Study of a Remote Wind Resource Assessment System Integrated with Internet of Things
Wind energy is an emerging and popular source of clean energy due to its non-polluting nature and low cost. The efficient use of wind energy requires accurate and precise wind parameter measurements, which is where wind resource assessment (WRA) comes into play. The IoT and cloud-based systems have...
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| Format: | Article |
| Language: | English |
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Universitas Negeri Malang
2024-07-01
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| Series: | Journal of Mechanical Engineering Science and Technology |
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| Online Access: | https://journal2.um.ac.id/index.php/jmest/article/view/53273 |
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| author | Filian Arbiyani Filbert Filbert Anthony Nathanael Theo |
| author_facet | Filian Arbiyani Filbert Filbert Anthony Nathanael Theo |
| author_sort | Filian Arbiyani |
| collection | DOAJ |
| description | Wind energy is an emerging and popular source of clean energy due to its non-polluting nature and low cost. The efficient use of wind energy requires accurate and precise wind parameter measurements, which is where wind resource assessment (WRA) comes into play. The IoT and cloud-based systems have been applied to remote monitoring systems and provide crucial solutions for data acquisition, storage, and analytics in wind energy technology. This study aims to build a remote WRA system integrated with the Internet of Things. This study utilizes an Arduino Uno microcontroller, RK100-01 wind speed sensor, BMP280 temperature and pressure sensor, and SIM800L GPRS module to collect and transfer real-time data to the ThingSpeak cloud. The experiment was conducted at Atma Jaya Catholic University of Indonesia - Campus 3 BSD with the remote WRA system installed inside Stevenson screens to protect it from environmental conditions. Wind speed data is measured at a height of 10 meters, while air pressure and temperature data are measured at a height of 1.5 meters. Data retrieval utilizes two methods, viz. direct measurement every 15 minutes, and cloud-based retrieval every 30-second intervals. The study demonstrates that a remote WRA system integrated with IoT can measure, display, and upload three crucial parameters for assessing wind energy potential, namely wind speed, air pressure, and air temperature. This remote WRA system also provides flexibility in real-time data collection since it is accessible anytime and anywhere, thereby reducing the need for site visits during deployment. |
| format | Article |
| id | doaj-art-e81cd475e0d447359961034ac2a83a63 |
| institution | Kabale University |
| issn | 2580-0817 2580-2402 |
| language | English |
| publishDate | 2024-07-01 |
| publisher | Universitas Negeri Malang |
| record_format | Article |
| series | Journal of Mechanical Engineering Science and Technology |
| spelling | doaj-art-e81cd475e0d447359961034ac2a83a632025-02-04T00:25:58ZengUniversitas Negeri MalangJournal of Mechanical Engineering Science and Technology2580-08172580-24022024-07-018121522810.17977/um016v8i12024p21511737Study of a Remote Wind Resource Assessment System Integrated with Internet of ThingsFilian Arbiyani0Filbert Filbert1Anthony Nathanael Theo2Atma Jaya Catholic University of IndonesiaAtma Jaya Catholic University of IndonesiaAtma Jaya Catholic University of IndonesiaWind energy is an emerging and popular source of clean energy due to its non-polluting nature and low cost. The efficient use of wind energy requires accurate and precise wind parameter measurements, which is where wind resource assessment (WRA) comes into play. The IoT and cloud-based systems have been applied to remote monitoring systems and provide crucial solutions for data acquisition, storage, and analytics in wind energy technology. This study aims to build a remote WRA system integrated with the Internet of Things. This study utilizes an Arduino Uno microcontroller, RK100-01 wind speed sensor, BMP280 temperature and pressure sensor, and SIM800L GPRS module to collect and transfer real-time data to the ThingSpeak cloud. The experiment was conducted at Atma Jaya Catholic University of Indonesia - Campus 3 BSD with the remote WRA system installed inside Stevenson screens to protect it from environmental conditions. Wind speed data is measured at a height of 10 meters, while air pressure and temperature data are measured at a height of 1.5 meters. Data retrieval utilizes two methods, viz. direct measurement every 15 minutes, and cloud-based retrieval every 30-second intervals. The study demonstrates that a remote WRA system integrated with IoT can measure, display, and upload three crucial parameters for assessing wind energy potential, namely wind speed, air pressure, and air temperature. This remote WRA system also provides flexibility in real-time data collection since it is accessible anytime and anywhere, thereby reducing the need for site visits during deployment.https://journal2.um.ac.id/index.php/jmest/article/view/53273cloud storage, internet of things, real-time, remote system, wind resource assessment |
| spellingShingle | Filian Arbiyani Filbert Filbert Anthony Nathanael Theo Study of a Remote Wind Resource Assessment System Integrated with Internet of Things Journal of Mechanical Engineering Science and Technology cloud storage, internet of things, real-time, remote system, wind resource assessment |
| title | Study of a Remote Wind Resource Assessment System Integrated with Internet of Things |
| title_full | Study of a Remote Wind Resource Assessment System Integrated with Internet of Things |
| title_fullStr | Study of a Remote Wind Resource Assessment System Integrated with Internet of Things |
| title_full_unstemmed | Study of a Remote Wind Resource Assessment System Integrated with Internet of Things |
| title_short | Study of a Remote Wind Resource Assessment System Integrated with Internet of Things |
| title_sort | study of a remote wind resource assessment system integrated with internet of things |
| topic | cloud storage, internet of things, real-time, remote system, wind resource assessment |
| url | https://journal2.um.ac.id/index.php/jmest/article/view/53273 |
| work_keys_str_mv | AT filianarbiyani studyofaremotewindresourceassessmentsystemintegratedwithinternetofthings AT filbertfilbert studyofaremotewindresourceassessmentsystemintegratedwithinternetofthings AT anthonynathanaeltheo studyofaremotewindresourceassessmentsystemintegratedwithinternetofthings |