Smart Grids Data Analysis: A Systematic Mapping Study
| Authors | |
|---|---|
| Year of publication | 2020 |
| Type | Article in Periodical |
| Magazine / Source | IEEE Transactions on Industrial Informatics |
| MU Faculty or unit | |
| Citation | |
| web | https://ieeexplore.ieee.org/document/8903549 |
| Doi | http://dx.doi.org/10.1109/TII.2019.2954098 |
| Keywords | Cyber-physical systems; data analytics; literature survey; smart grids (SG); systematic mapping study (SMS) |
| Description | 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. |
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