Professor of Mechanical Engineering and Smart Structures, School of Computing Engineering and Mathematics, Western Sydney University, Australia. His research interests cover Industry 4.0, Additive Manufacturing, Advanced Engineering Materials and Structures (Metals and Composites), Multi-scale Modelling of Materials and Structures, Metal Forming and Metal Surface Treatment.
Abstract— This study exhibits an optimal scheme for designing and analyzing a hybrid renewable energy management system (HREMS) with the help of artificial control techniques over conventional techniques. The system is an integration of photovoltaic array, AC wind generator, biogas generator, battery and converter. Size optimization of the system components has been done using Homer. For the utilization of renewable sources and minimization of the power loss, an energy management system has been designed and optimized through Fuzzy logic controller (FLC). FLC monitors the load demand and generates control signal for switching depending on knowledge based fuzzy rules and ensures the effective supply of energy to the load. To extract the maximum power from the photovoltaic array and to improve the system response a genetic algorithm tuned PID controller based maximum power point tracker (MPPT) is designed and employed to deliver maximum power at varying weather conditions. Simulation result of control technique has been compared with other conventional system like adaptive neuro fuzzy interference systems. Proposed method shows the improved efficiency in MPPT system, flexibility in use, cost effectiveness of management system and lower carbon emission.
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