Policy Economics of Carbon Trading in the Renewable Energy Sector: <scp>AI</scp> ‐ <scp>MCDA</scp> Analysis Applied to the Beijing–Tianjin–Hebei Region

ABSTRACT This study examines how alternative designs of an emissions trading system (ETS) can better support renewable energy development in the Beijing–Tianjin–Hebei (BTH) region. A hierarchical analytic hierarchy process (AHP) is used to derive weights for six dimensions and 18 sub‐criteria covering economic, environmental, market, institutional, social, and technological aspects of ETS design. These global weights feed into a fuzzy VIKOR model that ranks six policy scenarios, while an AI module clusters experts and tests the robustness of the results. The findings show that environmental effectiveness and technological and innovation impact receive the highest weights ( w = 0.220 and w = 0.195, respectively), followed by economic performance. Within these, CO 2 reduction potential, renewable energy investment response, grid integration support, and carbon price stability emerge as key priorities. The integrated reform scenario is ranked first ( Q = 0.27; Rank = 1) and remains robust across extensive sensitivity tests. It combines a tighter cap, broader sector coverage, price‐stability tools, and earmarked revenues for renewable deployment and grid upgrades. The study concludes that, for BTH, an ETS design that links strong carbon constraints with predictable prices, credible institutions, and targeted renewable support is most preferred under a multi‐criteria assessment.