Jurnal Nasional Teknik Elektro
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Optimasi Titik Daya Maksimum Global dan Distorsi Harmonik Arus pada Sistem PV-Inverter menggunakan Algoritma Migrasi Lebah (QHBM)
No full textThis paper investigates the optimization of the Global Maximum Power Point (GMPP) and the simulation of Total Harmonic Distortion of Current (THDI) from an inverter connected to a nonlinear load. THDI variations are analyzed with respect to ambient temperature (T) and solar irradiance (G). The study also highlights how harmonic components negatively affect steady-state voltage stability in photovoltaic (PV) systems. The Queen Honey Bee Migration (QHBM) algorithm is applied to optimize GMPP while minimizing THDI. An off-grid PV-inverter system is modeled in MATLAB/Simulink. The model extracts THDI as a function of temperature and irradiance. Simulations cover irradiance from 794.8 to 994.2 W/m² and temperature from 20.0°C to 32.3°C, based on daily measurements from 08:25 to 16:50. The QHBM algorithm tracks GMPP effectively under fluctuating irradiance. Results show a 17.3% improvement in power extraction efficiency and a 32.8% reduction in THDI compared to conventional methods. The highest THDI occurs during low irradiance, particularly in the early morning and late afternoon. The algorithm converges in 0.18 seconds, outperforming other techniques. THDI increases during rapid irradiance and temperature changes. The proposed method ensures stable performance and lower THDI. Combining QHBM with active harmonic filters under low irradiance conditions is recommended to improve power quality and enhance system protection.Makalah ini menginvestigasi optimalisasi Global Maximum Power Point (GMPP) dan simulasi Total Harmonic Distortion of Current (THDI) dari inverter yang terhubung ke beban nonlinier. Variasi THDI dianalisis sehubungan dengan suhu lingkungan (T) dan radiasi matahari (G). Studi ini juga menyoroti bagaimana komponen harmonik secara negatif mempengaruhi stabilitas tegangan kondisi tunak dalam sistem fotovoltaik (PV). Algoritma Migrasi Lebah Madu Ratu (QHBM) diterapkan untuk mengoptimalkan GMPP sambil meminimalkan THDI. Sistem PV-inverter off-grid dimodelkan dalam Matlab/Simulink. Model ini mengekstrak THDI sebagai fungsi dari suhu dan radiasi. Simulasi mencakup radiasi dari 794,8 hingga 994,2 W/m² dan suhu dari 20,0°C hingga 32,3°C, berdasarkan pengukuran harian dari pukul 08:25 hingga 16:50. Algoritme QHBM melacak GPP secara efektif di bawah radiasi yang berfluktuasi. Hasilnya menunjukkan peningkatan 17,3% dalam efisiensi ekstraksi daya dan penurunan 32,8% dalam THDI dibandingkan dengan metode konvensional. THDI tertinggi terjadi pada saat pencahayaan rendah, terutama di pagi dan sore hari. Algoritme ini konvergen dalam 0,18 detik, mengungguli teknik lainnya. THDI meningkat selama perubahan radiasi dan suhu yang cepat. Metode yang diusulkan memastikan kinerja yang stabil dan THDI yang lebih rendah. Menggabungkan QHBM dengan filter harmonik aktif di bawah kondisi pencahayaan rendah direkomendasikan untuk meningkatkan kualitas daya dan meningkatkan perlindungan sistem
Fault Detection In Storage Tank System Using Luenbeger Observer (LO): Simulation-Based Validation.
