Combined simulation and optimization framework to quantify the impact of policy tools in agents’ decision making in the transition towards a low carbon energy system

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Provides a novel integrated methodology for comparing behavior-driven and cost-optimal pathways, with clear quantification of policy-induced inefficiencies.

🏢実務担当者:The IESA framework can be used to design and stress-test policy portfolios, assessing which interventions are most cost-effective under different agent behaviors.

🏛政策担当者:Highlights that full decarbonization requires targeted sectoral policies beyond carbon pricing, and that upfront costs peak between 2035-2045, informing fiscal planning.

This study presents a novel integrated methodology that combines harmonized simulation and optimization models to evaluate the effectiveness and efficiency of low-carbon policy instruments. We introduce IESA-Sim, a simulation model that uses agent-based modeling to represent heterogeneous investment behavior and a broad range of policy tools, including CO 2 taxes, subsidies, and technology portfolio standards. IESA-Sim is harmonized with IESA-Opt, a cost-optimization model that shares the same energy system architecture, database, and temporal resolution. This alignment enables direct comparison between behavior-driven and cost-optimal decarbonization pathways, which is a novelty in the field; the IESA framework enables a structured evaluation of how policy instruments interact with behavioral diversity, system architecture, and economic constraints. It provides a transparent and modular tool to explore the implications of different policy mixes, agent behaviors, and technology assumptions. The framework is applied to the Netherlands, assessing four scenarios that combine different policy portfolios and agent preference structures. Results show that renewable technologies are adopted even under weak policies, but full decarbonization requires targeted interventions, especially in harder-to-abate sectors. Heterogeneous agents accelerate adoption under weak policies but increase inefficiency under strong ones. Comparing scenarios against a Pareto front from IESA-Opt reveals transition inefficiencies of 2.6–5.7 billion euros per year, or 28 to 48 euros per mitigated ton of CO 2 . Our analysis concludes that a fully decarbonized system is more affordable by 2050 than a fossil-based alternative (considering a very conservative development of EUA prices), but reaching that point requires high upfront investments and an accelerated turnover of technologies. These costs are concentrated between 2035 and 2045, driven by early adoption, immature supply chains, and the premature replacement of fossil-based assets. Nonetheless, once installed, the clean energy system benefits from low operating costs and a reduced fuel dependence. • We present IESA, a hybrid simulation-optimization framework for policy analysis. • IESA-Sim captures agent heterogeneity and diverse low-carbon policy tools. • Full decarbonization requires targeted policies beyond market incentives. • Agent diversity speeds adoption under weak policy but increases inefficiency under strong. • IESA quantifies cost-efficiency gaps and supports scenario-based policy design.

• openalex https://doi.org/10.1016/j.enpol.2026.115342first seen 2026-05-17 05:41:51