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The present study aims to comprehensively assess the solar irradiance patterns in the western zone of the Mantaro Valley, a region of ecological and agricultural significance in the central Peruvian Andes. Leveraging radiation data from the Baseline surface Radiation Network (BSRN) sensors located in the Huancayo Geophysical Observatory (HYGO-12.04°S,75.32°W, 3350 masl) spanning from 2017 to 2022, the research delves into the seasonal variations and trends in surface solar irradiance components. Actually, the study investigates the diurnal and seasonal variations of solar irradiance components, namely diffuse (EDF), direct (EDR), and global (EG) irradiance. Results demonstrate distinct peaks and declines across seasons, with EDR and EDF exhibiting opposing seasonal trends, influencing the overall variability in, EG. Peaks of, EG occurred in spring (3.32 MJ m-2 h-1 at noon), particularly during October (24.14 MJ m-2 day-1), probably associated with biomass-burning periods and heightened aerosol optical depth (AOD). These findings highlight the impact of biomass-burning aerosols on solar radiation dynamics in the region. In general, the seasonal variability of, EG on the HYGO is lower than that observed in other regions of South America at higher latitudes and reach its maximums during spring months. Moreover, the research evaluates various irradiation models to establish correlations between sunshine hours, measured with a solid glass sphere heliograph, and, EG and EDF at different time scales, showing acceptable accuracy to predict. In addition, the sigmoid logistic function emerges as the most effective in correlating the hourly diffuse fraction (…) and the hourly clearness index (…), showcasing superior performance compared to alternative functions and exhibiting strong statistical significance and providing valuable insights for future solar radiation forecasting and modeling efforts. This study offers valuable insights for solar radiation forecasting and modeling efforts, emphasizing the importance of interdisciplinary research for solar power generation, sustainable development and climate resilience in mountainous regions like the Peruvian Andes. [ABSTRACT FROM AUTHOR]

The transition to a low-carbon economy is one of the main challenges of our time. In this context, solar energy, along with many other technologies, has been developed to optimize performance. For example, solar trackers follow the sun's path to increase the generation capacity of photovoltaic plants. However, several factors need consideration to further optimize this process. Important variables include the distance between panels, surface reflectivity, bifacial panels, and climate variations throughout the day. Thus, this paper proposes an artificial intelligence-based algorithm for solar trackers that takes all these factors into account—mainly weather variations and the distance between solar panels. The methodology can be replicated anywhere in the world, and its effectiveness has been validated in a real solar plant with bifacial panels located in northeastern Brazil. The algorithm achieved gains of up to 7.83% on a cloudy day and obtained an average energy gain of approximately 1.2% when compared to a commercial solar tracker algorithm. [ABSTRACT FROM AUTHOR]

The present study aims to comprehensively assess the solar irradiance patterns in the western zone of the Mantaro Valley, a region of ecological and agricultural significance in the central Peruvian Andes. Leveraging radiation data from the Baseline surface Radiation Network (BSRN) sensors located in the Huancayo Geophysical Observatory (HYGO-12.04°S,75.32°W, 3350 masl) spanning from 2017 to 2022, the research delves into the seasonal variations and trends in surface solar irradiance components. Actually, the study investigates the diurnal and seasonal variations of solar irradiance components, namely diffuse (EDF), direct (EDR), and global (EG) irradiance. Results demonstrate distinct peaks and declines across seasons, with EDR and EDF exhibiting opposing seasonal trends, influencing the overall variability in, EG. Peaks of, EG occurred in spring (3.32 MJ m−2 h−1 at noon), particularly during October (24.14 MJ m-2 day-1), probably associated with biomass-burning periods and heightened aerosol optical depth (AOD). These findings highlight the impact of biomass-burning aerosols on solar radiation dynamics in the region. In general, the seasonal variability of, EG on the HYGO is lower than that observed in other regions of South America at higher latitudes and reach its maximums during spring months. Moreover, the research evaluates various irradiation models to establish correlations between sunshine hours, measured with a solid glass sphere heliograph, and, EG and EDF at different time scales, showing acceptable accuracy to predict. In addition, the sigmoid logistic function emerges as the most effective in correlating the hourly diffuse fraction (KDh) and the hourly clearness index (KTh), showcasing superior performance compared to alternative functions and exhibiting strong statistical significance and providing valuable insights for future solar radiation forecasting and modeling efforts. This study offers valuable insights for solar radiation forecasting and modeling efforts, emphasizing the importance of interdisciplinary research for solar power generation, sustainable development and climate resilience in mountainous regions like the Peruvian Andes.