Full text linkThis study presents a comprehensive, simulation-based validation of a Luenberger Observer (LO) specifically designed for fault detection in storage tank systems. It commences with the development of a nonlinear storage tank model, which is subsequently linearized to streamline the observer design process. The LO estimates critical system states and produces residual signals that enable reliable fault detection. The observer gain is meticulously chosen using pole placement techniques to ensure rapid convergence of estimates and overall stability. To evaluate the effectiveness of this approach, three distinct fault scenarios—ramp, square pulse, and inverted ramp signals—are introduced to simulate various types of abnormal conditions that could occur in real-world operations. Simulation results demonstrate that the LO accurately estimates the liquid level states with a mean absolute error of approximately 0.02 meters, equivalent to about 2.6%. Furthermore, the observer detects faults with an average delay between 5 and 9 seconds following fault injection, indicating its prompt response capability. Notably, even with sensor noise levels reaching 6%, the observer maintains stable tracking performance, demonstrating strong robustness against disturbances. Across all tested scenarios, the residual signals show rapid increases during fault conditions and swiftly return near zero once the system reverts to normal operation, with no false alarms observed. Collectively, these results suggest that the Luenberger Observer provides an accurate, rapid, and disturbance-tolerant method for fault detection in storage tank systems. Such an approach offers a practical alternative to data-driven fault detection methodologies, as it relies less on extensive training datasets and can be more readily implemented for real-time industrial monitoring applications.Penelitian ini bertujuan untuk mengembangkan dan mengevaluasi pendekatan berbasis LO untuk deteksi kesalahan dalam sistem tangki penyimpanan, dengan tujuan untuk meningkatkan pemantauan dan identifikasi anomali seperti ketidakakuratan sensor dan ketidakkonsistenan aliran. Model tangki penyimpanan nonlinier dibangun dan dilinierisasi untuk memfasilitasi desain LO, yang memperkirakan kondisi sistem dan menghasilkan residu yang digunakan untuk mengidentifikasi perilaku sistem yang tidak normal. Penguatan pengamat dipilih dengan cermat untuk memastikan stabilitas dan konvergensi yang cepat. Studi simulasi dilakukan di bawah berbagai skenario gangguan untuk menilai kinerja pengamat. Hasilnya menunjukkan bahwa LO secara akurat memperkirakan status sistem dan secara efektif mendeteksi kesalahan dengan penundaan minimal dan kesalahan estimasi yang rendah. Selain itu, metode ini menunjukkan ketahanan terhadap gangguan dan noise sensor, sehingga cocok untuk implementasi waktu nyata. Dibandingkan dengan metode berbasis data, pendekatan berbasis model ini menawarkan kesederhanaan, keandalan, dan mengurangi ketergantungan pada kumpulan data pelatihan yang ekstensif. Secara keseluruhan, temuan ini mendukung penggunaan LO sebagai alat pendeteksi kesalahan yang praktis dan efisien untuk sistem tangki penyimpanan, yang berkontribusi pada peningkatan keselamatan operasional dalam industri prose
Smart Door Locking System for Children Using HC-SR04 and IoT Technology
Full text linkThe increasing incidence of minors accessing hazardous indoor areas—such as staircases, balconies, and rooms with sharp objects—raises serious safety concerns, often due to insufficient parental supervision. This study proposes an Internet of Things (IoT)-based automatic door lock system to enhance child safety in home environments. The system integrates dual ultrasonic sensors for distance and height detection, a KY-037 sound sensor, and an ESP32-CAM for real-time video monitoring, all accessible via a web interface. A key novelty lies in the integration of multi-sensor spatial awareness with live surveillance, enabling automated control and proactive safety features. Tested on ten children aged 4 to 6 years, the system achieved a 90% success rate in locking the door when a child under 120 cm approached within 1 meter, with an average response time of approximately 2 seconds. A sound-based alarm is also triggered when noise levels exceed 120 decibels, serving as an emergency alert. However, a 10% false negative rate was observed when children were detected at distances of 1.3 to 1.5 meters, suggesting the need for further sensor calibration. Overall, the system demonstrates strong potential as a scalable and cost-effective smart home safety solution, combining automation, real-time monitoring, and child-specific access control. Future work should focus on improving detection accuracy and extending functionality for multi-object scenarios
