Prediction of Rooftop Photovoltaic Power Generation Using Artificial Neural Network

Yun Nee Wee, A. Nor
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引用次数: 1

Abstract

Photovoltaic (PV) system is known as one of the most popular renewable energy types in generating electricity power. However, one of the drawbacks of PV system is that the performance of PV panel output is incompatible and affected due to changing climate condition. Hence, it is important to predict the optimal power output of PV system. This study will cover the implementation of PV system at the rooftop of Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia. Then, the optimal PV output power on the rooftop will be predicted using calculation method and Artificial Neural Network (ANN). The results have shown that ANN has the ability to predict the PV output close to the calculation method.
基于人工神经网络的屋顶光伏发电预测
光伏(PV)系统被认为是最受欢迎的可再生能源发电类型之一。然而,光伏系统的缺点之一是光伏板输出性能不兼容,且受气候条件变化的影响。因此,对光伏发电系统的最优输出功率进行预测是十分重要的。本研究将涵盖在马来西亚敦胡赛因大学电气与电子工程学院屋顶的光伏系统的实施。然后,屋顶上的最佳光伏输出功率将预测使用的计算方法和人工神经网络(ANN)。结果表明,人工神经网络具有接近计算方法的PV输出预测能力。
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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