Smart Grids Data Analysis: A Systematic Mapping Study

Data analytics and data science play a significant role in nowadays society. In the context of smart grids, the collection of vast amounts of data has seen the emergence of a plethora of data analysis approaches. In this article, we conduct a systematic mapping study aimed at getting insights about different facets of SG data analysis: application subdomains (e.g., power load control), aspects covered (e.g., forecasting), used techniques (e.g., clustering), tool support, research methods (e.g., experiments/simulations), and replicability/reproducibility of research. The final goal is to provide a view of the current status of research. Overall, we found that each subdomain 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.