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Smartphone for palm oil fruit counting to reduce embezzlement in harvesting season Aripriharta, Aripriharta; Firmansah, Adim; Mufti, Nandang; Horng, Gwo-Jiun; Rosmin, Norzanah
Bulletin of Social Informatics Theory and Application Vol. 4 No. 2 (2020)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v4i2.283

Abstract

Harvest estimation is an essential parameter in the agriculture industries to estimate transportation facilities and storage areas in the harvesting season. Meanwhile, companies are required to calculate crop yields quickly and accurately. This paper reports on an experimental study in the form of a smart application to count oil palm fruit in the field quickly and accurately. The system used a single shot detector algorithm to count the number of fresh fruit bunches (FFB) on-site using a smartphone camera. The cutting area (CA) at the top of the collection was collected in various positions in the database. Our research documented that the algorithm matched the CA with the picture taken by the operator. Hence, the application automatically calculated the number of harvests per-site in the FFB unit. The data were then sent to the cloud database via a wireless router in a warehouse or through a cellular network. The main advantage of this application is reducing the theft that usually occurs on the spot. The model used performs very well for agricultural applications, with 94% to 99% accuracy.
Queen honey bee migration (QHBM) optimization for droop control on DC microgrid under load variation Aripriharta, Aripriharta; Al Rasyid, Mochammad Syarifudin; Bagaskoro, Muhammad Cahyo; Fadlika, Irham; Sujito, Sujito; Afandi, Arif Nur; Omar, Saodah; Rosmin, Norzanah
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 15, No 1 (2024)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2024.742

Abstract

Transmission line impedance in DC microgrids can cause voltage dips and uneven current distribution, negatively impacting droop control and voltage stability. To address this, this study proposes an optimization approach using heuristic techniques to determine the optimal droop parameters. The optimizcv ation considers reference voltage constraints and virtual impedance at various load conditions, particularly resistive. The optimization problem is addressed using two techniques: queen honey bee migration (QHBM) and particle swarm optimization (PSO). Simulation results show that QHBM reaches an error of 0.8737 at the fourth iteration. The QHBM and PSO algorithms successfully optimized the performance of the DC microgrid under diverse loads, with QHBM converging in 5 iterations with an error of about 0.8737, and PSO in 40 iterations drawn error is 0.9 while keeping the current deviation less than 1.5 A and voltage error less than 0.5 V. The deviation of current control and virtual impedance values are verified through comprehensive simulations in MATLAB/Simulink.
Load forecasting analysis for estimating transformer capacity of Karangkates Substations using Holt-Winters method in Python Rahmawati, Yuni; Kaki, Gregorius Paulus Mario Laka; Aripriharta, Aripriharta; Sujito, Sujito; Afandi, Arif Nur; Wibawa, Aji Prasetya; Purwatiningsih, Ayu; Bagaskoro, Muhammad Cahyo; Omar, Saodah; Rosmin, Norzanah
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i4.pp2222-2233

Abstract

In the six years from 2010 to 2015, the peak load in the East Java region increased by an average of 284MW per year. Karangkates Substation is part of an interconnected electrical system that supplies Java Island. To ensure a high level of reliability in its service, it is necessary to prepare for load growth to make sure that it does not exceed its ideal conditions, therefore special analysis of transformer capacity is needed. Using the Holt-Winters (HW) method as a reference for processing the data can be used as a reference in planning and anticipating the growing electricity demand. The results of this study are with the accuracy of the HW method with mean absolute percentage error (MAPE) = 2.645%, while the accuracy of the fuzzy time series (FTS) method = 6.399%. A forecast result done with HW methods shows the transformer at the substation Karangkates reached its normal working capacity in March 2018 at 99.583% of installed capacity and exceeded the maximum capacity in April 2018 at 101.493% of installed capacity.
MPPT Performance Analysis for PV Energy Harvesting Using Grey Wolf Optimization (GWO) Algorithm Aripriharta, Aripriharta; Syabani, Muhiban; Sendari, Siti; Wibawa, Aji Prasetya; Susilo, Suhiro Wongso; Bagaskoro, Muhammad Cahyo; Rosmin, Norzanah
ELKHA : Jurnal Teknik Elektro Vol. 17 No.1 April 2025
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v17i1.91643

Abstract

Renewable energy is a key solution to meeting the growing demand for electricity while reducing reliance on non-renewable sources. Among various renewable technologies, photovoltaic (PV) systems are widely used in solar power plants (PLTS) to harness solar energy. However, PV efficiency is affected by environmental factors such as fluctuating solar irradiance and temperature, which cause instability in output voltage and power. To address these issues, Maximum Power Point Tracking (MPPT) techniques are applied to optimize power extraction. This study proposes the Grey Wolf Optimization (GWO) algorithm for MPPT and evaluates its performance through MATLAB/SIMULINK simulations under varying irradiance and temperature conditions. Inspired by the hunting behavior and social hierarchy of grey wolves, GWO dynamically adjusts the converter's duty cycle based on real-time voltage and current measurements to maximize output power. The study focuses on PV systems in Malang, Indonesia, and compares GWO with the Particle Swarm Optimization (PSO) method in terms of accuracy and stability. The results indicate that increased solar irradiance substantially enhances PV power output, while rising temperatures tend to reduce efficiency. The GWO algorithm achieves an average tracking accuracy of 94.5632%, slightly lower than the 96.9851% achieved by PSO. However, GWO demonstrates superior performance in terms of stability, with faster convergence and reduced oscillations during the tracking process. A comparison of system performance before and after applying the GWO method shows notable improvements in tracking consistency and power extraction efficiency, especially under dynamic environmental changes. The novelty of this study lies in its use of real-world environmental data collected over a 30-day period in a tropical setting, which is rarely addressed in previous GWO-based MPPT research. These findings highlight the potential of the GWO-based MPPT strategy to enhance PV system reliability and efficiency in real-time renewable energy applications.
Design and Performance Evaluation of A Portable Low-Head Pico-Hydro System using A Rewound Axial Generator for Rural Energy Aripriharta, Aripriharta; Nibrosoma, Ahmad Dhaffa; Afandi, Arif Nur; Faiz, Mohamad Rodhi; Rahmadhani, Nur Aini Syafrina; Bagaskoro, Muhammad Cahyo; Rosmin, Norzanah
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 9 No. 1 (2025)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v9i1.1489

Abstract

This study evaluates the performance of a pico-hydro system installed on a river with low head and discharge. The system was assessed under no-load and varying load conditions (25–100%). The results indicate that the generator performs according to the initial design, despite some fluctuations in output parameters. Under no-load conditions, the generator maintains a stable output voltage between 12–14 VAC, with a rotational speed of 590–600 RPM, a system frequency of 59–60 Hz, and zero current. The step-up transformer successfully raises the voltage to 220–222 V with high stability, although minor ripple is observed in the output signal. Under load, the generator voltage slightly decreases to 12–14 V as the load increases. The rotational speed also declines (560–590 RPM), affecting frequency stability, which drops from 59 Hz at 25% load to 56 Hz at full load. The current rises proportionally with the load, from 0.10 A at 25% to 0.45 A at 100%. The observed performance drop under load highlights the effect of load on generator speed and overall system output. The primary impacts of the 25–100% load range are evident in generator speed, frequency stability, and waveform quality. Overall, the system performs satisfactorily for low-head pico-hydro applications with a power capacity of up to 100 Watts, suitable for rural street lighting.