干旱区生态环境知识资源中心(Arid): Tree-based ensemble methods for predicting the module temperature of a grid-tied photovoltaic system in the desert

Arid

DOI	10.1080/15435075.2021.1904945
	Tree-based ensemble methods for predicting the module temperature of a grid-tied photovoltaic system in the desert
	Ziane, Abderrezzaq; Dabou, Rachid; Necaibia, Ammar; Sahouane, Nordine; Mostefaoui, Mohammed; Bouraiou, Ahmed; Khelifi, Seyfallah; Rouabhia, Abdelkrim; Blal, Mohamed
通讯作者	Ziane, A (corresponding author), Route Reggane,BP 478, Adrar, Algeria.
来源期刊	INTERNATIONAL JOURNAL OF GREEN ENERGY
ISSN	1543-5075
EISSN	1543-5083
出版年	2021
英文摘要	The PV module temperature is a crucial parameter in the performance of a grid-tied PV station and it has an important effect on the PV system efficiency. In this work, we are interested in predicting the module temperature of a grid-tied photovoltaic system using tree-based ensemble methods, namely random forest and boosted decision tree. The linear least square method and the artificial neural network method were used as a frame of reference to evaluate the results of tree-based ensemble methods. The hyper-tuning of the tree ensemble method was done to optimize the model's parameters and to improve accuracy and prevent overfitting. All developed models have similar accuracy during the training and they are equally applicable for predicting PV module temperature. The results showed that during testing, the tree-based ensemble methods maintained their accuracy with R2 above 0.98. Meanwhile, the accuracy of other methods declined, which proves the utility of the tree-based ensemble over the classical method especially the ANN
英文关键词	Photovoltaic module temperature machine learning prediction
类型	Article ; Early Access
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000637246900001
WOS类目	Thermodynamics ; Green & Sustainable Science & Technology ; Energy & Fuels
WOS研究方向	Thermodynamics ; Science & Technology - Other Topics ; Energy & Fuels
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/352270
作者单位	[Ziane, Abderrezzaq; Dabou, Rachid; Necaibia, Ammar; Sahouane, Nordine; Bouraiou, Ahmed; Khelifi, Seyfallah; Rouabhia, Abdelkrim; Blal, Mohamed] CDER, Ctr Dev Energies Renouvelables, URERMS, Unite Rech Energie Renouvelables Milieu Saharien, Adrar 01000, Algeria; [Mostefaoui, Mohammed] Ecole Natl Super Informat, Sidi Bel Abbes, Algeria
推荐引用方式 GB/T 7714	Ziane, Abderrezzaq,Dabou, Rachid,Necaibia, Ammar,et al. Tree-based ensemble methods for predicting the module temperature of a grid-tied photovoltaic system in the desert[J],2021.
APA	Ziane, Abderrezzaq.,Dabou, Rachid.,Necaibia, Ammar.,Sahouane, Nordine.,Mostefaoui, Mohammed.,...&Blal, Mohamed.(2021).Tree-based ensemble methods for predicting the module temperature of a grid-tied photovoltaic system in the desert.INTERNATIONAL JOURNAL OF GREEN ENERGY.
MLA	Ziane, Abderrezzaq,et al."Tree-based ensemble methods for predicting the module temperature of a grid-tied photovoltaic system in the desert".INTERNATIONAL JOURNAL OF GREEN ENERGY (2021).