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A Statistical Approach to Solar Photovoltaic Module Lifetime Prediction.

机译：太阳能光伏组件寿命预测的统计方法。

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摘要

The main objective of this research is to develop an approach to PV module lifetime prediction. In doing so, the aim is to move from empirical generalizations to a formal predictive science based on data-driven case studies of the crystalline silicon PV systems. The evaluation of PV systems aged 5 to 30 years old that results in systematic predictive capability that is absent today. The warranty period provided by the manufacturers typically range from 20 to 25 years for crystalline silicon modules. The end of lifetime (for example, the time-to-degrade by 20% from rated power) of PV modules is usually calculated using a simple linear extrapolation based on the annual field degradation rate (say, 0.8% drop in power output per year). It has been 26 years since systematic studies on solar PV module lifetime prediction were undertaken as part of the 11-year flat-plate solar array (FSA) project of the Jet Propulsion Laboratory (JPL) funded by DOE. Since then, PV modules have gone through significant changes in construction materials and design; making most of the field data obsolete, though the effect field stressors on the old designs/materials is valuable to be understood. Efforts have been made to adapt some of the techniques developed to the current technologies, but they are too often limited in scope and too reliant on empirical generalizations of previous results. Some systematic approaches have been proposed based on accelerated testing, but no or little experimental studies have followed. Consequently, the industry does not exactly know today how to test modules for a 20--30 years lifetime. This research study focuses on the behavior of crystalline silicon PV module technology in the dry and hot climatic condition of Tempe/Phoenix, Arizona. A three-phase approach was developed: (1) A quantitative failure modes, effects, and criticality analysis (FMECA) was developed for prioritizing failure modes or mechanisms in a given environment; (2) A time-series approach was used to model environmental stress variables involved and prioritize their effect on the power output drop; and (3) A procedure for developing a prediction model was proposed for the climatic specific condition based on accelerated degradation testing.
机译：这项研究的主要目的是开发一种预测光伏组件寿命的方法。这样做的目的是从经验总结到基于晶体硅光伏系统数据驱动案例研究的正式预测科学。对5至30岁的光伏系统的评估导致了当今缺乏系统的预测能力。制造商提供的晶体硅模块的保修期通常为20至25年。光伏组件的寿命终止（例如，从额定功率下降到20％的时间）通常是根据年场退化率（例如每年功率输出下降0.8％）使用简单的线性外推法计算得出的）。自DOE资助的喷气推进实验室（JPL）进行为期11年的平板太阳能阵列（FSA）项目以来，已经进行了有关太阳能光伏组件寿命预测的系统研究已有26年。从那时起，光伏组件在建筑材料和设计上发生了重大变化。尽管大多数旧的设计/材料上的场应力源的影响值得理解，但大多数场数据已过时。已经做出努力以使一些开发的技术适应当前技术，但是它们常常在范围上受限并且太依赖于先前结果的经验概括。已经基于加速测试提出了一些系统的方法，但是没有或很少进行实验研究。因此，业界目前尚不完全了解如何在20--30年的使用寿命内测试模块。这项研究的重点是在亚利桑那州坦佩/凤凰城的干热气候条件下，晶体硅光伏组件技术的行为。开发了一种三阶段方法：（1）开发了定量的故障模式，影响和临界分析（FMECA），用于在给定的环境中确定故障模式或机制的优先级； （2）使用时间序列方法对涉及的环境应力变量进行建模，并优先考虑它们对功率输出下降的影响； （3）提出了基于加速退化测试的气候特定条件预测模型的开发程序。

著录项

  • 作者

    Kuitche, Joseph Mathurin.;

  • 作者单位

    Arizona State University.;

  • 授予单位 Arizona State University.;
  • 学科 Industrial engineering.;Statistics.;Alternative Energy.
  • 学位 Ph.D.
  • 年度 2014
  • 页码 205 p.
  • 总页数 205
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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