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Data analytics and data science play a significant role in nowadays society. In the context of Smart Grids (SG), the collection of vast amounts of data has seen the emergence of a plethora of data analysis approaches. In this paper, we conduct a Systematic Mapping Study (SMS) aimed at getting insights about different facets of SG data analysis: application sub-domains (e.g., power load control), aspects covered (e.g., forecasting), used techniques (e.g., clustering), tool-support, research methods (e.g., experiments/simulations), replicability/reproducibility of research. The final goal is to provide a view of the current status of research. Overall, we found that each sub-domain has its peculiarities in terms of techniques, approaches and research methodologies applied. Simulations and experiments play a crucial role in many areas. The replicability of studies is limited concerning the provided implemented algorithms, and to a lower extent due to the usage of private datasets.
The integration of renewable sources, communication and power networks with information and communication technologies is one of the main challenges in Smart Grids (SG) large-scale testing. For this reason, the coupling of simulators is commonly used
The conventional approach to pre-process data for compression is to apply transforms such as the Fourier, the Karhunen-Lo`{e}ve, or wavelet transforms. One drawback from adopting such an approach is that it is independent of the use of the compressed
Due to limited metering infrastructure, distribution grids are currently challenged by observability issues. On the other hand, smart meter data, including local voltage magnitudes and power injections, are communicated to the utility operator from g
One source of software project challenges and failures is the systematic errors introduced by human cognitive biases. Although extensively explored in cognitive psychology, investigations concerning cognitive biases have only recently gained populari
The utilisation of blockchain has moved beyond digital currency to other fields such as health, the Internet of Things, and education. In this paper, we present a systematic mapping study to collect and analyse relevant research on blockchain technol