In this chapter, turbulent flow of water-based optimization (TFWO) inspired based on whirlpools created in turbulent flow of water is used to solve the maximum power point tracking (MPPT) of photovoltaic systems in partial shading conditions. The TFWO is used to determine the optimal duty cycle of the DC/DC converter with the objective of maximizing the extracted power of the photovoltaic system. The capability of proposed method is evaluated in different patterns of partial shading to achieve global optimal power. The simulation results showed that TFWO is able to track the global maximum power point (GMPP), successfully in PSC and also fast climate changing. The TFWO has a better tracking capability with faster tracking speed and accuracy than particle swarm optimization (PSO) in obtaining the GMPP. Moreover, the results indicate that the use of buck–boost converter led to faster and more accurate access to the global optimal point than the system equipped with boost converter. The results showed that photovoltaic system with boost converter cannot obtain global maximum power in climate changing condition and limited the efficiency of the MPPT algorithm, while the photovoltaic system with buck–boost converter could be tracked GMPP due to its wider operating area.