Sünter, Sedat

Profile Picture
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

Sustainable Development Goals

14

LIFE BELOW WATER
LIFE BELOW WATER Logo

0

Research Products

2

ZERO HUNGER
ZERO HUNGER Logo

0

Research Products

11

SUSTAINABLE CITIES AND COMMUNITIES
SUSTAINABLE CITIES AND COMMUNITIES Logo

0

Research Products

1

NO POVERTY
NO POVERTY Logo

0

Research Products

12

RESPONSIBLE CONSUMPTION AND PRODUCTION
RESPONSIBLE CONSUMPTION AND PRODUCTION Logo

0

Research Products

7

AFFORDABLE AND CLEAN ENERGY
AFFORDABLE AND CLEAN ENERGY Logo

2

Research Products

5

GENDER EQUALITY
GENDER EQUALITY Logo

0

Research Products

3

GOOD HEALTH AND WELL-BEING
GOOD HEALTH AND WELL-BEING Logo

1

Research Products

9

INDUSTRY, INNOVATION AND INFRASTRUCTURE
INDUSTRY, INNOVATION AND INFRASTRUCTURE Logo

0

Research Products

13

CLIMATE ACTION
CLIMATE ACTION Logo

1

Research Products

6

CLEAN WATER AND SANITATION
CLEAN WATER AND SANITATION Logo

0

Research Products

10

REDUCED INEQUALITIES
REDUCED INEQUALITIES Logo

0

Research Products

4

QUALITY EDUCATION
QUALITY EDUCATION Logo

0

Research Products

15

LIFE ON LAND
LIFE ON LAND Logo

0

Research Products

16

PEACE, JUSTICE AND STRONG INSTITUTIONS
PEACE, JUSTICE AND STRONG INSTITUTIONS Logo

0

Research Products

17

PARTNERSHIPS FOR THE GOALS
PARTNERSHIPS FOR THE GOALS Logo

1

Research Products

8

DECENT WORK AND ECONOMIC GROWTH
DECENT WORK AND ECONOMIC GROWTH Logo

0

Research Products
Documents

36

Citations

458

h-index

12

Go to Scopus profile
Documents

30

Citations

262

Go to WoS profile
Scholarly Output

3

Articles

2

Views / Downloads

34/0

Supervised MSc Theses

1

Supervised PhD Theses

0

WoS Citation Count

12

Scopus Citation Count

16

WoS h-index

1

Scopus h-index

1

Patents

0

Projects

0

WoS Citations per Publication

4.00

Scopus Citations per Publication

5.33

Open Access Source

0

Supervised Theses

1

Google Analytics Visitor Traffic

JournalCount
Electrical Engineering1
Energies1
Current Page: 1 / 1

Scopus Quartile Distribution

Competency Cloud

GCRIS Competency Cloud

Filters

20251
Reset filters

Settings

Author: Alarabi, M.A.

Scholarly Output Search Results

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.
    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.