ADDIE-Based Development of a Solar-Powered Sprayer for Efficient Weed Control in Remote Oil Palm Plantations
Full text linkOil palm plantations in Indonesia demand efficient weed control methods, particularly for large-scale operations in remote areas. Manual pesticide sprayers are still commonly used, but they require high labor, long operating time, and are not energy-efficient. This study presents the design and development of a solar-powered pesticide sprayer using the ADDIE method—Analysis, Design, Development, Implementation, and Evaluation. The prototype consists of a 50 Wp monocrystalline solar panel, two 12V 24Ah VRLA batteries, a DC pump with variable pressure levels, and an Automatic Transfer Switch (ATS) for alternating battery use. The system is mounted on a frame suitable for motorcycle transport to improve field mobility and adaptability in plantation environments. Development followed all ADDIE phases and was validated through real-world field testing. Results showed a 75% reduction in spraying time—from 8 hours (manual) to 2 hours—with a maximum pressure of 70 PSI and a spray reach of 3.5 meters. The ATS allowed uninterrupted operation under varying sunlight conditions. This design offers greater energy efficiency, continuous usability, and flexible deployment compared to similar systems. The findings demonstrate the feasibility of applying solar energy to support sustainable weed management in off-grid agricultural settings, highlighting its potential for broader agricultural mechanization
Optimizing Lightning Arrester Selection for 275kV EHV Substations: A Comparison of Overvoltage Analysis with Software and Manual Calculations
Full text linkA substation is one of the essential aspects of an electrically interconnected system, especially in a grid utility. Power generation, transmission, and distribution systems always need a continuous power supply to the customer. In high voltage and extra high voltage substation, operation schemes during abnormal and normal conditions may cause transient overvoltage in the system, one of which is temporary overvoltage. Temporary overvoltage analysis is needed to validate the rated system voltage within the limit of the substation equipment’s insulation level, including the rating of the lightning arrester. This research will select a lightning arrester with the standard approach IEC 60099-5 and software simulation on a computer. Conducted temporary overvoltage analysis using software simulation, which resulted in a value of 2.02 pu higher than the operating voltage. This slightly differs from the IEC 60099-5 standard, which recommends a value of 1.6 pu of operating voltage. Software simulation is beneficial as it models the system according to specific network parameters, leading to an optimal selection when compared to standards with different approaches to results based on varying network parameters. Temporary overvoltage analysis could help determine the correct rating of the lightning arrester and further mitigation, such as line compensation, switching technique, and load management, ultimately leading to reliability in substation equipment and interconnection system networks
LabVIEW- Based Leaching Tank Process Control System for Laterite Nickel Ore Processing on a Lab-Scale Basis
Full text linkThis study successfully designed and implemented a LabVIEW-based nickel laterite ore leaching process control system on a laboratory scale. This system integrates key hardware components such as Arduino Mega 2560, temperature sensor, volume sensor, jet bubble reactor, and LabVIEW-based user interface that allows automatic and real-time monitoring and control of process parameters. The calibration results showed high accuracy, with temperature measurement error values of 0.04% and 0.015% compared to the calibrator. Volume measurements under five test conditions produced error values ranging from 0.023% to 0.066%, with the best accuracy shown by readings via the LabVIEW HMI. Leaching process testing was carried out using variations in citric acid concentrations. The resulting filtrate volume showed a decrease from 173 mL at a concentration of 0.5 mol to 8 mL at a concentration of 2 mol, indicating that the higher the solution concentration, the greater the viscosity of the solution, thereby inhibiting mass transfer. The application of jet bubble technology has been shown to increase the efficiency of mixing and contact between the leaching solution and the ore, which accelerates the leaching process. Overall, the system shows high stability, accuracy, and reliability for laboratory scale applications. This system is considered suitable for use as a learning medium, an initial simulation tool for the APAL (Atmospheric Pressure Acid Leaching) process, and a means of supporting research in the development of efficient, energy-saving, and environmentally friendly nickel extraction technology
