Power Quality Controller using Remote Control System

The most important activity in the electric power industry is to deliver a good quality of electric power to consumers since electricity has become the fundamental element of electrical equipment operation. This paper aims to design a Remote Monitoring System (RMS) to control and improve electric power quality by employing the Artificial Neural Network (ANN). Therefore, comprehensive research is carried out, and artificial data simulation is performed to achieve the targeted goals. Two main parameters such as voltage and current, are used to monitor the systems. On the other hand, Wireless Sensor Network (WSN) is used to collect the data, and then the data is transmitted by radio waves. Subsequently, the collected data are regrouped in a remote-control center where computers control the information. The control center is equipped with an ANN, and the remotely controlled system uses a deep learning technique to perform the decisions accurately. ANN first learns the powerful signals and compares them with the received signals. Hence, the proposed system demonstrates an intelligent way of monitoring the quality of electric power without human intervention.