The transition to a low-carbon economy is one of the main challenges of our time. In this context, solar energy, along with many other technologies, has been developed to optimize performance. For example, solar trackers follow the sun’s path to increase the generation capacity of photovoltaic plants. However, several factors need consideration to further optimize this process. Important variables include the distance between panels, surface reflectivity, bifacial panels, and climate variations throughout the day. Thus, this paper proposes an artificial intelligence-based algorithm for solar trackers that takes all these factors into account—mainly weather variations and the distance between solar panels. The methodology can be replicated anywhere in the world, and its effectiveness has been validated in a real solar plant with bifacial panels located in northeastern Brazil. The algorithm achieved gains of up to 7.83% on a cloudy day and obtained an average energy gain of approximately 1.2% when compared to a commercial solar tracker algorithm.

Bifacial photovoltaic modules along highways provide energy supply and act as sound barriers simultaneously. This study examines the impact on energy production when incorporating sound barriers with varying light reflection properties into this integrated solar infrastructure along roadways. Specifically, we use advanced computational simulations to analyze the effects of integrating black, ideal specular, and ideal diffuse (Lambertian) reflectors into an existing highway solar power plant located in the Netherlands. Our analysis combines realistic spectro-angular irradiance data as input with our in-house reverse ray tracing software. Our calculations show that for an east-west facing system, an ideal diffuse reflector increases the annual yield by 70%, while a specular reflector decreases the yield due to shading. Most notably, the diffuse reflector doubles the energy yield during winter months, thereby offering a pathway to decrease the seasonal energy demand and supply gap.

A novel automatic filtering methodology is proposed for 1-min GHI and DIF data using surface measurements obtained at five sites located in various climate zones of Argentina. The methodology contemplates DIF information obtained through the use of a shadowband or shading ring instead of the shading ball that requires a solar tracker. Three different flags are presented for suspicious or erroneous data identified by the filters of the methodology, which respond to the weight or strictness of the corresponding filter. The methodology uses filters established in the literature and proposes new filters capable of identifying slight misalignments of the shadowband as well as measurements below a minimum threshold empirically established for heavily overcast or thunderstorm conditions. A statistical analysis based on data obtained at a high-quality reference station and the modification of a pre-existing methodology is also presented. In general terms and at all sites, it is observed that the total amount of suspicious data increases significantly as the solar zenith angle increases. Overall, the methodology is able to identify and flag 15.0–44.6% erroneous or suspicious values, depending on site. The proposed methodology is applicable at any world station where the global and diffuse irradiance components are both measured. [ABSTRACT FROM AUTHOR]

In the literature several models have been derived by different authors in order to predict the solar irradiance intensity over inclined surfaces, however for the most models accuracy at various inclinations have not been verified. The study evaluated the estimation of solar irradiance at different tilt angles by means of different models based on the experimental measurements. For this purpose, two groups of models (isotropic and anisotropic) were carried out: the first group of models was used for estimating the diffuse solar irradiance component, and the second group was used for estimating the global solar irradiance. Five models have been selected and implemented for the estimation of the diffuse solar irradiance component, and five models have been selected for the estimation of global solar irradiance. The results of the analysis were compared with local experimental measurements for diffuse radiation and global irradiance. There are three tilt angles (0°, 30°, 60°) and a two-axis tracking system has been determent for comparison experiments with the model estimated results. The results showed all the selected models generated an error percentage in both the diffuse and global irradiance investigations. [ABSTRACT FROM AUTHOR]

Modules utilized in vehicle-integrated photovoltaics (VIPV) have particularities that make them differ from standard PV modules. These particularities are related to their curvature and operating conditions (changing locations, orientations, etc.) and they need to be addressed in the characterization. A vital characterization test is the angular response test, which allows obtaining the electrical response of the module under different angles of incidence and orientations. Results from these tests on real commercial modules presented some dispersion, which is related to diffuse irradiance. Two outdoors experiments involving a programmable dual-axis tracker were conducted to verify its impact: the first one was made with a 1D highly curved module under cloudy sky conditions to identify the effect of diffuse irradiance on such modules and the second experiment assessed the angular response of a 2D commercial curved module under clear sky conditions. Based on the findings, recommendations are given to minimize dispersion in outdoors angular response measurements. [ABSTRACT FROM AUTHOR]

The decomposition of global horizontal irradiance into its direct and diffuse components is critical in many applications. To guarantee accurate results in practice, the existing separation techniques need to be validated against reference ground measurements from a variety of stations. Here, four versions of the recent GISPLIT model are compared to a strong benchmark constituted from nine leading models of the literature. The validation database includes ≈24 million data points and is constituted of one calendar year of 1-min high-quality data from 118 research-class world stations covering all continents and all five major Köppen-Geiger climates. The results are analyzed with various statistical metrics to be as generalizable and explicative as possible. It is found that even the simpler GISPLIT version reduces the mean site RMSE of the best benchmark model by ≈11 % for the direct component and ≈17 % for the diffuse component. The improvement reaches ≈17 % and ≈25 %, respectively, when using the best GISPLIT version. The improvements are more important in cases of highly variable sky cloudiness, per the CAELUS sky classification scheme. A ranking analysis shows that all four versions of GISPLIT ranked higher than the benchmark models, and that the use of machine learning significantly improves the separation performance. In contrast, only marginal improvements are obtained through preliminary conditioning by Köppen-Geiger climate class. Overall, it is concluded that GISPLITv3, which is not dependent on climate class but makes use of machine learning for the most challenging sky conditions, can be asserted as the new high-performance quasi-universal separation model. [Display omitted] • Global validation database built from stations unused during models' development. • Separation modeling performance has unevenly improved during the latest two decades. • 1-min separation conditioned by sky variability classes now proved highly effective. • All GISPLIT versions outperform all benchmark models under all climatic conditions. • The global ML-assisted GISPLITv3 is the recommended component-separation model. [ABSTRACT FROM AUTHOR]

