Abstract
In Bali, especially at Tiga Nusa, the need for electricity is increasing along with the development of the construction of resorts and hotels. In this study, a sample of cases was taken in 2014 regarding the Lembongan feeder network system which was still installed with several LBS (Load Break Switch) which used to localize interference. Therefore, to anticipate interference and improve the reliability of feeders, one of many ways is to add an automatic back cover (recloser). This study aims to determine the optimal recloser location in the Lembongan feeder by using a combined method of fuzzy logic and particle swarm optimization with the help of MATLAB software. The results of this study obtained the best location of the recloser in group 5, namely the area between LBS SD 3, LBS Celagi Empak, and LBS Lembongan by adding one recloser. The SAIFI value is 1,9471 times / customer / year and the SAIDI value is 1,4596 hours / customer / year where the world class service parameter standard for the SAIFI reliability index is 3 times / customer / year and the SAIDI reliability index is 2,5 hours / customer / year.
Highlights
In Bali, especially at Tiga Nusa, the need for electricity is increasing along with the development of the construction of resorts and hotels
This study aims to determine the optimal recloser location in the Lembongan feeder by using a combined method of fuzzy logic and particle swarm optimization with the help of MATLAB software
[10] Kennedy J Ana Eberhart R, “Particle Swarm Optimizer,” IEEE International Conference on Neural Network (Perth, Australia), IEEE Service Center Piscataway, NJ, IV, pp1942-1948, 1995
Summary
Meningkatnya pariwisata di Bali khususnya di Tiga Nusa (Pulau Nusa Penida, Pulau Nusa Lembongan, Pulau Nusa Ceningan) menyebabkan kebutuhan energi listrik juga semakin meningkat sehingga perlu ditingkatkan keandalannya. Berdasarkan data dari PT PLN (Persero) Area Bali Timur nilai indeks keandalan tahun 2014 untuk Penyulang Lembongan memliki nilai SAIFI sebesar 76 kali/ pelanggan/ tahun dan nilai SAIDI sebesar 95,85 jam/ pelanggan/ tahun. Beberapa metode telah digunakan untuk menyelesaikan permasalahan optimasi penempatan recloser, salah satunya adalah penelitian yang dilakukan oleh Lesmana Putra tahun 2015 yaitu menggunakan metode kombinasi logika fuzzy dengan algoritma genetika untuk menentukan letak recloser yang optimal dengan hasil memilih nilai fitness tertinggi dari hasil running program menggunakan MATLAB sebagai posisi recloser yang optimal. Azwar Rachman pada tahun 2013, menggunakan particle swarm optimization (PSO) untuk menganalisis posisi recloser yang paling tepat dengan melakukan pengujian pada nilai SAIFI dan SAIDI.
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