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首页> 外文期刊>Journal of optoelectronics and advanced materials >Building Integrated Photovoltaic (BIPV)systems in Romania. Monitoring, modelling and experimental validation
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Building Integrated Photovoltaic (BIPV)systems in Romania. Monitoring, modelling and experimental validation

机译:在罗马尼亚构建集成光伏(BIPV)系统。监测,建模和实验验证

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摘要

The study is dedicated to the performance analysis of a BIPV (Building Integrated Photovoltaic) system developed in Romania and mounted on the building of the Polytechnic University of Bucharest (PUB); such systems highly depend on the fluctuation of incoming solar radiation reaching the PV system's surface. The estimation of the energy production of the BIPV system, on a short term period (two days), is considered as the main objective of the article. In the first part of the article, the BIPV demonstrative system is presented, as well as the meteorological station used. In the second part of the study, short-term solar irradiation forecasts are elaborated in two ways, based on the meteorological experimental datasets. First, forecasting tests are run using Autoregressive Integrated Moving Average (ARIMA) models. Second, artificial neural network (ANN) techniques are also evaluated (based on meteorological variables) in order to enhance the forecasts of solar irradiation. Finally, we conclude by validating the obtained results by real measurements determining the error range of forecasted values quantifying by the root-mean-square error (RMSE), as well as an estimation of energy production between forecasted and measured values.
机译:这项研究致力于对罗马尼亚开发并安装在布加勒斯特理工大学(PUB)建筑物上的BIPV(建筑物集成光伏)系统的性能进行分析;这样的系统高度依赖于到达光伏系统表面的太阳辐射的波动。在短期内(两天)估算BIPV系统的能源产量被认为是本文的主要目标。在本文的第一部分中,将介绍BIPV演示系统以及所使用的气象站。在研究的第二部分中,基于气象实验数据集,以两种方式详细阐述了短期太阳辐射预报。首先,使用自回归综合移动平均线(ARIMA)模型运行预测测试。其次,还评估了人工神经网络(ANN)技术(基于气象变量),以增强对太阳辐射的预报。最后,我们通过对实际测量值进行验证来确定获得的结果,这些测量值确定了由均方根误差(RMSE)量化的预测值的误差范围,并估算了预测值与测量值之间的能量。

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