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Data Consistency for Data-Driven Smart Energy Assessment

Gianfranco Chicco¹

¹Dipartimento Energia "Galileo Ferraris," Politecnico di Torino, Torino, Italy.

Frontiers in Big Data

|May 31, 2021

Abstract:

In the smart grid era, the number of data available for different applications has increased considerably. However, data could not perfectly represent the phenomenon or process under analysis, so their usability requires a preliminary validation carried out by experts of the specific domain. The process of data gathering and transmission over the communication channels has to be verified to ensure that data are provided in a useful format, and that no external effect has impacted on the correct data to be received. Consistency of the data coming from different sources (in terms of timings and data resolution) has to be ensured and managed appropriately. Suitable procedures are needed for transforming data into knowledge in an effective way. This contribution addresses the previous aspects by highlighting a number of potential issues and the solutions in place in different power and energy system, including the generation, grid and user sides. Recent references, as well as selected historical references, are listed to support the illustration of the conceptual aspects.

Keywords:

big data data analytics data-driven internet of things knowledge extraction machine learning smart energy uncertainty

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