MPPT method of photovoltaic system based on ant colony optimization and variable step size disturbance observation algorithms

Abstract

The invention discloses a MPPT strategy of a partial overshadowing photovoltaic system based on ant colony optimization and variable step size disturbance observation algorithms. According to a MPPT method, the problem of searching a global maximum power point when multiple peak values occur in the photovoltaic system under a partial overshadowing condition is solved. When a proper situation appears, the early stage of photovoltaic output is tracked by virtue of an ant colony algorithm, so that the phenomenon that the trapping of a system in a partial maximum power point by a disturbance observation algorithm is avoided, and meanwhile, the convergence speed is increased. After the secondary iteration of the ant colony algorithm ends, the algorithm is stopped, the later stage of the photovoltaic output is tracked by virtue of the variable step size disturbance observation algorithm, and the steady-state oscillation of the system caused by the ant colony algorithm is avoided by virtue of the robustness of the variable step size disturbance observation algorithm. Finally, the global maximum power point of the partial overshadowing photovoltaic system can be rapidly, accurately and stably tracked.

Description

technical field [0001] The invention belongs to the technical field of photovoltaic power generation, and specifically relates to a tracking strategy that can quickly, accurately and stably search for the maximum power point of a photovoltaic system, especially based on the mixed algorithm of ant colony optimization and variable step size disturbance observation in the partial shading of photovoltaic systems A photovoltaic system MPPT method for tracking the global maximum power point. Background technique [0002] At present, the existing maximum power point tracking algorithms for photovoltaic systems are divided into two categories, non-intelligent algorithms and intelligent algorithms. Among them, the non-intelligent algorithms include the perturbation and observation method, the conductance increment method, etc. Although these methods have faster convergence speed and less steady-state oscillation, when the photovoltaic system has partial shadows, such as sunrise, suns...

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Problems solved by technology

Since this scheme uses the traditional ant colony algorithm, the number of iterations is too many and the amount of calculation is large, which will lead to too slow convergence speed and too long convergence time; at the same time, a small fixed step size is used as the disturbance amount in the later stage, which will also lead to a slow convergence process

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