In situ hyperspectral remote-sensing reflectance ( R r s (λ) ) is used to derive water quality products and perform autonomous monitoring of aquatic ecosystems. Conventionally, above-water R r s (λ) is estimated from three spectroradiometers which measure downwelling planar irradiance ( E d (λ) ), sky radiance ( L s (λ) ), and total upwelling radiance ( L t (λ) ), with a scaling of L s (λ) / E d (λ) used to correct for surface-reflected radiance. Here, we incorporate direct and diffuse irradiance, ( E d d (λ) ) and E d s (λ) ), from a hyperspectral pyranometer (HSP) in an R r s (λ) processing algorithm from a solar-tracking radiometry platform (So-Rad). HSP measurements of sun and sky glint (scaled E d d (λ) / E d (λ) and E d s (λ) / E d (λ) ) replace model-optimized terms in the 3C (three-glint component) R r s (λ) algorithm, which estimates R r s (λ) via spectral optimization of modelled atmospheric and water properties with respect to measured radiometric quantities. We refer to the HSP-enabled method as DD (direct-diffuse) and compare differences in R r s (λ) and R r s (λ) variability (assessed over 20 min measurement cycles) between 3C and DD as a function of atmospheric optical state using data from three ports in the Western Channel. The greatest divergence between the algorithms occurs in the blue part of the spectrum where DD has significantly lower R r s (λ) variability than 3C in clearer sky conditions. We also consider R r s (λ ) processing from a hypothetical two-sensor configuration (using only the L t (λ) spectroradiometer and the HSP and referred to as DD2) as a potential lower-cost measurement solution, which is shown to have comparable R r s (λ ) and R r s (λ ) variability to DD in clearer sky conditions. Our results support that the HSP sensor can fulfil a dual role in aquatic ecosystem monitoring by improving precision in R r s (λ) alongside its primary function to characterize aerosols. [ABSTRACT FROM AUTHOR]

The increasing demand for energy in the building sector is mostly due to heat, ventilation and air conditioning (HVAC) systems. In the absence of the clear sky beam optical depth (CSBOD) and clear sky diffuse optical depth (CSDOD), there is a challenge to determine the solar heat gain for different orientations of the surface areas of buildings for HAVC design. The purpose of this research is to determine CSBOD and CSDOB from the available solar radiation data for the calculation of the cooling load in buildings. The numerical values of CSBOD and CSDOD are determined from simulations using three years of measured clear sky beam and diffuse irradiance data for the Umlazi area as a case study. From these results, the autoregressive integrated moving average (ARIMA) for both CSBOD and CSDOD was obtained, with ARIMA (2,1,1) (1,1,0) [12] and ARIMA (3,1,0) (1,1,0) [12] for CSBOD and CSDOD, respectively. The obtained values of 0.68073 and 2.64413 for CSBOD and CSDOD, respectively, were used to calculate the cooling load due to the solar irradiance heat gain for the hottest month of February in a newly built room in Mangosuthu University of Technology (MUT). The value of 1124 W was obtained using the radiant time series method (RTSM). A further study can be performed to use these models for the long-term forecasting of the solar radiation cooling load for optimal control of the HVAC systems. [ABSTRACT FROM AUTHOR]

Shadow-bands are a low cost alternative when a precision solar tracker is not available. Adequate precision may be achieved if the measured diffuse irradiance is corrected to account for the sky portion blocked by the shadow-band. The isotropic sky assumption leads to a systematic under estimation of diffuse irradiance. Several correction methods have been proposed to take into account the anisotropic effects. However, their performance at a given site depends on the dominant local climate. In this work, it is shown that the local adaptation of shadow band correction methods results in a significant improvement in the diffuse irradiance measurement's accuracy. Nine well-known correction methods are implemented and tested (both in their original and locally adapted versions) for the Pampa Húmeda region of southeastern South America. In absence of local adaptation, only one of the pre-existing methods improves the simple isotropic model. All locally adapted versions perform similarly well and outperform significantly the original methods. A new model based on the parametrization of Battle's model is proposed. It provides the best performance compared to all locally adapted pre-existing models, under all-sky and discriminated sky conditions. • Nine preexisting shadow-band correction methods are tested in the Pampa Húmeda region. • The impact of local adaptation on the correction methods is quantified. • A new method is proposed, based on Batlle's parametrization. • It outperforms previous methods both under all-sky and discriminated sky conditions. [ABSTRACT FROM AUTHOR]

