Relevant bibliographies by topics / System average interruption duration index (SAIDI)

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Academic literature on the topic 'System average interruption duration index (SAIDI)'

Author: Grafiati
Published: 11 December 2022
Last updated: 11 June 2025

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Journal articles on the topic "System average interruption duration index (SAIDI)"

1

Abidin, Zainal, and Abdul Hadi. "Analisis System Avarage Interruption Frequency Index dan System Average Interruption Duration Index Beroreantasi Pelanggan Pada Gangguan Jaringan Tegangan Rendah dan Menengah." INOVTEK - Seri Elektro 2, no. 2 (2020): 63. http://dx.doi.org/10.35314/ise.v2i2.1427.

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Nilai indeks parameter SAIFI dan SAIDI dipengaruhi oleh waktu keluar (pemadaman), waktu masuk (nyala) dan wama padam (durasi) yang dialami rata-rata pelanggan selama satu tahun. SAIFI dan SAIDI tahun 2019 sistem distribusi 20 kV PT. PLN (Persero) rayon bengkalis merupakan SAIFI dan SAIDI terbaik disemua gangguan SR & APP, SUTR dan SUTM jika dibandingkan SAIFI dan SAIDI tahun 2017 dan 2018. SAIFI = 0,998746 dan SAIDI = 0,169709 terendah tahun 2019 di SUTR, dan SAIFI = 4,142909 tertinggi tahun 2018 serta SAIDI = 3,642906 tahun 2017 di SR & APP. SAIDI tahun 2019 hasil perhitungan memenuhi standar (sistim handal) terhadap nilai Standar SPLN 68-2 : 1986 di SR & APP, SUTR , SUTM, dan terhadap nilai Standar IEEE Std 1366-2003 di SUTR dan SUTM. Persentase gangguan terbesar terjadi pada peralatan JTM = 46% dan layang-layang = 24%, yang mengakibatkan terhentinya pasokan energi listrik kekonsumen dengan berdampak padamnya feeder 4 = 28% dan feeder 3 = 26%
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2

Ajenikoko, Ganiyu Adedayo, and Ridwan Abiola Oladepo. "Impact of System Average Interruption Duration Index Threshold on the Reliability Assessment of Electrical Power Distribution Systems." International Journal of Electrical and Electronics Research 6, no. 2 (2018): 17–31. http://dx.doi.org/10.37391/ijeer.060203.

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System Average Interruption Duration Index (SAIDI) is one of the parametric indices used for assessment of the performance of electrical power network. It is the ratio of customers’ interruption duration to the total number of customers served. SAIDI threshold is used to determine the calendar days upon which either the system design limits or operational limits are exceeded. This research paper presents the impact of SAIDI threshold on the reliability assessment of electrical power distribution system. Data were collected from ten selected feeders of Ibadan distribution system for a period of five years. The daily SAIDI, natural logarithm of SAIDI, the log-average of SAIDI and the standard derivation of the logarithm of SAIDI were used as input parameters in the development of SAIDI threshold model. The result of the research paper shows that the SAIDI threshold values fluctuate over the years with the least and highest SAIDI threshold values as 2.11596 and 4.62518 respectively which were recorded in the months of September and April. The SAIDI thresholds in the months of January, February, March, April, May and June are 3.18318, 3.32458, 4.22242, 4.62518, 2.71360 and 3.27760 respectively suggesting an indefinite pattern in the SAIDI threshold as a result of unexpected interruptions experienced by customers attached to the distribution feeders. SAIDI threshold forms a basis for power system planning and maintenance strategies.
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3

Rizal, Syaipul, Zulfahri Zulfahri, and Usaha Situmeang. "Studi Optimalisasi Keandalan Jaringan Distribusi 13,8 kV pada Bangko Substation PT. Chevron Pacific Indonesia (CPI)." JURNAL TEKNIK 15, no. 1 (2021): 56–65. http://dx.doi.org/10.31849/teknik.v15i1.6215.

