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Improved cuckoo photovoltaic global maximum power tracking method under local shading conditions

A maximum power tracking, cuckoo technology, applied in photovoltaic power generation, instruments, control/regulation systems, etc., can solve problems such as failure

Inactive Publication Date: 2020-06-09
TIANJIN UNIV
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  • Abstract
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  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The traditional maximum power tracking algorithm will fail due to the existence of multiple local maxima in the P-V characteristic curve under partial shading conditions

Method used

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  • Improved cuckoo photovoltaic global maximum power tracking method under local shading conditions
  • Improved cuckoo photovoltaic global maximum power tracking method under local shading conditions
  • Improved cuckoo photovoltaic global maximum power tracking method under local shading conditions

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Embodiment Construction

[0018] In photovoltaic power generation systems, the traditional maximum power algorithm is limited by the local maximum power value under local shading conditions. After studying the application of cuckoo search algorithm to solve multi-peak MPPT, an improved cuckoo search method is proposed. ICS replaces the random step size in the original algorithm, introduces the concept of low power, high power, normal and marked areas, and realizes adaptive step adjustment according to different stages of nest location. The algorithm uses large step sizes in low-power regions and marked regions to reduce search time, and uses small step sizes in high-power regions to improve search accuracy.

[0019] In the original cuckoo algorithm (Cuckoo search, CS) algorithm, Lévy flight is usually used to generate a random step. However, this step size will vary from time to time, which is not conducive to the balance between maximum power tracking speed and accuracy. The Improved Cuckoo search (I...

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Abstract

The invention relates to a method for improving cuckoo photovoltaic whole-situation largest power tracing under the local sheltering condition. The method comprises the following steps that k points are selected from [0,1] as the duty ratios corresponding to evenly distributed initial nest positions; under the local sheltering condition, the output current IPV and the output voltage VPV of a photovoltaic array are measured, and the corresponding powers Pi are calculated and ranked; and (3) according to the definition of the low-power zone, the high-power zone, the normal zone and the marked zone, the zone positions where the current powers Pi are located are determined; the adopted steps in the current zones are determined; and whether standard deviation sigma of all nest positions is smaller than the set threshold value epsilon or not is judged, if yes, the whole-situation largest power point is regarded, if not, the steps are adjusted according to the step (4), and searching is continued.

Description

technical field [0001] The invention belongs to the technical field of new energy photovoltaic power generation, and relates to a maximum power tracking method. Background technique [0002] All over the world, with the maturity of photovoltaic power generation technology and the increasing attention to the environment, solar energy is gradually being rapidly and widely used. Solar energy is an environmentally friendly energy source, and its related power generation equipment has the advantages of simple structure and low cost. A stable and efficient photovoltaic maximum power tracking (Maximum Power PointTracking, MPPT) algorithm plays an important and positive role in improving the power generation efficiency of photovoltaic modules and promoting the sustainable development of the solar industry. [0003] The traditional maximum power tracking algorithm will fail due to the existence of multiple local maxima in the P-V characteristic curve under partial shadowing conditio...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05F1/67
CPCG05F1/67Y02E10/56
Inventor 石季英胡露薛飞凌乐陶杨文静乔文
Owner TIANJIN UNIV