In situ hyperspectral remote-sensing reflectance (Rrs(λ)) is used to derive water quality products and perform autonomous monitoring of aquatic ecosystems. Conventionally, above-water Rrs(λ) is estimated from three spectroradiometers which measure downwelling planar irradiance (Ed(λ)), sky radiance (Ls(λ)), and total upwelling radiance (Lt(λ)), with a scaling of Ls(λ)/Ed(λ) used to correct for surface-reflected radiance. Here, we incorporate direct and diffuse irradiance, (Edd(λ)) and Eds(λ)), from a hyperspectral pyranometer (HSP) in an Rrs(λ) processing algorithm from a solar-tracking radiometry platform (So-Rad). HSP measurements of sun and sky glint (scaled Edd(λ)/Ed(λ) and Eds(λ)/Ed(λ)) replace model-optimized terms in the 3C (three-glint component) Rrs(λ) algorithm, which estimates Rrs(λ) via spectral optimization of modelled atmospheric and water properties with respect to measured radiometric quantities. We refer to the HSP-enabled method as DD (direct-diffuse) and compare differences in Rrs(λ) and Rrs(λ) variability (assessed over 20 min measurement cycles) between 3C and DD as a function of atmospheric optical state using data from three ports in the Western Channel. The greatest divergence between the algorithms occurs in the blue part of the spectrum where DD has significantly lower Rrs(λ) variability than 3C in clearer sky conditions. We also consider Rrs(λ) processing from a hypothetical two-sensor configuration (using only the Lt(λ) spectroradiometer and the HSP and referred to as DD2) as a potential lower-cost measurement solution, which is shown to have comparable Rrs(λ) and Rrs(λ) variability to DD in clearer sky conditions. Our results support that the HSP sensor can fulfil a dual role in aquatic ecosystem monitoring by improving precision in Rrs(λ) alongside its primary function to characterize aerosols.

• Hay transposition model is modified to account for the row shading in PV plants. • Distribution of all irradiance components along the width of PV rows is modelled. • Diffuse irradiance masking is responsible for 50–80% of total shading losses. • Effect of row spacing and module arrangement on the shading losses is quantified. • 1 × 20 module arrangement is the best for inverters with multiple MPPT. Ground-mounted PV plants with multiple parallel mounting structure rows became the most common type of PV systems, where the shading of the adjacent rows results in significant energy losses. This paper presents a detailed modelling method of the inter-row shading to calculate irradiance distribution along the width of the PV rows. A modification of the Hay transposition model is proposed to account for the shading of the sky diffuse, circumsolar, and ground-reflected irradiance components. The effect of the uneven irradiance on the power output is considered by the cellwise calculation and aggregation of the I-V characteristics. The method is demonstrated by a case study, where the annual energy production and the reflection, shading, and cable losses are calculated for different string arrangements and row spacings. The proposed detailed shading model is compared to a simple shading calculation, where only the shading of the beam irradiance is considered. This simple method underestimates the shading losses by 50–80%, which underlines the importance of the proper calculation of the diffuse irradiance masking losses. The electrical mismatch losses due to the shading are compared for different string arrangements, where the best arrangement is also influenced by the number of the maximum power point trackers. As a general conclusion, the modules at the same height should be connected to the same string to minimise the shading losses. The presented method can improve the accuracy of PV simulations and the optimisation of the shading-related design parameters, like the module orientation and row spacing. [ABSTRACT FROM AUTHOR]

This paper presents the results from an extensive interlaboratory comparison of angular‐dependent measurements on encapsulated photovoltaic (PV) cells. Twelve international laboratories measure the incident angle modifier of two unique PV devices. The absolute measurement agreement is ±2.0% to the weighted mean for angles of incidence (AOI) ≤ 65°, but from 70° to 85°, the range of measurement deviations increases rapidly from 2.5% to 23%. The proficiency of the measurements is analysed using the expanded uncertainties published by seven of the laboratories, and it is found that most of the angular‐dependent measurements are reproducible for AOI ≤ 80°. However, at 85°, one laboratory's measurement do not agree to the weighted mean within the stated uncertainty, and measurement uncertainty as high as 16% is needed for the laboratories without uncertainty to be comparable. The poor agreement obtained at 85° indicates that the PV community should place minimal reliance on angular‐dependent measurements made at this extreme angle until improvements can be demonstrated. The cloud‐based Daidalos ray tracing model is used to simulate the angular‐dependent losses of the mono‐Si device, and it is found that the simulation agrees to the median measurement within 0.6% for AOI ≤ 70° and within 1.4% for AOI ≤ 80°. Finally, the impact that the angular‐dependent measurement deviations have on climate specific energy rating (CSER) is evaluated for the six climates described in the IEC 61853‐4 standard. When one outlier measurement is excluded, the angular‐dependent measurements reported in this work cause a 1.0%–1.8% range in CSER and a 1.0%–1.5% range in annual energy yield, depending on the climate. [ABSTRACT FROM AUTHOR]

