Analysis of Deviation Values of Electrical Energy Measuring and Limiting Instruments in the Indirect Measuring System of PT PLN UP3 Belitung
Keywords:
APP, Measurement Deviation, PLN, Machine Learning, WS2330Abstract
This study aims to analyze the deviation value of the Measuring and Limiting Device (APP) in the indirect measurement system of medium voltage customers at PT PLN (Persero) UP3 Belitung. Measurements were carried out using two approaches, namely manually using the WS2330 Portable Standard Meter and digitally through the PLN Daily Performance Monitoring (DPM) system. Tests were conducted on industrial customers, namely PT Tommy Utama, PT Timah TBK, and PT Hafidar Sukses Nusantara. The measurement results showed a significant decrease in the deviation value after technical repair actions. Before the repair, the highest deviation value of 3.2% occurred in PT Timah TBK customers. The average deviation value after the repair was within the tolerance limit of SPLN 34-2:2012 (±0.5%–1%). In addition, the measurement data were used to build a Random Forest Classifier model to automatically classify APP conditions based on the WS2330 and DPM output parameters. The simulation results showed an accuracy of 83.8% indicating the great potential of applying machine learning in supporting the early detection system for APP deviations. This study recommends the development of a Hybrid Monitoring System based on the integration of field and digital data to improve the reliability of the measurement system at PLN.
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