The power of precision: GenAI is revolutionizing transmission network and asset models

Over the last two decades, electric utilities have reactively transformed their Transmission business processes and ecosystems—using digitization and simple analytics. Today, with increasing load growth, regulatory orders, aging infrastructure and the ever present need to operate the grid more efficiently, Transmission operators and developers are leveraging new technologies, including Generative AI. While other industries were early adopters, embracing AI for competitive edge, the traditionally cautious power and utility sector needed clear line-of-sight to the value proposition for GenAI—particularly in their transmission functions.

Network models are the digital DNA of transmission functions, powering planning simulations, real-time operations and supporting asset management decision making. Yet many utilities still struggle to maintain accurate, up to date and relevant models, due in part to the sheer scale and complexity of modern utility infrastructure. GenAI changes the game—automating model upkeep, enriching simulation fidelity and enabling decision making with greater precision and speed.

Challenges Facing Transmission Models Transmission Planning

Transmission planning hinges on accurate and timely data and asset models to simulate power flows, project load growth, identify optimal points of interconnection and grid operations under contingency scenarios. However, current modeling applications and platforms are often outdated or incomplete, plagued by fragmented data from engineering teams, third-party consultants and GIS systems.

Challenge: Long planning cycles with incomplete data inputs and manual model updates increase the risk of missed opportunities and compromised long-range plans.

Transmission Network Operations

Transmission System operators require real-time network visibility for grid stability, congestion management and response to disturbances. Additionally, proper Transmission switching can alleviate transmission violations and reduce operating costs. SCADA, EMS and outage management systems depend on models that reflect current network topology, operational states and equipment status to support operators’ decisions.

Challenge: Manual updates to operations models cannot keep pace with daily and compromised network changes, especially as renewable penetration increases power generation and volatility.

Transmission Asset Management

Transmission assets such as lines, breakers and transformers demand high-fidelity models for lifecycle condition assessments, risk-based maintenance and investment planning. Yet Transmission owners and operators often operate with siloed asset registries and static conditions data.

Challenge: Inability to dynamically update asset health conditions and operating limits and risk profiles results in unexpected failures, inflated O&M budgets and more regulatory scrutiny.

Enter GenAI: A New Paradigm for Transmission Models

Generative AI combines the intelligence of machine learning with the creative flexibility of natural language processing. For transmission utilities, GenAI can act as a dynamic "model steward," continuously synthesizing data, interpreting patterns and autonomously enhancing network models reducing the need for manual work and improving model accuracy.

1. Automated Model Completion and Synchronization

GenAI can ingest vast datasets—from “as-built” drawings to SCADA inputs, GIS databases, sensor streams and even operator notes—and reconcile them to maintain a single, accurate source of truth. No more inconsistencies between planning and operations models.

A real-world example is a transmission utility using GenAI to harmonize data across its EMS and planning models. Within weeks, GenAI flagged 400+ discrepancies in breaker statuses and line impedance values, enabling corrective actions that avoided potential contingency violations during a heatwave.

2. Predictive Asset Modeling

By layering AI-generated insights atop real-time sensor data, utilities can better simulate potentially many forecasted events on the operations, maintenance and investment opportunities of critical assets. These models not only reflect current conditions but also project future states—enabling risk-based maintenance and CAPEX deferral.

Example: One utility reduced unplanned transformer outages by 23% in 12 months using a GenAI-enhanced digital twin to identify substation-level thermal anomalies ahead of time.

3. Interconnection simulations

With GenAI, transmission planners can run simulations and automate due diligence on interconnection requests for more accurate accounting for load growth, stability, or system impacts without waiting for manual study setups and of course, volume constraints. By leveraging AI more broadly, planners can auto-generate plausible scenarios, validate constraints and visualize contingencies in minutes.

Example: A regional transmission utility used GenAI to model the impact of a 2 GW offshore wind project under various grid conditions, cutting study time from several months to six weeks and supporting a successful interconnection request.

How Transmission Utilities Can Get Started 1. Start With the Business Problem

Like “analytics” were first used by utilities, having a defined use case or a set of use cases can prioritize a focused approach with a particular Transmission function, (Operations, Planning, Field/Asset Management), where model fidelity directly affects cost, reliability, or regulatory compliance. Asset management and operations are great entry points.

2. Launch a Pilot Around the Targeted Use Case

Choose a contained problem—like dynamic line rating updates, interregional planning considerations or transformer condition modeling. Use GenAI to synthesize missing network or asset data models before running any tasks.

3. Measure the Difference in Results

Efforts are based on using GenAI to address model deficiencies so the delta will be clear, with and without using GenAI. Quantifying the difference between the scenarios and tasks will help to justify the ROI to others. Repurposing benefits sure as dollars saved will allow the benefit to be repurposed for our use cases.

Conclusion: Why Transmission Can’t Wait on GenAI

Transmission developers and operators are at a critical juncture. The need to leverage modern technology and GenAI, for an aging electric grid makes sense. Network models which reflect the physical world must evolve just as fast as load growth continues to increase.

GenAI offers a transformative path forward. By closing the model accuracy gap, transmission owners and operators gain sharper foresight, better operational agility and stronger infrastructure resilience. It’s not just about adopting AI, it’s about enabling a more efficient way to plan, operate and maintain the Transmission grid.

Start with the models. That’s where GenAI can deliver exponential value—and you don’t need to wait for a regulator to act upon it either.