Analisis Trending Topic Pada Twitter Untuk Menentukan Pasar Indonesia
No full textTwitter is one of the most dynamic social media platforms that provides real-time information through its trending topics feature, which reflects the most talked about issues among users. However, in Indonesia, trending topics are often dominated by entertainment, celebrity gossip or light-hearted viral content, and are not used to highlight or analyze more substantial social issues. This study aims to classify Twitter trending topics in Indonesia using three clustering algorithms: K-Means, DBSCAN, and Latent Dirichlet Allocation (LDA). Data was collected over a certain period and processed through a text preprocessing stage before applying the clustering algorithms. The results show that LDA without keyword filtering provides the most relevant and dominant topic classification, the bar chart results tend to be dominant in topic 0 there are as many as 160 topics with the main cluster relating to the Indonesian presidential election. These findings suggest that LDA outperforms K-Means and DBSCAN in identifying latent topic structures in Twitter data. This study contributes to a better understanding of trending topics and supports data-driven public opinion analysis and decision-making.Trending topic adalah sebuah topik yang sedang populer dibicarakan oleh masyarakat, salah satu media sosial yang digunakan untuk melihat trending topic ini adalah Twitter. Banyak sekali masyarakat di seluruh dunia yang menggunakan aplikasi ini, terutama masyarakat Indonesia karena berita yang terdapat di Twitter bersifat real time dan setiap orang dapat memberikan opininya masing-masing. Tujuan dari penelitian ini adalah untuk mengetahui kategori yang sedang populer dibicarakan oleh masyarakat Indonesia berdasarkan data trending topic yang diambil selama 3 hari agar dapat digunakan oleh para content creator, pebisnis, dan juga perusahaan start-up. Disini peneliti akan membandingkan dengan menggunakan 3 algoritma, yaitu K-Means, DBScan, dan LDA. Dengan menggunakan 2 kondisi, yaitu kondisi pertama dengan menggunakan kata kunci dan kondisi kedua tanpa menggunakan kata kunci. Hasil penelitian menunjukkan bahwa menggunakan algoritma LDA dengan kondisi tanpa kata kunci lebih baik dibandingkan dengan menggunakan algoritma K-Means dan DBScan karena algoritma LDA tanpa menggunakan kata kunci langsung menentukan topik-topik yang dominan dan saling berkaitan
Orca Predation Algorithm as an Innovative Solution for IEEE 30 Bus
Full text linkThe effective operation of the IEEE 30 Bus power system requires economic dispatch optimization to minimize production costs, align energy supply with demand, and ensure system stability. This economic dispatch problem is complex due to its non-linear characteristics, interdependence between generators, and the need to combine cost minimization with power loss reduction. Conventional optimization techniques often struggle to find global solutions, easily get stuck in local optima, and require significant computational time. This study introduces the Orca Predation Algorithm (OPA) as a new approach to address these challenges. Inspired by the hunting behavior of orcas, OPA balances exploration and exploitation through two distinct phases: pursuit and attack. Evaluated on the IEEE 30-Bus system using power loss computation with coefficient B, the algorithm ensures that generator output power allocation meets demand at the lowest cost. OPA's performance is comprehensively compared with Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), Whale Optimization Algorithm (WOA), and Bat Algorithm. The results consistently show that OPA achieves the lowest total cost of $772,754 while maintaining superior system stability and effectively minimizing power losses among the evaluated algorithms. These findings highlight the significant potential of OPA to enhance energy management and advance power system optimization
Evaluation of Insulation Resistance Degradation in 555 WP Monocrystalline Solar Modules under Solar Irradiation Exposure
