Work

Mapping the methodological landscape of coupling carbon and electricity markets: A critical review of models, applications, and future pathways

Year: 2026

Type: article

Abstract: Coupled carbon-electricity markets are increasingly important for power-sector decarbonization, but existing studies remain fragmented in their modeling objectives, assumptions, and methodological choices. To address this gap, this study develops a bibliometric-informed methodological review to clarify how different modeling paradigms can be matched with specific research questions in coupled carbon-electricity market studies. Through bibliometric analysis, we identify four analytical domains and nine research problems, covering price interaction, market mechanism evolution, participant decision-making, and market-technology synergy. We then systematically compare six modeling paradigms, namely simulation, econometric, optimization, assessment, machine learning, and power system models, in terms of their research purposes, data requirements, uncertainty treatment, computational burden, interpretability, and policy relevance. This analysis establishes a structured mapping between model categories and research domains, while critically evaluating applicability, limitations, and methodological evolution of different modeling approaches across research problems. Results indicate that model selection should be treated as a research design problem rather than a purely technical choice. Model applicability is strongly conditioned on market maturity, data availability, uncertainty structure, computational tractability, and policy purpose. Finally, we identify critical pathways for advancing integrated modeling approaches, including multi-model coupling techniques, strategies for adapting models to future research scenarios, and the potential of data-driven modeling paradigms.

Source: Sustainable Energy Technologies and Assessments

DOI: 10.1016/j.seta.2026.105401

Authors: Zhenwei Lu, Zhe Yu, Jingjing Jiang, Bin Su, Junhua Zhao, Bin Ye