English(EN) SmartMeterFM: Flow Matching for Smart Meter Data Generation, Imputation, and Super-Resolution Without Retraining

SmartMeterFM 使用流匹配技术处理多种智能电表数据任务

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-02 05:00

研究人员开发了 SmartMeterFM，这是一种新颖的条件流匹配模型，用于生成、插补和超分辨率智能电表数据。该模型通过条件化客户属性和数值配置文件约束，可以使用一组相同的权重执行所有这些任务，而无需进行特定任务的重新训练。一项使用荷兰智能电表数据的案例研究表明，SmartMeterFM 在插补和超分辨率任务上优于现有的特定任务基线，取得了显著更好的结果。 AI

影响该模型为智能电表数据处理提供了一种统一的方法，有望简化能源行业分析和预测的工作流程。

排序理由该项目是一篇研究论文，详细介绍了一个新模型及其在特定任务上的性能。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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报道来源 [1]

arXiv cs.LG TIER_1 English(EN) · Nan Lin, Yanbo Wang, Jacco Heres, Peter Palensky, Pedro P. Vergara · 2026-11-02 05:00

SmartMeterFM: Flow Matching for Smart Meter Data Generation, Imputation, and Super-Resolution Without Retraining

arXiv:2601.21706v3 Announce Type: replace Abstract: Distribution system operators need realistic load and generation profiles when measurements are unavailable, incomplete, or too coarse for the intended analysis. Training separate models for synthetic data generation, imputation…

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SmartMeterFM: Flow Matching for Smart Meter Data Generation, Imputation, and Super-Resolution Without Retraining

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