The constant voltage tracking(CVT) method usually neglects the change of external conditions during the maximum power point tracking(MPPT) process

to enhance the tracking accuracy and electricity generation efficiency of the photovoltaic systems

an MPPT method for photovoltaic(PV) system based on the hybrid algorithm using particle swarm optimization(PSO) algorithm and pattern search algorithm(PSA) was proposed. Simulation and analysis on the PV cell model were carried out

and the output characteristic curves under the change of external conditions were plotted to observe the effects of environmental condition change on the maximum power point. The convergence rate

accuracy and stability in the process of solving benchmark function were compared with that of the PSO algorithm

to verify the effectiveness of the PSO-PSA method. Then the outputs of the simulation model and hybrid algorithm optimization in different environments were compared

which verified that the latter has a higher accuracy. Finally

to match the dynamic output of the model and the theoretical calculating value

the control structure based on the PSO-PSA and PV array was combined and applied to the Boost circuit

which achieved the maximum power point tracking effectively. The results show the PSO-PSA-based MPPT technology for PV system has reasonable technology basis and high tracking accuracy

which compensates the lack of energy waste when using the CVT method.