The logic of policies for energy price regulation in the future: A synergistic developmental perspective based on energy and carbon markets

Xing Zhou, Jianze Xu, Fenglan Zhang, Pingping Ma and Yi Jin

Renewable and Sustainable Energy Reviews, 2025, vol. 222, issue C

Abstract: Establishing a mechanism to regulate energy prices in the future requires the synergistic development of carbon markets, with a clear understanding of how energy prices influence the price of carbon as a prerequisite. In this study, we use an explainable machine learning framework to analyze the main, interactive, combined, and pile-up effects of energy prices, and simulate the impacts of 11 policies for energy price regulation. The results revealed significant spatial and temporal heterogeneities in the impact of energy prices on carbon prices. The importance of coal for Hubei's carbon price was 5.97 % higher in the summer and autumn than in the winter and spring. Achieving a balance between low energy prices and high carbon prices requires setting policy thresholds beyond the range of the main effect, while the simultaneous regulation of different energy price policies dilutes the impact of each policy on carbon prices. Even at a relatively low level, the substitution effect of new energy can reduce the deviation between the curves of carbon prices of Hubei and Guangdong, and the government's expected curve by 1 % and 0.41 %, respectively. Our findings provide theoretical and practical insights for government policy-making and carbon market stability, highlighting that dynamic threshold settings and seasonal adjustments can enhance market stability while minimizing the transition costs of energy restructuring.

Keywords: Machine learning; Mechanism of action; Analog simulation; Energy price policies (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.rser.2025.115940

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