A Novel Approach to Achieve MPPT for Photovoltaic System Based SCADA
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F22%3A50020233" target="_blank" >RIV/62690094:18450/22:50020233 - isvavai.cz</a>
Result on the web
<a href="https://www.mdpi.com/1996-1073/15/22/8480" target="_blank" >https://www.mdpi.com/1996-1073/15/22/8480</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/en15228480" target="_blank" >10.3390/en15228480</a>
Alternative languages
Result language
angličtina
Original language name
A Novel Approach to Achieve MPPT for Photovoltaic System Based SCADA
Original language description
In this study, an improved artificial intelligence algorithms augmented Internet of Things (IoT)-based maximum power point tracking (MPPT) for photovoltaic (PV) system has been proposed. This will facilitate preventive maintenance, fault detection, and historical analysis of the plant in addition to real-time monitoring. Further, the simulation results validate the improved performance of the suggested method. To demonstrate the superiority of the proposed MPPT algorithm over current methods, such as cuckoo search algorithms and the incremental conductance approach, a performance comparison is offered. The outcomes demonstrate the suggested algorithm's capability to track the Global Maximum Power Point (GMPP) with quicker convergence and less power oscillations than before. The results clearly show that the artificial intelligence algorithm-based MPPT is capable of tracking the GMPP with an average efficiency of 88%, and an average tracking time of 0.029 s, proving both its viability and effectiveness.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20704 - Energy and fuels
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
ENERGIES
ISSN
1996-1073
e-ISSN
1996-1073
Volume of the periodical
15
Issue of the periodical within the volume
22
Country of publishing house
CH - SWITZERLAND
Number of pages
29
Pages from-to
"Article Number: 8480"
UT code for WoS article
000887191900001
EID of the result in the Scopus database
2-s2.0-85142679245