Photovoltaic array MPPT method based on cuckoo search algorithm

Abstract

The invention discloses a photovoltaic array MPPT method based on a cuckoo search algorithm. The point with the highest power of a photovoltaic array is tracked mainly through the combination of the cuckoo search algorithm with a fuzzy PI control algorithm. The method includes the steps that firstly, the overall-station point with the highest power in the photovoltaic array is quickly and accurately found through the novel species iteration overall-station rapid search technology, namely, the cuckoo search algorithm; secondly, the point with the highest power is tracked through fuzzy PI control, and therefore efficiency of a photovoltaic power generation system can be effectively improved. The method is simple in algorithm conception, less in adjustment parameter, high in search accuracy, high in tracking speed and easy to achieved, and the photovoltaic array can stably run at the point with the highest power.

Description

technical field [0001] The invention relates to a photovoltaic array MPPT method, in particular to a photovoltaic array MPPT method based on a cuckoo search algorithm. Background technique [0002] In recent years, photovoltaic power generation has been an important application method of solar power generation. With its advantages of small capacity, low voltage level, close to the load, and little impact on the power grid, its large-scale application prospects are extremely broad. Photovoltaic array is a key component of photovoltaic grid-connected power station system. Its I-U characteristics are a set of nonlinear functions jointly affected by solar radiation intensity, ambient temperature and photovoltaic module parameters, and the output power characteristic curve is easily changed by changes in the external environment. The maximum output power point fast optimization algorithm needs to quickly search for the maximum value, and use the pulse width modulation (hereinafte...

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Problems solved by technology

[0004] Traditional PI controllers are difficult to achieve ideal control effects for systems with large model parameter changes and external disturbances. The fuzzy PI control algorithm is a control technology that imitates human thinking and does not depend on the mathematical model of the controlled process. Excellent dynamic performance such as fast dynamic response, strong anti-interference ability, good robustness, and high steady-state accuracy have been widely used

[0005] The existing mature technology generally uses the conductance incremental method, which is not real-time and will fall into the local optimum under the multi-peak curve; secondly, the global scanning method can find the global optimum, but it takes a long time. And every time the external conditions change, it needs to re-scan, which cannot achieve the effect of real-time tracking

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