Solar Radiation Model Research Articles

2018년 여름 집계구 단위의 상세 폭염취약성 원인 분석 : 구례군과 순창군을 대상으로

This study attempted to analyze the characteristics of heatwave damage in Gurye-gun and Sunchang-gun in 2018, at the height of a severe heatwave, and to identify detailed heatwave-vulnerable areas through spatial analysis. Data were assembled in units of aggregation zones for detailed spatial analysis. Shadow patterns, Sky view factor (SVF), and average radiation temperature distributions of 5m resolution were calculated using a solar radiation model for high-resolution thermal environment analysis. Individuals, environments, diseases, and weather factors that can affect heat wave damage were analyzed in units of census, and variables with spatial autocorrelation for Gurye-gun and Sunchang-gun were extracted through the model of Global Moran

Design and analysis of hybrid electric multi-lobed airship for cargo transportation

Though a lot of curiosity has been developed towards a sustainable mode of cargo transportation, multi-lobed hybrid airships are touted to be a viable alternative to the conventional aircraft. The advantages of these Lighter Than Air (LTA) vehicles can further be boosted by incorporating a renewable source of energy. The requirements of high power in cargo airships and the current technological barriers call for the development of a hybrid propulsion system that can couple the best of both conventional and electric propulsion. The electric propulsion system is established by integrating solar arrays with fuel cells, which is then combined with conventional engines in a parallel power train architecture ensuring minimum transfer of energy and compact size. A solar irradiance model is adopted, to evaluate the amount of energy generated by the solar arrays installed over the airship envelope. A multi-lobed hybrid airship model is presented whose aerodynamic characteristics are obtained using computational fluid dynamic tools, which are then utilized to evaluate the power requirements through flight performance analysis. The hybrid propulsion system is then modified in accord with the power needs of the hybrid airship. Finally, detailed weight distribution between hybrid-powered and conventional hybrid-airship is presented displaying significant reduction in fuel weight of ∼350 kg due to the hybrid propulsion system.

Performance Evaluation of Temperature-Based Global Solar Radiation Models—Case Study: Arar City, KSA

Solar radiation is considered the main renewable energy source which reshapes the global sustainability plan for future development. Due to the lack of solar radiation measurements, this work investigates the performance of several temperature-based hybrid solar radiation models combining the parametric, statistical and satellite data approaches to estimate the global solar radiation on a horizontal surface. Over 35 years of meteorological data in the new location, Arar City, KSA (Latitude 30°96′ N and longitude 41°05′ E) are employed to establish and validate the models. These models are validated using two datasets with different averaging time spans to investigate the accuracy and reliability of different models as forecasting tools for the solar radiation. The mostly common statistical indicators are calculated to identify the most accurate model. The results show that Model (1) has the best performance among all models with high reliability as a solar radiation forecasting tool in this new location. This model is also validated against the widely-used datasets, namely NASA, On-Site measurements and PVGIS-SARAH data. The model shows excellent values for statistical indicators with high values of coefficient of determination, R2 > 0.955, presenting the best performance regardless of the time span of the validation datasets.

Country-level evaluation of solar radiation data sets using ground measurements in China

Solar radiation is a crucial parameter that affects the thermal environment in buildings. The spatial and temporal distributions of solar radiation data are important for energy-efficient building design. Models that correlate solar radiation with other parameters can address the lack of solar radiation data. Satellite-derived products and reanalysis data sets have been produced using solar radiation models. The accuracy of these products directly affects building thermal environment design. To choose the most appropriate data set, it is necessary to evaluate the deviation in different data sets based on ground measurements. We used data acquired between 2001 and 2016 from 98 solar radiation measurement stations in China to verify two satellite-derived products (SARAH-E and CERES-SYN1deg) and two reanalysis data sets (ERA5 and MERRA-2). The CERES-SYN1deg and SARAH-E products performed better than the ERA5 and MERRA-2 data sets at estimating the daily global solar radiation. The daily global radiation products were more accurate than direct, diffuse, and hourly global solar radiation products. The models merged ground measurements show good performance. Further improvement in solar radiation estimation especially direct and diffuse in areas where there are no ground measurements and taking into account the effect of inadequate weather conditions on the hourly solar radiation is required. These findings may provide the basis for solar radiation models and products, especially applications in the building industry.

