Prediction PV Power Based on Artificial Neural Networks

被引：1
|
作者：
Miloudi, Lalia [1 ]
Acheli, Dalila [1 ]
Mekhilef, Saad [2 ]
机构：
[1] Univ Boumerdes, Boumerdes, Algeria
[2] Univ Malaya, Kuala Lumpur, Malaysia
来源：
RENEWABLE ENERGY FOR SMART AND SUSTAINABLE CITIES: ARTIFICIAL INTELLIGENCE IN RENEWABLE ENERGETIC SYSTEMS | 2019年 / 62卷
关键词：
Artificial neural network (ANNs); Multiple-layer perceptron (MLP); Radial basic function (RBF); Photovoltaic (PV) power; HARDWARE IMPLEMENTATION; SIMULATION; TRACKING;
D O I：
10.1007/978-3-030-04789-4_13
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
The goal of this contribution is to estimate the power delivered by a multicrystals solar photovoltaic module based on artificial neural networks. Two structures of ANNs were tested: multiple-layer perceptron and radial basic function. The results obtained gave good coefficients of correlation, the statistical R-2-value obtained is about 0.96 to predict this important parameter.
引用
收藏
页码：122 / 128
页数：7
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