Abstract: The photovoltaic (PV) maximum power point tracking (MPPT) based on biological swarm chasing behavior is proposed to increase the MPPT performance for a module-integrated PV power system. Each Module is viewed as a particle, and as a result, the maximum power point is viewed as the moving target. Thus, every PV module can chase the maximum power point (MPP) automatically. Comparing with a typical perturb and observe (P&O) MPPT method, the MPPT efficiency (η-MPPT) is improved about 12.19% in transient state by the proposed MPPT as theoretical prediction.
One of the most popular swarm intelligence paradigms is the particle swarm optimization (PSO), which is basically developed through the simulation of social behavior of bird flocking and fish schooling. PSO is a global optimization algorithm for dealing with problems on which a point or surface in an n- dimensional space represents a best solution. Particles move through the problem space, then, a certain fitness criterion evaluates them. Several areas have adopted the idea that swarms can solve complex problems.The PV module can automatically chase the MPP by proposed bio-MPPT algorithm. One sampling time is required to decide accurately the MPP tracking direction. The bio-MPPT algorithm build in the master controller runs and command operating voltages. Irradiation and temperature are automatically recorded in the bio-MPPT controller. The MPPT behavior of the proposed bio- MPPT is still confused with partial shadow effect.

| DOI: 10.17148/IJIREEICE.2021.9908A