All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

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&apos;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

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20704 - Energy and fuels

Result continuities

  • Project

  • 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