Articles
<![CDATA[Analisis Kurva Magnetisasi dan Karakteristik Inrush Current Akibat Pengaruh Cara Pemotongan Inti Transformator ]]>
<![CDATA[Negara, I Made Yulistya]]>;
<![CDATA[Fahmi, Daniar]]>;
<![CDATA[Pamuji, Feby Agung]]>;
<![CDATA[Ksatria, Arief Budi]]>
<![CDATA[ JAVA Journal of Electrical and Electronics Engineering Vol 13, No 1 (2015) ]]>
Publisher : <![CDATA[JAVA Journal of Electrical and Electronics Engineering ]]>
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<![CDATA[Telah banyak dilakukan studi mengenai fenomena inrush current. Inrush current merupakan fenomena yang terjadi pada saat transformator pertama kali diberikan sumber tegangan. Inrush current dapat dianalisa menggunakan kurva magnetisasi pada inti transformator. Pada studi ini, dilakukan simulasi menggunakan perangkat lunak untuk mengetahui pengaruh cara pemotongan inti transformator terhadap kurva magnetisasi. Sedangkan perhitungan matematis dilakukan untuk mendapatkan nilai puncak dari inrush current]]>
<![CDATA[Peramalan Irradiance Cahaya Matahari pada Sel Surya untuk Memenuhi Kebutuhan Energi Listrik dengan Metode Support Vector Regression (SVR) ]]>
<![CDATA[Arumsari, Nurvita]]>;
<![CDATA[Pamuji, Feby Agung]]>
<![CDATA[ JURNAL NASIONAL TEKNIK ELEKTRO Vol 6, No 1: Maret 2017 ]]>
Publisher : <![CDATA[Jurusan Teknik Elektro Universitas Andalas ]]>
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DOI: 10.25077/jnte.v6n1.367.2017
<![CDATA[This paper suggests the use of support vector regression (SVR) method for forecasting irradiance of sunlight on solar cells so that the energy produced by the solar cells can be predicted to meet electricity needs. This prediction is very important because to provide electrical energy that is sustainable and has a good reliability which has the constant frequency and constant voltage. From the simulation results can be seen that the SVR method has not a fairly good prediction results. So that, the approximate energy of solar cell that can be transfered to meet the electricity needs of the next month still not accurate with this method. Future research will be tried SVR hybrid time series method.Keywords : Electrical Energy, Irradiance,Support vector regression (SVR).Abstrak— Pada tulisan ini digunakan metode Support Vector Regression (SVR) untuk peramalan irradiance cahaya matahari pada sel surya sehingga besar energi yang dihasilkan sel surya bisa diprediksi untuk memenuhi kebutuhan energi listrik. Prediksi ini sangat penting dikarena untuk menyediakan energi listrik yang berkelanjutan dan mempunyai keandalan yang baik yaitu mempunyai frekuensi konstan dan tegangan konstan. Dari hasil simulasi dapat dilihat bahwa metode SVR mempunyai hasil prediksi yang masih rendah. Sehingga perkiraan energi solar cell yang dapat dikirim untuk memenuhi kebutuhan listrik satu bulan ke depan masih belum cukup akurat dengan menggunakan metode ini. Pada penelitian mendatang, akan dicoba penggunaan metode SVR berbasis time series.Kata Kunci : Energi listrik, Irradiance, Support Vector Regression (SVR).]]>
<![CDATA[Desain Kontrol Multi – Input DC–DC Converter Sistem Hibrid Turbin Angin dan Sel Surya Menggunakan Kontrol Fuzzy Logic untuk Tegangan Rendah ]]>
<![CDATA[Pamuji, Feby Agung]]>;
<![CDATA[Dibyo, Soe]]>
<![CDATA[ JURNAL NASIONAL TEKNIK ELEKTRO Vol 4, No 2: September 2015 ]]>
Publisher : <![CDATA[Jurusan Teknik Elektro Universitas Andalas ]]>
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DOI: 10.25077/jnte.v4n2.165.2015
<![CDATA[this paper describes a hybrid system that consist of  Wind Turbines and Photovoltaic to supply electricity continuously for  load. Output of Wind Turbines and Photovoltaic is controlled in order to generate maximum power. Multiple-input dc-dc converters is used to control power flow in order to have MPP (Maximum Power Point). Converter control using Fuzzy logic controller to control the output in order to be obtained MPP (Maximum Power Point) from Wind Turbines and Photovoltaic, so the efficiency of wind turbines and photovoltaic can be improved.Keywords : Maximum Power Point, Hybrid System, Fuzzy logic controllerAbstrak—Dalam makalah ini diuraikan sistem hibrid yang menggabungkan Turbin Angin dan Photovoltaic untuk memasok listrik terus-menerus pada beban. Output dari Turbin Angin dan Photovoltaic diatur agar menghasilkan daya yang maksimum. Konverter multiple-input buck-boost dc-dc digunakan untuk mengatur aliran daya agar didapatkan MPP(Maximum Power Point). Kontrol konverter menggunakan Fuzzy Logic controller untuk mengkontrol output sehingga didapat MPP(Maximum Power Point) dari Turbin Angin dan Photovoltaic, sehingga effisiensi dari Turbin Angin dan Photovoltaic dapat ditingkatkan.Kata Kunci : Maximum Power Point, system hibrid, Fuzzy Logic controller ]]>
