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Performance evaluation of stand alone solar photovoltaic system using ANFIS predicted solar radiation: An experimental case study

机译:使用ANFIS预测太阳辐射的独立太阳能光伏系统的性能评估:一个实验案例研究

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摘要

In South India, Tamil Nadu has enormous solar potential, because of its location on the Deccan plateau, with an annual average solar radiation ranging from 4-7 kWhm-2. This study, presents an adaptive neuro-fuzzy inference system (ANFIS) based modelling approach to predict the monthly global solar radiation (MGSR) in Tamil Nadu (India). The statistical performance parameters on predicted and measured values validate the model. In addition, a case study was discussed on the application of predicted solar radiation for sizing of the standalone PV system design including battery and their results were observed to be satisfactory when compared with the other earth regions found in the literature. A detailed investigation on the complete standalone PV system emphasize that the performance is satisfactory from predicted solar radiation and sizing co-efficients for any geographical location and particularly in isolated sites where the global solar radiation data is not always available.
机译:在印度南部,泰米尔纳德邦(Tamil Nadu)具有巨大的太阳能潜力,因为它位于Deccan高原上,年平均太阳辐射范围为4-7 kWhm-2。这项研究提出了一种基于自适应神经模糊推理系统(ANFIS)的建模方法,以预测印度泰米尔纳德邦的每月全球太阳辐射量(MGSR)。有关预测值和测量值的统计性能参数可验证模型。此外,还讨论了一个案例研究,该案例研究了将预测的太阳辐射应用于包括电池在内的独立光伏系统设计的规模,与文献中发现的其他地球区域相比,观察到的结果令人满意。对完整的独立光伏系统进行的详细调查强调,对于任何地理位置,特别是在并非始终可获得全球太阳辐射数据的偏远地区,预测的太阳辐射和上浆系数的性能均令人满意。

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