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Jurnal Teknologi Elekterika
Published by Politeknik Negeri Ujung Pandang
ISSN : 14128764     EISSN : 26560143     DOI : http://dx.doi.org/10.31963/elekterika
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering
Jurnal Teknologi Elekterika: Jurnal penelitian PNUP sebagai wadah komunikasi ilmiah antar akademisi, peneliti dan praktisi dalam menyebarluaskan hasil penelitian bidang rumpun elektro dan informatika yaitu teknik listrik, energi, elektronika, kontrol, telekomunikasi, komputer dan jaringan, dan Multimedia.
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 3 Documents
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Search results for , issue "Vol. 22 No. 2 (2025): Nopember" : 3 Documents clear
IoT-Based Sensor System for Electricity Consumption Forecasting in Boarding Rooms Using Kalman Filter Algorithm Dewi, Dewi Humeira Amriah; Farid; Muhammad Fathur Rahman N; Riesa Krisna Astuti Sakir; Muh. Erdin; Nurfitri
Jurnal Teknologi Elekterika Vol. 22 No. 2 (2025): Nopember
Publisher : Jurusan Teknik Elektro Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/elekterika.v22i2.5760

Abstract

Humans demand electricity to conduct their daily tasks. Indonesia undergoes a yearly escalation in its electricity use. Moreover, customers encounter the difficulty of overestimating their electrical energy consumption, since they remain unaware of the power utilization linked to each frequently utilized electrical load and possess limited control over their electricity expenditure. The Kalman Filter Algorithm was utilized to estimate electricity usage via the execution of a research system. The Kalman Filter can forecast future states using minimal information. This system incorporates an IoT framework with a network communication module, the Raspberry Pi, which relays data to the database. The PZEM-004T sensor is utilized to gather data on electrical parameters from loads, including voltage, current, active power, and energy consumption. The electrical consumption was documented every 15 minutes over a duration of 60 days. The dataset was divided in an 80:20 ratio, allocating 80% for training and 20% for testing. RMSE, MSE, and MAPE are utilized to determine the accuracy metrics of each test. Additionally, the fan load is assessed in one evaluation, yielding an error percentage of 0.077% for the training data and 0.076% for the test data, determined using RMSE. The error percentage calculated using the MSE equation is 0.006% for the training data and 0.005% for the test data. The error percentage calculated by MAPE is 0.789% for the training dataset and 0.202% for the testing dataset. The findings indicate that the Kalman Filter prediction method is exceptionally proficient in forecasting electrical load consumption
Design and Development of a Three-Phase Induction Motor Speed Control System Using Altivar 61 Based on Temperature Sensor and Internet of Things (IoT) Buwarda, Sukriyah; Mutmainnah, Mutmainnah; Yakob, Muh. Fhadly
Jurnal Teknologi Elekterika Vol. 22 No. 2 (2025): Nopember
Publisher : Jurusan Teknik Elektro Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/elekterika.v13i2.5785

Abstract

Penggunaan motor induksi tiga fasa di industri semakin meningkat karena keandalan, efisiensi energi, dan kemudahan perawatannya. Namun, motor ini sulit dikendalikan kecepatannya karena berputar pada kecepatan konstan. Penelitian ini bertujuan merancang sistem pengaturan kecepatan motor induksi tiga fasa menggunakan Variable Speed Drive (VSD) Altivar 61 yang dikendalikan oleh mikrokontroler ESP32 berbasis Internet of Things (IoT) dengan masukan dari sensor suhu DHT22. Sistem ini mampu menyesuaikan kecepatan motor secara otomatis berdasarkan suhu lingkungan. Hasil pengujian menunjukkan bahwa pada suhu 28°C motor berhenti, pada suhu 30–34°C motor berputar pada 560 RPM, pada suhu 36–38°C motor berputar pada 1070 RPM, dan pada suhu ≥40°C motor mencapai 1486 RPM. Akurasi sensor DHT22 mencapai 96,97%, dan sistem mampu memberikan pengendalian kecepatan motor secara efisien sesuai kondisi suhu ruangan
The Optimal Integration of Photovoltaic (PV) and Battery Energy Storage Systems in Power Distribution Using Hybrid Flower Pollination and β-Hill Climbing ramadan, m.sahrul; Ihlas, Ihlas; Assalam, Imam Faried; Asri, Andarini; Arief, Ardiaty; Nappu, Muhammad Bachtiar
Jurnal Teknologi Elekterika Vol. 22 No. 2 (2025): Nopember
Publisher : Jurusan Teknik Elektro Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/elekterika.v22i2.5805

Abstract

This study discusses the optimization of the placement and capacity of Photovoltaic (PV) and Battery Energy Storage System (BESS) units in the IEEE 33-bus distribution system using the Hybrid Flower Pollination Algorithm (FPA) and β-Hill Climbing (βHC) or HyFPAβHC methods. The primary objective of this research is to enhance the performance of the distribution system by reducing power losses and improving the voltage profile. Based on the optimization results, three PV units with capacities of 749.3 kW, 577.5 kW and 620 kW were optimally placed at buses 8, 13 and 20, respectively, while one BESS unit with a capacity of 1112.4 kW was installed at bus 24. Simulation results indicate that the integration of PV and BESS significantly reduces the total system power losses from approximately 50 kW on several main feeders under the base condition (without Distributed Generation) to below 5 kW after optimization. In addition, the voltage profile improved from a minimum value of 0.92 p.u. to a stable range of 0.98–1.0 p.u. Furthermore, the integration of PV and BESS contributes to mitigating power fluctuations, enhancing energy efficiency, and improving the reliability of the distribution system operation. Therefore, the HyFPAβHC method is proven to be effective in determining the optimal configuration of PV and BESS units to improve the technical performance of electrical distribution systems.

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