Klasifikasi Kesiapan Remotisasi Pembangkit Listrik Tenaga Air Yang Tersebar Menggunakan Logika Fuzzy

Arif, Zainal (2025) Klasifikasi Kesiapan Remotisasi Pembangkit Listrik Tenaga Air Yang Tersebar Menggunakan Logika Fuzzy. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

PLTA di PLN Nusantara Power yang telah mengadopsi teknologi remotisasi kurang dari 42%, terutama karena setiap pembangkit berada pada tingkat kematangan teknologi yang berbeda-beda. Penentuan prioritas PLTA yang akan di-upgrade teknologinya membutuhkan asesmen kesiapan teknologi remotisasi. Namun, proses asesmen dan klasifikasi menggunakan kategori Technology Readiness Level (TRL) yang dilakukan saat ini masih bersifat manual dan sangat bergantung pada opini para ahli, sehingga berpotensi menimbulkan hasil yang subjektif dan kurang konsisten. Penelitian ini mengusulkan penggunaan metode logika fuzzy melalui Fuzzy Inference System—Takagi-Sugeno-Kang (FIS-TSK) untuk mengklasifikasikan tingkat kesiapan teknologi remotisasi PLTA. Metode ini mengubah pengetahuan para ahli menjadi aturan yang jelas, sehingga proses klasifikasi menjadi lebih objektif dan konsisten. Asesmen kesiapan teknologi remotisasi didasarkan pada enam faktor utama yaitu: infrastruktur Information and Communication Technologies (ICT), sistem kontrol Sequence (SQC) start-stop, sistem kontrol Turbin Governor (GOV), sistem kontrol excitation Generator dengan Automatic Voltage Regulator (AVR), Supervisory Control and Data Acquisition (SCADA), dan sistem Substation Control and Protection (SCP). Hasil penelitian menunjukkan bahwa metode FIS-TSK mampu mengungguli metode Artificial Neural Network (ANN) dengan nilai Mean Absolute Percentage Error (MAPE) hanya 0,06% pada asesmen Remote Operation Readiness Level (RORL) untuk 23 PLTA, serta mencapai akurasi, presisi, dan recall hingga 100% dalam klasifikasi TRL. Temuan ini juga membuka peluang untuk pengembangan aplikasi klasifikasi berbasis web di masa depan. Hasil penelitian ini dapat menjadi panduan dalam mengidentifikasi peralatan PLTA yang perlu di-upgrade agar siap dioperasikan secara remote. Metode ini juga dapat membantu dalam pengambilan keputusan untuk menentukan prioritas peningkatan teknologi remotisasi di lingkungan PLN Nusantara Power.
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Less than 42% of hydropower plants at PLN Nusantara Power have adopted remotization technology, primarily because each plant is at a different stage of technological maturity. Determining the priority of hydropower plants for technology upgrades requires an assessment of remotization technology readiness. However, the current assessment and classification process, which utilizes the Technology Readiness Level (TRL) categories, remains manual and heavily reliant on expert opinions, resulting in subjective and inconsistent outcomes. This study proposes the use of fuzzy logic through the Fuzzy Inference System—Takagi-Sugeno-Kang (FIS-TSK) to classify the readiness level of hydropower plant remotization technology. This method transforms expert knowledge into clear rules, making the classification process more objective and consistent. The assessment of remotization technology readiness is based on six main factors: Information and Communication Technologies (ICT) infrastructure, start-stop Sequence control system (SQC), turbine Governor control system (GOV), excitation generator with Automatic Voltage Regulator control system (AVR), Supervisory Control and Data Acquisition (SCADA), and Substation Control and Protection (SCP) system. The results show that the FIS-TSK method outperforms the Artificial Neural Network (ANN) method, achieving a Mean Absolute Percentage Error (MAPE) of only 0.06% in the assessment of the Remote Operation Readiness Level (RORL) for 23 hydropower plants, as well as reaching up to 100% accuracy, precision, and recall in TRL classification. These findings open up opportunities for developing web-based classification applications in the future work. The results of this study can guide the identification of hydropower plant equipment that requires upgrading to enable remote operation. This method can also help in decision-making to determine the priority of improving remote technology within PLN Nusantara Power.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	logika fuzzy, PLTA, remotisasi, SCADA, TSK, TRL. fuzzy logic, hydropower plant, remotization, SCADA, TSK, TRL.
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1519.S68 Hydroelectric power plants
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20101-(S2) Master Thesis
Depositing User:	Zainal Arif
Date Deposited:	22 Jul 2025 07:43
Last Modified:	22 Jul 2025 07:43
URI:	http://repository.its.ac.id/id/eprint/120567

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