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Analisa keandalan sistem distribusi membutuhkan informasi yang akurat untuk menilai kinerja sistem, sehingga keandalan dapat ditingkatkan dengan maksimal dan keinginan pelanggan terpenuhi. Tingkat keandalan sistem distribusi dapat diukur dari sejauh mana penyaluran tenaga listrik dapat berlangsung secara kontiniu kepada pelanggan tanpa harus terjadi pemadaman. Saat ini, perhitungan keandalan sistem distribusi pada PT. CPI masih menggunakan perhitungan konvensional, sehingga akan sangat sulit untuk membandingkan keandalan sistem distribusi PT.CPI dengan industri lainnya karena tidak menggunakan standar perhitungan yang sama. Beberapa indeks yang sudah banyak digunakan untuk menghitung kinerja keandalan sistem tenaga listrik antara lain adalah System Average Interruption Duration Index (SAIDI), System Average Interruption Frequency Index (SAIFI), dan Costumer Average Interruption Duration Index (CAIDI). Pada tugas akhir ini akan dilakukan Studi Optimalisasi indeks keandalan penyulang # 1 Gardu Induk Bangko menggunakan pendekatan historical assessment dan predictive assessment dengan metode Reliability Index Assessment (RIA). Dari studi ini diketahui bahwa pada Tahun 2019, rata-rata indeks keandalan SAIDI adalah 6.9358 hour/costumer/year, SAIFI = 2,87 interruption/costumer/year dan CAIDI = 2,4166 hour/costumer interruption. Sedangkan untuk memperbaiki indeks keandalan menggunakan metode RIA, dari 5 opsi yang ditetapkan, diperoleh sistem ke 5 dapat menghasilkan penurunan yang optimal yaitu SAIDI = 13,8829 hour/costumer/year atau turun 57,0 % jika dibanding kondisi eksisting, SAIFI = 8,6537 interruption/costumer/year atau naik 0,5 % dibanding kondisi eksisting, dan CAIDI = 1,6043 hours/costumer interruption atau turun 57,7 % dibanding kondisi eksisting.adapun perkiraan Biaya Penambahan Peralatan untuk sistem ke 5 ini sebesar RP 1,182,150,000.00
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4

Paillin, Daniel B., and Galang Pradipta. "PENGARUH PENGGUNAAN SISTEM SCADA PADA KEANDALAN JARINGAN DISTRIBUSI PT. PLN AREA MASOHI." ARIKA 12, no. 1 (2018): 41–52. http://dx.doi.org/10.30598/arika.2018.12.1.41.

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Penelitian ini bertujuan untuk mengetahui pengaruh sebelum dan sesudah penggunanan system SCADA terhadap keandalan jaringan distribusi PT. PLN Wilayah Maluku dan Maluku Utara Area Masohi. Hasil penelitian menunjukan adanya peningkatan indeks keandalan setelah terintegrasi dengan sistem Supervisory Control And Data Acquisition (SCADA) dengan parameter indeks System Average Interruption Duration Index (SAIDI) sebesar 15,04 Jam/pelanggan dan System Average Interruption Frequency Index (SAIFI) sebesar 14,92 kali/pelanggan serta penghematan sebesar Rp 35.369.361
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5

Sugianto, Sugianto, and Asri Dewi Mustikasari. "PEMASANGAN AUTOMATIC CHANGE OVER (ACO) UNTUK MENINGKATKAN KEANDALAN PADA PELANGGAN PREMIUM." Jurnal Ilmu Teknik dan Komputer 3, no. 1 (2019): 57. http://dx.doi.org/10.22441/jitkom.2020.v3.i1.008.

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ABSTRACT Energi listrik memegang peranan yang sangat dominan dalam kehidupan masyarakat sehari-hari, sehingga jika terjadi pemadaman listrik akan menimbulkan kerugian. Guna mengurangi pemadaman maka diperlukan back up sumber tegangan untuk mensupply beban. Back up sumber tegangan dipasang parallel yang bekerja secara bergantian otomatis sebelum sebelum masuk ke beban yang disebut System Spot Network. System parallel dua sumber tegangan menggunkan suatu kubikel tegangan menengah yang disebut Automatic Change Over. Untuk mengetahui keandalan sebelum dan sesudah dipasang ACO maka ditetapkan suatu indeks keandalan yaitu SAIDI (System Average Interruption Duration Index) dan SAIFI (System Average Interruption Frequency Index). Setelah dipasang ACO tidak pernah mengalami pemadaman sehingga nilai perhitungan indeks SAIFI realisasi di lapangan sebelumnya adalah 0,05 pemadaman/tahun menjadi Nol. Begitu pula dengan perhitungan SAIDI realisasi di lapangan sebelumnya adalah 0,112 jam/tahun menjadi Nol
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6

