Article Per Year (5 Year)
p-Index From 2021 - 2026
4.842
P-Index
This Author published in this journals
All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) International Journal of Applied Power Engineering (IJAPE) Elektron Jurnal Ilmiah TELKOMNIKA (Telecommunication Computing Electronics and Control) JURNAL NASIONAL TEKNIK ELEKTRO Proceeding of the Electrical Engineering Computer Science and Informatics PROtek : Jurnal Ilmiah Teknik Elektro Indonesian Journal of Electrical Engineering and Computer Science Jurnal Surya Teknika Warta Pengabdian Andalas: Jurnal Ilmiah Pengembangan Dan Penerapan Ipteks Jurnal Amplifier: Jurnal Ilmiah Bidang Teknik Elektro dan Komputer Andalasian International Journal of Applied Science, Engineering, and Technology Andalas Journal of Electrical and Electronic Engineering Technology Jurnal Andalas: Rekayasa dan Penerapan Teknologi Emitor: Jurnal Teknik Elektro Jurnal Surya Energy
Novizon, Novizon
Jurusan Teknik Elektro Fakultas Teknik Universitas Andalas
Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Mechanical Engineering Medicine & Pharmacology Social Sciences Other

Published : 36 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 36 Documents
Search

 1   2   3   4 
Impact of Noise on Fault Classification in High-Voltage Transmission Lines Using LVQ Neural Networks Hardiyanti Mursat, Marta; Novizon, Novizon; Sulthanah, Hana
Emitor: Jurnal Teknik Elektro Vol 25, No 3: November 2025
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/emitor.v25i3.13620

Abstract

Accurate fault detection and classification in high-voltage transmission lines are essential to ensure system reliability and operational safety. However, the presence of noise and transient disturbances often degrades the accuracy of conventional protection schemes. This study investigates the impact of Gaussian noise on fault classification performance using a neural network-based framework combined with Discrete Wavelet Transform (DWT) and Fast Fourier Transform (FFT) feature extraction. Four types of faults, single line to ground, line to line, double line to ground, and three phase to ground were simulated on a 150 kV transmission system using ATPDraw under various noise levels 40 dB. Linear Discriminant Analysis (LDA) and Learning Vector Quantization (LVQ3) were employed for feature reduction and classification, respectively. The proposed model achieved a test accuracy of 98.84% under free noise conditions and 96.80% under noisy conditions. This is outperforming traditional classifiers such as Support Vector Machine (SVM) and Decision Tree (DT). Results indicate that incorporating time-frequency domain features with noise-resilient neural architectures significantly enhances classification robustness and reliability. This research contributes a novel approach for noise-tolerant fault classification, offering practical potential for real-world implementation in intelligent protection systems and smart grid applications.
Pengaruh Stray Capacitance pada Model Coupling Capacitor Voltage Transformer terhadap Penentuan Lokasi Gangguan Saluran Transmisi 150 kV Menggunakan Metode Transformasi Wavelet Diskrit Septiyeni, Tesya Uldira; Novizon, Novizon; Sonia, Fanni; Qatrunnada, Rusvaira; Hasanah, Mardini
SURYA TEKNIKA Vol 13 No 1 (2026): JURNAL SURYA TEKNIKA
Publisher : Fakultas Teknik UMRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jst.v13i1.11648

Abstract

Long transmission systems in open areas frequently face challenges in detecting fault locations quickly and accurately. The primary factor behind this inaccuracy stems from the imprecision of the voltage sensor model used. Therefore, this study analyzes the Capacitor Coupling Voltage Transformer (CCVT) model by integrating the effects of stray capacitance. A case study was conducted on the transmission line from the Maninjau Hydroelectric Power Plant (PLTA) to the Pauh Limo Substation (GI). Utilizing the single-ended method assisted by Daubechies 4 wavelet, the simulation results indicate that the CCVT model accounting for stray capacitance yields a lower error rate, resulting in higher accuracy compared to the conventional CCVT model without stray capacitance. Furthermore, the use of a 1 MHz sampling frequency provides higher fault location accuracy than sampling frequencies of 10 kHz and 500 kHz.
Enhancing security in portable solar power supply design for alternative energy applications Syafii Syafii; Benny Dwika Leonanda; Novizon Novizon; Rindina Armysa
International Journal of Applied Power Engineering (IJAPE) Vol 15, No 1: March 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v15.i1.pp120-131