As cooling and heating energy consumptions of buildings are closely related to outdoor climate variations, the reliability of building energy simulation results is significantly influenced by the accuracy of weather data being used. We intend to construct a new typical meteorological year (TMY) for Taipei. As no beam or diffuse solar irradiance data have been recorded at local weather stations, a preliminary study on the influences of currently available hourly solar diffuse fraction models (DFMs) to the building cooling loads was performed. A 2.30%–5.18% range of annual cooling load variation was observed, which drove a need for searching suitable DFMs. To this end, the observed diffuse irradiance data of an in-situ experiment was compared to the DFM modeled values to identify the suitable DFM. It was found that Kuo's model, which has its coefficient been adapted to the local weather and further uses solar altitude, the daily clearness index as predicting variables, performed best and was used herein. The representativeness against the long-term climate of the three antiquated TMYs and the new one was discussed with a simulation-based comparison from 12 existing buildings. The reliability and accuracy of the new TMY in representing the local climate conditions are much improved. • Hourly solar diffuse fraction model suitable for generating TMY was identified. • Uncertainties of diffuse fraction models on building cooling loads were discussed. • The influences of solar fraction model on building cooling energy are 2.30%–5.18%. • A new TMY representing recent climate for Taipei, Taiwan was constructed. • Historical TMYs were compared on a building-energy-simulation basis. [ABSTRACT FROM AUTHOR]

• Novel efficient approach to separate 1-min GHI into its direct and diffuse components. • Separation conditioned by dynamically constraining 1-min sky conditions with CAELUS. • Only marginal benefit of also considering the station's Köppen-Geiger primary climate. • Supporting the GHI separation by extreme gradient boosting does improve results. • RMSE of DNI prediction at 66 unseen sites combined is ≤16 % for all model versions. The separation of global horizontal irradiance (GHI) into its direct and diffuse components is necessary in a variety of applications, most specially in solar energy utilization, where knowledge of direct normal irradiance (DNI) is of paramount importance. Here a novel and efficient model, referred to as GISPLIT, is presented to perform this task accurately, using time series of measured data at 1-min resolution. To better describe the radiative effects of different cloud situations, the model takes advantage of a preliminary classification of the sky conditions into six sky types. An empirical submodel is assigned to each sky class to split GHI into its components, using a limited number of predictors that are related to GHI's magnitude and variability, and to coincident estimates of the clear-sky irradiance components. Those submodels are trained and validated using rigorously quality-assessed measurements from 120 radiometric stations over all continents and all five major Köppen-Geiger (KG) climate classes, totaling ≈64 million valid data points. Four model versions are evaluated using training data for either all KG climate regions combined or conditioned by KG climate, and either with or without additional support from machine learning. The validation of the four versions suggests that the conditioning by KG climate does not add any significant benefit over the "all-climates" training approach and that, overall, the model version trained with data from all KG climates combined and supported by machine learning generally predicts DNI with the best RMSE results at unseen sites, although with little difference over the other versions. [ABSTRACT FROM AUTHOR]

In this study, we use the data of Polish typical meteorological years and 15 transposition models to obtain global solar irradiance on sloped surfaces to calculate solar irradiance on external building partitions, solar gains, heating demands, and primary nonrenewable energy for heating and domestic hot water (EPH+W) of two typical Polish residential buildings, each for two variants in five locations. In relation to TMYs, annual solar gains were lower by −31% and −36% on average in a single and multifamily building, respectively, and the annual heating demands increased by 9% and 16%, respectively. Consequently, averaged EPH+W in relation to TMYs rose by 1.4 kWh/m2 and 4.5 kWh/m2, respectively. The mean differences between TMYs and the new method from the recently published EN-ISO 52010 standard for test Building 1 were 1.6 and 1.2 kWh/m2, for Variants 1 and 2, respectively. Similarly, for test Building 2, the mean differences were 5.1 kWh/m2 and 3.9 kWh/m2, respectively. This means that the simulation model that is chosen has a visible impact on a building’s energy performance indicators and its rating without any changes in the physical structure and use of the building.

