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DESIGN POWER SYSTEM STABILIZER MENGGUNAKAN FUZZY LOGIC Ivo Salvador Soares Miranda; I Made Mataram; I Nyoman Setiawan
Jurnal SPEKTRUM Vol 1 No 1 (2014): Jurnal SPEKTRUM
Publisher : Program Studi Teknik Elektro UNUD

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1664.095 KB)

Abstract

Stabiltas merupakan kemampuan sistem untuk menjaga kondisi operasi seimbang dan kembali kekondisi operasi normal ketika terjadi gangguan. Penerapan power system stabilizer pada sistem tenaga mampu memberikan sinyal respon yang cepat atas berbagai kondisi gangguan dan mengupayakan tidak meluasnya jangkauan gangguan. Dalam mendesign power system stabilizer menggunakan robust fuzzy logic, menggunakan satu sinyal input yaitu kecepatan deviasi rotor. Hasil simulasinya dibandingkan dengan metode fuzzy logic dan kovensional. Studi simulasi menunjukan, design power system stabilizer menggunakan robust fuzzy logic memiliki nilai sinyal peak time dan settling time relatif kecil dibandingkan dengan metode fuzzy logic dan konvensional.
PERBANDINGAN KOMBINASI FUNGSI PELATIHAN JARINGAN SYARAF TIRUAN BACKPROPAGATION PADA PERAMALAN BEBAN Gede Teguh Pradnyana Yoga; Gede Dyana Arjana; I Made Mataram
Jurnal SPEKTRUM Vol 7 No 1 (2020): Jurnal SPEKTRUM
Publisher : Program Studi Teknik Elektro UNUD

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (301.87 KB) | DOI: 10.24843/SPEKTRUM.2020.v07.i01.p6

Abstract

Electricity system planning is very important for electricity providers (PLN). One of them is electricity load forecasting. Backpropagation artificial neural network is one of the best methods used in electricity load forecasting because it can give high accuracy values. In application, backpropagation neural networks often provide poor convergence speed values during the training process. Therefore, it is necessary to do various combinations of training functions to accelerate the convergence of network training. In this study, a backpropagation neural network model was developed with a combination of gradient descent training functions (traingdm, traingda, traingdx). The architecture of this network model uses 24 inputs, 1 hidden layer consisting of 16 neurons and 1 output. This model uses peak load data from Pemecutan Kelod Substation and the number of kWh sold in the South Bali area as an input variable. The results show that the best model of the neural network is using the traingdx training function. In this model, the MSE training is 1.03x10-8 and with a training convergence speed is 4 seconds and MAPE testing is 6.24% with a network accuracy is 93.75%.
ANALISIS BEBAN TAKSEIMBANG TERHADAP RUGI-RUGI DAYA DAN EFISIENSI TRANSFORMATOR KL0005 JARINGAN DISTRIBUSI SEKUNDER PADA PENYULANG KLUNGKUNG I Putu Gede Kartika; I Ketut Wijaya; I Made Mataram
Jurnal SPEKTRUM Vol 5 No 2 (2018): Jurnal SPEKTRUM
Publisher : Program Studi Teknik Elektro UNUD

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (393.349 KB) | DOI: 10.24843/SPEKTRUM.2018.v05.i02.p40

Abstract

Load imbalance will always occur in low voltage network systems (JTR), this is due to the uneven use of one phase load on customers coming from household elektrical appliances. The uneven use of loads will cause power losses in the network and drop in voltage. Load equalization on the network is one way to reduce power losses and voltage drop. This research was conducted by analyzing power losses and unbalanced load voltage drop and balanced load on the KL0005 transformer secondary distribution network on the Klungkung Feeder. Based on the result of the analysis, the power losses in the unbalanced load state obtained a result of 3.029 kW and the voltage drop in phase R was 6,1%, phase S was 3,5% and phase T was 0%, while the result of the power loss analysis balanced load obtained 2,9 kW and voltage drop in phase R is 2,6%, phasa S is 1,3% and phase T is 3% with difference in balanced load efficiency and unbalance load of 0,1%.
ANALISIS KOORDINASI RELAY ARUS LEBIH (OCR) DAN RECLOSER PADA SISTEM EKSISTING PENYULANG BUKIT JATI Wayan Wijana; I Ketut Wijaya; I Made Mataram
Jurnal SPEKTRUM Vol 5 No 2 (2018): Jurnal SPEKTRUM
Publisher : Program Studi Teknik Elektro UNUD

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (306.493 KB) | DOI: 10.24843/SPEKTRUM.2018.v05.i02.p08

