Rancang Bangun Sistem Pemantauan Perbaikan Faktor Daya Otomatis pada Sistem Kelistrikan Rumah Tangga Berbasis Internet of Things

Abstract

The amount of electrical energy consumption is due to the large number and variety of electrical equipment (load) used. While the electrical loads used are generally inductive and capacitive, while capacitive loads emit reactive power. This reactive power is useless power so it cannot be converted into power but is needed for the process of transmitting electrical energy to the load. So what causes a waste of electrical energy is that many devices are inductive. In general, the use of many electronic devices in the household and industry is inductive, such as electric motors, water pumps, fans, transformers, air conditioners, TL lamp ballasts, and so on. Electrical loads that are inductively reactive cause the current wave to lag behind the Voltage wave, so that it will cause a decrease in the power factor (cos phi). Conventional reactive power compensation systems are generally only by installing capacitor banks in parallel in electrical installations. The model of the manual installation system, usually the value of the capacitor installed is fixed. This research will be carried out to design and build automatic power factor compensators as an effort to increase electricity efficiency. The tool that will be made later is expected to be able to improve and increase the power factor value on inductive loads automatically and can also be monitored using the thingspeak platform. Based on the results of research on power factor improvement systems in household electricity, the average increase in power factor in this power factor improvement system is around 0,12 with a rective power compensation of around 148,19 VAR, where the average current measurement error rate in this system is only about 4 .46% and the average Voltage measurement error rate in this system is only about 0.51% and the power factor improvement system can send sensor readings and power factor measurement results to the thingspeak platform in graphic format, this power factor improvement system will continue to update data once in 1 minutes.