<![CDATA[Perancangan dan Simulasi Full Bridge Inverter Lima Tingkat dengan Dual Buck Converter Terhubung Jaringan Satu Fasa ]]>
<![CDATA[Zamratul Fuadi]]>;
<![CDATA[Mochamad Ashari]]>;
<![CDATA[Feby Agung Pamuji]]>
<![CDATA[ Jurnal Teknik ITS Vol 3, No 1 (2014) ]]>
Publisher : <![CDATA[Direktorat Riset dan Pengabdian Masyarakat (DRPM), ITS ]]>
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DOI: 10.12962/j23373539.v3i1.5402
<![CDATA[Inverter merupakan perangkat elektronika daya yang berfungsi mengonversi sumber searah menjadi bolak-balik. Full bridge inverter adalah satu jenisnya yang mampu menghasilkan tegangan tiga tingkat jika menggunakan teknik modulasi unipolar. Penambahan sirkuit dual buck converter pada full bridge inverter mampu menghasilkan tegangan dalam lima tingkat. Dua saklar pada rangkaian dual buck converter switching pada frekuensi tinggi 20 kHz, sedangkan empat saklar pada full bridge inverter switching pada frekuensi rendah 50 Hz. Teknik modulasi in phase disposition PWM (PDPWM) digunakan untuk mengatur penyalaan saklar dual buck converter. Keluaran inverter lima tingkat dibandingkan dengan tiga tingkat. Total harmonic distortion tegangan (THDV) dan arus (THDi) inverter lima tingkat bernilai 23.2281 % dan 23.0975 %, sedangkan inverter tiga tingkat sebesar 51.9302 % dan52.2458 %. Ketika daya 1004.08 watt disumbangkan ke jala-jala, inverter lima tingkat menghasilkan power factor senilai 0.99 dan THDi 4.1 %. Pada sumbangan daya yang sama, inverter tiga tingkat menghasilkan power factor sebesar 0.919 dan THDi bernilai 45.64 %.]]>
<![CDATA[Studi Kelayakan Pemasangan PLTS 80 KW Pada Sistem Kelistrikan PT. Indonesia Kendaraan Terminal ]]>
<![CDATA[Pius Aditya Kurnia Ray]]>;
<![CDATA[Rony Seto Wibowo]]>;
<![CDATA[Feby Agung Pamuji]]>
<![CDATA[ Jurnal Teknik ITS Vol 10, No 1 (2021) ]]>
Publisher : <![CDATA[Direktorat Riset dan Pengabdian Masyarakat (DRPM), ITS ]]>
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DOI: 10.12962/j23373539.v10i1.59320
<![CDATA[PLTS sebagai salah satu pembangkit listrik terdistribusi adalah jenis pembangkit yang paling efisien untuk di terapkan pada lahan industri. Banyak industri menengah hingga besar di Indonesia yang tertarik untuk mulai menerapkan PLTS pada lahan usaha mereka. PT. Indonesia Kendaraan Terminal menjadi salah satu pelaku industri besar yang tertarik untuk menerapkan PLTS pada jaringan listrik mereka. Namun sebelum menjalankan menerapkan hal tersebut harus dilakukan analisa terlebih dahulu terhadap kelayakan investasinya. Pada tugas akhir ini akan dianaliasa alternatif-alternatif investasi, untuk mendapatkan alternatif investasi seperti apa yang paling cocok dan paling menguntungkan dalam penerapan rencana ini. Oleh karena itu analisa kelayakan ekonomi teknik perlu dilakukan. Pada penelitian ini penulis merencakan penggunaan 195 buah panel surya untuk diterapkan, dengan energi yang dihasilkan 89.83 MWh per tahun dan penghematan sebesar Rp 110.051.317,00. Metode ekonomi Teknik diterapkan untuk mendapatkan kelayakan dari investasi ini. Pada analisa ekonomi yang dilakukan didapatkan alternatif investasi terbaik dengan nilai NPV Rp 81.346.406,00, nilai IRR sebesar 0,54%. Sehingga proyek ini layak untuk dijalankan.]]>
<![CDATA[Desain Kontrol Multi – Input DC–DC Converter Sistem Hibrid Turbin Angin dan Sel Surya Menggunakan Kontrol Fuzzy Logic untuk Tegangan Rendah ]]>
<![CDATA[Feby Agung Pamuji]]>;
<![CDATA[Soe Dibyo]]>
<![CDATA[ JURNAL NASIONAL TEKNIK ELEKTRO Vol 4 No 2: September 2015 ]]>
Publisher : <![CDATA[Jurusan Teknik Elektro Universitas Andalas ]]>
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DOI: 10.25077/jnte.v4n2.165.2015
