Evidence map›Paper›PMID 40678512›Full record

ArticleiScience2025

Scenario-based projections of electricity prices in China's carbon-neutral transition.

Shurui Wang, Jianlei Mo, Jie Yang, Mingxi Liu, Jiaofeng Pan, Xunpeng Shi, Ye Huang

Abstract read
In one paragraph

Article in iScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Shurui WangInstitutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China.
Jianlei MoInstitutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China.
Jie YangInstitutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China.
Mingxi LiuInstitutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China.
Jiaofeng PanInstitutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China.
Xunpeng ShiUniversity of Technology Sydney, Sydney, NSW, Australia.
Ye HuangUlster University, Belfast, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

China's carbon neutrality goal by 2060 presents major challenges and opportunities for its electricity market. This study analyzes baseline, low-efficiency, and high-efficiency scenarios to represent potential decarbonization pathways in China up to 2060, aiming to estimate the range of electricity prices for each province. A comprehensive dataset covering 5680 coal power units, 342 hydroelectric plants, 172 gas power stations, 19 nuclear power stations, and various solar and wind farms, provides a solid foundation for a bottom-up calculation approach. The results show that most provinces will see a decline in electricity prices due to technological advancements and optimized power generation. The findings in this research contribute to the academic understanding of regional electricity market dynamics under long-term decarbonization scenarios and offer a quantitative basis for evaluating policy impacts on future electricity pricing.

Indexed as

EconomicsEnvironmental managementEnvironmental policy

Identifiers

PMID40678512
PMCPMC12270656

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.