Smart Grids Data Analysis: A Systematic Mapping Study

ROSSI, Bruno and Stanislav CHREN. Smart Grids Data Analysis: A Systematic Mapping Study. IEEE Transactions on Industrial Informatics. IEEE, 2020, vol. 16, No 6, p. 3619-3639. ISSN 1551-3203. Available from: https://dx.doi.org/10.1109/TII.2019.2954098.

Basic information

• Original name: Smart Grids Data Analysis: A Systematic Mapping Study
• Authors: ROSSI, Bruno (380 Italy, guarantor, belonging to the institution) and Stanislav CHREN (703 Slovakia, belonging to the institution).
• Edition: IEEE Transactions on Industrial Informatics, IEEE, 2020, 1551-3203.

Other information

• Original language: English
• Type of outcome: Article in a journal
• Field of Study: 10201 Computer sciences, information science, bioinformatics
• Country of publisher: United States of America
• Confidentiality degree: is not subject to a state or trade secret
• WWW: URL
• Impact factor: Impact factor: 10.215
• RIV identification code: RIV/00216224:14610/20:00115135
• Organization unit: Institute of Computer Science
• Doi: http://dx.doi.org/10.1109/TII.2019.2954098
• UT WoS: 000526381800001
• Keywords in English: Cyber-physical systems; data analytics; literature survey; smart grids (SG); systematic mapping study (SMS)
• Tags: rivok
• Tags: International impact, Reviewed

Abstract

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.

Links

• EF16_013/0001802, research and development project: Name: CERIT Scientific Cloud
• MUNI/A/1076/2019, interní kód MU: Name: Zapojení studentů Fakulty informatiky do mezinárodní vědecké komunity 20 (Acronym: SKOMU)

Investor: Masaryk University, Category A

• MUNI/A/1411/2019, interní kód MU: Name: Aplikovaný výzkum: softwarové architektury kritických infrastruktur, bezpečnost počítačových systémů, zpracování přirozeného jazyka a jazykové inženýrství, vizualizaci velkých dat a rozšířená realita.

Investor: Masaryk University, Category A