Maulana, Mohammad Fiqih (2023) Desain Dan Imlementasi Sistem Rekomendasi Penagnanan Gangguan Pada Suhu Minyak Trafo Distribusi Menggunakan Metode Logika Fuzzy. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Penelitian ini membahas tentang penerapan sistem rekomendasi "Experience-Based Recommendation" menggunakan aturan logika fuzzy untuk penanganan gangguan pada trafo distribusi. Trafo distribusi memainkan peran penting dalam menjaga stabilitas pasokan listrik di era peningkatan kebutuhan energi dan perkembangan teknologi. Namun, meningkatnya kompleksitas dan tantangan operasional trafo distribusi membutuhkan pendekatan yang lebih presisi dan adaptif. Sistem rekomendasi yang diusulkan menggabungkan pengalaman berbasis pengetahuan ahli dengan metode logika fuzzy untuk memberikan rekomendasi penanganan gangguan yang lebih efektif. Sistem ini menggunakan data input seperti arus, tegangan, suhu minyak, tekanan minyak, dan level minyak trafo, yang diterjemahkan ke dalam variabel linguistik menggunakan fungsi keanggotaan. Dalam uji pembebanan trafo, sistem rekomendasi berhasil mendeteksi gangguan undervoltage dan perubahan panas pada minyak trafo. Rekomendasi yang diberikan adalah melakukan trip pada low voltage trafo saat terjadi gangguan pada jaringan distribusi beban, dan melakukan trip pada high voltage trafo saat terjadi gangguan pada minyak trafo serta perawatan rutin pada saat trafo dalam kondisi normal, untuk menjaga keandalan trafo. Dari hasil dan pembahasan pengujian beban terdapat kenormalan pada arus trafo A disaat pembebanan, yaitu beban dengan kapasitas penuh mengakibatkan terjadi arus yang mengalir sangat besar, namun masih dalam taraf maksimal operasi yang bisa ditampung oleh trafo, Pada saat penerapan aturan fuzzy data ke 24 saat pengujian beban penuh, didapat output sebesar 0,486. Pada fungsi keanggotaan output normal memiliki nilai dengan 0 < normal < 0,5 yang mengindikasikan bahwa status dari trafo tersebut masih dalam kondisi normal pada saat beroperasi, sehingga tidak direkomendasikan untuk melakukan trip pada trafo. Dari hasil dan pembahasan semua pengujian beban trafo B, mengindikasikan bahwa trafo tersebut rentan terhadap beban besar. Saat penerapan aturan fuzzy data selama 24 jam pengujian dengan beban step 80% kapasitas trafo B, didapatkan output sebesar 1. Pada fungsi keanggotaan output, nilai "abnormal" memiliki rentang 0,5 < abnormal ≤ 1, menandakan bahwa trafo B berada dalam kondisi abnormal, dengan suhu sebesar 94°C, tekanan 271 mBar, dan level 189 cm³. Oleh karena itu, direkomendasikan untuk melakukan trip pada trafo. Sistem rekomendasi dalam penanganan gangguan minyak trafo dapat diimplementasikan untuk pendeteksian suhu, tekanan, dan level minyak trafo, dengan melakukan percobaan pada dua objek trafo dengan perbedaan kapasitas dan masa penggunaan.
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This study discusses the implementation of the "Experience-Based Recommendation" recommendation system using fuzzy logic rules for handling disturbances in distribution transformers. Distribution transformers play an important role in maintaining the stability of electricity supply in an era of increasing energy demand and technological developments. However, the increasing complexity and operational challenges of distribution transformers require a more precise and adaptive approach. The proposed recommendation system combines expert knowledge-based experience with fuzzy logic methods to provide more effective troubleshooting recommendations. This system uses input data such as current, voltage, oil temperature, oil pressure, and transformer oil level, which are translated into linguistic variables using membership functions. In the transformer loading test, the recommendation system was successful in detecting undervoltage disturbances and heat changes in the transformer oil. The recommendations given are to trip on a low voltage transformer when there is a disturbance in the load distribution network, and to trip on a high voltage transformer when there is a disturbance in transformer oil and routine maintenance when the transformer is in normal condition, to maintain the reliability of the transformer. From the results and discussion of the load test, there is normality in the current of transformer A when loading, that is, a full capacity load results in a very large flowing current, but it is still at the maximum level of operation that can be accommodated by the transformer. When applying the 24th fuzzy data rule during testing full load, the output is 0.486. In the normal output membership function, it has a value of 0 < normal < 0.5 which indicates that the status of the transformer is still in normal condition during operation, so it is not recommended to trip the transformer. From the results and discussion of all transformer B load tests, it indicates that the transformer is vulnerable to large loads. When applying fuzzy data rules for 24 hours of testing with a step load of 80% of transformer B's capacity, an output of 1 is obtained. In the output membership function, the "abnormal" value has a range of 0.5 < abnormal ≤ 1, indicating that transformer B is in an abnormal condition , with a temperature of 94°C, a pressure of 271 mBar, and a level of 189 cm³. Therefore, it is recommended to trip the transformer. A recommendation system for handling transformer oil disturbances can be implemented to detect transformer oil temperature, pressure, and level, by conducting experiments on two transformer objects with different capacities and lifetimes.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Logika Fuzzy, Sistem Rekomendasi, Minyak Trafo, Fuzzy Logic, Recommendation System, Transformer Oil |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK3030 Electric power distribution systems T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK6565.T7 Transformers T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7878 Electronic instruments |
| Divisions: | Faculty of Vocational > 36304-Automation Electronic Engineering |
| Depositing User: | Mohammad Fiqih Maulana |
| Date Deposited: | 15 Sep 2023 06:31 |
| Last Modified: | 18 Mar 2024 03:08 |
| URI: | http://repository.its.ac.id/id/eprint/104614 |
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