Comparing 2D and 3D Solar Radiation Modeling in Urban Areas

The use of solar radiation in the urban environment is becoming increasingly important for the sustainable development of cities and human societies. Several factors influence the distribution of solar radiation in urban areas, including urban morphology and the physical properties of urban materials. Most of these factors can be modeled with a relatively high accuracy using 2D and 3D solar radiation models. In this paper, the r.sun and v.sun solar radiation models are used to calculate solar radiation for the city of Košice in Eastern Slovakia to assess the accuracy of both approaches for vertical surfaces frequently found in urban areas. The results were validated by pyranometer measurements. The results showed relatively good estimates by the 3D v.sun model and poor estimates by the 2D r.sun model. This can be attributed to an improper representation of vertical surfaces by a digital surface model, which has a strong impact on solar resource assessments. We found that 3D city models prepared in level of detail 2 (LoD2) are not always adequate in case of complex buildings with morphological structures, such as terraces. These cast shadows on facades especially when solar altitude is high and, thus, assessments, even by a 3D model, are inaccurate.

Study on the evaluation method of diffuse radiation models——taking 5 typical cities in China as examples

Diffuse solar radiation models play an extremely important role in solar photothermal utilization, resource assessment and energy consumption simulation, etc. The accuracy of these diffuse solar radiation models usually need to be evaluated by various statistical parameters. Among these statistical parameters, the Global Performance Index (GPI) has been extensively employed in recent years because of its comprehensiveness and wide applicability. This paper takes five cities in China as representatives of 5 typical climate regions, and 12 solar scattered radiation models are fitted with the meteorological data of 5 cities. Based on the comparative analysis of the existing GPI calculation methods, this paper points out that there are some defects in the existing GPI, and modifies the existing GPI based on the comprehensive consideration of statistical parameters, normalization preprocessing of statistical parameters, unified evaluation direction of parameters, weight redistribution of statistical parameters, and adjustment of extreme coefficient. 12 types of new GPI are established in this paper, and the performance of diffuse solar radiation models are compared based on these GPI. The rationality of GPI corrective measures is analyzed by means of the method reasonable index (MRI). The results show that the GPI calculation method (N10) which takes five corrective measures has the best performance, and the accuracy of the existing GPI can be improved by 13.33 to 65%.

A nonstationary and non‐Gaussian moving average model for solar irradiance

AbstractHistorically, power has flowed from large power plants to customers. Increasing penetration of distributed energy resources such as solar power from rooftop photovoltaic has made the distribution network a two‐way‐street with power being generated at the customer level. The incorporation of renewables introduces additional uncertainty and variability into the power grid. Distribution network operation studies are being adapted to include renewables; however, such studies require high quality solar irradiance data that adequately reflect realistic meteorological variability. Data from satellite‐based products are spatially complete, but temporally coarse, whereas solar irradiances exhibit high frequency variation at very fine timescales. We propose a new stochastic method for temporally downscaling global horizontal irradiance (GHI) to 1 min resolution, but we do not consider the spatial aspect due to limited availability of the in situ irradiance measurements. Solar irradiance's first and second‐order structures vary diurnally and seasonally, and our model adapts to such nonstationarity. Empirical irradiance data exhibits highly non‐Gaussian behavior; we develop a nonstationary and non‐Gaussian moving average model that is shown to capture realistic solar variability at multiple timescales. We also propose a new estimation scheme based on Cholesky factors of empirical autocovariance matrices, bypassing difficult and inaccessible likelihood‐based approaches. The model is demonstrated for a case study of three locations that are located in diverse climates through the United States. The model is compared against competitors from the literature and is shown to provide better uncertainty and variability quantification on testing data.