Samudra, Hery, I. G. Dyana Arjana, and I. Wayan Artha Wijaya. "Studi Peningkatan Kualitas Pelayanan Penyulang Menggunakan Load Break Switch (LBS) Three Way." Majalah Ilmiah Teknologi Elektro 15, no. 1 (2016): 48. http://dx.doi.org/10.24843/mite.2016.v15i01p09.

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Pada sistem distribusi, kualitas keandalan dapat dilihat dari lamanya pemadaman atau SAIDI (System Average Interruption Duration Index) dan seberapa sering pemadaman terjadi dalam satuan waktu atau SAIFI (System Average Interruption Frequency Index). Sebuah upaya yang telah dilakukan oleh PT. PLN (persero) Distribusi Bali AJ Bali Selatan untuk mengurangi jumlah pelanggan padam saat terjadi gangguan yaitu dengan cara pemasangan LBS Three Way. Berdasarkan hasil perhitungan kualitas keandalan pada penyulang Gunung Agung setelah pemasangan LBS Three Way yaitu SAIFI sebesar 0.989688526 dan SAIDI sebesar 5.737530618, penyulang Imam Bonjol setelah pemasangan LBS Tree Way yaitu SAIFI sebesar 0.683913253 dan SAIDI sebesar 3.908243775. Hasil analisa pengaruh pemasangan LBS Three Way terhadp pelanggan DB0133 (United Overseas Bank) yaitu pelanggan pada DB133 tidak mengalami pemadaman apabila terjadi gangguan pada penyulang Gunung Agung karena pelanggan dapat dimanuver oleh penyulang Imam Bonjol. Berdasarkan perhitungan kemampuan manuver beban pada penyulang Gunung Agung dan Imam Bonjol dapat dikatakan penyulang Gunung Agung mampu memanuver beban seksi I dan III pada penyulang Imam Bonjol, dan penyulang Imam Bonjol mampu memanuver beban seksi III, IV dan V pada penyulang Gunung Agung. DOI: 10.24843/MITE.1501.09
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7

Makruf, Abdul, Rani Ilham, Bima Sakti, Erdin Syam, Muhammad Akbar, and Y. Yudistira. "Analisis Keandalan Sistem Distribusi 20 Kv dari Gi Tengkawang Pada Penyulang T4." Emitor: Jurnal Teknik Elektro 22, no. 2 (2022): 155–60. http://dx.doi.org/10.23917/emitor.v22i2.16770.

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Abstrak-.Listrik merupakan kebutuhan pokok manusia didalam menjalankan aktivitasnya sehari-hari. PLN merupakan perusahaan milik negara yang melayani kebutuhan listrik diindonesia. Semakin banyak industri dan perusahaan serta rumah tangga yang tumbuh dan berkembang, maka dibutuhkan tenaga listrik yang handal, murah dan ekonomis. Dengan demikian kebutuhan listrik tersebut membutuhkan pengembangan kapasitas pembangkit dan saluran transmisi atau distribusinya. Jarak antara pembangkit dan konsumen sangatlah jauh, hal ini dapat memicu terjadinya gangguan pada jaringan udara terbuka, gangguan ini dapat menyebabkan arus gangguan yang akan menggangu sistem distribusi, yang berakibatkan suatu sistem tidak bisa dikatakan handal.Untuk meningkatkan nilai keandalan yaitu dengan mengurangi frekuensi terjadinya gangguan dan dilakukan pemeliharaan secara preventif guna meningkatkan keandalan dari sistem distribusi. Agar dapat melihat keandalan dari sistem distribusi diperlukan perhitungan terhadap nilai SAIDI (System Average Interruption Duration Index) dan SAIFI (System Average Interruption Frequency Index) Kata kunci: Sistem Distribusi, Keandalan, Gangguan, SAIDI, SAIFI
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8

Jurnal, Redaksi Tim. "ANALISA NILAI SAIDI SAIFI SEBAGAI INDEKS KEANDALAN PENYEDIAAN TENAGA LISTRIK PADA PENYULANG CAHAYA PT. PLN (PERSERO) AREA CIPUTAT." Energi & Kelistrikan 10, no. 1 (2019): 70–77. http://dx.doi.org/10.33322/energi.v10i1.330.