An empirical method of the PM10 to reduce the global irradiance has been developed with the observed 14-day data in 2009 at the Erdene site in the Asian dust source region of Mongolia. The observed data at a 10-min interval are used to get all parameters for the estimation of the beam and diffuse irradiances except for the properties of Asian dust aerosols such as the single scattering albedo (ω0), scattering transmittance (τa) and transmittance due to aerosol absorption (τaa) using the parametric solar radiation model. To determine these parameters, firstly τa is calculated with the observed global irradiance for a given ω0 value using all sampled data. And then the estimated τas are correlated with observed dust concentration to find an optimal regression equation between τa and the observed dust concentration. The optimal ω0 value is found that the error between the calculated global irradiance using the optimal regression equation and the observed global irradiance becomes minimum. It is found that the single scattering albedo of Asian dust aerosol (ω0) is 0.85 and its reduction rate of the global irradiance is up 34.4% of that of the dust free atmosphere for the heavy dust case. This reduction is mainly contributed by the reduction of the beam irradiance whereas the diffuse irradiance enhances slightly (about 1.8%) the global irradiance. The presently developed optimal regression equation between τa and the observed dust concentration has a great potential to estimate the impact of Asian dust aerosols on the solar irradiance. [ABSTRACT FROM AUTHOR]

• A normal distribution model for diffuse radiation is proposed. • The normal distribution is related to the incident angle of direct radiation. • Weather and season do not influence the normal distribution. • Weather only influences the value of diffuse radiation. • The normal distribution has higher accuracy than other models. Solar radiation is an important factor in the design and simulation of transparent systems. The angle-dependent optical properties of transparent systems are hard to predict because it is difficult to obtain the incidence angle of diffuse irradiance. In this paper, a normal distribution model is proposed for diffuse radiation. It is assumed that diffuse irradiance follows normal distribution. The expectation of the distribution is the incidence angle of direct radiation, while the variance is expressed as the isotropy index. Through the experimental results for a transparent double-glazing (DG) system, it is found that the values of isotropy index are related to the incidence angle of direct radiation. The normal distribution model is evaluated with the diffuse irradiance map given by the researchers in SRRL. And then the indoor diffuse irradiance through the DG system is calculated by the normal distribution model and other distribution models. The calculated results are compared with the experimental results. It is assumed that the outdoor diffuse irradiance incident on a DG system follows normal distribution. The diffuse irradiance and transmittance through a DG system are predicted by the interface energy-balance method. The predicted diffuse irradiance and transmittance by the model are compared with measured values and those predicted by other distribution models. The predicted indoor irradiance or transmittance for the proposed normal distribution model has better accuracies than the Perez and isotropic model. [ABSTRACT FROM AUTHOR]

Highlights • Model of the impact of any incident radiance condition on the output of devices. • Consideration of angle of incidence effects on the spectral responsivity. • And of spectral radiance of the sky and ground reflected irradiation on tilted surfaces. • Procedure for the correction of angular and spectral effects on PV devices. • Reduction in uncertainty for measurements under diffuse light sources. Abstract In the domain of solar irradiance measurements, a wide range of irradiation conditions exist in indoor and outdoor environments. While the primary calibration of reference solar irradiance detectors is usually performed using only direct irradiance, secondary calibrations are conducted with a diffuse incident irradiance component. If the optical detector properties vary between the reference and the device under test, spectral and angular dependencies of incident irradiance and the detectors' responsivities may result in a mismatch when referring to defined reference conditions. This becomes particularly significant when photovoltaic (PV) devices are measured under global natural sunlight. In the field of PV metrology, diffuse solar irradiance is commonly considered to be isotropic, which is generally not the case. In this work, we present a novel multidimensional model that introduces spectral-angular effects to this field, with a focus on quantifying their impact on high-accuracy device calibration. Our enhanced approach allows anisotropic solar spectral radiance to be considered for any device orientation, including spectrally resolved ground reflections. To account for these effects, we consider both the spectral radiance of the source and the angular dependent spectral responsivities of the detectors. Angular mismatches of more than 1% were found for the examples investigated. This allowed detailed studies to be carried out on the impact of the detectors' optical losses and on the resulting mismatch of spectral and angular properties. Our model allows the spectral and angular effects to be determined and corrected, resulting in the measurement uncertainties for high-accuracy outdoor measurements decreasing significantly. It can be also used in other areas of photometric and radiometric applications, where a wide range of irradiance characteristics have an effect on measurements. As a consequence of this study, we propose assigning a directional property to the reference condition defined in international standards (i.e., direct beam only). [ABSTRACT FROM AUTHOR]

This article describes the method of deriving Global Horizontal Irradiance ( GHI) from combining power measurements with static meta data (tilt, orientation, brand/type) of rooftop photovoltaic ( PV)-systems. This inverse PV model implements a forward yield model that is based on a modified Orgill and Hollands decomposition model and the Perez transposition model for irradiance. The forward as well as the inverse PV model were validated with DC power measurements of four different mono- and polycrystalline modules combined with weather station data (2 minute resolution data over a period ranging from the 11th of June through the 24th of August 2014). The bias-corrected forward PV model shows a best (r) RMSE of 16.0 W (15.1%) with a (r) MBE of −1.67 W (−1.57%) for one of the polycrystalline modules. The bias-corrected inverse PV model shows a best (r) RMSE of 65.6 Wm−2 15.1% with a (r) MBE of 0.994 Wm−2 (0.229%) for one of the polycrystalline modules. Similar results were obtained for the three other modules. [ABSTRACT FROM AUTHOR]

