From Reactive to Predictive: Turning Energy into Profit with Digital Twins

As U.S. energy markets become more volatile and complex, industrial and commercial operators are under increasing pressure to control costs and manage risk. Traditional Demand Response has delivered value, but it often remains reactive, event-driven, and disconnected from core operations. This webinar explores how leading organizations are moving from reactive energy strategies to predictive, continuous optimization using digital twin technology.

We will show how digital twins of on-site processes create a real-time operational layer where energy decisions are automated, context-aware, and continuously optimized against the constraints of each asset and industrial process. By combining operational data, market signals, and AI-driven forecasting, sites can anticipate price movements, demand shifts, and system conditions, and respond in a way that aligns with production priorities and commercial outcomes.

Rather than focusing on a single program, this session provides a practical framework for embedding energy strategy into day-to-day operations. Attendees will gain a clear understanding of how digital twins act as an operational co-pilot, enabling smarter participation in energy markets while maintaining performance, quality, and reliability.

Key Takeaways:

• What “reactive vs predictive” energy management means in practice.
• How digital twins model industrial processes to access flexibility safely.
• The role of AI and forecasting in improving energy decision-making.
• How to move beyond event-based Demand Response to continuous optimization.
• Ways to access new value streams from U.S. energy markets.
• Best practices for integrating energy strategy into core operations without disruption