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Employing a Gene Expression-based Technique to Improve the Accuracy of Estimating the Total Generated Power by Neighboring Photovoltaic Systems

机译:采用基于基因表达的技术来提高邻近光伏系统估算总发电量的准确性

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The penetration of photovoltaic systems (PVs) is increasing and they are considered attractive options for electricity generation in distribution networks. This study focuses on estimating the total power generated by a group of neighboring PVs, spread in a locality while using a single pyranometer for measuring the solar irradiance. A new model has been proposed which employs the Gene Expression Programming (GEP) technique for developing a correlation between the distribution of the PVs and the irradiance measured by the pyranometer in estimating the total power generated. The proposed technique considers the geographic variability reduction and employs a Wavelet Transform technique for the calculations. The effective performance of the proposed model is validated using the real data collected by the Solar Project at the University of Queensland, Brisbane, Australia. The studies reveal that the proposed technique yields more accurate results against the other existing approaches.
机译:光伏系统(PVs)的普及率不断提高,它们被认为是配电网络中发电的有吸引力的选择。这项研究的重点是估算一组邻近的PV产生的总功率,这些PV散布在一个地方,同时使用单个日射强度计测量太阳辐照度。已经提出了一种新模型,该模型采用基因表达编程(GEP)技术来建立PV的分布与由日射强度计测得的辐照度之间的相关性,以估算产生的总功率。提出的技术考虑了地理变异性的降低,并采用小波变换技术进行计算。该模型的有效性能已通过澳大利亚布里斯班昆士兰大学太阳能项目收集的真实数据进行了验证。研究表明,与其他现有方法相比,所提出的技术可产生更准确的结果。

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