Improved conductance increment and fuzzy control double-mode MPPT control method

Abstract

The invention discloses an improved conductance increment and fuzzy control double-mode MPPT control method, and belongs to the technical field of MPPT (Maximum Power Point Tracking) of a photovoltaic power generation system. The step size in an conductance increment control algorithm is adjustable, a fuzzy control algorithm is combined, and a fuzzy control search strategy is carried out on right of the maximum power point. According to the control method of the invention, the tracking speed is high, violent oscillation and a dead tracking zone can be avoided when illumination changes widely, only a small amount of fluctuation occurs near the maximal power point, and stable-state oscillation is reduced; and compared with existing MPPT, the tracking performance, the response precision and tracking efficiency are high, the method is easy to realize, energy loss is reduced, and corresponding problems as oscillation, inaccurate response, low tracking efficiency, violent oscillation and occurrence of a dead tracking zone of the existing algorithms can be solved.

Description

technical field [0001] The invention relates to an improved conductance increment and fuzzy control dual-mode MPPT control method, which belongs to the technical field of maximum power point tracking of photovoltaic power generation systems. Background technique [0002] In recent years, energy conservation and emission reduction has become an important direction of national economic development, and energy conservation has become a top priority. Photovoltaic power generation system has the advantages of environmental protection, cleanness, wide distribution, and renewable, and has great potential in the field of new energy applications. However, the output of photovoltaic cells is highly nonlinear because it is easily affected by light, temperature, etc., so that photovoltaic cells cannot output at maximum power, which reduces the power generation efficiency of the system. Therefore, many scholars have carried out research on the maximum power point tracking (MPPT) of phot...

AI Technical Summary

Problems solved by technology

[0003] (1) The short-circuit current method needs to continuously test the current open-circuit voltage or short-circuit current of the photovoltaic panel due to changes in the environment, which is not only difficult to fully realize, but also leads to energy loss;

[0004] (2) Disturbance and observation method: After tracking a maximum power point, the subsequent tracking will be disturbed in two directions, so vibration will occur, resulting in energy loss;

[0005] (3) The performance of the conductance incremental method is greatly affected by the step size control model. Too small step size will lead to slow tracking speed, and too large step size will cause oscillation, and cannot respond accurately when the light suddenly increases; There is also the problem of tracking dead zone

[0006] (4) When the neural network algorithm changes the temperature and sunlight, the characteristics of the photovoltaic panel will also change accordingly. As a result, the neural network needs to be continuously trained by the changing photovoltaic characteristics in order to track accurately, but this implementation is difficult

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