A simple and reliable empirical model with two predictors for estimating 1-minute diffuse fraction

Paulescu, Eugenia; Blaga, Robert

doi:10.1016/j.solener.2019.01.029

Cited by 30 publications

(21 citation statements)

References 35 publications

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“…Moreover, other restrictions were considered to examine whether the recorded solar irradiation data were within the physical limits. The intense transient effects of cloud enhancement can increase the ground horizontal solar irradiance for a 1 min time resolution. , As reported by Gueymard and Ruiz-Arias, the 1 min I g could occasionally be 50% larger than the extraterrestrial horizontal irradiance ( I 0 ), with the maximum clearness index ( K t ) between 1.0 and 1.5. Consequently, the limit of 0–1.5 for K t was considered in the quality control procedure.…”

Section: Materials and Methodsmentioning

confidence: 99%

Quantification of the Impact of Fine Particulate Matter on Solar Energy Resources and Energy Performance of Different Photovoltaic Technologies

2022

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Ambient fine particulate matter (PM2.5) could be a potential environmental risk for decreasing the available solar energy resources and solar photovoltaic (PV) power generation. This study quantifies the attenuation effects of PM2.5 on surface solar irradiance and system performance of different solar PV technologies in Hong Kong. The analysis based on observational irradiation data shows that the global horizontal irradiance decreased by more than 5% in most months under the conditions of PM2.5 concentration exceeding 33.5 μg/m 3 . During the experiment, the average PM2.5-related losses in the energy output of crystalline silicon and thin-film PV systems could be up to 7.00 and 9.73%, respectively. The measured energy outputs of the experimental PV modules suggest that PM2.5 affects the energy performance of thin-film solar cells with a larger band gap more significantly than that of crystalline silicon PV modules. Moreover, an increasing trend in the performance ratio of monocrystalline silicon, polycrystalline silicon, and copper indium gallium selenide PV systems with the increase of PM2.5 concentration is observed. In contrast, the amorphous silicon and cadmium telluride PV systems with a narrower spectral response range show a decreasing trend in the performance ratio over the experiment. Results indicate that the losses in the available solar energy resources and PV energy potential are expected to increase in areas where heavier PM2.5 pollution exists.

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Section: Materials and Methodsmentioning

confidence: 99%

Quantification of the Impact of Fine Particulate Matter on Solar Energy Resources and Energy Performance of Different Photovoltaic Technologies

2022

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“…Additional quality controls are applied on the raw data as described in Refs. [9,10]. A screening for cvasi-clear days is performed using the indicator I introduced in Ref.…”

Section: Datamentioning

confidence: 99%

Bias-Correction of Diffuse Solar Irradiance Modeled Through Parametric Models

Blaga

2022

Annals of West University of Timisoara - Physics

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In this paper, a bias-correction of clear-sky models in prediction of the diffuse solar irradiance is presented. High quality ground date from two networks is used for model input and validation: aerosol optical depth from AERONET and diffuse solar irradiance from BSRN. Four established clear-sky models are tested: REST2, Yang, PS and MAC2. Two types of bias-corrections are developed: i) a correction for multiple aerosol scattering (MSC), accounting for extinction at high turbidity, and ii) a general regression on the model errors as a function of Sun elevation angle (h) and turbidity (β) correction (MOS). While the impact of MSC proves marginal, the MOS correction shows good results. Two versions of MOS are developed, one on the global dataset and a site-specific adaptation. Both versions bring significant improvements over the original implementation of the models, while the site-specific version reduces the errors with a few additional percentage points. The aggregate nRMSE of the REST2 model is reduced from 17.8% (no correction) to 11.3% (global MOS) and 9.4% (site-specific MOS).

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“…Predicting global solar irradiance and its three components at a given location is crucial for the optimal design, installation, simulation, and evaluation of solar PV systems [ 1 ]. In particular, to measure diffuse horizontal irradiance ( Dh ), a pyranometer with sun blocking disk mounted on sun tracker can be a solution [ 2 , 3 ]. This represents high installation and maintenance costs that in developing countries such as Colombia, South America, can be difficult to afford, especially when underprivileged communities are the ones that will benefit from PV systems.…”

Section: Introductionmentioning

confidence: 99%

Prediction of site-specific solar diffuse horizontal irradiance from two input variables in Colombia

Miranda¹,

Fierro²,

Narváez³

et al. 2021

Heliyon

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Accurate measurements of diffuse irradiance are essential to design a solar photovoltaic system. However, in-situ radiation measurements in Colombia, South America, can be limited by the costs of the implementation of meteorological stations equipped with a pyranometer mounted on a sun tracker with a shading device, which is required to measure diffuse irradiance. Furthermore, the databases found in Colombia contain missing data, which raises the need for implementing models that are trained with very few features. In this paper, we introduce a methodology based on simple angle calculations and a regression model to predict half-hourly diffuse horizontal solar irradiance from only the measure of global horizontal irradiance and a geographic coordinate as inputs. Using measurements taken from the national solar radiation database for 6 different sites in Colombia and state-of-the-art machine learning models for regression, we validated the accuracy prediction of the proposed methodology. The results showed a prediction error ranging from 5 . 86 to 9 . 36 [ W/m 2 ], and a coefficient of determination ranging from 0 . 9974 to 0 . 9983. The data-set used along with the feature engineering process and the deep neural network model created can be found in a Github repository referenced in the paper.

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A simple and reliable empirical model with two predictors for estimating 1-minute diffuse fraction

Cited by 30 publications

References 35 publications

Quantification of the Impact of Fine Particulate Matter on Solar Energy Resources and Energy Performance of Different Photovoltaic Technologies

Quantification of the Impact of Fine Particulate Matter on Solar Energy Resources and Energy Performance of Different Photovoltaic Technologies

Bias-Correction of Diffuse Solar Irradiance Modeled Through Parametric Models

Prediction of site-specific solar diffuse horizontal irradiance from two input variables in Colombia

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