Thesis Type: Postgraduate
Institution Of The Thesis: Yildiz Technical University, Graduate School Of Natural And Applied Sciences, Turkey
Approval Date: 2023
Thesis Language: Turkish
Student: REEM FARIS ABOOD ABOOD
Supervisor: Ali DurusuAbstract:
Renewable energy sources are receiving more attention as a result of the population's rapid increase and growing worry over global warming. Because they cut carbon emissions and generate cheap electricity, renewable energy sources have a big impact on the environment. In comparison to other energy sources, solar energy and wind turbine have lower operating and maintenance expenses and is thus the most widely used renewable energy source. Due to the irregularity of solar energy and wind turbine energy the s The PV-wind turbine-battery-integrated module must be operated safely and effectively, which requires effective power flow control. The PV-wind turbine-battery-integrated module system has to implement an energy management system to meet consumer demand. This work highlights the importance of different possible operating modes that may occur during system operation. The grid power's contribution to meeting the load demand will be determined by an optimization factor produced using an artificial intelligence technique. This study aims to optimize the PV-wind turbine-battery system's efficiency by using a particle swarm optimization algorithm based on an artificial intelligent method that is used to achieve maximum power point tracking in terms of enhancing the power quality and energy management of the PV-wind turbine-battery module.