Optimization of ACS712 Sensor Current Measurement in Solar Power System through Regression Modeling

Autor: Lantana Dioren Rumpa, Yusri AM Ambabunga, Martina Pineng
Jazyk: English<br />Indonesian
Rok vydání: 2023
Předmět:
Zdroj: Journal of Applied Informatics and Computing, Vol 7, Iss 2, Pp 198-201 (2023)
Druh dokumentu: article
ISSN: 2548-6861
DOI: 10.30871/jaic.v7i2.6511
Popis: This study aims to improve the accuracy of current measurements in solar power systems using the ACS712 sensor and linear regression modeling. While the ACS712 sensor is commonly used for current measurement in solar systems, it often faces accuracy issues. In this research, we measured current using the ACS712 sensor alongside a validated reference device and applied a linear regression model to correct any inaccuracies. The results show that our linear regression model significantly boosts the accuracy of ACS712 sensor current measurements. We also conducted performance tests with the model on the Arduino Uno platform, which revealed increased measurement accuracy in various testing scenarios. Before implementing the model, the average difference between ACS712 sensor measurements and reference device readings was 0.364. After implementing the model, this difference dropped substantially to just 0.044.
Databáze: Directory of Open Access Journals