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Bektaş, Enes

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Author-ID : 6996058

Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Mechanical Engineering

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Enhancing Harmonic Reduction in Multilevel Inverters using the Weevil Damage Optimization Algorithm Bektaş, Enes; Aldabbagh, Mohammed M; Ahmed, Saadaldeen Rashid; Hussain, Abadal-Salam T.; Taha, Taha A.; Ahmed, Omer K; Ezzat, Sarah B.; Hashim, Abdulghafor Mohammed
Journal of Robotics and Control (JRC) Vol 5, No 3 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i3.21544

In this study, we investigate the efficacy of the newly developed Weevil Damage Optimization Algorithm (WDOA) for addressing harmonic distortion in multilevel inverters. Specifically, harmonics of the fifth and seventh orders are targeted for elimination in a seven-level cascaded multilevel inverter, while harmonics of the fifth, seventh, eleventh, and thirteenth orders are addressed in an eleven-level cascaded multilevel inverter. Through simulation studies encompassing different modulation index values, we demonstrate the effectiveness of the WDOA optimization algorithm in selectively removing harmonics and reducing overall harmonic distortion. While the results showcase promising outcomes, further quantitative metrics and comparative analysis are warranted to fully evaluate the algorithm's performance and its potential implications for practical applications in multilevel inverter systems.

Enhanced Transformer Protection Using Fuzzy-Logic-Integrated Differential Relays: A Comparative Study with Rule-based Methods Hussein, Raad Ibrahim Hussein; Gökşenli, Nurettin; Bektaş, Enes; Teke, Mustafa; Tümay, Mehmet; Yaseen, Ethar Sulaiman Yaseen; Bektaş, Yasin; Taha, Taha A.
Journal of Robotics and Control (JRC) Vol 5, No 5 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i5.21937

The power transformers are the important part of electrical networks where transformer reliability and operational lifetime depends on sufficiently accurate and reliable protective means. Other traditional forms of differential protection that were developed initially also suffer from the inability to distinguish between a fault and normal operation such as inrush currents in transformers and CT saturation. This paper presents the development of an improved differential relay augmented by Fuzzy-Logic Control System (FLC), to improve (a) dependability, (b) performance of the existing transformer protection systems, and (c) accuracy in fault identification possible due to uncertainty and non-linearity in transformer operation. They include the proposed methodology compared to the traditional Rule-based current differential method in outlining the protection settings. MATLAB/Simulink model of the power transformer and protection methods suggested in the study form a part of the investigation. Computer simulations show that the presented scheme provides a substantial increase in the speed and resolution of fault detection and fault types identification relating to current differential method based on the Rule. The system’s accuracy rate is the average of 98% for internal faults and 95% for external faults while its response time is 25ms for internal faults and 30ms for external faults. Furthermore, the Fuzzy-Logic-based system has an 90% efficiency in detect the defect and 85% efficiency in identify the inrush currents. The findings of this research prove that the differential relay based on Fuzzy-Logic enhances the flexibility and reliability of transformer protection and opens the road to the introduction of further improvements in the intelligent protection systems in the future.

Enhanced Transformer Protection Using Fuzzy-Logic-Integrated Differential Relays: A Comparative Study with Rule-based Methods Hussein, Raad Ibrahim Hussein; Gökşenli, Nurettin; Bektaş, Enes; Teke, Mustafa; Tümay, Mehmet; Yaseen, Ethar Sulaiman Yaseen; Bektaş, Yasin; Taha, Taha A.
Journal of Robotics and Control (JRC) Vol. 5 No. 5 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i5.21937

The power transformers are the important part of electrical networks where transformer reliability and operational lifetime depends on sufficiently accurate and reliable protective means. Other traditional forms of differential protection that were developed initially also suffer from the inability to distinguish between a fault and normal operation such as inrush currents in transformers and CT saturation. This paper presents the development of an improved differential relay augmented by Fuzzy-Logic Control System (FLC), to improve (a) dependability, (b) performance of the existing transformer protection systems, and (c) accuracy in fault identification possible due to uncertainty and non-linearity in transformer operation. They include the proposed methodology compared to the traditional Rule-based current differential method in outlining the protection settings. MATLAB/Simulink model of the power transformer and protection methods suggested in the study form a part of the investigation. Computer simulations show that the presented scheme provides a substantial increase in the speed and resolution of fault detection and fault types identification relating to current differential method based on the Rule. The system’s accuracy rate is the average of 98% for internal faults and 95% for external faults while its response time is 25ms for internal faults and 30ms for external faults. Furthermore, the Fuzzy-Logic-based system has an 90% efficiency in detect the defect and 85% efficiency in identify the inrush currents. The findings of this research prove that the differential relay based on Fuzzy-Logic enhances the flexibility and reliability of transformer protection and opens the road to the introduction of further improvements in the intelligent protection systems in the future.

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