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Automation of Risk Priority Number Calculation of Photovoltaic Modules and Evaluation of Module Level Power Electronics.

机译:光伏模块风险优先级数字计算的自动化和模块级电力电子设备的评估。

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Part -- I.;This part of the thesis involves automation of statistical risk analysis of photovoltaic (PV) power plants. Statistical risk analysis on the field observed defects/failures in the PV power plants is usually carried out using a combination of several manual methods which are often laborious, time consuming and prone to human errors. In order to mitigate these issues, an automated statistical risk analysis (FMECA) is necessary. The automation developed and presented in this project generates about 20 different reliability risk plots in about 3-4 minutes without the need of several manual labor hours traditionally spent for these analyses. The primary focus of this project is to automatically generate Risk Priority Number (RPN) for each defect/failure based on two Excel spreadsheets: Defect spreadsheet; Degradation rate spreadsheet. Automation involves two major programs -- one to calculate Global RPN (Sum of Performance RPN and Safety RPN) and the other to find the correlation of defects with I-V parameters' degradations. Based on the generated RPN and other reliability plots, warranty claims for material defect and degradation rate may be made by the system owners.;Part -- II.;This part of the thesis involves the evaluation of Module Level Power Electronics (MLPE) which are commercially available and used by the industry. Reliability evaluations of any product typically involve pre-characterizations, many different accelerated stress tests and post-characterizations. Due to time constraints, this part of the project was limited to only pre-characterizations of about 100 MLPE units commercially available from 5 different manufacturers. Pre-characterizations involve testing MLPE units for rated efficiency, CEC efficiency, power factor and Harmonics (Vthd (%) and Ithd (%)). The pre-characterization test results can be used to validate manufacturer claims and to evaluate the product for compliance certification test standards. Pre-characterization results were compared for all MLPE units individually for all tested parameters listed above. The accelerated stress tests are ongoing and are not presented in this thesis. Based on the pre-characterizations presented in this report and post-characterizations performed after the stress tests, the pass/fail and time-to-failure analyses can be carried out by future researchers.
机译:第一部分:论文的这一部分涉及光伏电站的统计风险分析自动化。对光伏电站现场观察到的缺陷/故障的统计风险分析通常是使用几种人工方法的组合来进行的,这些方法通常很费力,费时且容易发生人为错误。为了减轻这些问题,有必要进行自动统计风险分析(FMECA)。在该项目中开发和展示的自动化功能在大约3-4分钟内生成了大约20个不同的可靠性风险图,而无需花费传统上用于这些分析的几个人工时间。该项目的主要重点是基于两个Excel电子表格为每个缺陷/故障自动生成风险优先级编号(RPN)。降级率电子表格。自动化涉及两个主要程序-一个用于计算全局RPN(性能RPN和安全RPN的总和),另一个用于查找缺陷与I-V参数退化的相关性。根据生成的RPN和其他可靠性图,系统所有者可以对材料缺陷和降级率提出保修索赔。第二部分-本部分涉及对模块级电力电子设备(MLPE)的评估,可商购并由工业使用。任何产品的可靠性评估通常都涉及特征前,许多不同的加速应力测试和特征后。由于时间限制,该项目的这一部分仅限于从5家不同制造商处购买的约100 MLPE装置的预特性。预先表征涉及测试MLPE单元的额定效率,CEC效率,功率因数和谐波(Vthd(%)和Ithd(%))。表征前的测试结果可用于验证制造商的要求并评估产品的符合性认证测试标准。比较了所有MLPE单元针对以上列出的所有测试参数的表征前结果。加速应力测试正在进行中,本文未介绍。根据本报告中介绍的前特性和在压力测试后进行的后特性,将来的研究人员可以进行通过/失败和失败时间分析。

著录项

  • 作者

    Moorthy, Mathan Kumar.;

  • 作者单位

    Arizona State University.;

  • 授予单位 Arizona State University.;
  • 学科 Alternative Energy.;Electrical engineering.;Engineering.
  • 学位 M.S.
  • 年度 2015
  • 页码 148 p.
  • 总页数 148
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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