Measurement and modeling of diffuse irradiance masking on tilted planes for solar engineering applications

Photovoltaic and solar thermal projects require accurate solar irradiance data and models for the design, assessment, and forecasting of power output. For panels and solar collectors installed in arrays, the view toward the sky and ground is restricted by the surrounding rows. This paper analyzes the impact of view obstructions on the diffuse irradiance distribution in fixed-tilt arrays, addressing the insufficient research coverage to date. Irradiance was measured using high-precision pyranometers placed at ten positions throughout an experimental solar collector array for 3.5 and 6 m row spacings and 30°, 37.5°, and 45° tilt angles (relative row spacings between 0.68 and 1.51). A novel anisotropic transposition model was developed to calculate the diffuse tilted irradiance along the collector height, accounting for diffuse irradiance masking due to view obstructions. The model was also solved inversely, obtaining local global horizontal irradiance from global tilted irradiance. The validation showed that the model accurately captures the distinct shape of the diffuse irradiance distribution. Results indicate a strong effect of view obstructions for narrow row spacings and steep tilt angles. For the most extreme configuration (3.5 m row spacing, 45° tilt angle, 1.67 relative row spacing), the diffuse irradiance was reduced to 64% at the bottom and 89% on average, relative to the top of the collector. As a consequence, measurements at the top can result in biased performance assessments.

Ångström-Prescott Models of Solar radiation over Earth surface

The current energy demand increases every day and the deficit of electricity generation in Colombia due to technical aspects such as the lack of generation infrastructure, cost overruns in the construction projects of new plants and environmental variability as a consequence of climate change, entail a high risk of energy rationing; for this reason some of the users, whether industrial or residential, have decided to seek multiple alternatives to reduce the costs of their billing in interconnected areas and even supply their energy needs.Among these alternatives is found solar energy in its thermal and photovoltaic use, a resource that must be characterized in order to determine the technical and budgetary aspects involved in the implementation of profitable energy generation projects. This article seeks to provide technical tools for the design and implementation of generation projects based on solar energy, providing physical-mathematical approach based in the classical Angström-Prescott model that allow engineers and researchers to model the global solar radiation on the Earth’s surface in order to maximize the use of this resource in a specific geographical location.Although there are different ways to characterize the solar resource on the earth’s surface, this paper presents a review study focused on the most important global solar radiation estimation models present in the literature.

Investigation on the distribution patterns and predictive model of solar radiation in urban street canyons with panorama images

Solar radiation is the main driving force responsible for adjusting the urban climate and heat balance in street canyons. In this study, the model for predicting urban solar radiation used in RayMan is improved with respect to the reflected radiation and its accuracy is verified in field experiments. In total, 35763 sample sites in Xi'an are generated and categorized using basic urban morphology parameters (building density, average building height, and floor area ratio). The verified model is used to calculate the solar radiation intensities based on Baidu panorama images. The solar radiation distributions in Xi'an are mapped. The patterns of urban morphology affecting solar radiation are investigated. The results shows that solar radiation is affected by street canyons and the morphology of urban plots, as follows. (1) The effect of the width of street canyons on the solar radiation intensity is stronger in the transition and cold season (September to May) than the hot season (June to August), where the influence is stronger when the season is colder. (2) In east–west street canyons, the effects on solar radiation of urban morphology parameters in southern plots are stronger. (3) The relationship between the floor area ratio and solar radiation is strongest and negative.

Spectral Characteristics of Solar Radiation in Timisoara, Romania

Abstract This study deals with the spectral distribution of solar radiation in Timisoara, Romania. Solar spectrum at the ground level was estimated based on Leckner’s spectral solar irradiance model and measured atmospheric parameters over the years 2019-2020. The average photon energy index (APE) was used to capture the characteristic signature of the solar radiation spectrum. The results emphasize considerable differences between the solar radiation spectrum in Timisoara and the standard AM1.5G spectrum. During 2019-2020, APE has taken values between 1.841 eV and 1.929 eV, indicating both red- and blue-shift from the standard AM1.5G spectrum. To our best knowledge this is the first study which discusses the signature of solar radiation spectrum in terms of APE for a location in Romania.