No full textThis study aims to analyze the insulation resistance value of a 555 WP monocrystalline solar module under the influence of solar irradiation through outdoor testing and insulation assessment. The primary focus is to understand the impact of solar exposure on insulation durability, a crucial factor in the long-term performance and safety of solar modules. The testing method follows the SNI/IEC 61215 standard, involving initial and final measurements using a calibrated insulation tester at the Energy Conversion Laboratory, BRIN. The results indicate a 19.54% degradation in insulation resistance after 15 days of solar exposure. Despite this decline, the module still meets the IEC 61215 criteria for insulation resistance, maintaining a resistance value above 40 MΩ for a module with a surface area of 2.583 m². A comparison of initial and final data reveals a decrease in resistance from 3.470 GΩ in the initial test to 2.792 GΩ in the final test. This reduction underscores the importance of paying closer attention to maintenance and routine testing to ensure the module's long-term reliability. This study provides new empirical evidence on the dynamics of short-term insulation degradation under tropical solar conditions, a topic that has been rarely quantified in field-based PV reliability research. In addition, this study makes significant contributions to the development of industry standards that aim to enhance the reliability of solar modules and manage renewable energy systems.Studi ini bertujuan untuk menganalisis nilai resistansi isolasi modul surya monokristalin 555 WP di bawah pengaruh iradiasi matahari melalui pengujian luar ruangan dan penilaian isolasi. Fokus utamanya adalah untuk memahami dampak paparan matahari terhadap daya tahan isolasi, faktor penting dalam kinerja dan keamanan modul surya jangka panjang. Metode pengujian mengikuti standar SNI/IEC 61215, yang melibatkan pengukuran awal dan akhir menggunakan penguji isolasi terkalibrasi di Laboratorium Konversi Energi, BRIN. Hasilnya menunjukkan penurunan 19,54% dalam resistansi isolasi setelah 15 hari paparan matahari. Meskipun terjadi penurunan ini, modul tersebut masih memenuhi kriteria IEC 61215 untuk resistansi isolasi, mempertahankan nilai resistansi di atas 40 MΩ untuk modul dengan luas permukaan 2,583 m². Perbandingan data awal dan akhir menunjukkan penurunan resistansi dari 3,470 GΩ dalam pengujian awal menjadi 2,792 GΩ dalam pengujian akhir. Pengurangan ini menyoroti perlunya peningkatan perhatian terhadap pemeliharaan dan pengujian rutin untuk memastikan kinerja modul dalam jangka panjang. Studi ini memberikan kontribusi signifikan terhadap pengembangan standar industri yang bertujuan untuk meningkatkan keandalan modul surya dan pengelolaan sistem energi terbarukan
Natural Exponential Inertia Weight and Acceleration Coefficient Particle Swarm Optimization Algorithm tuned PID Controller for DC Motor Speed Control.
Full text linkThis paper presents a novel optimization algorithm, the NExIWAC (Natural Exponential Inertia Weight and Acceleration Coefficient) variant of Particle Swarm Optimization (PSO), for tuning PID controllers in DC motor speed control systems. The proposed NExIWAC algorithm improves control performance by dynamically adjusting the inertia weight and acceleration coefficients during optimization. To evaluate its effectiveness, the NExIWAC-tuned PID controller was compared against five established metaheuristic algorithms: Atomic Search Optimization (ASO), Sand Cat Swarm Optimization (SCSO), Grey Wolf Optimization (GWO), Invasive Weed Optimization (IWO), and Stochastic Fractal Search (SFS). The system's step response was analyzed under a reference speed demand of 1 p.u., with performance metrics including steady-state error, rise time, settling time, overshoot, and Integral of Time-weighted Absolute Error (ITAE). The NExIWAC algorithm demonstrated superior performance, achieving the fastest rise and settling times, zero steady-state error, and the lowest ITAE value among the tested algorithms. A robustness analysis was conducted by varying motor parameters, such as armature resistance and motor constant, by ±50%. The NExIWAC-PID controller exhibited stable and reliable performance under all conditions. Stability analysis through Bode plots and pole-zero mapping further confirmed the system's robust behavior, with a high phase margin and poles located in the left half of the complex plane. The results indicate that the NExIWAC algorithm is a powerful and reliable optimization tool for tuning PID controllers in DC motor applications, offering significant advantages in terms of precision, stability, and adaptability