Abstract

Access to reliable electricity remains a challenge in remote and off-grid areas, where conventional power sources are often unreliable or unavailable. This paper presents the design and development of an internet of things (IoT) system for monitoring and securing a portable solar power station tailored for alternative energy applications. The system, which can be recharged using photovoltaic energy sources, employs a coulomb counting method to accurately estimate the battery's state of charge (SoC) and prevent overcharging and overdischarging. The portable power supply provides stable direct current (DC) outputs (5 V, 12 V, 24 V) and an alternating current (AC) output for various remote area applications, including telecommunications and household use. A dual-relay mechanism is used for battery protection: one relay disconnects charging at 100% SoC and reactivates at 70%, while the other disconnects the load at 20% SoC to avoid deep discharge. IoT connectivity enables real-time monitoring and remote control via smartphone. This development promotes efficient energy management, battery longevity, and improved access to sustainable electricity in underserved regions.
Assessment of AEKF SoC Estimation in a LiFePO₄ Battery System with Relay Switching Control Imam Hidayat Usman; Syafii Syafii; Novizon Novizon; Aulia Aulia
PROtek : Jurnal Ilmiah Teknik Elektro Vol 13 No 2 (2026): Protek : Jurnal Ilmiah Teknik Elektro
Publisher : Program Studi Teknik Elektro Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/protk.v13i2.11204

Abstract

This study implements an Adaptive Extended Kalman Filter (AEKF) for real-time state of charge (SoC) estimation to support charge–discharge regulation in a LiFePO₄ battery system integrated with photovoltaic (PV) generation. Due to the variability of PV output, accurate and stable SoC estimation is essential for ensuring reliable battery operation. A first-order equivalent circuit model (1RC ECM) is employed to represent battery dynamics based on measured current and terminal voltage. The proposed AEKF algorithm is implemented on a Raspberry Pi 5 to enable real-time computation, and the estimated SoC is directly used as the control variable in a dual-relay switching mechanism to regulate charging and discharging processes. Experimental results show that the proposed method achieves a Mean Absolute Error (MAE) of 1.24% and a Root Mean Square Error (RMSE) of 1.58%, which are both below the 5% target specified in the system design. The system successfully maintains the battery within a safe SoC range of 57.5% to 85.2%, while ensuring stable relay operation without chattering under dynamic load and charging conditions. These results demonstrate that the proposed AEKF-based approach provides accurate, stable, and practical SoC estimation, making it suitable for real-time battery management in small-scale energy storage applications.
Design of an integrated forecasting and scheduling model for power plants to balance solar and wind energy variability using real-time weather data Syafii Syafii; Novizon Novizon; Imra Nur Izrillah
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v17.i3.pp2112-2126

Abstract

The integration of variable renewable energy sources such as solar and wind creates challenges for power system stability and operational scheduling due to their intermittent characteristics. This study proposes an integrated forecasting and scheduling framework using real-time weather data for a hybrid renewable power system consisting of photovoltaic, wind, geothermal, and hydropower plants. Solar irradiance and wind speed data were collected using pyranometer and anemometer sensors and modeled using ARIMA for 24-hour-ahead forecasting. Based on AIC and BIC evaluation, ARIMA (2, 1, 2) and ARIMA (1, 1, 1) were selected for solar irradiance and wind speed forecasting, respectively. The forecasting results achieved MAPE values of 18.43% for solar irradiance and 14.12% for wind speed. The forecasted renewable outputs were integrated into a generation scheduling model, where geothermal power operated as a base-load unit and hydropower acted as a balancing source. The proposed scheduling strategy was evaluated through a 24-hour Newton-Raphson load flow simulation. Results showed that system power losses remained below 2% and bus voltage levels were maintained within acceptable limits, demonstrating reliable operation under fluctuating weather conditions.
Analisis Pengaruh Kontaminasi Debu Vulkanik Gunung Marapi terhadap Tahanan Isolasi Isolator Porselin: Studi Kasus Gardu Induk Padang Luar Yudia Meka Seftiani; Novizon Novizon; Ari Fitra Adhi
Jurnal Surya Energy Vol. 11 No. 1 (2026)
Publisher : Teknik Elektro, Universitas Muhammadiyah Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32502/jse.v11i1.1789

