableIQ Underground Monitoring Platform

A real-time monitoring platform for underground assets, featuring:

• CableIQ Cloud Service: Provides cloud-based analytics that enable proactive maintenance.

• CableIQ Sensors: Installed along underground cables to measure and transmit data to the Communicator.

• CableIQ Communicator: Placed at manholes to gather data from the Sensors and wirelessly upload it to the Cloud Service.

Benefits for Power Utilities

• Enhanced Grid Resilience and Efficiency: Improved fault recovery, reduced energy waste, and optimized resource utilization lead to lower operational costs.

• Risk Mitigation: Predictive maintenance and automated fault detection help prevent outages and reduce downtime.

• Sustainability Leadership: Aligning with sustainable practices and reducing carbon footprints boosts the utility's reputation and attracts eco-conscious consumers and investors.

Use Cases

• Critical Infrastructure: Microgrids ensure power during outages for hospitals.

• Municipal Utilities: DERMS improves grid balance and renewables integration.

• Residential Microgrids: Optimizes local solar energy use.

• Commercial Demand-Response: AI automates load adjustments to reduce costs.

• Industrial Microgrids: Optimized storage and renewable use lower operational costs.

• Predictive Maintenance: Real-time analytics reduce downtime for grid operators.