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Model estimation for solar generation forecasting using cloud cover data

delete2017-11-01
delete15
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OA
AI
D
Daniele Pepe
G
Gianni Bianchini *
A
Antonio Vicino
DOI:10.1016/j.solener.2017.08.086delete
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摘要

摘要

En 中文
This paper presents a parametric model approach to address the problem of photovoltaic generation forecasting in a scenario where measurements of meteorological variables, i.e., solar irradiance and temperature, are not available at the plant site. This scenario is relevant to electricity network operation, when a large number of PV plants are deployed in the grid. The proposed method makes use of raw cloud cover data provided by a meteorological service combined with power generation measurements, and is particularly suitable in PV plant integration on a large-scale basis, due to low model complexity and computational efficiency. An extensive validation is performed using both simulated and real data.
Keyword:
Photovoltaic generation
Modeling
Estimation
Forecasting
Cloud cover
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Solar Energy
IF:
6.6
论文数:
1.4W
被引数:
6.2W

机构

U
University of Siena
学者数:
463
论文数: 178
被引数: 0
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