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Driving Mechanisms and Scenario-Based Simulation of Renewable Energy Penetration Evolution in China

中国における再生可能エネルギー普及進化の推進メカニズムとシナリオベースのシミュレーション (AI 翻訳)

Yasi Yang, Wensheng Wang, Xia Liu

Sustainability📚 査読済 / ジャーナル2026-07-20#再生可能エネルギーOrigin: CN対象セクター: power
DOI: 10.3390/su18147395
原典: https://doi.org/10.3390/su18147395

🤖 gxceed AI 要約

日本語

本研究はシステムダイナミクスを用いて中国の再生可能エネルギー普及率(REP)の進化を2012～2060年までシミュレーション。BAUシナリオでは2060年に77.17%に達し、政策支援シナリオで最も高い80.71%を示す。市場拡大の効果は2030年以降に増大し、政策と市場の相乗効果が最も効果的な経路であることが明らかになった。

English

This study uses system dynamics to simulate the evolution of renewable energy penetration (REP) in China from 2012 to 2060. Under business-as-usual, REP reaches 77.17% by 2060, with the highest at 80.71% under policy support. Market expansion effects intensify after 2030, and policy-market synergy proves the most effective pathway.

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

📝 gxceed 編集解説 — Why this matters

日本のGX文脈において

中国の政策主導型再生可能エネルギー普及の研究は、日本のFITや市場メカニズムとの比較に示唆を与える。特に2030年以降の市場需要拡大の効果や政策・市場の相乗効果は、日本の長期エネルギー計画（例：第6次エネルギー基本計画）の策定に参考となる。

In the global GX context

This paper models China's renewable energy penetration under various policy-technology-market scenarios, offering insights for global energy transition strategies. The finding that policy-market synergy outperforms policy alone is relevant for ISSB-aligned transition planning and national decarbonization pathways.

👥 読者別の含意

🔬研究者:System dynamics model for renewable penetration simulation; useful for energy policy modeling and scenario analysis.

🏢実務担当者:Understanding policy-market synergy effects can inform corporate renewable procurement and lobbying strategies in China.

🏛政策担当者:Highlights the importance of coordinating market mechanisms with policy support; underscores post-2030 market demand as a key driver.

📄 Abstract（原文）

Enhancing renewable energy penetration (REP) is essential for accelerating the low-carbon transition of the power system. The evolution of REP is driven by the interaction of multiple factors, including policy, technology, market demand, and environmental constraints. Based on the system dynamics (SD) method, this study constructs a model to simulate the evolution of REP in China during 2012–2060 under business-as-usual (BAU), single-factor, and synergistic scenarios. The results show that, by 2060, REP reaches 77.17% under the BAU scenario. REP improvement is most pronounced under the policy support scenario, reaching 80.71%, while REP increases by 4.58%, 1.94%, 2.36%, and 1.30% relative to BAU under the policy support, technological innovation, market demand expansion, and environmental constraint scenarios, respectively. After 2030, the effect of market demand expansion gradually strengthens and surpasses environmental constraints and technological innovation, with the crossover points corresponding to REP levels of 41.69% and 57.19%, respectively. The synergistic scenario analysis further shows that policy–market synergy is the most effective pathway, with REP reaching 81.21% by 2060, followed by policy–technology synergy at 80.89%. In contrast, policy–environment synergy (80.48%) does not outperform the single policy support scenario. This suggests that environmental constraints need to be coordinated with market-based consumption and technological support to effectively promote REP.

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