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All Journal Rotasi Jurnal EECCIS Jurnal Teknologi Elektro ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika INVOTEK: Jurnal Inovasi Vokasional dan Teknologi Budimas : Jurnal Pengabdian Masyarakat Jurnal INOVTEKSeri Elektro Emitor: Jurnal Teknik Elektro Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics
Rachma Prilian Eviningsih, Rachma Prilian
Jurusan Teknik Elektro Institut Teknologi Sepuluh Nopember
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Design and Implementation MPPT Improved Whale Optimization Algorithm to Overcome Partial Shading Condition on Solar Panel Habibi, Muhammad Nizar; Prakoso, Rifqi Noviantono; Adila, Ahmad Firyal; Efendi, Moh. Zaenal; Windarko, Novie Ayub; Eviningsih, Rachma Prilian
invotek Vol 24 No 2 (2024): INVOTEK: Jurnal Inovasi Vokasional dan Teknologi
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/invotek.v24i2.1219

Abstract

Solar energy is a type of renewable energy whose capacity is tremendous and fast in increasing its capacity so that it can be used for energy sustainability in the future. Solar panels are the only devices that can be used to utilize solar energy. Maximum Power Point Tracking (MPPT) is a method to maximize the power generated by solar panels. However, the problem with solar panels is the condition of partial shading, this occurs due to something blocking the rate of solar irradiation to the solar panel. The result is that there are 2 or more maximum power points from solar panels, the highest power is the Global Maximum Power Point (GMPP) and the other is the Local Maximum Power Point (LMPP). This partial shading condition cannot use conventional MPPT methods due to the complexity of finding GMPP. So, MPPT optimization method is needed, one of which is the Improved Whale Optimization Algorithm (IWOA). IWOA is a development of the Whale Optimization Algorithm (WOA) by applying the Sine-Tent-Cosine Map for the first time the algorithm works to be more effective in the initialization process of the algorithm population and can ensure a more uniform distribution of population distribution throughout the search space. IWOA will be applied to the MPPT system to achieve the GMPP of the solar panel under partial shading conditions.
Electric Energy Measurement System For Energy Management Household With Convolutional Neural Network Method Rozali, devan; Eviningsih, Rachma Prilian; Ayub Windarko , Novie
Emitor: Jurnal Teknik Elektro Vol 25, No 2: July 2025
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/emitor.v25i2.10357

Abstract

Abstract- Short Term Load Forecasting (STLF) is becoming very important as the use of distributed energy sources, renewable energy, and demand side management increases. Electrical energy is one of the most widely used energy, especially in households. To avoid excessive electricity consumption, we propose a household electricity consumption forecasting system using Convolutional Neural Network (CNN) method. The input of CNN is the power of several household loads measured for one week at 10-minute intervals. This data is used to train the model and predict household electricity consumption for the next week. Forecasting results for a week show a difference in consumption of 3.623 kWh, while with the load management method the difference is 3.439 kWh. With an electricity tariff of Rp1.352/kWh, the estimated electricity cost for the following week is Rp4.892.00, and with load management, the cost drops to about Rp4.649.52 (5% savings).The testing method is done by comparing the forecasting results and actual data for one week. The results show an average difference of only 1.57W with an average error of 0.07%. The CNN method is also compared with the Long Short-Term Memory (LSTM) method. As a result, CNN has better performance with CNN RMSE value of 3.688, CNN management of 3.354, while LSTM RMSE of 12.603, and LSTM management of 13.132. CNN is proven to be more accurate for household short-term electricity load forecasting..
UPS With Half-Bridge Converter Based On Type-2 Fuzzy Logic Controller Setiawan, David Benny; Efendi, Moh Zaenal; Eviningsih, Rachma Prilian
Jurnal Teknologi Elektro Vol 16, No 1 (2025)
Publisher : Electrical Engineering, Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/jte.2025.v16i1.008

