Enterprise AI in Utilities: A Vision for Next-Gen Distribution Engineering

Umair Zia – LIPA

The grid of the future will be a dynamic, highly orchestrated ecosystem of millions of data points. From bi-directional Distributed Energy Resources (DERs) and Vehicle-to-Grid (V2G) infrastructure, to intelligent heat pumps and smart home devices, the future utility must act as a singular system, harmonizing these assets in real-time. In this holistic scenario, distribution planning and engineering can no longer exist in reactive silos; they must be entirely integrated and predictive. One bottleneck to realizing this vision is the legacy engineering practices and workflows. For example, within Distribution Engineering, service applications still rely on manual, high-latency processes involving site visits, siloed GIS and CAD systems, manual entries to create work packages, resulting in significant delays.

In this presentation, we explore the paradigm shift from manual drafting to AI-powered, spatially-aware distribution engineering. We will demonstrate how artificial intelligence can eliminate data silos and automate the cognitive and procedural tasks of a distribution engineer. Through an interactive demonstration of a residential capacity upgrade project, attendees will see how an AI system can instantly ingest a customer application, analyze data from multitude of sources, and calculate dynamic load profiles, Bill of Materials, tariff based CIAC and construction ready CAD schematics.

Crucially, we will showcase how the architecture moves beyond reactive design by cross-referencing external, predictive datasets, such as recent neighborhood EV purchases, to preemptively optimize transformer and secondary circuit sizing for clustered load growth.

Briefly, we will also expand the aperture to highlight other transformative AI use cases across the utility enterprise.