A point prediction method based automatic machine learning for day-ahead power output of multi-region photovoltaic plants

Solar power generation (SPG) is essentially dependent on spatial and meteorological characteristics which makes the planning and operation of power systems difficult. To promote the integration of solar power into electric power grid, accurate prediction of geographically distributed SPG is needed....

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Veröffentlicht in:	Energy Jg. 223; S. 120026
Hauptverfasser:	Zhao, Wei, Zhang, Haoran, Zheng, Jianqin, Dai, Yuanhao, Huang, Liqiao, Shang, Wenlong, Liang, Yongtu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Oxford Elsevier Ltd 15.05.2021 Elsevier BV
Schlagworte:	algorithms Automatic machine learning Electric power Electric power distribution Electric power generation Electric power grids Electric power systems Electricity distribution energy Genetic algorithm Genetic algorithms Geographical distribution Japan Learning algorithms Machine learning Multi-region photovoltaic plants Photovoltaic cells Photovoltaics power generation Power plants prediction Prediction models solar collectors Solar energy Solar power Solar power generation Solar power generation prediction Weather Solar power generation prediction Automatic machine learning Multi-region photovoltaic plants Genetic algorithm
ISSN:	0360-5442, 1873-6785
Online-Zugang:	Volltext
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