Abstract
Accurately quantifying stranded assets from early coal plant retirements is essential for shaping China's coal phase-out strategy under global carbon targets. This study compiles an updated database of 3652 coal-fired units in 30 provinces. It introduces a Monte Carlo simulation multi-criteria framework to evaluate retirement priorities, incorporating technical, economic, and environmental indicators. The intensity of research and development (R&D) investment can reflect the region's innovative capacity at the technological level. Unlike previous studies that relied on subjective weights, this study uses Monte Carlo simulation to construct a statistically robust multicriteria framework that eliminates expert bias. Using the overnight capital cost method, we assess stranded assets under four mitigation scenarios (S1074-S1374) from 2022 to 2060. Results show that: (1) Liaoning, Sichuan, and Jiangxi could be prioritized for early retirement; (2) Xinjiang and North China face the highest stranded asset risks; and (3) Northeast China may face more significant transition barriers. (4) The findings support targeted R&D investments and differentiated regional policies for prudent planning of additional coal-fired units to facilitate an equitable and efficient energy transition. This study enhances understanding of stranded asset risks from coal plant closures and additions, supporting China's energy transition and carbon neutrality policymaking.
| Original language | English |
|---|---|
| Article number | 127940 |
| Journal | Applied Energy |
| Volume | 416 |
| DOIs | |
| Publication status | Published - 1 Aug 2026 |
| Externally published | Yes |
Keywords
- China
- Coal-fired power generation
- Monte Carlo simulation
- Overnight capital cost
- Stranded assets
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