Abstract

Electricity is one of the most important needs. There are many electronic devices that support and facilitate human. Electrical disturbances are an inseparable part of the existence of electrical energy and we often encounter power outages with very fast and sudden time lags. The sudden disconnection of the power source can cause various losses, one of which is damage to the electronic equipment used or the loss of important data. Losses resulting from an abrupt power source failure can be effectively managed and reduced by incorporating a UPS (Uninterruptible Power Supply) unit between the power source and electronic devices. The converter and method used in this journal is the Half-Bridge Converter with the Type 2 Fuzzy Logic Controller method which functions to control the output of the Converter to be stable. The PLN source or input will be rectified with the Rectifier and lowered by the Half-Bridge Converter which will later be used to charge the battery. The output of the Half-Bridge Converter will be controlled using the Type 2 Fuzzy Logic Controller method. When the PLN source is still there, the battery will be in a charging position, and after the PLN source is lost or extinguished, the static switch will change the load source from the PLN source to a battery source. The output from the battery will be forwarded to the inverter and directly to the load. In this journal, the results of each simulation carried out are appropriate and close to the value of the plan. From the tests that carried out with Fuzzy Type-2, the average voltage value was 13.802V with an average error value of 0.055%, which is close to the planning and the error obtained is relatively small.
Multiple Output Buck Converter (SIMO) Untuk Pengaturan Kecepatan Motor DC Penguat Terpisah Berbasis Fuzzy Logic Control Fabianto, Farhan; Suhariningsih, Suhariningsih; Eviningsih, Rachma Prilian
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 16 No. 1 (2022)
Publisher : Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v16i1.680

Abstract

Motor DC merupakan suatu perangkat yang berfungsi untuk mengubah energi listrik menjadi energi kinetik. Perangkat ini dapat disebut sebagai Motor Arus Searah dan perangkat ini memiliki 2 input tegangan yaitu kumparan jangkar dan kumparan medan, agar dapat menggerakannya. Di dalam klasifikasi Motor DC, banyak sekali jenis Motor DC yang digunakan. Pada Jurnal ini Motor DC yang digunakan adalah Motor DC Penguat Terpisah. Sesuai namanya, Motor DC Penguat Terpisah ini mempunyai dua tegangan masukan yang mempunyai sumber individu, yang mana salah satunya untuk menyuplai tegangan pada kumparan jangkar dan salah satunya untuk menyuplai tegangan pada kumparan medan Pada jurnal ini akan dibuat sebuah pemodelan SIMO Buck Converter yang mempunyai tegangan keluaran banyak yang digunakan untuk menyuplai Motor DC Penguat Terpisah dan mengatur kecepatan menggunakan pengaturan tegangan masuk pada Motor DC Penguat Terpisah. Untuk mengatur kecepatan dari Motor DC Penguat Terpisah, maka dibutuhkan pengaturan tegangan sedemikian rupa guna mencapai kecepatan yang diinginkan dengan cara mengatur Duty Cycle pada setiap keluaran pada konverter menggunakan Fuzzy Logic Control, agar pengaturan tegangan keluar dari konverter menjadi halus dan tidak menimbulkan Overshoot disaat menggunakan untuk mensuplai Motor DC Penguat Terpisah. Hasil simulasi menunjukkan bahwa sebelum adanya kontrol fuzzy Motor DC memiliki rise time sebesar 1.306s, dan untuk mencapai kondisi steady state dari 0s sebesar 1.585 sedangkan setelah adanya kontrol fuzzy Motor DC memiliki rise time sebesar 445.556ms, untuk mencapai kondisi steady state dari 0s sebesar 668.683ms, dan mempunyai overshoot sebesar 11 RPM dari setpoint yang telah ditentukan. Ketika Motor DC dengan logika fuzzy diberi gangguan pada detik 0,4s respon fuzzy sangat baik, dan Ketika dirubah setpoint menjadi 1000 RPM dan 500 RPM respon dari fuzzy sangat bagus.
Co-Authors Abdilla, M. Rafi Damas Ahmad Firyal Adila Anggara Trisna Nugraha Ayub Windarko , Novie Dimas Okky Anggriawan Efendi, M. Zaenal Efendi, Moh Zaenal Eka Prasetyono, Eka Epyk Sunarno Fabianto, Farhan Habibi, Muhammad Nizar Hartono, Helleina Rejeki Putri Indhana Sudiharto Jaya, Raihan Rafly Kusuma Lucky Pradigta Setiya Raharja Luki Septya Mahendra Mohammad Zaenal Efendi Novie Ayub Windarko NUGROHO, MOCHAMAD ARI BAGUS Nugroho, Mochammad Ari Bagus Prakoso, Rifqi Noviantono Prasetya, Farhan Dwi Rakhmawati, Renny Romadloniyah, Nur Shinta Rozali, devan Rusli, Muhammad Rizani Setiawan, David Benny Sony Junianto Suhariningsih Sutedjo Sutedjo SUYADI, ENJELS FATKHUR ROHMAN Ummah, Karunia Vio Nita Rusyatul WIDYANTO, AVIE ALIA Yahya Chusna Arif Yanaratri, Diah Septi