Hydrogen Network Optimization in Refineries using AI PlantOps Framework

The Challenge: Hydrogen is one of the most valuable and constrained utilities in modern refineries. With deeper crude processing, stricter fuel norms, and rising hydroprocessing severity, managing hydrogen efficiently has become critical for profitability, energy efficiency, and sustainability.

Traditional manual hydrogen balancing cannot keep up with real-time fluctuations in hydrogen demand, purity shifts, PSA recovery variations, or feed changes. Such variations can lead to hydrogen losses and suboptimal unit performance.

This webinar introduces an AI PlantOps Driven - Hydrogen Network Optimization framework that predicts hydrogen demand, estimates supply from HGU/CCR/PSA systems, and recommends optimal allocation across refinery units, minimizing flaring, improving recovery, and reducing energy costs.

 Join us to learn how AI PlantOps, through its hydrogen optimization use case, can unlock 5–10% hydrogen savings while enhancing operational stability and lowering carbon footprint.

Key Takeaways

 What makes AI-based Hydrogen Optimization transformative?
✅ End-to-End Hydrogen Balance Intelligence – Real-time visibility across HGU, CCR, PSA, and hydroprocessing units.
✅ AI/ML Forecasting for Demand and – Predict hydrogen demand under varying feed, severity, and catalyst activity.
✅ Optimization Engine – Recommend optimal hydrogen allocation to minimize losses and improve margins.
✅ Physics-Aligned & Explainable – Insights validated by hydrogen fundamentals, mass balance, and process constraints.
✅ Lower Energy Cost & Carbon Reduction – Reduce excess firing, and unnecessary HGU load.

What Will Be Covered?

• Why Hydrogen Management Is Critical in Modern Refineries – Rising processing severity, variable feeds, and hydrogen scarcity, and the economic impact of hydrogen losses across units
• Deep Dive into the Hydrogen Optimization Framework – Demand forecasting, Supply and recovery modeling, optimization and advisory engine.

• Real-World Use Cases & Demonstrations – Predicting hydrotreating unit hydrogen demand, identifying hydrogen losses and purity deterioration, Advisories for optimal network balancing.
• AI + First-Principles Hybrid Approach – Ensuring predictions comply with refinery physics, explainability for operator trust and adoption
• Live Q&A & Next Steps – How refiners can adopt hydrogen optimization solutions, expected benefits and roadmap for deployment

Why Attend?

✅ Understand how AI transforms hydrogen management
✅ Learn how to reduce refinery hydrogen losses by 5–10%
✅ See real case studies on network optimization
✅ Gain practical insights into implementation and scaling
✅ Explore how hydrogen optimization supports decarbonization and energy efficiency initiatives

📍 Secure Your Spot Now!

Be part of this focused technical session and learn how AI-enabled hydrogen optimization can significantly enhance your refinery operations.