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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS) Jurnal Teknik Elektro Universitas Tanjungpura ELKHA : Jurnal Teknik Elektro Elektron Jurnal Ilmiah Bulletin of Electrical Engineering and Informatics International Journal of Community Service Learning Telecommunications, Computers, and Electricals Engineering Journal Journal of Electrical Engineering, Energy, and Information Technology
Fitriah Husin
Tanjungpura University
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Social Sciences

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Journal : International Journal of Electrical and Computer Engineering

 1 
Photovoltaic parameters estimation of poly-crystalline and mono-crystalline modules using an improved population dynamic differential evolution algorithm Ayong Hiendro; Ismail Yusuf; Fitriah Husin; Kho Hie Khwee
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4538-4548

Abstract

Photovoltaic (PV) parameters estimation from the experimental current and voltage data of PV modules is vital for monitoring and evaluating the performance of PV power generation systems. Moreover, the PV parameters can be used to predict current-voltage (I-V) behavior to control the power output of the PV modules. This paper aimed to propose an improved differential evolution (DE) integrated with a dynamic population sizing strategy to estimate the PV module model parameters accurately. This study used two popular PV module technologies, i.e., poly-crystalline and mono-crystalline. The optimized PV parameters were validated with the measured data and compared with other recent meta-heuristic algorithms. The proposed population dynamic differential evolution (PDDE) algorithm demonstrated high accuracy in estimating PV parameters and provided perfect approximations of the measured I-V and power-voltage (P-V) data from real PV modules. The PDDE obtained the best and the mean RMSE value of 2.4251E-03 on the poly-crystalline Photowatt-PWP201, while the best and the mean RMSE value on the mono-crystalline STM6-40/36 was 1.7298E-03. The PDDE algorithm showed outstanding accuracy performance and was competitive with the conventional DE and the existing algorithms in the literature.
Real-time paddy grain drying and monitoring system using long range-internet of things Hiendro, Ayong; Syaifurrahman, Syaifurrahman; Wigyarianto, F. Trias Pontia; Husin, Fitriah
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i1.pp448-454

Abstract

Grain drying environmental parameters are an important issue throughout the paddy grain production process. A real-time monitoring system requires rapid, online, and accurate measurement results. In the paddy grain drying process, the heated air velocity, temperature, relative humidity, and moisture content have to be carefully monitored and maintained to ensure product quality and safety. This study aimed to propose a real-time paddy grain drying and monitoring system using a long-range internet of things (LoRa-IoT). The real-time monitoring system consisted of sensors, LoRa, and IoT platforms. The LoRa end node and gateway were utilized as a wireless radio communication platform of IoT for long-distance signal transmission. From the experiment, the gateway received data from the end node at a distance of 2 km with a time on air (ToA) of 981 ms. As a result, the proposed monitoring system succeeded in measuring and recording the heated air velocity, temperature, and relative humidity data during the paddy grain drying process from 25% moisture content down to 14%. Regarding moisture content, the accuracy of real-time monitoring information was confirmed with a direct measurement method, resulting in a root mean square error (RMSE) of 6.17%.
Co-Authors -, Purwoharjono Abqori Aula Agebeto Silalahi, Simon Agung Arsyad, Muhammad Iqbal Aula, Abqori Ayong Hiendro Bambang Hermanto Bianda, Sari Bonar Sirait Bonar Sirait BRAVOE ROLLY MORRISON SINAGA Iqram, Andi Muhammad Ismail Yusuf Junaidi Junaidi Kho Hie Khwee Kho Hie Khwee Kurniawan, Ari Kurniawan M. Iqbal Arsyad Managam Rajagukguk Muhammad Muchlis Ansor Muhammad Taufiqurrahman, Muhammad Muzakkir, Chaerul Purwoharjono - Rudi Kurnianto Rudy Gianto, Rudy Santo, Eduardus Sirait, Alen Gonzales Sirait, Bonar Syaifurrahman Syaifurrahman Tiya Nurul Lestari Trivaldo, Angga Vanisa Gustiana Wigyarianto, F. Trias Pontia Zainal Abidin Zein, Izuwar Muhammad