Abstract

Protection systems play an important role to maintain the reliability of distribution line. Over current relay (OCR) is one of the equipments used as a protection line of 20 kV distribution. Feeder of Bukit Jati is equipped over current protection relay equipment installed in Recloser of Banda and relay in the substation feeder. Based on the data of PT. PLN (Persero) APD Bali, there are 5 time-short circuit disorders which one of them tripped the Bukit Jati feeder. Problems over current relay coordination failures can be overcome by analyzing the coordination of protection systems in the feeder of Bukit Jati. The analysis was done by recalculating the over current relay setting and create the coordination curve of the existing setting and compared it with the coordination curve setting according to the calculation result. The results of the calculation of instant recloser recycling settings obtained by 1.246 A with time multiple setting (Tms) of 0.11 while the value of the instant current setting of the feeder of 2.992 A with Tms of 0.38. Based on the simulation result using ETAP program, it is known that over current relay coordination has worked according to the protection zone when the noise occurrence behind the recloser bus did not result in a trip feeder.
ANALISIS DESAIN DAN PERHITUNGAN LAMPU PENERANGAN JALAN BERBASIS KENYAMANAN DAN KEAMANAN I Ketut Wijaya; I Made Mataram
Jurnal SPEKTRUM Vol 7 No 4 (2020): Jurnal SPEKTRUM
Publisher : Program Studi Teknik Elektro UNUD

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (500.845 KB) | DOI: 10.24843/SPEKTRUM.2020.v07.i04.p4

Abstract

Street lighting is installed for the benefit of the community to help build a creativeeconomy. Street lights in the government's effort to create creativity help the family economy.The method used is counting the number of lights used on the road with a distance of 1500meters and giving road users a questionnaire of comfort and safety. Street lighting is analyzedin an egonomic way to achieve effective, comfortable, safe, healthy and efficient work. Theresults obtained are the light intensity of 12.799 Lux (fulfilling SNI-2008) and the comfort andsafety of 11.067 and 10,300 likes after improving conditions.
PERAMALAN BEBAN JANGKA PENDEK PADA HARI LIBUR DI BALI MENGGUNAKAN METODE GENERALIZED REGRESSION NEURAL NETWORK (GRNN) Juniar Doan Wihardono; Agus Dharma; I Made Mataram
Jurnal SPEKTRUM Vol 3 No 2 (2016): Jurnal SPEKTRUM
Publisher : Program Studi Teknik Elektro UNUD

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (138.185 KB)

Abstract

Peramalan beban merupakan suatu kegiatan untuk memperkirakan kondisi beban pada hari yang akan datang. Kondisi beban pada saat hari libur merupakan suatu fenomena yang sangat menarik untuk diketahui. Fenomena ini terjadi di Bali yaitu pada saat hari Raya Nyepi. Karena, kondisi beban pada hari Raya Nyepi akan mengalami penurunan yang sangat drastis. Kondisi tersebut perlu diketahui agar operasi sistem tenaga listrik dapat berjalan secara optimal. Metode peramalan beban pada penelitian ini menggunakan metode Generalized Regression Neural Nework (GRNN) yang dibandingkan dengan metode Radial Basis Function Neural Network (RBFNN). Data pada proses peramalan menggunakan data beban puncak harian pada hari libur di Bali antara tahun 2010 sampai 2014. Pemilihan data difokuskan pada data beban puncak pada 5 hari sebelum hari libur (h-4) sampai hari libur (h). Metode GRNN menghasilkan Mean Square Error (MSE) sebesar 0.020089 dan Mean Absolute Percentage Error (MAPE) sebesar 2.01%. sedangkan metode RBFNN menghasilkan MSE sebesar 0.022757 dan MAPE sebesar 2,28%.
OPTIMASI PENEMPATAN DAN KAPASITAS KAPASITOR UNTUK MEMINIMALKAN SUSUT DAYA PADA PENYULANG TABANAN DENGAN MENGGUNAKAN METODE ANT COLONY OPTIMIZATION (ACO) Fadil Arialdi; Rukmi Sari Hartati; I Made Mataram
Jurnal SPEKTRUM Vol 6 No 4 (2019): Jurnal SPEKTRUM
Publisher : Program Studi Teknik Elektro UNUD

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (268.048 KB) | DOI: 10.24843/SPEKTRUM.2019.v06.i04.p1

Abstract

Electricity is one of the needs of society that must be met, because electricity is very instrumental in helping everyday life, such as lighting, and for the electronic needs. In distributing power to consumers there is a power loss in the distribution system channel. To reduce power loss, it is necessary to install capacitors. This study aims to reduce power losses in Tabanan feeders using the Ant Colony Optimization (ACO) method with 10 attempts using MATLAB. The total power loss before the capacitor is installed is 0.421 MW (6,4%), after the analysis is obtained the placement of the capacitor located on bus 10 with a capacity of 1000 KVAR, can reduce the power loss to 0.145 MW (2,2%)
PERAMALAN BEBAN LISTRIK JANGKA PENDEK MENGGUNAKAN METODE ADAPTIVE NEURO FUZZY INFERENCE SYSTEM (ANFIS) DI GARDU INDUK NUSA DUA BALI I Made Satriawan; I Made Mataram; A. A. Ngurah Amrita
Jurnal SPEKTRUM Vol 7 No 1 (2020): Jurnal SPEKTRUM
Publisher : Program Studi Teknik Elektro UNUD

