Under partial shading conditions(PSC)

the P-U characteristics of a solar photovoltaic array may exhibit multi-peak phenomena. Conventional algorithms tend to fall into local maximum power point(LMPP)

while maximum power point tracking(MPPT) methods based on meta heuristic algorithms are difficult to balance speed and accuracy. In this regard

this paper designs a hybrid algorithm based on the improved particle swarm optimization(IPSO) with embedded the improved perturbation and observation(IPO). The velocity and position of the particle are first updated by the IPSO algorithm. Then

perform MPPT based on the position of particles using the IPO algorithm. The tracked power is used as the fitness value of the particles

so that IPSO can find the global maximum power point(GMPP) among many LMPPs. Finally

with the global optimal output of IPSO as the initial position

IPO is used again for global maximum power point tracking(GMPPT). Comparing the proposed algorithm with IPO

IPSO

and IPSO-PO through simulation

the simulation results show that the proposed algorithm performs excellently in tracking speed and accuracy

especially in the case of a wide voltage search range

and has smaller power oscillations during the tracking process.