Güneş enerjisi kontrol sistemi esaslı metaheuristik yöntem

This thesis examines the issue of figuring out the particle swarm optimization method's maximum power point tracking algorithm for solar energy systems. Before putting a solar cell to use, the manufacturer typically characterizes the device using empirical data. Measurement or detection of a variety of solar energy degradation pathways is important. Thus, it is advantageous to actively measure solar energy factors throughout time. We provide an approach to enhance the maximum power point tracking algorithm for an equivalent model of a typical solar energy system using a smart method based on particle swarm optimization. This technique enables routine updating of the solar energy system, which can be used to identify the system's maximum output power. The 1400 Watt was reached for PV power efficiency, and the irradiation value was 1000 Watt/m2. 95.45% of both the suggested method and the MPPT method were accurate. Its precision is measured in terms of maximum power (252.44 Watts), cells per module (40), and open circuit voltage (35.44 Volts), accordingly.