Modeling of global solar radiation in Algeria based on geographical and all climatic parameters

The design of photovoltaic or solar systems and estimating their performance require knowledge of the intensity of solar radiation. The measurement of this parameter for some sites in Algeria is unfortunately not obvious. However, researchers are moving towards the modeling, estimation and prediction. To model the global solar radiation in Algeria, we must take into account the geographical and climatic parameters such as sunshine duration, relative humidity, temperature, latitude site, etc... In this study, the modeling of daily global solar radiation on a horizontal plane according to the parameters mentioned above is based on the statistical linear regression technique. The daily data used in the development and validation of models are extracted from the database of O. N. M (National Office of Meteorology, Dar el Beida. Algeria) for 2001-2005. We test the proposed models on two sites such as Djelfa and Ain-Bessam. For each site, validity and performance of the model will be studied based on the number of parameters introduced in the analytical expressions and results are discussed in terms of statistical errors as: R, MBE and RMSE between the measured global solar radiation and global solar radiation estimated. It was found that air temperature and relative humidity are indeed important climatic parameters for the prediction of solar radiation.

Performance Assessment of Global Horizontal Irradiance Models in All-Sky Conditions

Solar irradiance models contribute to mitigating the lack of measurement data at a ground station. Conventionally, the models relied on physical calculations or empirical correlations. Recently, machine learning as a sophisticated statistical method has gained popularity due to its accuracy and potential. While some studies compared machine learning models with other models, a study has not yet been performed that compares them side-by-side to assess their performance using the same datasets in different locations. Therefore, this study aims to evaluate the accuracy of three representative models for estimating solar irradiance using atmospheric variables measurement and cloud amount derived from satellite images as the input parameters. Based on its applicability and performance, this study selected the fast all-sky radiation model for solar applications (FARMS) derived from the radiative transfer approach, the Hammer model that simplified atmospheric correlation, and the long short-term memory (LSTM) model specialized in sequential datasets. Global horizontal irradiance (GHI) data were modeled for five distinct locations in South Korea and compared with hourly measurement data of two years to yield the error metrics. When identical input parameters were used, LSTM outperformed the FARMS and the Hammer model in terms of relative root mean square difference (rRMSD) and relative mean bias difference (rMBD). Training an LSTM model using the input parameters of FARMS, such as ozone, nitrogen, and precipitable water, yielded more accurate results than using the Hammer model. The result shows unbiased and accurate estimation with an rRMSD and rMBD of 23.72% and 0.14%, respectively. Conversely, the FARMS has a faster processing speed and does not require significant data to make a fair estimation.

The modified layer-by-layer weakening solar radiation models based on relative humidity and air quality index

Air pollution has a significant weakening effect on solar radiation. Therefore, it is important for the development and utilization of solar energy to establish a solar radiation model under the influence of fog and haze. Based on the analysis of existing layer-by-layer weakening solar radiation models, the discontinuous meteorological data provided by MODIS satellite are replaced by continuous measured data from meteorological stations. The beam solar radiation model and diffuse solar radiation model are modified by using relative humidity (φ) and air quality index (AQI). The results show that the correction effects of these modified models are better. The R value of beam solar radiation models have increased by 5.74%, the R value of diffuse solar radiation models have increased by 41.27%, and other statistical parameters (RSE, RMSE and NSE) have also been improved to a certain extent. The calculated value of the modified models is closer to the measured data. In addition, the order of correction parameters also has an effect on the results. The research shows that the best correction effect is to use relative humidity first and then AQI. According to this method, the layer-by-layer weakening solar radiation models can be more accurate and reliable.

Modeling benthic solar exposure (UV and visible) in dynamic coastal systems to better inform seagrass habitat suitability

Seagrass meadows worldwide provide valuable ecosystem services but have experienced sharp declines in recent decades. This rapid loss has prompted numerous restoration efforts with variable levels of success, often depending on the suitability of the restoration sites. The selection of sites can be guided by simple habitat suitability models driven with environmental variables deemed critical to the successful growth of new transplants. Habitat suitability models typically consider the influence of bathymetry, sediment type, salinity, wave exposure, and water quality. However, they typically do not explicitly include benthic exposure to ultraviolet (UV) and commonly use depth as a coarse proxy for photosynthetically active radiation (PAR). Benthic exposure to UV and PAR are both key parameters for habitat suitability but can be challenging to determine, especially in coastal environments influenced by rivers and tides where they are extremely variable. Here, we demonstrate the development of a simple but effective model of spectrally-resolved benthic solar irradiance for a dynamic marsh-influenced mesotidal estuary in Massachusetts. In-situ measurements were used to develop and validate an empirical model predicting the UV–visible vertical diffuse attenuation coefficient spectra of downwelling irradiance, Kd(λ), from simple physical parameters about tides, river discharge and location. Spectral benthic solar irradiances (280–700 nm) were calculated hourly for 3 years (2017–2019) using modeled and validated cloud-corrected surface downwelling irradiances, estimates of water depth, and the modeled Kd(λ) spectra. The mapped irradiances were used to provide improved seagrass habitat suitability maps that will guide future restoration efforts in the estuary. We expect the approach presented here can be adapted to other dynamic coastal environments influenced by tides and rivers and/or applied to other light-dependent organisms and biogeochemical processes.

