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FIELD DATA COLLECTION FOR QUANTIFICATION OF RELIABILITY ANDAVAILABILITY FOR PHOTOVOLTAIC SYSTEMS

机译:用于量化可靠性和光伏系统可靠性和AVAILAIF的现场数据收集

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Predicting reliability and availability is a data driven capability of interest to the entire photovoltaic community, from material suppliers to system owners. Sandia National Laboratories is developing a predictive model and a host of methodologies needed for creating accurate predictions. Operational and maintenance (O&M) data from operating systems is only one piece of a broader data set required to make accurate predictions. Estimating reliability and availability of fielded photovoltaic systems requires times-to-failure or times-to-suspension and downtime data for each of the major components of each system. This paper addresses the collection (data set) and organization (standardized format) of data necessary for reliability and availability analyses. Typically, for a large photovoltaic system the data are censored. The data sets are composed of a mixture of components with failure and components without failure. The data sets must be organized into times to failure, or suspension time in use—without failure, for each component that is being analyzed. To accurately estimate availability the various contributors to system downtime, such as corrective or preventative maintenance and grid perturbations, must also be identified and modeled. Preparation of the data for analysis usually consumes a significant percentage of the time required to generate a system reliability or availability estimate. A case study with data froma five year period of a fielded photovoltaic system is used to illustrate how a commercially available software tool for failure reporting and corrective action, XFRACAS~(TM), was adapted to efficiently organize field data and transfer data into a suite of software tools. The software tool Weibull++~(TM) was used to fit life distributions or growth models and to estimate parameters of the distributions. Another software tool, BlockSirn 7~(TM) was used for Reliability Blobk Diagram (RBD) development and simulation Of system reliability and availability. XFRACAS~(TM) is a Web-based application that provides the capability for point of source data entry into a centralized data base. With some slight modifications, XFRACAS~(TM) is capable of exporting data from the database that is properly organized and formatted for analysis:by the life data analysis or reliability growth analysis tools.
机译:预测可靠性和可用性是整个光伏社区感兴趣的数据驱动能力,从材料供应商到系统所有者。桑迪亚国家实验室正在开发一种预测模型和创造准确预测所需的一系列方法。操作系统的操作和维护(O&M)数据仅是进行准确预测所需的一件更广泛的数据集。估计有关光伏系统的可靠性和可用性,需要对每个系统的每个主要组件的时分失败或暂停和停机时间数据。本文讨论了可靠性和可用性分析所需的数据的集合(数据集)和组织(标准化格式)。通常,对于大的光伏系统,数据被删除。数据集由具有故障和组件的组件的混合组成,而不会发生故障。对于正在分析的每个组件,必须将数据集组织成失败,或者在使用中的暂停时间。要准确估计可用性,还必须识别和建模各种贡献者对系统停机时间的各种贡献者,例如纠正性或预防性维护和电网扰动。分析数据的准备通常消耗产生系统可靠性或可用性估计所需的显着百分比。使用来自Fielded光伏系统的五年期间数据的案例研究用于说明如何为失败报告和纠正措施,XFACAS〜(TM)进行市售软件工具,适用于有效地组织现场数据并将数据传输到套件中软件工具。软件工具Weibull ++〜(TM)用于适合寿命分布或增长模型,并估计分布的参数。另一个软件工具,BlockSirn 7〜(TM)用于可靠性BLOBK图(RBD)开发和系统可靠性和可用性的仿真。 XFacas〜(TM)是一种基于Web的应用程序,提供源数据进入到集中数据库的位置的功能。通过一些略微的修改,XFacas〜(TM)能够从数据库导出数据,该数据库被正确组织和格式化以进行分析:通过生命数据分析或可靠性增长分析工具。

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