Computation and validation of the Expected Value of Power of Two Terminal Series–Parallel PV arrays

IF 7.1 2区 工程技术 Q1 ENERGY & FUELS
Jesús M. Ceresuela , Daniel Chemisana , Nacho López
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引用次数: 0

Abstract

PV arrays are susceptible to various types of failures such as partial shading that can negatively affect their performance and efficiency. Studying the impact of these circumstances in the performance of the PV array is key for the development of more efficient PV systems. In this study, the definition of the expected value of power (EVP) that a PV array can produce under a random failure scenario is revised and improved. An algorithm to compute EVP that minimizes the number of simulations is developed and tested in three different PV arrays. Results show a 96.6% reduction on average of the number of simulations needed to compute the EVP for PV arrays made up of 9 modules. The model is validated through an experiment that reproduces the random fault scenario and determines the mean power produced by the PV arrays. For all three experiments, the computed EVP fits the experimental data with R2>0.995.

双终端串并联光伏阵列功率预期值的计算和验证
光伏阵列容易受到各种故障的影响,如部分遮光,从而对其性能和效率产生负面影响。研究这些情况对光伏阵列性能的影响是开发更高效光伏系统的关键。本研究修订并改进了光伏阵列在随机故障情况下可产生的预期功率值 (EVP) 的定义。开发了一种计算 EVP 的算法,可最大限度地减少模拟次数,并在三种不同的光伏阵列中进行了测试。结果显示,对于由 9 个模块组成的光伏阵列,计算 EVP 所需的模拟次数平均减少了 96.6%。该模型通过一项实验进行了验证,该实验重现了随机故障场景,并确定了光伏阵列产生的平均功率。在所有三个实验中,计算出的 EVP 与实验数据的 R2>0.995 相吻合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Sustainable Energy Technologies and Assessments
Sustainable Energy Technologies and Assessments Energy-Renewable Energy, Sustainability and the Environment
CiteScore
12.70
自引率
12.50%
发文量
1091
期刊介绍: Encouraging a transition to a sustainable energy future is imperative for our world. Technologies that enable this shift in various sectors like transportation, heating, and power systems are of utmost importance. Sustainable Energy Technologies and Assessments welcomes papers focusing on a range of aspects and levels of technological advancements in energy generation and utilization. The aim is to reduce the negative environmental impact associated with energy production and consumption, spanning from laboratory experiments to real-world applications in the commercial sector.
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