<![CDATA[this paper describes a hybrid system that consist of Wind Turbines and Photovoltaic to supply electricity continuously for load. Output of Wind Turbines and Photovoltaic is controlled in order to generate maximum power. Multiple-input dc-dc converters is used to control power flow in order to have MPP (Maximum Power Point). Converter control using Fuzzy logic controller to control the output in order to be obtained MPP (Maximum Power Point) from Wind Turbines and Photovoltaic, so the efficiency of wind turbines and photovoltaic can be improved.Keywords : Maximum Power Point, Hybrid System, Fuzzy logic controllerAbstrak—Dalam makalah ini diuraikan sistem hibrid yang menggabungkan Turbin Angin dan Photovoltaic untuk memasok listrik terus-menerus pada beban. Output dari Turbin Angin dan Photovoltaic diatur agar menghasilkan daya yang maksimum. Konverter multiple-input buck-boost dc-dc digunakan untuk mengatur aliran daya agar didapatkan MPP(Maximum Power Point). Kontrol konverter menggunakan Fuzzy Logic controller untuk mengkontrol output sehingga didapat MPP(Maximum Power Point) dari Turbin Angin dan Photovoltaic, sehingga effisiensi dari Turbin Angin dan Photovoltaic dapat ditingkatkan.Kata Kunci : Maximum Power Point, system hibrid, Fuzzy Logic controller ]]>
<![CDATA[Peramalan Irradiance Cahaya Matahari pada Sel Surya untuk Memenuhi Kebutuhan Energi Listrik dengan Metode Support Vector Regression (SVR) ]]>
<![CDATA[Nurvita Arumsari]]>;
<![CDATA[Feby Agung Pamuji]]>
<![CDATA[ JURNAL NASIONAL TEKNIK ELEKTRO Vol 6, No 1: Maret 2017 ]]>
Publisher : <![CDATA[Jurusan Teknik Elektro Universitas Andalas ]]>
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DOI: 10.25077/jnte.v6n1.367.2017
<![CDATA[This paper suggests the use of support vector regression (SVR) method for forecasting irradiance of sunlight on solar cells so that the energy produced by the solar cells can be predicted to meet electricity needs. This prediction is very important because to provide electrical energy that is sustainable and has a good reliability which has the constant frequency and constant voltage. From the simulation results can be seen that the SVR method has not a fairly good prediction results. So that, the approximate energy of solar cell that can be transfered to meet the electricity needs of the next month still not accurate with this method. Future research will be tried SVR hybrid time series method.Keywords : Electrical Energy, Irradiance,Support vector regression (SVR).Abstrak— Pada tulisan ini digunakan metode Support Vector Regression (SVR) untuk peramalan irradiance cahaya matahari pada sel surya sehingga besar energi yang dihasilkan sel surya bisa diprediksi untuk memenuhi kebutuhan energi listrik. Prediksi ini sangat penting dikarena untuk menyediakan energi listrik yang berkelanjutan dan mempunyai keandalan yang baik yaitu mempunyai frekuensi konstan dan tegangan konstan. Dari hasil simulasi dapat dilihat bahwa metode SVR mempunyai hasil prediksi yang masih rendah. Sehingga perkiraan energi solar cell yang dapat dikirim untuk memenuhi kebutuhan listrik satu bulan ke depan masih belum cukup akurat dengan menggunakan metode ini. Pada penelitian mendatang, akan dicoba penggunaan metode SVR berbasis time series.Kata Kunci : Energi listrik, Irradiance, Support Vector Regression (SVR).]]>
<![CDATA[A Robust Frequency Control Approach in PV-Diesel Hybrid Power System ]]>
<![CDATA[Heri Suryoatmojo]]>;
<![CDATA[Adi Kurniawan]]>;
<![CDATA[Feby Agung Pamuji]]>;
<![CDATA[Nursalim ST MT]]>;
<![CDATA[IGP Suta Wijaya]]>;
<![CDATA[Herbert Innah]]>
<![CDATA[ IPTEK Journal of Proceedings Series Vol 1, No 1 (2014): International Seminar on Applied Technology, Science, and Arts (APTECS) 2013 ]]>
Publisher : <![CDATA[Institut Teknologi Sepuluh Nopember ]]>
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DOI: 10.12962/j23546026.y2014i1.208