Light pollution is closely correlated with the meteorological factors, specifically cloudiness that is one of the major amplifiers of night sky radiances in urban regions. Although the decisive effects of cloud deck on artificial nighttime skyglow have been recognized experimentally, the radiative transfer modelling in a heterogeneous nocturnal environment illuminated from many light sources is a non-trivial problem that is difficult to solve both theoretically and numerically. A satisfactorily accurate evaluation of ground-reaching diffuse light is, however, an important issue as some optical properties (e.g. horizontal irradiance) are usually difficult to obtain with common instruments. Overcast sky represents a special class of situations in which clouds can act as amplifiers of the light pollution of the city. In this paper we proceeded with a simple two-stream approach to solve the scalar radiative transfer equation (RTE) under overcast conditions. The technique we are using allows for a rapid prediction of ground irradiances in densely populated regions assuming various emission functions. We have shown that the classical RTE concept can be adopted in determining the diffuse irradiance, while the model abilities are illustrated in a set of numerical experiments for low and high turbidity states. [ABSTRACT FROM AUTHOR]

This paper presents a study of a strong desert dust episode over the Iberian Peninsula, and its effect on the spectral ultraviolet (UV) irradiance in Granada, Spain. Remote sensing measurements, forecast models, and synoptic analysis are used to identify a Saharan desert dust outbreak that affected the Iberian Peninsula starting 20 July 2009. Additionally, a Bentham DMc150 spectroradiometer is employed to obtain global, direct and diffuse spectral UV irradiances every 15 minutes in Granada. The desert dust caused a large attenuation of the direct UV irradiance (up to 55%), while the diffuse UV irradiance increased up to 40% at 400 nm. The UVSPEC/LibRadtran radiative transfer model is used to study the spectral dependence of the experimental UV irradiance ratios (ratios of spectral irradiance for the day with the highest aerosol load to that measured in days with low–moderate load). The spectral increase or decrease of the UV direct irradiance ratios depends on a new parameter: a threshold wavelength. The spectral dependence of the UV diffuse irradiance ratio can be explained because under the influence of the intense dust outbreak, the Mie scattering by aerosols at shorter wavelengths is stronger than the Rayleigh scattering by gases. Finally, the sensitivity analysis of the aerosol absorption properties shows a substantial attenuation of UV spectral irradiance with a weak spectral dependence.

The perforated shadow band enables the decomposition of global horizontal solar irradiance (GHI) so as to obtain diffuse horizontal and direct normal irradiance components (DHI and DNI). As a single-pyranometer system, it offers a low-cost alternative to dual-sensor radiometric schemes, but a comprehensive performance analysis has only been conducted under clear sky conditions. This study addresses perforated band (PB) behavior in the presence of cloud when the resulting radiometric trace exhibits stochasticity and a sensor exposure model is required to separate resulting fragmented GHI and DHI components prior to reconstitution as continuous time-series. Various interpolation techniques are tested for replacing patches of missing data caused by the band’s operation with the aim of minimizing root mean square difference (RMSD) relative to reference data. Given the effect of cloud on performance, uncertainties are reported as a function of daily clearness index, rather than as constants. For GHI, the RMSD uncertainties range between 6% for high clearness indices and around 36% for values between 0.3 and 0.4. Bias is typically negative, and the PB system underestimates GHI by between 1% (clearer skies) and 7% (partly cloudy skies). It is found that deploying interpolation schemes adaptively in response to the prevailing clearness index effectively reconstitutes fragmented GHI curves when cloud is present, while decomposition models assist in replacing missing DHI data under heavily cloudy and overcast conditions. Root mean square differences of around 20% can be expected for DHI measurements with mean bias varying between −5% for overcast conditions and +8% for clearer skies. The DNI results are obtained by calculation from DHI and GHI values, with RMSD peaking at about 200 W/m 2 in the mid-clearness index range, reducing to 30 W/m 2 under mainly overcast conditions and to 90 W/m 2 for high clearness index values. The results of the study also offer insight to the more general problem of replacing missing data in radiometric time series. [ABSTRACT FROM AUTHOR]

