Context

Pipeline operators manage thousands of kilometers of gas network assets where pressure, flow, and valve states change continuously throughout the day. Maintaining network stability requires real-time visibility into these dynamic conditions, along with the ability to simulate operational scenarios before issues escalate. A lightweight digital-twin layer helps operators understand how the network behaves, anticipate risks, and optimize performance without the complexity of full-scale simulation platforms.

Challenges

Conventional monitoring relies on SCADA views, manual checks, and operator judgement—making it difficult to detect subtle anomalies, assess interacting factors, or validate operational decisions. Supervisors lack a structured mechanism to review and approve recommendations, and insights often remain siloed across multiple reports. Without an integrated model of network segments, valves, and pressure readings, both operators and supervisors face delayed responses, inconsistent decisions, and limited ability to plan proactively.

Solution

Digital-Twin Lite for Pipeline Optimization uses Copilot-powered intelligence, Dataverse network models, and real-time dashboards to create a simplified but highly actionable digital representation of the gas network. Operators access AI-generated insights, scenario analysis, risk detection, and explainable recommendations through the Gas Network Copilot Advisor, while supervisors validate actions using a dedicated Copilot agent. Power BI reports visualize operations, and automated flows ensure approved recommendations are tracked end-to-end,enabling faster decisions, improved network stability, and more reliable pipeline performance.