Experimental and numerical study on the annual performance of semi-transparent photovoltaic glazing in different climate zones

Semi-transparent photovoltaic (STPV) glazing can beautify the architectural appearance, generate power in-place. However, few researches study the climate adaptability of monocrystalline silicon STPV glazing. For the STPV glazing system, this paper develops a multi-physics model including the solar radiation, optical, electrical, and thermal models to analyze its overall performance. The model is validated by experiment. The performance of the STPV glazing system with different solar cell coverage ratios (R) in various climate zones of China (Guangzhou, Changsha, Kunming, Lhasa, and Beijing) is also studied. Among the five cities, the energy output of the STPV glazing system is proportional to the R value, and all follow approximately the same trend as the incident solar radiation. However, the geographic latitude has a greater impact on the electrical performance of the STPV glazing system than solar radiation. The thermal performance is primarily affected by the ambient temperature. The STPV glazing system performs well in the temperate area, with low cooling demand and high annual energy output. Compared with the traditional single clear glazing, the overall performance of the STPV glazing system is better, especially when the large solar cell coverage ratio. This paper provides a research basis for application in different climate zones.

Solar module orientation and tracking type performance and optimization

The efficiency and performance of solar cells and modules are typically evaluated and reported at normal incidence under peak solar radiation. We present a simple clear-sky model for solar irradiance that can be used to study the angular and annual performance of new photovoltaic materials. Using this model, we study the effect of solar module orientation for fixed-tilt module installations and different types of tracking (seasonal, 1D, and 2D) as a function of latitude. For fixed-tilt modules, the optimum tilt as a fraction of latitude varies from 0.83 at 1 deg to 0.73 at 60 deg. The effect of tilt misorientation for panels at the optimum azimuth is not very strong as the solar irradiance is about 94.5% of its optimum at ±20 deg mistilt. Both azimuth misorientation and tilt misorientation are studied. Optimized tilts and times of year for tilting are also obtained for modules that are seasonally adjusted twice and three times a year. The annual solar insolation of fixed modules is compared with modules that are seasonally adjusted twice and three times a year, continuously tracked in the north/south direction, continuously tracked in the east/west direction, and continuously tracked in two directions. The use of single-axis tracking in the east/west direction is preferable to north/south tracking and potentially improves overall energy collection by 16.2% to 31.0%. Continuous dual-axis tracking enhances overall annual energy collection by 36.0% to 45.5%. The model and provision of open source code provides for a way to assess the performance of new materials.

Evaluation of the observation methods of outdoor mean radiant temperature in a subtropical city

The outdoor mean radiant temperature (MRT) has been used as an indicator to characterize radiation in an outdoor thermal environment. To investigate outdoor MRT, the cost-effective and portable black-globe thermometer method has commonly been used, though its shortcomings have been noted, such as limited accuracy and environmental applicability. The objective of this paper is to evaluate MRT estimation results of the black-globe thermometer method and upper and lower hemispheric radiation method through the MRT results of the six-directional radiation method as a benchmark for three open sites with different underlying surfaces in a subtropical city. The hourly diffuse solar radiation model applicable to the subtropical region was further explored through statistical evaluation. Numerous findings were noteworthy: (i) the different values of albedo of the materials of underlying surfaces critically affected the long-wave radiation environment in the corresponding sites, which in turn led to differences in the MRT across the sites; (ii) the Orgill model exhibited the highest accuracy in characterizing the diffuse solar radiation for both hourly and minutely data; (iii) the upper and lower hemispheric radiation method registered significantly lower deviations for the MRT estimation results than the black-globe thermometer method, and (iv) the MRT results with the Orgill model were closer to the benchmark values than those with the measured data. In general, the upper and lower hemispheric radiation method has demonstrated accuracy, cost-effectiveness, and environmental applicability, reflecting its appropriateness for observational studies on subtropical outdoor thermal environments.

