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Review of Fundamental Active Current Extraction Techniques for SAPF

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F22%3A10250766" target="_blank" >RIV/61989100:27240/22:10250766 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.mdpi.com/1424-8220/22/20/7985" target="_blank" >https://www.mdpi.com/1424-8220/22/20/7985</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.3390/s22207985" target="_blank" >10.3390/s22207985</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Review of Fundamental Active Current Extraction Techniques for SAPF

  • Original language description

    The field of advanced digital signal processing methods is one of the fastest developing scientific and technical disciplines, and is important in the field of Shunt Active Power Filter control methods. Shunt active power filters are highly desirable to minimize losses due to the increase in the number of nonlinear loads (deformed power). Currently, there is rapid development in new adaptive, non-adaptive, and especially hybrid methods of digital signal processing. Nowadays, modern methods of digital signal processing maintain a key role in research and industrial applications. Many of the best practices that have been used to control shunt active power in industrial practice for decades are now being surpassed in favor of new progressive approaches. This systematic research review classifies the importance of using advanced signal processing methods in the field of shunt active power filter control methods and summarizes the extant harmonic extraction methods, from the conventional approach to new progressive methods using genetic algorithms, artificial intelligence, and machine learning. Synchronization techniques are described and compared as well.

  • 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

    20201 - Electrical and electronic engineering

Result continuities

  • Project

    <a href="/en/project/EF17_049%2F0008425" target="_blank" >EF17_049/0008425: A Research Platform focused on Industry 4.0 and Robotics in Ostrava Agglomeration</a><br>

  • Continuities

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

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

    Sensors

  • ISSN

    1424-3210

  • e-ISSN

    1424-8220

  • Volume of the periodical

    22

  • Issue of the periodical within the volume

    20

  • Country of publishing house

    CH - SWITZERLAND

  • Number of pages

    41

  • Pages from-to

    nestrankovano

  • UT code for WoS article

    000875198200001

  • EID of the result in the Scopus database