SISTEM MONITORING DAN MANAJEMEN KETERSEDIAAN ENERGI HULU HILIR DENGAN ALGORITMA K-MEANS CLUSTERING PADA PEMBANGKIT LISTRIK TENAGA SURYA (PLTS)
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
Hendrian, Edwin
Haris, Abdul
Prayitno, Budi
Haris, Abdul
Prayitno, Budi
Subject
Teknik Informatika
Datestamp
2022-09-23 02:29:57
Abstract :
Solar Power Plant is an alternative power supply. One of the problems with solar power plant is that there is no continuous and automatic monitoring of the generating system and also a short battery life because it is not controlled in charging and using it. This study produces a real-time and automatic monitoring and management system that can monitor the performance of solar panels, batteries, and electricity usage by users, and can regulate the battery by disconnecting the charging when the battery voltage reaches the maximum threshold and disconnects usage when the battery voltage reaches the threshold minimum. Data transmission from the monitoring to the server is carried out by the microcontroller through a Wi-Fi module ESP8266 using 802.11b communication protocol. Monitoring data will be displayed on Web monitoring and will be processed using the K-Means Clustering algorithm to classify the power produced by solar panels to assist in the performance analysis of solar panels. The test results show that the overall monitoring and management devices function and the level of accuracy of data testing using the K-Means Clustering algorithm produces a Root Mean Square Error (RMSE) value of 0.2888.
Solar Power Plant is an alternative power supply. One of the problems with solar power plant is that there is no continuous and automatic monitoring of the generating system and also a short battery life because it is not controlled in charging and using it. This study produces a real-time and automatic monitoring and management system that can monitor the performance of solar panels, batteries, and electricity usage by users, and can regulate the battery by disconnecting the charging when the battery voltage reaches the maximum threshold and disconnects usage when the battery voltage reaches the threshold minimum. Data transmission from the monitoring to the server is carried out by the microcontroller through a Wi-Fi module ESP8266 using 802.11b communication protocol. Monitoring data will be displayed on Web monitoring and will be processed using the K-Means Clustering algorithm to classify the power produced by solar panels to assist in the performance analysis of solar panels. The test results show that the overall monitoring and management devices function and the level of accuracy of data testing using the K-Means Clustering algorithm produces a Root Mean Square Error (RMSE) value of 0.2888.
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