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Interlinking Heterogeneous Data for Smart Energy Systems

机译:互连异构数据以实现智能能源系统

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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:总体上,智能能源系统,尤其是太阳能分析,最近引起了越来越多的兴趣。这主要是由于更加关注智能节能解决方案以及光伏(PV)电池的最新发展。研究界正在提出各种数据驱动和机器学习框架。但是,这些框架执行了分析,并且是针对特定的,异构的和隔离的数据集进行设计的,这些数据集分布在不同的站点和源中,因此很难比较结果并在相似数据上重现分析。我们提出了一种基于Web(W3C)标准和链接数据技术的方法,用于表示PV和天气记录并将其转换为基于资源描述框架(RDF)图的数据格式。这种格式和提出的方法非常适合数据集成方案,在这种方案中,数据需要转换为同质形式,并且可以互连不同的数据集以进行分布式分析。

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