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (396.46 KB) | DOI: 10.24843/SPEKTRUM.2020.v07.i01.p12

Abstract

Electric load in Nusa Dua Bali has increased from 2013-2017 by an average of 11.83%. The increase in electric load requires the electrical energy service provider to be able to adjust the electricity demand and be able to increase its reliability, The effort that can be done is to predict the electric load. Electric load forecasting can be done by various methods, ANFISo (Adaptiveo Neuroo Fuzzyo Inferenceo Systemo) is one method that is often used in forecasting electrical loads. ANFIS is able to explain the reasoning process and do data learning. The data used are the electric load, temperature, humidity and time, the data was chosen because changes in temperature and humidity affect people's habitual patterns in using air conditioners (electric load patterns). The electric load pattern is trained 100 times using ANFIS with the type of membership function is trimf, and [3 3 3 3] is the number of membership function. The indicator to determining the accuracy of the electrical load forecasting pattern results with the real electric load pattern used the MAPE (Mean Absolute Percentage Error) value, which the MAPE standard value that good is less than 10%. The test results from this study produced a MAPE value of 6.98%.
STUDI ANALISIS GOVERNOR SEBAGAI LOAD FREQUENCY CONTROL PADA PLTG MENGGUNAKAN FUZZY LOGIC CONTROLLER Gusti Made Ngurah Christy Aryanata; I Nengah Suweden; I Made Mataram
Jurnal Teknologi Elektro Vol 17 No 1 (2018): (Januari - April) Majalah Ilmiah Teknologi Elektro
Publisher : Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (756.455 KB) | DOI: 10.24843/MITE.2018.v17i01.P15

Abstract

Sistem tenaga listrik yang baik merupakan suatu sistem yang dapat melayani beban secara berkelanjutan serta tegangan dan frekuensinya stabil. Perubahan frekuensi terjadi disebabkan oleh permintaan beban yang berubah-ubah dari waktu ke waktu. Pengaturan frekuensi pada sistem pambangkit PLTG tergantung pada pengisisan daya aktif dalam sistem. Pengaturan daya aktif ini dilakukan dengan mengatur besarnya kopel penggerak generator. Pengaturan frekuensi dilakukan dengan menambah dan mengurangi jumlah energi primer (bahan bakar) dan dilakukan pada governor. Simulasi dalam studi analisis governor sebagai load frequency control pada PLTG menggunakan fuzzy logic controller dilakukan dengan memberikan empat jenis pembebaban yaitu sebesar 0,1 pu, 0,2pu, 0,3 pu dan 0,4 pu. Simulasi dilakukan untuk membandingkan output respon frekuensi dinamik dan waktu kestabilan yang dihasilkan menggunakan fuzzy logic controller dengan PI controller. Berdasarkan hasil analisis perbandingan yang dilakukan membuktikan bahwa governor sebagai load frequency control menggunakan fuzzy logic control lebih baik dibandingkan dengan menggunakan PI kontroller. Hal ini dapat dilihat dari output respon frekuensi dan waktu kestabilannya.
Identifikasi Jenis Gangguan pada Jaringan Transmisi Menggunakan Metode Jaring Syaraf Tiruan I Made Widiarsana; I Made Mataram; Yanu Prapto Sudarmojo
Jurnal Teknologi Elektro Vol 17 No 1 (2018): (Januari - April) Majalah Ilmiah Teknologi Elektro
Publisher : Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1311.32 KB) | DOI: 10.24843/MITE.2018.v17i01.P01

Abstract

Pada jaringan transmisi sering terjadi berbagai macam jenis gangguan, antara lain gangguan hubung singkat satu phasa ke tanah, gangguan hubung singkat phasa ke phasa, gangguan antar phasa ke tanah dan gangguan simetris. Pendeteksian terhadap gangguan tersebut dapat dilakukan dengan metode jaring syaraf tiruan. Jaring syaraf tiruan terdiri dari sejumlah elemen penghitung tak linier yang masing-masing dihubungkan secara paralel melalui suatu pembobot. Proses training pada jaring syaraf tiruan ini terdiri dari proses pelatihan terhadap gangguan hubung singkat satu phasa ke tanah, gangguan hubung singkat phasa dengan phasa, gangguan hubung singkat antar phasa dengan tanah, dan gangguan simetris. Proses pelatihan pada jaringan transmisi ini menggunakan konfigurasi 6 data intput, 10 hidden layer, 6 data target, dan 6 output (6-10-6-6). Hasil pelatihan menunjukkan bahwa nilai arus dan tegangan gangguan untuk semua jenis gangguan pada jaringan transmisi berhasil di bangkitkan, dimana output berupa nilai tegangan dan arus dari proses pelatihan akan disimpan dan dijadikan sebagai refrensi untuk menentukan jenis gangguan hubung singkat yang terjadi pada jaringan transmisi. Data hasil simulasi jaringan transmisi dapat dikatakan normal saat mendekati nilai output atau sebaliknya ketika jaringan transmisi mengalami gangguan hubung singkat. [TURNITIN CHECK 75 19042017]