Prediction method and prediction system for residual life of photovoltaic module

A photovoltaic module and life prediction technology, which is applied in the direction of prediction, instrumentation, random CAD, etc., can solve the problems of increasing the life error and monotony of photovoltaic modules, and achieve the effect of improving accuracy

Pending Publication Date: 2022-07-29
LANZHOU UNIVERSITY OF TECHNOLOGY
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Problems solved by technology

[0004] At present, the method of predicting the remaining life of photovoltaic modules based on data modeling basically uses the Gamma process to establish a performance degradation model of photovoltaic modules, which presupposes that the degradation process of photovoltaic modules is strictly monotonous and ignores the relationship with the actual degradation process of photovoltaic modules. The difference will increase the error of PV module life prediction

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  • Prediction method and prediction system for residual life of photovoltaic module
  • Prediction method and prediction system for residual life of photovoltaic module
  • Prediction method and prediction system for residual life of photovoltaic module

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[0046] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that the present disclosure will be more thoroughly understood, and will fully convey the scope of the present disclosure to those skilled in the art.

[0047] Photovoltaic modules are mainly installed outdoors. Considering the influence of natural factors (such as shading, etc.), the performance degradation process of the modules will show non-monotonic characteristics. The performance degradation of photovoltaic modules refers to the degradation and failure process caused by the composite effect of natural environment, mechanical stress and other factors on the modules, th...

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Abstract

The invention discloses a photovoltaic module residual life prediction method and prediction system. The method comprises the steps that the output power degradation amount of a target photovoltaic module at the current moment is acquired; updating preset model parameters according to the output power degradation amount; inputting the updated model parameters into a residual life prediction model, and outputting a residual life distribution result of the target photovoltaic module at the current moment; according to the method, when the degradation characteristics of the target photovoltaic module are described, the non-monotonicity, randomness and individual difference presented by the degradation of the photovoltaic module are considered, and the result can be updated by using the real-time output power degradation amount data, so that the accuracy of predicting the residual life of the photovoltaic module is improved.

Description

technical field [0001] The invention belongs to the technical field of photovoltaic power generation, in particular to a method and a prediction system for predicting the remaining life of a photovoltaic module. Background technique [0002] Photovoltaic modules are the core components of photovoltaic power generation systems, and their service life is an important factor in determining the unit power generation cost of photovoltaic systems. With the increase of the service life of photovoltaic modules and the influence of internal and external random factors, the performance of photovoltaic modules will gradually decline, and the accumulation of degradation will affect the reliability of photovoltaic power generation. At the same time, due to the low performance degradation rate of PV modules, it is difficult to collect long-term data to confirm the degradation path and lifetime. Therefore, it is necessary to establish a stochastic degradation model to describe the unstabl...

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Application Information

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IPC IPC(8): G06F30/20G06F17/18G06Q10/04G06Q50/06G06F111/08G06F119/04
CPCG06F30/20G06F17/18G06Q10/04G06Q50/06G06F2119/04G06F2111/08
Inventor 陈伟雷欢李旭斌林洁裴婷婷孙存育李明丁聪印宇杰王思聪谭森铭
Owner LANZHOU UNIVERSITY OF TECHNOLOGY
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