Smart Grids Data Analysis: A Systematic Mapping Study

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14610%2F20%3A00115135" target="_blank" >RIV/00216224:14610/20:00115135 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/8903549" target="_blank" >https://ieeexplore.ieee.org/document/8903549</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TII.2019.2954098" target="_blank" >10.1109/TII.2019.2954098</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Smart Grids Data Analysis: A Systematic Mapping Study

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Smart Grids Data Analysis: A Systematic Mapping Study

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/EF16_013%2F0001802" target="_blank" >EF16_013/0001802: CERIT Scientific Cloud</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

IEEE Transactions on Industrial Informatics

ISSN

1551-3203

e-ISSN

1941-0050

Svazek periodika

16

Číslo periodika v rámci svazku

6

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

21

Strana od-do

3619-3639

Kód UT WoS článku

000526381800001

EID výsledku v databázi Scopus

2-s2.0-85081581363