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Interlinking Heterogeneous Data for Smart Energy Systems

机译:智能能量系统的交互异构数据

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Smart energy systems in general, and solar energy analysis in particular, have recently gained increasing interest. This is mainly due to stronger focus on smart energy saving solutions and recent developments in photovoltaic (PV) cells. Various data-driven and machine-learning frameworks are being proposed by the research community. However, these frameworks perform their analysis - and are designed on - specific, heterogeneous and isolated datasets, distributed across different sites and sources, making it hard to compare results and reproduce the analysis on similar data. We propose an approach based on Web (W3C) standards and Linked Data technologies for representing and converting PV and weather records into an Resource Description Framework (RDF) graph-based data format. This format, and the presented approach, is ideal in a data integration scenario where data needs to be converted into homogeneous form and different datasets could be interlinked for distributed analysis.
机译:智能能量系统通常,特别是太阳能分析,最近获得了越来越兴趣的兴趣。这主要是由于强烈关注智能节能解决方案和光伏(PV)细胞的最新发展。研究界提出了各种数据驱动和机器学习框架。但是,这些框架执行了分析 - 并且是特定于特定的异构和隔离的数据集,分布在不同的站点和源上,使得难以比较结果并再现对类似数据的分析。我们提出了一种基于Web(W3C)标准的方法和链接数据技术,用于将PV和天气记录转换为资源描述框架(RDF)图形的数据格式。这种格式和呈现的方法是在数据集成场景中的理想选择,其中数据需要转换为同一性形式,并且可以对分布式分析交互不同的数据集。

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