ArticleNature communications2026
Behavioral uncertainty in EV charging drives heterogeneous grid load variability under climate goals.
Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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.
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Who cites it
1 citing paper in PubMed.
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Large-scale deployment of electric vehicles (EVs) to meet climate goals imposes dual pressures on power system reliability: increased electricity demand and intensified daily load variability arising from uncertain charging behavior. This study quantifies the magnitude and spatial distribution of behavior-induced load variability in China under alternative climate scenarios, using a scalable model calibrated with minute-level EV charging data. EV adoption consistent with carbon-neutrality goals is projected to raise electricity demand by 3.2% in 2050, requiring an additional annual investment of approximately 220 billion CNY (about 31 billion USD) in battery storage capacity. Accounting for behavioral uncertainty, potential load fluctuations could increase by up to 82.7%. Regional heterogeneity in charging patterns drives distinct spatial profiles of electricity variability, influencing the effectiveness of demand-side management strategies. These findings highlight the importance of targeted, behaviorally informed interventions to mitigate grid reliability risks under deep EV adoption.
Identifiers
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Registered trials
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.