Sünter, Sedat

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Profile URL
https://hdl.handle.net/20.500.14411/6825
Name Variants
S., Sunter
S.,Sünter
S., Sünter
Sunter,Sedat
S.,Sedat
Sedat Sünter
S., Sedat
S.,Sunter
Sünter, Sedat
Sunter S.
Sedat, Sünter
Sedat, Sunter
Sunter,S.
Sünter S.
Sünter,S.
Sunter, Sedat
Job Title
Profesör Doktor
Email Address
sedat.sunter@atilim.edu.tr
Main Affiliation
Electrical-Electronics Engineering
Status
Website
https://www.atilim.edu.tr/tr/eee/page/2207/akademik-personel
ORCID ID
0000-0002-4013-0876
Scopus Author ID
7004164902
Turkish CoHE Profile ID
3692
Google Scholar ID
SfVuEoIAAAAJ
WoS Researcher ID
W-1422-2018

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NO POVERTY1
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ZERO HUNGER2
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1
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QUALITY EDUCATION4
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GENDER EQUALITY5
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0
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CLEAN WATER AND SANITATION6
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AFFORDABLE AND CLEAN ENERGY7
AFFORDABLE AND CLEAN ENERGY
2
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DECENT WORK AND ECONOMIC GROWTH8
DECENT WORK AND ECONOMIC GROWTH
0
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INDUSTRY, INNOVATION AND INFRASTRUCTURE9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
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REDUCED INEQUALITIES10
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SUSTAINABLE CITIES AND COMMUNITIES11
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0
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RESPONSIBLE CONSUMPTION AND PRODUCTION12
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0
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CLIMATE ACTION13
CLIMATE ACTION
1
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LIFE BELOW WATER14
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LIFE ON LAND15
LIFE ON LAND
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PEACE, JUSTICE AND STRONG INSTITUTIONS
0
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PARTNERSHIPS FOR THE GOALS17
PARTNERSHIPS FOR THE GOALS
1
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Documents

36

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458

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3

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2

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34/0

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1

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WoS Citation Count

13

Scopus Citation Count

16

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0

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4.33

Scopus Citations per Publication

5.33

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0

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Electrical Engineering1
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Author: Sünter, S.Subject: MPPT

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Now showing 1 - 1 of 1
  • Thumbnail Image
    Article
    Ann-Based Maximum Power Tracking for a Grid-Synchronized Wind Turbine-Driven Doubly Fed Induction Generator Fed by Matrix Converter
    (Multidisciplinary Digital Publishing Institute (MDPI), 2025) Alarabi, M.A.; Sünter, S.; Suenter, Sedat
    The integration of renewable energy sources, such as wind power, into the electrical grid is essential for the development of sustainable energy systems. Doubly fed induction generators (DFIGs) have been significantly utilized in wind energy conversion systems (WECSs) because of their efficient power generation and variable speed operation. However, optimizing wind power extraction at variable wind speeds remains a major challenge. To address this, an artificial neural network (ANN) is adopted to predict the optimal shaft speed, ensuring maximum power point tracking (MPPT) for a wind energy-driven DFIG connected to a matrix converter (MC). The DFIG is controlled via field-oriented control (FOC), which allows independent power output regulation and separately controls the stator active and reactive power components. Through its compact design, bidirectional power flow, and enhanced harmonic performance, the MC, which is controlled by the simplified Venturini modulation technique, improves the efficiency and dependability of the system. Simulation outcomes confirm that the ANN-based MPPT enhances the power extraction efficiency and improves the system performance. This study shows how wind energy systems can be optimized for smart grids by integrating advanced control techniques like FOC and simplified Venturini modulation with intelligent algorithms like ANN. © 2025 by the authors.