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All Journal EMITTER International Journal of Engineering Technology Jurnal Elementer (Elektro dan Mesin Terapan) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat Jurnal INOVTEKSeri Elektro Jurnal Abdimas Berdaya : Jurnal Pembelajaran, Pemberdayaan dan Pengabdian Masyarakat Jurnal Rekayasa elektrika TECHNOLOGIC
Endro Wahjono, Endro
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Real-Time Detection of Power Quality Disturbance Using Fast Fourier Transform and Adaptive Neuro-Fuzzy Inference System Syahrin, Ahmad Alvi; Anggriawan, Dimas Okky; Prasetyono, Eka; Sunarno, Epyk; Wahjono, Endro; Sudiharto, Indhana; Suhariningsih, Suhariningsih
Jurnal Rekayasa Elektrika Vol 20, No 1 (2024)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v20i1.33695

Abstract

Power quality disturbances cause equipment damage or financial losses. Therefore, the electric power system needs to identify and distinguish any power quality disturbances to reduce problems. This paper proposes hybrid methods combining FFT and ANFIS algorithm for detection of power quality disturbances. There are 11 types of power quality disturbances that can be detected, such as sag, swell, undervoltage, overvoltage, voltage flicker, voltage harmonic, sag + harmonic, swell + harmonic, undervoltage + harmonic, overvoltage + harmonic, and flicker + harmonic. The parameters used to detect disturbances are Vrms, Duration, THDv (Total Harmonic Distortion voltage), and Fluctuation-Count. The detection process starts by sensing voltage and calculating all the parameters, where THDv was obtained by Fast Fourier Transform. All the parameters such as Vrms, Duration, THDv, and Fluctuation-Count are processed by Adaptive Neuro-Fuzzy Inference System, and the result is the type of disturbance. Matlab simulations show that the suggested method performs outstandingly to identify 11 type of Power Quality Disturbances with 99.3% accuracy.
SISTEM PENYIMPANAN ENERGI LISTRIK BERBASIS BATERAI DARI PANEL SURYA UNTUK LISTRIK RUMAH IBADAH DI DESA CARANG WULUNG Rusli, Muhammad Rizani; Raharja, Lucky Pradigta Setiya; Nugraha, Syechu Dwitya; Adila, Ahmad Firyal; Jaya, Arman; Sutedjo, Sutedjo; Agusalim, Imam Dui; Suharyanto, Hendik Eko Hadi; Suryono, Suryono; Irianto, Irianto; Wahjono, Endro; Rakhmawati, Renny; Ferdiansyah, Indra; Murdianto, Farid Dwi; Eviningsih, Rachma Prilian
Abdimas Galuh Vol 5, No 2 (2023): September 2023
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/ag.v5i2.10440

Abstract

Dikarenakan kondisi tipografi dan bentuk wilayah yang berupa perbukitan dengan wilayah yang luas, maka di Desa Carang Wulung masih terdapat dusun yang belum ada jaringan listrik tegangan rendah dari PLN yaitu Dusun Gondang. Akibat keterbatasan tersebut, terdapat rumah ibadah (musala) di Dusun Gondang yang masih kurang diperhatikan dan termasuk dalam kategori tidak layak jika dilihat dari sisi ketersediaan listrik. Masyarakat di dusun yang mayoritas beragama Islam ini mengalami kendala penerangan saat shalat berjamaah di malam hari hingga subuh. Tidak adanya sumber listrik untuk pengeras suara juga mengakibatkan tidak dapat digunakannya pengeras suara untuk menandai masuknya waktu sholat. Berdasarkan latar belakang tersebut, maka dikembangkan sistem penyimpanan energi listrik berbasis baterai dengan menggunakan panel surya dalam kegiatan pengabdian masyarakat ini. Tahapan kegiatan pengabdian masyarakat yang dilakukan adalah melakukan survey kebutuhan pemasangan sistem instalasi panel surya dan baterai, perakitan beberapa komponen sistem, melakukan pengujian sistem skala laboratorium, pemasangan sistem yang telah dirakit dan diuji, serta melakukan sosialisasi dan pelatihan kepada warga tentang penggunaan panel surya, pengoperasian dan pemeliharaan sistem. Warga mengaku senang dengan terselenggaranya kegiatan pengabdian masyarakat ini karena dapat beribadah dengan nyaman setiap saat dengan sumber listrik yang tidak mengandalkan sumber dari PLN.
Load Identification Using Harmonic Based on Probabilistic Neural Network Anggriawan, Dimas Okky; Amsyar, Aidin; Prasetyono, Eka; Wahjono, Endro; Sudiharto, Indhana; Tjahjono, Anang
EMITTER International Journal of Engineering Technology Vol 7 No 1 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (529.473 KB) | DOI: 10.24003/emitter.v7i1.330

Abstract

Due to increase power quality which are caused by harmonic distortion it could be affected malfunction electrical equipment. Therefore, identification of harmonic loads become important attention  in the power system. According to those problems, this paper proposes a Load Identification using harmonic based on probabilistic neural network (PNN). Harmonic is obtained by experiment using prototype, which it consists of microcontroller and current sensor. Fast Fourier Transform (FFT) method to analyze of current waveform on loads become harmonic load data. PNN is used to identify the type of load. To load identification, PNN is trained to get the new weight. Testing is conducted To evaluate of the accuracy of the PNN from combination of four loads. The results demonstrate that this method has high accuracy to determine type of loads based on harmonic load
Co-Authors -, Irianto -, Suryono -, Sutedjo Agusalim, Imam Dui Ahmad Firyal Adila Akbar, Bagus Alfaridzi Akbar Alvi, Vania Kurnia Amsyar, Aidin Amsyar, Aidin Anang Budikarso, Anang Anang Tjahjono, Anang Arman Jaya Bahtiar, Ade Candra Bahtiar Dimas Okky Anggriawan Dui Agusalim, Imam Dwi Murdianto, Farid Dwi Murdianto Eka Prasetyono, Eka Eko Hadi Suharyanto, Hendik Epyk Sunarno Era Purwanto Farid Dwi Murdianto Ferdiansyah, Indra Indhana Sudiharto Irianto Irianto Lucky Pradigta Setiya Raharja Luki Septya Mahendra Muna, M. Faza Zidnal Nafi, Nasrul Annafi Nugraha, Syechu Dwitya Prilian Eviningsih, Rachma Qudsi, Ony Asrarul Rachma Prilian Eviningsih, Rachma Prilian Rakhmawati, Renny Rizqi, Afifuddin Rochmanu, Ade Rusli, Muhammad Rizani Sasetyo, Muhammad Yudha Septi Yanaratri, Diah Setiya Raharja, Lucky Pradigta Suhariningsih Suharyanto, Hendik Eko Hadi Suryono Suryono Suryono Sutedjo Sutedjo Syahrin, Ahmad Alvi