Comparative performance analysis of grid-connected photovoltaic system by use of existing performance models
Comparative performance analysis of grid-connected photovoltaic system by use of existing performance models
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DOI：
10.1016/j.enconman.2017.08.001
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发表时间：
2017-10
影响因子：
10.4
通讯作者：
Elias Roumpakias;A. Stamatelos
中科院分区：
文献类型：
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作者：
Elias Roumpakias;A. Stamatelos
事实证明，对光伏发电装置的实际效率进行性能分析是一项具有挑战性的任务，对光伏发电园区 3 年监测运行数据的处理就证明了这一点。建立一个基于真实世界系统监测数据评估光伏电站性能的程序非常重要。空气质量和清晰度指数变化在这种情况下的作用已得到充分确定，并且分析是在这些因素的帮助下进行的。该分析有三个主要目标：（i）评估三个现有模型，（ii）性能比计算以及（iii）制定基于标准报告条件标准化的评估程序。监测数据的处理揭示了标准化效率的显着分散。 2013 年至 2015 年期间，年能源产量波动 10%。为了揭示这一事实背后的原因，分析这种波动非常重要。性能比分析、标准化程序和模型比较表明，光伏电池板的效率比运行第一年有所下降。然而，这是制造商保修条款涵盖的小幅下降。应用所提出的程序来分析旧装置的数据预计将提高对光伏电池板老化影响的理解和评估。
Performance analysis of real world efficiency of photovoltaic installations is proven to be a challenging task, as demonstrated by the processing of data from monitoring operation of a photovoltaic park for a period of 3 years. It is important to establish a procedure which evaluates the photovoltaic plant performance based on real world system monitoring data. The role of air mass and clearness index variations in this context is well established and the analysis is conducted with the aid of these factors. The analysis has three main objectives: (i) the evaluation of three existing models, (ii) performance ratio calculation and (iii) the formulation of an evaluation procedure based on normalization to Standard Reporting Conditions. Processing of the monitoring data reveals significant scatter in normalized efficiency. A 10% fluctuation in yearly energy production is observed in the period 2013–2015. It is important to analyze this fluctuation in order to shed light to the reasons behind this fact. Performance ratio analysis, normalization procedure and models comparison, point to a decrease in PV panel’s efficiency from the first year of operation. However, this is a small decrease covered by the terms of the manufacturer’s warranty. Application of the proposed procedure to the analysis of data from older installations is expected to improve understanding and assessment of aging effects in the PV panels.