Abstract

Porcelain insulators are essential components in electric power transmission and distribution systems, functioning to electrically isolate conductors while preventing leakage current. The performance of porcelain insulators can deteriorate due to environmental contamination, particularly volcanic ash in areas affected by the eruption of Mount Marapi. This study aims to analyze the effect of natural volcanic ash contamination on the insulation resistance of a 20 kV porcelain insulator under different moisture conditions. An experimental method was employed by measuring insulation resistance using an insulation tester with a 5 kV DC test voltage. The tests were conducted under four conditions: clean insulator, dry volcanic ash contamination, moist volcanic ash contamination (16 gr of volcanic ash with 5 mL of water), and wet volcanic ash contamination (16 gr of volcanic ash with 10 mL of water). Each condition was tested ten times, and the measurement results were analyzed using descriptive statistics, including the mean, standard deviation, and percentage reduction in insulation resistance. The results showed that the average insulation resistance decreased from 1010.6 MΩ under clean conditions to 885.7 MΩ under dry volcanic ash contamination, 567.6 MΩ under moist volcanic ash contamination, and 219.8 MΩ under wet volcanic ash contamination. Compared with the clean condition, the insulation resistance decreased by 12.36%, 43.83%, and 78.25%, respectively. The findings indicate a decreasing trend in insulation resistance as the moisture content of the volcanic ash increased. These results provide useful information for the inspection and maintenance of porcelain insulators in substations located in volcanic ash-prone areas.
Co-Authors . Darwison Abdul Rajab Abdul-Malek, Zulkarnain Akbar Abadi, Akbar Alfajri, Roan Amirul Luthfi Angraini, Tuti Anton Anton Ari Fitra Adhi Ari Fitra, A. Ariadi Hazmi Astri Astia Ningsih Aulia Aulia . Baharuddin Baharuddin Chatarina Umbul Wahyuni Dano Yustasia Daud, Darwison Dona Juliandri Dwi Gustiono Eka Putra Waldi Fahreza, Rahmad Firdaus Firdaus Gunawan, Eko Amri Hanalde Andre Hardiyanti Mursat, Marta Hasanah, Mardini Ikhsan, Intan Aprillia Imam Hidayat Usman Imra Nur Izrillah Juliandri, Dona Laksono, Heru Dibyo Leonanda, Benny Dwika M. A. Hafizi M. Heru Setiawan Maemonah, Maemonah Mardini Hasanah Mardini Hasanah Melda Latif Mondrizal Mondrizal Mubarok, Fatih Mumuh Muharam Mumuh Muharram N. Riska Nofriadi Nofriadi Nofriadi, Nofriadi Novandri, Athalla Novendra, Rico Nurfi Syahri Pratama, Rizki Wahyu Rahadian Asneli Putri Rahmad Fahreza Reri Afrianita Reri Afrianita Rindina Armysa Riska, N. Riza Widia Roan Alfajri Roza Susanti Rudy Fernandez Rusvaira Qatrunnada Rusydi, M Ilhamdi Seftiani, Yudia Meka Septiyeni, Tesya Uldira Silvia Wulandari Sitti Amalia Sonia, Fanni Sulthanah, Hana Syafii . Syukri Yunus Tesya Uldira Septiyeni Wati Wati Wati, Wati Widi Adriana , Anisa Yamashika, Herris Yudia Meka Seftiani Yusreni Warmi Yusreni Warmi Yustasia, Dano Zaini Zulkarnain Abdul-Malek Zulkurnain Abdul-Malek Zurnawita Zurnawita