The paper studies the horizontal global, direct-beam and sky-diffuse solar irradiance data measured in Hong Kong from 2008 to 2013. A machine learning algorithm was employed to predict the horizontal sky-diffuse irradiance and conduct sensitivity analysis for the meteorological variables. Apart from the clearness index (horizontal global/extra atmospheric solar irradiance), we found that predictors including solar altitude, air temperature, cloud cover and visibility are also important in predicting the diffuse component. The mean absolute error ( MAE ) of the logistic regression using the aforementioned predictors was less than 21.5 W/m 2 and 30 W/m 2 for Hong Kong and Denver, USA, respectively. With the systematic recording of the five variables for more than 35 years, the proposed model would be appropriate to estimate of long-term diffuse solar radiation, study climate change and develope typical meteorological year in Hong Kong and places with similar climates. [ABSTRACT FROM AUTHOR]

The optimum utilization of solar energy requires effective harvesting of both the direct and diffuse components of ground-reaching radiation. Although solar beams are typically key contributors to the total irradiance under cloudless conditions, the diffuse component becomes important especially in regions where clear skies are not dominant. Even if the cloud cover and cloud microphysics are known, it is not an easy task to estimate the diffuse irradiance at arbitrarily oriented sloped surfaces. This situation arises from the extreme difficulty in solving the radiative transfer equation in such a heterogeneous environment. Models of Homogeneous Skies (MHS) with a set of discrete sky types are commonly applied in determining irradiance or illuminance. However, experimental data usually differ significantly from data predicted by MHS, for initially daylighting purposes where a simple sky luminance distribution is most useful. In this paper we show that the MHS error can be exceptionally large, especially for some cardinal directions. The use of MHS could also lead to misinterpretation of a momentary sky state if different sky types are required to accurately simulate irradiances on arbitrarily oriented surfaces. Nevertheless, use of multiple sky types at one moment in time has no theoretical basis and thus is generally unacceptable. Therefore, we have demonstrate that a new Unified Model of Radiance Patterns (UMRP) is more consistent with physical measurement and is generally applicable to all situations, including clear-, partly-cloudy, and, overcast-sky conditions and, could accurately predict vertical irradiances or illuminances more accurately than MHS. UMRP implements heterogeneity of cloud systems and provides radiance or luminance distributions depending on the characteristic size of clouds, their albedo and their altitude. While the error in the irradiance computations is approximately 6% for UMRP, it can reach a value of 70% or even more in case of MHS. UMRP-based modeling of radiative fields is now simple using the UniSky Simulator, a heavily optimized multithreading application (publicly available at www.unisky.sav.sk/?lang=en&page=aplikacia ). We expect the UMRP concept to be a new choice for modelers and PV systems engineers to predict solar energy more accurately under any meteorological conditions. [ABSTRACT FROM AUTHOR]

Recent observational studies show that solar radiation incident on ground has not been stable over the last several decades but underwent significant multi-decadal variations. From the 1950s, solar radiation has had a general decreasing trend, named dimming. Since the late 1980s, a trend reversal and partial recovery has been observed at many observations sites across the globe; it is the so-called brightening. The present study examined temporal and spatial trends in surface solar radiation (global and diffuse) and sunshine duration in India using a 40-year data set (1971–2010) of the twelve stations of solar radiation network of the India Meteorological Department. The research work examines the global solar radiation trends in all-sky and cloud-free sky conditions. The long-term variability in the diffuse components of solar radiation, bright sunshine duration, and cloud cover has also been studied over India. India is one of the few regions that showed a continuous and steady decline in global solar radiation from the 1970s to 2000. The declining trend of all-sky global irradiance over India as a whole was 0.6 Wm − 2 year − 1 during 1971–2000 and 0.2 Wm − 2 year − 1 during 2001–2010. A third-order polynomial fit to the data indicated a reversal in all-sky global irradiance around 2001 at some sites. Reversal or stabilization of global irradiance is also seen in seasonal mean values at some of the stations. The reversal in clear-sky global irradiance was clearly evident from 2001. Similar trend is also observed in bright sunshine duration. This confirms the well-known phenomenon of global dimming and global brightening over India. The analysis of global irradiance data highlights the fact that in general the dimming/brightening is station dependent because of regional sources and meteorology which contribute to the variation in solar irradiance. [ABSTRACT FROM AUTHOR]

A new resource for sun strength data in Southern Africa has been established with the commissioning of a regional network of solar monitoring stations. The Southern African Universities Radiometric Network (SAURAN) is an initiative of Stellenbosch University and the University of KwaZulu-Natal (UKZN), and consists of an initial set of ten ground stations equipped with secondary standard thermopile radiometers. SAURAN's aim is to provide a long-term record of sun strength in a region that shows excellent potential for the deployment of solar energy technologies. Instruments measuring direct normal irradiance (DNI), diffuse horizontal irradiance (DHI) and global horizontal irradiance (GHI) feed time-averaged data over 1-minute, hourly and daily intervals to a central archive from where they are accessible to the public via a website interface. Meteorological data is also provided by most of the stations. This paper gives a brief background to the SAURAN project and describes the network's operation, coverage and future expansion. Examples of solar energy irradiance plots are also provided to illustrate the information available from the SAURAN database. [ABSTRACT FROM AUTHOR]