Publication

Abstract : Distributed generation, electric vehicle charging stations, critical and sensitive loads with varying supply quality requirements are integral parts of smart cities. The system is complicated in nature, due to the uncertain power generation and power demand, which necessitates smart and intelligent compensation strategies to alleviate power quality issues. Critical and sensitive equipment is used in hospitals, data centers, automation industries, banking services, etc., to optimize electrical power usage and perform system needs with optimum reliability. To provide these systems with stable, secure, and high-quality power, a hybrid power quality compensator is proposed which improves power quality at the point of common coupling with suitable mode of compensation. Renewable energy-based hybrid power quality compensator (ReHPQC)-based on deep learning networks is presented in this paper. The case study conducted on CIGRE low-voltage microgrid with multifeeders demonstrates the importance of this system for smart microgrid.