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The demand for electricity will continues to increase each time, this is because of the number of PLN’s customers will continues too to grow each year. Therefore, this is directly proportional to growing the amount of electricity that have to be streamed. With the increasing of the number of PLN’s customers, the provider (PLN) have to increase the amount of electricity supply as well. In the era of globalization, the efficiency of electrical power has always been the main issued, both from the providers and the customers. Therefore, the realibility of distribution system of electrical power will been the main issued as well. The index that showing the reliability of the distribution system of electrical power is SAIDI (System Average Interruption Duration Index) and SAIFI (System Average Interuption Frequency Index). As small as the value of the indexes, both SAIDI and SAIFI is so the more reliable the system, which means the efficiency of the distribution system is good (high efficiency). In this research will be discussed about the analysis of SAIDI and SAIFI values of Cahaya feeder, as well as how to suppress the value of SAIDI and SAIFI. Realibilty index SAIDI and SAIFI on Cahaya Feeder in the year of 2017 is 2.277 hours/costumers/year dan 2.406 time/costumers/years. That is reliable based on SPLN 59:1985 standard. Cost loss in year of 2017 due to outage on the Cahaya Feeder is IDR 12,794,305,-
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9

Rusyda Roslan, Nur Nabihah, NoorFatin Farhanie Mohd Fauzi, and Mohd Ikhwan Muhammad Ridzuan. "Variance reduction technique in reliability evaluation for distribution system by using sequential Monte Carlo simulation." Bulletin of Electrical Engineering and Informatics 11, no. 6 (2022): 3061–68. http://dx.doi.org/10.11591/eei.v11i6.3950.

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This paper discusses the need for variance reduction in simulations in order to reduce the time required to compute a simulation. The large and complex network is commonly evaluated using a large-scale Monte Carlo simulation. Unfortunately, due to the different sizes of the network, it takes some time to complete a simulation. However, variance reduction techniques (VRT) can help to solve the issues. The effect of VRT changes the behaviors of a simulation, particularly the time required to run the simulation. To evaluate the reliability indices, two sequential Monte Carlo (SMC) methods are used. SMC with VRT and SMC without VRT are the two options. The presence of VRT in the simulation distinguishes the two simulations. Finally, reliability indices: system average interruption frequency index (SAIFI), system average interruption duration index (SAIDI), and customer average interruption duration index (CAIDI) will be calculated at the end of the simulation to determine the efficiency for the SMC with and without VRT. Overall, the SMC with VRT is more efficient because it is more convenient and saves time than the SMC without VRT.
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10

Peter, Geno, Albert Alexander Stonier, Punit Gupta, Daniel Gavilanes, Manuel Masias Vergara, and Jong Lung sin. "Smart Fault Monitoring and Normalizing of a Power Distribution System Using IoT." Energies 15, no. 21 (2022): 8206. http://dx.doi.org/10.3390/en15218206.

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Conventional outage management practices in distribution systems are tedious and complex due to the long time taken to locate the fault. Emerging smart technologies and various cloud services offered could be utilized and integrated into the power industry to enhance the overall process, especially in the fault monitoring and normalizing fields in distribution systems. This paper introduces smart fault monitoring and normalizing technologies in distribution systems by using one of the most popular cloud service platforms, the Microsoft Azure Internet of Things (IoT) Hub, together with some of the related services. A hardware prototype was constructed based on part of a real underground distribution system network, and the fault monitoring and normalizing techniques were integrated to form a system. Such a system with IoT integration effectively reduces the power outage experienced by customers in the healthy section of the faulted feeder from approximately 1 h to less than 5 min and is able to improve the System Average Interruption Duration Index (SAIDI) and System Average Interruption Frequency Index (SAIFI) in electric utility companies significantly.
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