An Endogenous Behaviour-Driven Approach for Sectorized Energy Demand in an Integrated Assessment Model

Integrated Assessment Models (IAMs) are critical for mapping mitigation strategies. However, their energy demand projections are often constrained by reliance on deterministic, exogenous methods that often overlook the complexity of demand-side responses to fluctuations in the economy, climate, or the energy system itself.  While some process-based IAMs have replaced GDP-linked projections with endogenous cost-optimization or discrete-choice frameworks, they fail to fully couple these demand-side variables with wider system feedbacks, such as human behaviour related dynamics.

This study uses the FRIDA model, an IAM that introduces a comprehensive internal framework for behavioural change, replacing exogenous parameters or assumptions with a structure that simulates decision-making dynamics in the demand for resources and/or end services, leveraging the existing structure for livestock products demand in FRIDA.

The primary contribution of this work is the shift to a fully closed integration of behaviour-driven sectoral energy demand, specifically for transportation demand, reducing reliance on locked-in demand projections, and significantly improving the interconnectedness between economic, climate and energy sections of the model itself.

This implementation expands the existing behavioural change modelling framework in FRIDA, and internalizes energy demand by linking behavioural responses to sector-specific dynamics and systemic feedbacks. The model internalises climate-driven factors, such as the health risks posed by particulate emissions, the composition of the energy mix in production, and the energy carriers in demand, which dynamically drive or constrain energy demand. This structure, demonstrated with the transport sector, can then be replicated across other energy sectors in FRIDA to capture the fundamental dynamics that drive the behaviour determinants of demand.

This work is supported by FCT, I.P./MCTES through national funds (PIDDAC): LA/P/0068/2020 - https://doi.org/10.54499/LA/P/0068/2020 , UID/50019/2025, https://doi.org/10.54499/UID/PRR/50019/2025, UID/PRR2/50019/2025. This work has also received funding from the European Union’s Horizon 2.5 – Climate Energy and Mobility programme under grant agreement No. 101081661 through the 'WorldTrans – TRANSPARENT ASSESSMENTS FOR REAL PEOPLE' project.