Photovoltaic array multi-peak maximum power cluster searching optimization tracking method

Abstract

The invention discloses a photovoltaic array multi-peak maximum power cluster searching optimization tracking method, comprising steps of measuring output voltage and output current of a photovoltaic array; according to photovoltaic array component and shadow condition, acquiring peak value number n; using IGSO algorithm and tracking the voltage corresponding to the maximum photovoltaic power; making an impulse generator generate PWM signal according to voltage and then making a photovoltaic array run at an updated array voltage point as the maximum output power of photovoltaic array; when the power change rate is more than 0.015, restarting a searching process. According to the tracking method of photovoltaic array MPPT problem based on IGSO, number of member producer in the IGSO algorithm is arranged according to the array structure, thus the tracking efficiency is improved; according to the rule relationship between the maximum power point and the voltage, the initial position and the searching strategy are improved, and rover is omitted, and thereby avoiding partial extreme point and improving the algorithmic precision and stability.

Description

technical field [0001] The invention relates to the field of photovoltaic power generation, in particular to a multi-peak maximum power group search optimization tracking method for photovoltaic arrays. Background technique [0002] Photovoltaic power generation has the characteristics of huge reserves, inexhaustible supply, safety and convenience, so it has become an emerging industry that is generally concerned and focused on development by countries all over the world. However, in the development of photovoltaic power generation, there are still many problems that need to be solved urgently, including the selection of an appropriate multi-peak maximum power tracking (Maximum Power Point Tracking, MPPT) algorithm for photovoltaic arrays to improve the efficiency of photovoltaic systems. [0003] The maximum power point tracking of the photovoltaic array means that when the external environmental conditions such as the intensity of sunlight and the external temperature chan...

AI Technical Summary

Problems solved by technology

Conventional MPPT algorithms (such as hill-climbing method, perturbation and observation method, etc.) have a good tracking control effect on single-peak power, but in the case of partial shading, the power-voltage (P-U) curve of the photovoltaic array presents multiple power extremes The multi-peak problem of points makes the conventional MPPT algorithm easy to fall into local extreme points

Artificial intelligence methods (such as neural network, particle swarm method, etc.) have certain effects on local shadows, but neural network methods require long-term targeted training for different photovoltaic array systems; particle swarm method can improve the accuracy of results , but the implementation process is more complicated and will lead to an increase in the cost of hardware equipment

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