Aerosol properties and aerosol–radiation interactions in clear-sky conditions over Germany

Abstract. The clear-sky radiative effect of aerosol–radiation interactions is of relevance for our understanding of the climate system. The influence of aerosol on the surface energy budget is of high interest for the renewable energy sector. In this study, the radiative effect is investigated in particular with respect to seasonal and regional variations for the region of Germany and the year 2015 at the surface and top of atmosphere using two complementary approaches. First, an ensemble of clear-sky models which explicitly consider aerosols is utilized to retrieve the aerosol optical depth and the surface direct radiative effect of aerosols by means of a clear-sky fitting technique. For this, short-wave broadband irradiance measurements in the absence of clouds are used as a basis. A clear-sky detection algorithm is used to identify cloud-free observations. Considered are measurements of the short-wave broadband global and diffuse horizontal irradiance with shaded and unshaded pyranometers at 25 stations across Germany within the observational network of the German Weather Service (DWD). The clear-sky models used are the Modified MAC model (MMAC), the Meteorological Radiation Model (MRM) v6.1, the Meteorological–Statistical solar radiation model (METSTAT), the European Solar Radiation Atlas (ESRA), Heliosat-1, the Center for Environment and Man solar radiation model (CEM), and the simplified Solis model. The definition of aerosol and atmospheric characteristics of the models are examined in detail for their suitability for this approach. Second, the radiative effect is estimated using explicit radiative transfer simulations with inputs on the meteorological state of the atmosphere, trace gases and aerosol from the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis. The aerosol optical properties (aerosol optical depth, Ångström exponent, single scattering albedo and asymmetry parameter) are first evaluated with AERONET direct sun and inversion products. The largest inconsistency is found for the aerosol absorption, which is overestimated by about 0.03 or about 30 % by the CAMS reanalysis. Compared to the DWD observational network, the simulated global, direct and diffuse irradiances show reasonable agreement within the measurement uncertainty. The radiative kernel method is used to estimate the resulting uncertainty and bias of the simulated direct radiative effect. The uncertainty is estimated to −1.5 ± 7.7 and 0.6 ± 3.5 W m−2 at the surface and top of atmosphere, respectively, while the annual-mean biases at the surface, top of atmosphere and total atmosphere are −10.6, −6.5 and 4.1 W m−2, respectively. The retrieval of the aerosol radiative effect with the clear-sky models shows a high level of agreement with the radiative transfer simulations, with an RMSE of 5.8 W m−2 and a correlation of 0.75. The annual mean of the REari at the surface for the 25 DWD stations shows a value of −12.8 ± 5 W m−2 as the average over the clear-sky models, compared to −11 W m−2 from the radiative transfer simulations. Since all models assume a fixed aerosol characterization, the annual cycle of the aerosol radiation effect cannot be reproduced. Out of this set of clear-sky models, the largest level of agreement is shown by the ESRA and MRM v6.1 models.

Forecasting of solar radiation in photovoltaic power station based on ground‐based cloud images and BP neural network

The solar radiation near the surface is the main reason that affects photovoltaic power generation. Accurate ultra-short-term solar radiation prediction is the premise of photovoltaic power generation prediction. Here the cloud movement prediction method based on the ground-based cloud images is presented. The cloud recognition, cloud matching, cloud area correction and cloud movement prediction are performed to predict the drift trajectory of the clouds that will block the sun. Then, using digital image technology, 13 kinds of feature information are extracted from the ground-based cloud images. Then, these feature information are input into BP neural network, and the parameters of BP neural network are optimized by genetic algorithm. Through a large number of data training, a new ultra-short-term prediction model of solar radiation is established. Finally, through experimental comparison, the results show that the prediction accuracy of the model with the feature information of ground-based cloud images can reach 96%, compared with the model without the feature information of ground-based cloud images, the accuracy is improved by 5%. The proposed ultra-short-term solar radiation prediction model can effectively predict the radiation jumping process caused by cloud occlusion, and greatly improve the prediction accuracy, especially in cloudy weather.