Autonomous Workflow for Microgrid Isolation and Customer Cluster Communication

This workflow automates the critical operational bottleneck of manually identifying and communicating with customers during a microgrid isolation event. When a main grid fault triggers islanding, the system must instantly determine which customers are powered by the microgrid, estimate the duration of isolation, and initiate multi-channel notifications. The operational upside comes from eliminating manual call-center surge, preventing confusion, and providing accurate, timely information that improves customer satisfaction and reduces inbound inquiry volume by over 50% during such events.

Implementation requires tight integration with the Distribution Management System (DMS), Geographic Information System (GIS), and Customer Information System (CIS) via a central orchestrator, typically built with LangGraph or a similar framework. The architecture must include approval gates for message templates, real-time observability into notification status, and exception routing for customers who cannot be matched or who require critical care status overrides. Data quality from the microgrid controller and GIS feeder models is the primary constraint, necessitating validation logic before communication triggers.

When a main grid fault triggers a microgrid to island, a custom multi-agent workflow automatically identifies affected customers, determines their islanded status, and initiates personalized communication. This eliminates the manual, error-prone process of cross-referencing GIS feeder models with customer information systems (CIS) during a crisis. The operational upside comes from immediate, accurate customer assurance, which reduces inbound call volume by over 40% and prevents misinformation, while field crews focus on restoration without distraction.

Implementation requires tight integration with the Distribution Management System (DMS), microgrid controller APIs, and the CIS via a unified data layer. The orchestration agent, built on frameworks like LangGraph, manages the sequence: fault validation, customer cluster identification, message templating with live duration estimates, and multi-channel dispatch. Critical controls include approval gates for message templates, real-time observability into delivery status, and exception routing for customers with life-support equipment flags to ensure regulatory compliance.

Phase one establishes the core orchestration logic, integrating with the Distribution Management System (DMS) and Microgrid Controller for real-time isolation alerts. An AI orchestrator ingests the fault signal and geofence data, then queries the Customer Information System (CIS) to build the affected customer cluster. This initial integration, built on a framework like LangGraph for state management, creates the single source of truth for the outage event, enabling all downstream communication and coordination actions without manual data assembly.

Phase two layers on the communication engine and exception handling. The orchestrator retrieves pre-approved, jurisdiction-specific message templates, personalizes them, and dispatches notifications via SMS, IVR, and email through integrated telecom APIs. A dedicated exception queue, monitored by utility staff, captures failed deliveries or complex customer inquiries for manual review. The final phase adds closed-loop monitoring, where the orchestrator tracks the microgrid's reconnection signal from the DMS to automatically send restoration confirmations and post-event surveys, creating a fully autonomous communication lifecycle from fault to resolution.

This workflow's primary control is a human-in-the-loop approval gate before any mass notification is sent. Upon a main grid fault signal from the Distribution Management System (DMS), the orchestrator must first validate the isolation with the microgrid controller and confirm the customer cluster via GIS. A designated grid operator reviews the proposed message and affected list in a dedicated dashboard, ensuring accuracy before the system triggers communications via SMS, IVR, and email APIs. This gate prevents misinformation during critical infrastructure events.

Phased rollout begins with a shadow mode, where the system generates alerts and proposed actions without sending live communications, allowing operators to verify logic against historical events. Phase 1 targets a single, stable microgrid for live, operator-approved notifications. Phase 2 expands to multiple microgrids and introduces automated updates for extended islanding events. Each phase includes defined KPIs for notification accuracy, reduction in inbound customer calls, and operator burden, ensuring the system demonstrably improves operational response before full-scale deployment.