<![CDATA[Hybrid power generation system such as photovoltaic (PV)-diesel is one of the solution to reduce operational cost of the conventional diesel generation system. However, fluctuation of PV power due to uncertainty in weather condition may generate an unstable frequency of system. Further, it may reduce the reliability of the power utility, especially when the penetration of PV power is large. Therefore, a frequency control approach that involving PV with battery supervised by neural network algorithm is proposed to generate a stable system frequency. This method can reduce the frequency deviation without smoothing PV output power. The PV panels can generate maximum power according to the weather condition and frequency deviation. The PV output power and battery output power is controlled by neural network algorithm control. The neural network algorithm control is considering frequency deviation, average insolation and change of insolation as input. The proposed method is compared with similar system but without the existence of battery as energy storage system. The simulation results show that the proposed method can generate small frequency deviation compared with system without battery.]]>
<![CDATA[Predictive Duty Cycle of Maximum Power Point Tracking Based on Artificial Neural Network and Bootstrap Method for Hybrid Photovoltaic/ Wind Turbine System Considering Limitation Voltage of Grid ]]>
<![CDATA[Feby Agung Pamuji]]>;
<![CDATA[Nurvita Arumsari]]>;
<![CDATA[Mochamad Ashari]]>;
<![CDATA[Hery Suryoatmojo]]>;
<![CDATA[Soedibyo Soedibyo]]>
<![CDATA[ JAREE (Journal on Advanced Research in Electrical Engineering) Vol 4, No 2 (2020): October ]]>
Publisher : <![CDATA[Department of Electrical Engineering ITS and FORTEI ]]>
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DOI: 10.12962/j25796216.v4.i2.119
<![CDATA[In this paper, we propose a new control-based the neural network and bootstrap method to get the predictive duty cycle for the maximum power point of hybrid Photovoltaic (PV) and Wind Turbine generator system (WTG) connected to 380 V grid. The neural network is designed to be controller by learning the data control of multi-input DC/ DC converter. The artificial neural network (ANN) needs many data for training then the ANN can give the predictive duty cycle to multi input DC/ DC converter. To get much data, we can use the bootstrap method to generate data from the real data. From Photovoltaic characteristic, we can get 344 real data after the data are made by bootstrap method we can get 8000 data. The 8000 data of PV can be used for training artificial neural network (ANN) of PV system. From wind turbine characteristic we can get 348 real data after the data are made by bootstrap method we can get 6000 data. The 6000 data of WT can be used for training artificial neural network of WT system. This new control has two responsibilities, are to shift the voltage of PV and WTG to optimum condition and to maintain the stability of grid system. From the simulation results those can be seen that the power of hybrid PV / WTG system using MPPT controller is in maximum power and has constant voltage and constant frequency of grid system.Keywords: bootstrap, maximum power tracking, neural network, stability.]]>
<![CDATA[Pre-energize Analysis on 3 Phase Transformer by Considering Each Phase Flux ]]>
<![CDATA[Hadwim Septiawan]]>;
<![CDATA[I Made Yulistya Negara]]>;
<![CDATA[Feby Agung Pamuji]]>
<![CDATA[ JAREE (Journal on Advanced Research in Electrical Engineering) Vol 3, No 2 (2019): October ]]>
Publisher : <![CDATA[Department of Electrical Engineering ITS and FORTEI ]]>
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DOI: 10.12962/j25796216.v3.i2.90
<![CDATA[Inrush current is a transient phenomenon that occurs when a transformer is first energized to a voltage source at no-load conditions. It causes a very high inrush current. Inrush currents can adversely affect the electric power system and can cause improper work of a relay protection errors. The purpose of this study is to determine the amount of inrush current and minimize the amount of inrush current by using the pre-fluxing method. In this study, a test was carried out using a 3-kVA core type 3 phase transformer. This test is done by giving DC flux before the transformer is connected to the voltage source, then the three transformer phases are energized simultaneously at a certain voltage angle so that the inrush current may could be minimized. The test results show that the transformer that is given a DC flux always has a relatively small inrush current. In this test the inrush current is reduced to a minimum value at an ignition angle of 90 degrees with an inrush current value of 0.74 A in phase R, 3.41 A in phase S, and 3.80 A in phase T.Keywords: flux, inrush current, transformer, transient.]]>
