Harmonic Minimization Using Artificial Neural Network Technique For CHB-ML Inverter

Alakkad, Moataz M.A.; Rasin, Zulhani; Rasheed, Mohammed; Omar, Rosli

doi:10.1109/icpea51500.2021.9417759

Cited by 5 publications

(2 citation statements)

References 15 publications

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“…The application of artificial neural network (ANN) in the real-time implementation of PPWM require the offline training of the neural network for the switching angles. After that, this approach can generate optimal switching angles for a certain range of modulation indices [157][158][159]. Another method, called model predictive control (MPC), can control the selected harmonic components in real time with low switching frequency [160,161].…”

Section: Other Improved Methods For Real-time/online Implementationmentioning

confidence: 99%

Formulations, Solving Algorithms, Existing Problems and Future Challenges of Pre-Programmed PWM Techniques for High-Power AFE Converters: A Comprehensive Review

et al. 2022

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Considering the development of the hybrid wind and solar photovoltaic generation and smart grid, Active Front-End (AFE) converters for high-power applications are facing significant opportunities and challenges related to power quality and efficiency. The Pre-programmed Pulse-Width Modulation (PPWM) techniques can strictly control the harmonic spectrum of a specified voltage or current waveform generated by a high-power AFE converters, and have been extensively applied to reduce or even eliminate the harmonic distortion with low switching losses for high-power converters in order to deal with these issues aforementioned. For the PPWM techniques with low switching frequency, Selective Harmonic Elimination (SHE) and Selective Harmonic Mitigation (SHM) have been the prevailing solutions and gain widespread popularity, among which SHM can provide further control of the harmonic spectrum in cases of similar switching losses to SHE. Over the past several decades, the applications of SHE and SHM have been extended to high-power AFE converters. Thus, the aim of this study is to provide a comprehensive literature review regarding their various formulations, solving algorithms, and existing problems to high-power AFE converters. In addition, the suggestions for future applications of PPWM in high-power AFE converters are also discussed.

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Section: Other Improved Methods For Real-time/online Implementationmentioning

confidence: 99%

Formulations, Solving Algorithms, Existing Problems and Future Challenges of Pre-Programmed PWM Techniques for High-Power AFE Converters: A Comprehensive Review

et al. 2022

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“…ANN menggunakan interkoneksi neuron yang masif untuk mencapai kinerja yang baik. Perancangan FA untuk mendapatkan sudut penyaklaran terbaik yang dapat digunakan untuk meminimalkan harmonisa dibahas dalam [54] dan [55]. Penelitian telah dilakukan pada CHB-MLI 5 tingkat, 7 tingkat, dan 9 tingkat dengan simulasi pada software MATLAB.…”

Section: Hal Ini Bukan Merupakan Hasil Yang Bagus Namun Masih Lebihunclassified

Literature Review Metode Reduksi Harmonisa Berbasis Kecerdasan Buatan pada Multilevel Inverter

Wirsuyana¹,

Linawati²,

Manuaba³

et al. 2022

JTE

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Multilevel Inverter (MLI) merupakan salah satu jenis inverter yang memiliki gelombang tegangan keluaran bertingkat. Meskipun lebih baik dari inverter konvensional, MLI yang beroperasi pada frekuensi rendah masih mengandung harmonisa orde rendah pada tegangan dan arus keluaran yang berdampak negatif pada sistem kelistrikan. Untuk mengatasi masalah ini, banyak peneliti telah mengembangkan berbagai teknik kontrol dan pada modulasi inverter untuk mengurangi harmonisa dan meminimalkan kerugian penyaklaran dengan tujuan mengoptimalkan efisiensi inverter. Selective harmonic elimination pulse-width modulation (SHEPWM) adalah kontrol paling optimal dari semua metode yang telah dikembangkan untuk menghilangkan harmonisa orde rendah dari tegangan keluaran inverter. Namun, ada tantangan dalam proses analisis MLI menggunakan SHEPWM karena penyelesaian persamaan yang sulit. Bio-inspired intelligent algorithms (BIA) digunakan untuk memecahkan masalah ini. Paper ini menjelaskan secara lengkap review dari berbagai penelitian yang telah dilakukan sebelumnya terkait dengan prinsip operasi sembilan jenis BIA dan aplikasinya dalam mereduksi harmonisa. Kesimpulan dibuat berdasarkan informasi yang diambil dari literatur. Semua informasi penting dalam paper ini mengenai reduksi harmonisa pada MLI akan membantu penelitian di masa depan untuk merancang sistem konversi daya yang efisien. Kata Kunci— Bio-inspired algorithm, harmonisa, multilevel inverter, optimalisasi, selective harmonic elimination.

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Selective harmonic elimination using Newton-Raphson method applied with H-bridge inverter

Waleed,

Yasin,

Abed

2024

AIP Conference Proceedings

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Harmonic Minimization Using Artificial Neural Network Technique For CHB-ML Inverter

Cited by 5 publications

References 15 publications

Formulations, Solving Algorithms, Existing Problems and Future Challenges of Pre-Programmed PWM Techniques for High-Power AFE Converters: A Comprehensive Review

Formulations, Solving Algorithms, Existing Problems and Future Challenges of Pre-Programmed PWM Techniques for High-Power AFE Converters: A Comprehensive Review

Literature Review Metode Reduksi Harmonisa Berbasis Kecerdasan Buatan pada Multilevel Inverter

Selective harmonic elimination using Newton-Raphson method applied with H-bridge inverter

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