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**Harvard**

Ehnberg, J. och Bollen, M. (2003) *SIMULATION OF GLOBAL SOLAR RADIATION BASED ON CLOUD OBSERVATIONS*.

** BibTeX **

@conference{

Ehnberg2003,

author={Ehnberg, Jimmy and Bollen, Math},

title={SIMULATION OF GLOBAL SOLAR RADIATION BASED ON CLOUD OBSERVATIONS},

booktitle={ISES SWC 2003},

isbn={ISBN:91-631-4740-8},

abstract={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 behavior. The yearly and daily variations can be described in a deterministic way while the random behavior 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. 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 for a more general model. For some calculations higher resolution could be needed. This can be obtained by including a stochastic model for the short-term variations. Simulations have been verified by using measured data.},

year={2003},

}

** RefWorks **

RT Conference Proceedings

SR Print

ID 2508

A1 Ehnberg, Jimmy

A1 Bollen, Math

T1 SIMULATION OF GLOBAL SOLAR RADIATION BASED ON CLOUD OBSERVATIONS

YR 2003

T2 ISES SWC 2003

SN ISBN:91-631-4740-8

AB 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 behavior. The yearly and daily variations can be described in a deterministic way while the random behavior 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. 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 for a more general model. For some calculations higher resolution could be needed. This can be obtained by including a stochastic model for the short-term variations. Simulations have been verified by using measured data.

LA eng

OL 30