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Three PV plants performance analysis using the principal component analysis method

机译:三种PV工厂使用主成分分析方法进行性能分析

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摘要

This paper presents a comparative analysis of the performance of three grid-connected photovoltaic power plants, of about 2kWp for each plant, using the principal component analysis (PCA) method. These systems include three silicon technologies. The analysis is based on the performance parameters described in the international standard 1EC 61724. To perform this comparative analysis, the energy production, the operational and the meteorological data are first collected for a period of time. The performance evaluation of PV plants is then performed based on several performance indicators such as Final Yield, Performance Ratio, System Losses, Capture Losses, Array Efficiency and Capacity Factor. Using the PCA method, the correlation between the performance parameters and the meteorological variables is then studied and analyzed. The resulting analysis shows that the Polycrystalline silicon technology is the most performing one. The annual average values of the Performance Ratio were found to be 86.66% for the polycrystalline against 84.76% and 83%, for the monocrystalline and amorphous, respectively. For the daily data, the PCA method reveals that the Performance Ratio is independent of the solar irradiation but it has a slight correlation with temperature and System Losses and a strong correlation with Capture Losses. The result shows also that the temperature acts slightly on the amorphous compared to the crystalline ones.
机译:本文采用了主要成分分析(PCA)方法对每种植物约2KWP的三个电网电力电厂的性能进行了比较分析。这些系统包括三种硅技术。该分析基于国际标准1C 61724中描述的性能参数。为了执行这种比较分析,首先在一段时间内收集能量产生,操作和气象数据。然后基于若干性能指标进行PV植物的性能评估,例如最终产量,绩效比,系统损失,捕获损耗,阵列效率和容量因子。使用PCA方法,然后研究和分析了性能参数与气象变量之间的相关性。所得到的分析表明,多晶硅技术最表现。对于单晶和无定形的,绩效比率的年平均值为84.76%和83%,分别为84.76%和83%。对于日常数据,PCA方法显示性能比与太阳照射无关,但它与温度和系统损失有轻微的相关性,以及与捕获损失的强烈相关性。结果表明,与结晶物相比,温度略微作用于无定形。

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  • 来源
    《Energy》 |2020年第15期|118315.1-118315.14|共14页
  • 作者单位

    Laboratory of Industrial Engineering Faculty of Science and Technology University Sultan Moulay Slimane Beni Mellal Morocco;

    Laboratory of Industrial Engineering Faculty of Science and Technology University Sultan Moulay Slimane Beni Mellal Morocco;

    Laboratory of Industrial Engineering Faculty of Science and Technology University Sultan Moulay Slimane Beni Mellal Morocco;

    Innovation Lab for Operations Mohammed Ⅵ Polytechnic University Benguerir Morocco;

    Laboratory of Industrial Engineering Faculty of Science and Technology University Sultan Moulay Slimane Beni Mellal Morocco;

    Faculty of Sciences Semlalia Cadi Ayyad University Marrakech Morocco;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    PCA; Performance ratio; Final yield; Solar photovoltaic plant; Silicon PV technologies;

    机译:PCA;绩效比例;最终产量;太阳能光伏厂;Silicon PV Technologies;

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