Simulation of global solar radiation based on cloud observations

被引:111
作者
Ehnberg, JSG [1 ]
Bollen, MHJ [1 ]
机构
[1] Chalmers Univ Technol, Dept Elect Power Engn, SE-41296 Gothenburg, Sweden
关键词
solar power; Markov model; cloud coverage;
D O I
10.1016/j.solener.2004.08.016
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
A stochastic model for simulating global solar radiation on a horizontal surface has been developed for use in power systems reliability calculations. The importance of an appropriate model for global solar radiation has increased with the increased use of photovoltaic power generation. The global solar radiation shows not only regular yearly and daily variations but also a random behaviour. The yearly and daily variations can be described in a deterministic way while the random behaviour has a high correlation with the state of the atmosphere. The astronomic effects can easily be described mathematical with only some minor simplifications but the atmospheric effects are more complicated to describe. The transmittivity of solar radiation in the atmosphere depends on various factors, e.g. humidity, air pressure and cloud type. By using cloud observations as input for the simulations, the local meteorological conditions can be accounted for. The model is usable for any geographical location if cloud observations are available at the location or at locations with similar climatological conditions. This is especially useful for development countries where long-term solar radiation measurement can be hard to obtain. Cloud observations can be performed without any expensive equipment and have been a standard parameter for many years throughout the world. Standard observations are done according to the Oktas-scale. It is the interval between observations that sets the resolution of the simulation: the observations are normally only every hour or every third hour. The model can easily be combined with cloud coverage simulations, has been proposed, for a more general model. For some calculations higher resolution may be needed. This can be obtained by including a stochastic model for the short-term variations and simple model has been proposed. Errors and limitations of the model are estimated and discussed. (C) 2004 Elsevier Ltd. All rights reserved.
引用
收藏
页码:157 / 162
页数:6
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