Empirical Models for the Estimation of Solar Sky-Diffuse Radiation. A Review and Experimental Analysis

Pereira, Octavio; Gago, Eulalia Jadraque; Muneer, Tariq

doi:10.3390/en13030701

Cited by 32 publications

(25 citation statements)

References 60 publications

(97 reference statements)

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“…Once the LSTM-RNN model has been devised, the GHI prediction is made, followed by the estimation of the effective irradiance on the tilted plane of the PV module. Firstly, the calculation of the effective irradiance uses information from the two components of irradiance in the horizontal plane (direct and diffuse, since the albedo is zero in this case), calculated as a function of the clarity index (

), to obtain the diffuse fraction (

) [ 40 ]. Once this information is obtained, the conversion into the tilted plane is estimated with the diffuse irradiance [ 41 ] and the albedo:

where

is the albedo coefficient, considering that a value of

is the GHI and

is the tilted angle of the panels.…”

Section: Intra-day Power Forecasting Frameworkmentioning

confidence: 99%

Intra-Day Solar Power Forecasting Strategy for Managing Virtual Power Plants

Moreno

Santos

Martín

et al. 2021

Sensors

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Solar energy penetration has been on the rise worldwide during the past decade, attracting a growing interest in solar power forecasting over short time horizons. The increasing integration of these resources without accurate power forecasts hinders the grid operation and discourages the use of this renewable resource. To overcome this problem, Virtual Power Plants (VPPs) provide a solution to centralize the management of several installations to minimize the forecasting error. This paper introduces a method to efficiently produce intra-day accurate Photovoltaic (PV) power forecasts at different locations, by using free and available information. Prediction intervals, which are based on the Mean Absolute Error (MAE), account for the forecast uncertainty which provides additional information about the VPP node power generation. The performance of the forecasting strategy has been verified against the power generated by a real PV installation, and a set of ground-based meteorological stations in geographical proximity have been used to emulate a VPP. The forecasting approach is based on a Long Short-Term Memory (LSTM) network and shows similar errors to those obtained with other deep learning methods published in the literature, offering a MAE performance of 44.19 W/m2 under different lead times and launch times. By applying this technique to 8 VPP nodes, the global error is reduced by 12.37% in terms of the MAE, showing huge potential in this environment.

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), to obtain the diffuse fraction (

) [ 40 ]. Once this information is obtained, the conversion into the tilted plane is estimated with the diffuse irradiance [ 41 ] and the albedo:

where

is the albedo coefficient, considering that a value of

is the GHI and

is the tilted angle of the panels.…”

Section: Intra-day Power Forecasting Frameworkmentioning

confidence: 99%

Intra-Day Solar Power Forecasting Strategy for Managing Virtual Power Plants

Moreno

Santos

Martín

et al. 2021

Sensors

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“…The sensible and latent heat input are calculated using the well-known bulk transfer equations (e.g. Garratt, 1992):…”

Section: Energy Exchangementioning

confidence: 99%

Brief communication: Growth and decay of an ice stupa in alpine conditions – a simple model driven by energy-flux observations over a glacier surface

Oerlemans

Balasubramanian

Clavuot³

et al. 2021

The Cryosphere

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Abstract. We present a simple model to calculate the evolution of an ice stupa (artificial ice reservoir). The model is formulated for a cone geometry and driven by energy balance measurements over a glacier surface for a 5-year period. An “exposure factor” is introduced to deal with the fact that an ice stupa has a very rough surface and is more exposed to wind than a flat glacier surface. The exposure factor enhances the turbulent fluxes. For characteristic alpine conditions at 2100 m, an ice stupa may reach a volume of 200 to 400 m3 in early April. We show sensitivities of ice stupa size to temperature changes and exposure factor. The model may also serve as an educational tool, with which the effects of snow cover, switching off water during daytime, different starting dates, switching off water during high wind speeds, etc. can easily be evaluated.

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“…Total solar radiation was measured by a pyranometer (CMP11, Kipp & Zonen, Delftechpark, Delft, Netherlands). Pyranometers were connected to a data logger (34970A, Agilent Technologies, Inc., The clearness index k t was used for the calculation of γ diff, according to Berrizbeitia et al [57] and is valid for latitudes between 8.5 • and 28 • N.…”

Section: Drying Experimentsmentioning

confidence: 99%

“…The clearness index was used for the calculation of γdiff, according to Berrizbeitia et al[57] and is valid for latitudes between 8.5° and 28° N.…”

mentioning

confidence: 99%

Influence of Surface Reflection (Albedo) in Simulating the Sun Drying of Paddy Rice

2020

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The sun drying of agricultural products is a complicated process involving heat transfer, mass transfer, and variable weather conditions. Surface reflection (albedo), a crop’s radiative property, plays an essential role in energy balance, and understanding its contribution can improve the thermal analysis. In this study, field experiments were conducted in the Philippines to explore the influence of surface albedo on the sun drying of paddy rice. First, we implemented energy and mass balance equations in a transient model with the surroundings using a graphical programming language in Matlab/Simulink®. Second, we identified the influence of albedo on the sun drying model by using a sensitivity analysis. Third, we investigated the relationship of paddy rice albedo and the solar zenith angle. Lastly, we integrated the albedo function into the sun drying model. The simulation outputs were validated with field experiments. A better estimation of the measured exit temperature and instantaneous mass were obtained when a variable albedo was applied. This study makes clear that introducing a variable albedo has a positive impact on model improvement. This information is important for application in solar drying technologies, so that the drying process can be better assessed.

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Empirical Models for the Estimation of Solar Sky-Diffuse Radiation. A Review and Experimental Analysis

Cited by 32 publications

References 60 publications

Intra-Day Solar Power Forecasting Strategy for Managing Virtual Power Plants

Intra-Day Solar Power Forecasting Strategy for Managing Virtual Power Plants

Brief communication: Growth and decay of an ice stupa in alpine conditions – a simple model driven by energy-flux observations over a glacier surface

Influence of Surface Reflection (Albedo) in Simulating the Sun Drying of Paddy Rice

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