Deteksi Dan Implementasi Arcing Tegangan Rendah Pada Sistem Photovoltaic Berdasarkan Transformasi Wavelet

Septianto, Bagus (2025) Deteksi Dan Implementasi Arcing Tegangan Rendah Pada Sistem Photovoltaic Berdasarkan Transformasi Wavelet. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Renewable Energy yang berkembang masif mengharuskan adanya peningkatan dalam proteksi sistem Microgrid DC. Photovoltaic sangat masif berkembang karena harganya yang relatif sudah murah. Salah satu yang bisa menyebabkan sistem DC terutama PV rusak adalah adanya fenomena arcing. Arcing biasanya terjadi dalam waktu singkat, sehingga peralatan MCB dan fuse tidak dapat mendeteksi. Arcing seri sangat sulit dideteksi karena arus gangguan yang lebih kecil dari kondisi normal sehingga menyebabkan MCB dan fuse tidak mendeteksi penurunan arus sebagai adanya gangguan. Pada studi dilakukan pendeteksian Arcing menggunakan mikrokontroler berbasis Discrete Wavelet Transform (DWT). Center of Gravity dan Diagram radar digunakan untuk menentukan jenis wavelet terbaik dalam mendeteksi Series Arc Faults (SAF). Studi ini menggunakan empat jenis wavelet yaitu Haar, Db4, Symplet 4, dan Coiflet 4 dan menggunakan pemanjangan kabel 50M untuk mengetahui pengaruhnya. Algoritma mikrokontroler yang digunakan untuk mendeteksi arcing adalah mengambil arus setiap 700ms dengan 2048 sampel yang masuk ke mikrokontroller STM32F4 sebagai alat teknik pemrosesan sinyal arus dengan mempertimbangkan treshold transformasi wavelet. Ketika sampel yang dideteksi melebihi treshold dari 30 ADC sebagai treshold mengindikasikan adanya arcing. Hasil dari penelitian performa terbaik dalam pendeteksian berbasis mikrokontroler berurutan adalah Db4, Haar, Symplet 4, dan Coiflet 4. Pada beban 1300W dengan Daubechies 4, jarak CoG turun dari 0,423 menjadi 0,319 ketika kabel berukuran 50 meter. Fenomena busur api seri memiliki dua bagian utama yaitu inisiasi arcing dan steady state arcing. Pengujian Center of Gravity (CoG) memiliki hasil wavelet terbaik berurutan yaitu Db4, Haar, Symplet 4, dan Coiflet 4. Luas Area diagram radar memiliki hasil terbaik berurutan adalah Db4, Haar, Symplet 4, dan Coiflet 4. Dimana Daubechies 4 kembali menjadi yang paling terdampak akibat pemanjangan kabel 50M, dengan penurunan hingga 56,8% (dari 0,236 menjadi 0,102 pada 1300W).
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The significant expansion of renewable energy necessitates enhancements in the safeguarding of DC microgrid systems. The rapid proliferation of photovoltaic systems can be attributed to their relatively low costs. A primary factor contributing to the damage of DC systems, especially photovoltaic systems, is arcing. This phenomenon typically occurs within a very brief timeframe, complicating the detection efforts of miniature circuit breakers (MCBs) and fuses. Series arcing poses particular detection challenges, as the fault current is lower than the normal operating current, leading to the failure of MCBs and fuses to recognize the current drop as a fault. In this research, arcing detection was executed using a microcontroller that employs the Discrete Wavelet Transform (DWT). The study utilized center of gravity and radar diagrams to identify the optimal wavelet type for detecting Series Arc Faults (SAF). Four wavelet types were examined: Haar, Db4, Symplet 4, and Coiflet 4, with a 50-meter cable extension to evaluate their impacts. The algorithm implemented in the microcontroller for arc detection involved sampling the current every 700 milliseconds, with 2048 samples processed by the STM32F4 microcontroller as a tool for current signal processing, taking into account the wavelet transformation threshold. An arc was indicated when the detected sample surpassed the threshold of 30 ADC. The sequential detection performance results indicated that Db4, Haar, Symplet 4, and Coiflet 4 yielded the best outcomes. At a load of 1300 W with Daubechies 4, the Center of Gravity (CoG) distance reduced from 0.423 to 0.319 with a cable length of 50 meters. The serial arc phenomenon consists of two primary components: arc initiation and steady-state arcing. The CoG test produced the most favorable wavelet results in the following order: Db4, Haar, Symplet 4, and Coiflet 4. The radar area diagram results corroborated the sequential findings for Db4, Haar, Symplet 4, and Coiflet 4. Daubechies 4 was notably impacted by the increase in cable length, exhibiting a decrease of up to 56.8% (from 0.236 to 0.102 at 1300 W).

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Arcing, Deteksi Arcing, Discrete Wavelet Transform, Photovoltaic, Renewable Energy, Arcing, Arcing Detection, Discrete Wavelet Transform, Photovoltaic.
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1056 Solar power plants. Ocean thermal power plants T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1087 Photovoltaic power generation T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1322.6 Electric power-plants T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5102.9 Signal processing.
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20101-(S2) Master Thesis
Depositing User:	Septianto Bagus
Date Deposited:	21 Jul 2025 05:34
Last Modified:	21 Jul 2025 05:34
URI:	http://repository.its.ac.id/id/eprint/120251

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