Modelling and Simulation

The energy transition introduces complex technical, economic and policy interactions that cannot be understood in isolation. Decisions depend on how technologies perform within wider systems, how markets evolve and how uncertainties shift as systems develop. But decisions often need to be made faster than full-scale modelling allows. Effective analysis, therefore, requires a balance between responsiveness and rigour – delivering timely insights without compromising analytical depth.

For this reason, integrated modelling environments are critical: they combine engineering detail, financial tools and economic frameworks to create a coherent, decision-ready understanding of the transition.

Gréoux Research‘s integrated modelling approach combines thermodynamic performance analysis, cost projections, financial evaluation, social cost–benefit assessment and broader economic impact modelling. It also incorporates system dynamics modelling, enabling us to represent feedback loops, time-dependent behaviours and long-term structural effects that shape energy systems. A further component of the framework is dedicated to uncertainty and risk: we conduct systematic sensitivity analyses to identify key performance drivers and use probabilistic assessment techniques – including Monte Carlo simulation – to establish confidence intervals around projected metrics and expected outcomes.

These capabilities are often applied at the early stages of an investigation, supporting option screening, pathway exploration and trend analysis. This helps organisations understand the implications of different choices before committing significant time or resources, and ensures that market and policy realities are embedded in technical assessments. Bridging component-level models with system-wide considerations reveals interactions and constraints that would otherwise remain hidden.