Setiawati, Novie Elok (2019) Prediksi Sisa Umur Transformator Distribusi Menggunakan Metode Neuro Wavelet. Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Transformator distribusi adalah salah satu instrument penting dalam penyaluran listrik ke konsumen. Selain penggunaan normal, kondisi gangguan pada transformator dapat menyebabkan menurunnya umur transformator sehingga kinerja transformator tidak optimal sampai batas umur operasinya. Oleh karena itu penting sekali dilakukan menghitung sisa umur transformator. Tahapan yang dilakukan adalah menghitung sisa umur transformator menggunakan standar IEC 60076-7.
Selanjutnya dilakukan prediksi sisa umur transformator menggunakan wavelet transform dan backprogation neural network. Parameter-parameter yang diperlukan untuk penelitian ini antara lain sinyal arus transformator, pembebanan dan umur transformator. Pengukuran arus dan temperatur transformator distribusi dilaksanakan di Surabaya Utara dengan rating 20 KV / 380-220 Volt. Pengukuran arus transformator telah diolah dengan menggunakan wavelet transform untuk mendapatkan detail koefisien yang digunakan untuk menghitung nilai energi dan PSD. Nilai energi, PSD dan pembebanan transformator merupakan data latih dan
data testing pada backpropagation neural network. Output metode yang diharapkan adalah prediksi sisa umur transformator
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The distribution transformer is one of the vital components in the power system distribution, which is deliver electricity power to the consumer. In addition to normal use, the disturbance conditions on the transformer can cause a decrease of its performance of the transformer, so that it cannot reach its operation life. Therefore, it is important to calculate the remaining lifetime of trnasformer. The step that needs to be done is to calculate the remaining lifetime of transformer using the IEC standard 60076-7.
Furthermore, predicting the remaining lifetime of transformer using wavelet transform and backpropagation neural network. The parameters used for this research include current signal, load and remaining lifetime of transformer. Transformer current measurement is carried out in North Surabaya with a rating of 20 KV/380-220 V. The current of the distribution transformer has been processed using the wavelet transform to obtain the detail coefficients used to calculate the energi and PSD (power spectral density) value. Energi value and PSD (power spectral density) are inputs data used on training and testing of backpropagation neural network. The expected output method is the prediction remaining lifetime of transformer.
| Item Type: | Thesis (Masters) |
|---|---|
| Additional Information: | RTE 621.314 Set p-1 2019 |
| Uncontrolled Keywords: | transformator distribusi, IEC standart 60076-7, wavelet transform, energi, PSD, backpropagation neural network |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Electrical Technology > Electrical Engineering > 20101-(S2) Master Thesis |
| Depositing User: | Novie Elok Setiawati |
| Date Deposited: | 28 May 2021 07:26 |
| Last Modified: | 28 May 2021 07:26 |
| URI: | http://repository.its.ac.id/id/eprint/60221 |
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