Assessment of spatial and temporal variability in the US solar resource from radiometric measurements and predictions from models using ground-based or satellite data

The US National Renewable Energy Laboratory (NREL) is responding to a growing demand for high-accuracy solar resource data with uncertainties significantly lower than those of existing solar resource datasets, such as the National Solar Radiation Database (NSRDB). Measurements for long-term solar resource characterizations require years to complete, which is an unacceptable timeline for the rapidly emerging needs of renewable energy applications. This contribution seeks methods of reducing the uncertainty of existing long-term solar resource datasets by incorporating lower-uncertainty site-specific ground measurements of a limited period of record. In particular, various techniques are being explored to make full use of the existing high-resolution radiation data available in the NSRDB and other sources, and extrapolate them over time using locally measured data and other supportive information. The interannual variability in global and direct radiation is studied here using long-term data at various sites. NSRDB’s modeled data for the 1998-2005 period are compared to quality-controlled measurements to assess the performance of the model, which is found to vary greatly depending on climatic condition. The reported results are encouraging for applications involving concentrators at very sunny sites. Large seasonal biases are found at some cloudy sites. Various improvements are proposed to enhance the quality of the existing model and modeled data.The measurement of solar radiation to characterize the solar climate for renewable energy and other applications is a time consuming and expensive operation. Full climate characterization may require several decades of measurements—a prospect that is not practical for an industry intent on rapid deployment of solar technologies. This study demonstrates that the consistency of the solar resource in both time and space varies widely across the United States. The mapped results here illustrate regions with high and low variability and provide readers with quick visual information to help them decide where and how long measurements should be taken for a particular application. The underlying data that form these maps are also available from NREL to provide users the opportunity for more detailed analysis.     

Solar radiation in the Brazilian Northeast

The significant increase in recent years of the number of rural electrification systems (some thousands of them do exist) using photovoltaic technology installed in the Northeast of Brazil (1,500,000 km², approximately 42 million people) used for illumination or water pumping, calls for an improvement on the design procedures in order to reduce the burden of capital costs per unit of generated power. Such objective can be accomplished as long as a better knowledge about the solar resource is achieved, considering how much these applications depend on it.The sources of information on solar radiation in Brazil are quite varied at both institutional and publication level. At institutional level, among others, we can find the National Institute of Meteorology (INMET), State Departments of Agriculture, research institutes, universities and electric power generation and distribution utilities. Progress reports or scientific and technical journals are the main publishing vehicles where this information can be found. This way, data quality varies considerably, showing spatial and temporal discontinuities, in addition to the fact that measurement instruments and physical units of registered data are not standardized. The Solarimetric Atlas of Brazil was recently published [Brazilian Solarimetric Atlas, Final Technical Report I–IV (1997); Renewable Energy 18 (1998) 393] contains that information, which is grouped, evaluated, qualified, and presented in a standardized way. It is one of the best currently existing sources of information, and it certainly consists of almost the entirety of the existing information on the solar resource (data on solar radiation and sunshine hours) in Brazil.By using this database, simultaneous records of solar radiation (measured with pyranographs or pyranometers) and sunshine hours with heliographs were obtained in 35 different places in the Northeast region. Coefficients a and b were calculated for those different places using Angstrom's correlation. Using the geostatistical interpolation method known as ‘kriging’, the values of a and b were placed on contour maps, the coverage of which is the Northeast region. The relevant kriging estimate error maps were also obtained.The general objective of this paper is to improve the amount of the currently existing information on the solar radiation in the Northeast of Brazil. Regarding this, the contour maps of coefficients a and b have made possible estimating solar radiation in 82 additional locations, were only sunshine hours data were available.     

Models of solar radiation with hours of bright sunshine: A review

In the design and study of solar energy, information on solar radiation and its components at a given location is very essential. Solar radiation data are required by solar engineers, architects, agriculturists and hydrologists for many applications such as solar heating, cooking, drying and interior illumination of buildings. For this purpose, in the past, several empirical correlations have been developed in order to estimate the solar radiation around the world. The main objective of this study is to review the global solar radiation models available in the literature. There are several formulate which relate global radiation to other climatic parameters such as sunshine hours, relative humidity and maximum temperature. The most commonly used parameter for estimating global solar radiation is sunshine duration. Sunshine duration can be easily and reliably measured and data are widely available.     

Insolation modeling overview

This paper gives a summary of some of the major national projects in the area of solar radiation resource assessment. It also discusses the primary solar radiation data sources for the U.S. and the models that were used in developing these sources. Recommendations for appropriate solar radiation resource information for various types of solar system design and analysis needs are given.     

Performance model to assist solar thermal power plant siting in northern Chile based on backup fuel consumption

In response to environmental awareness, Chile introduced sustainability goals in its electricity law. Power producers must deliver 5% from renewable sources by 2010 and 10% by 2024. The Chilean desert has a large available surface with one of the highest radiation levels and clearest skies in the World. These factors imply that solar power is an option for this task. However, a commercial plant requires a fossil fuel system to backup the sunlight intermittency. The authors developed a thermodynamical model to estimate the backup fraction needed in a 100 MW hybrid -solar-fossil- parabolic trough power plant. This paper presents the model aiming to predicting the performance and exploring its usefulness in assisting site selection among four locations. Since solar radiation data are only available in a monthly average, we introduced two approaches to feed the model. One data set provided an average month with identical days throughout and the other one considered an artificial month of different daylight profiles on an hourly basis for the same monthly average. We recommend a best plant location based on minimum fossil fuel backup, contributing to optimal siting from the energy perspective. Utilities will refine their policy goals more closely when a precise solar energy data set becomes available.     

Spatial estimation of monthly mean daily sunshine hours and solar radiation across mainland China

Spatial databases of climate data in digital format are required for many agricultural and eco-environmental systems. This study compared 7 approaches for interpolating monthly mean daily sunshine hours and solar radiation over mainland China. The approaches included simple geostatistical approaches to incorporation of Universal Transverse Mercator (UTM) coordinates and elevation. Performance indicators (root mean square error, mean absolute percentage error, and modeling efficiency) showed thin plate smoothing spline with UTM coordinates and elevation (TPS) outperformed other models. Besides, multiple linear regression equations for estimating solar radiation using geographical parameters (UTM coordinates and elevation) and sunshine hours predicted by TPS performed well for the study site. Spatial datasets of annual and monthly mean daily sunshine hours and solar radiation with 1 km resolution were then obtained by the best performance models. Spatial and temporal variability was clearly observed in sunshine hours and solar radiation. For both annual and seasonal scenarios, higher values of sunshine hours and solar radiation existed in north and Tibetan Plateau and lower values were observed in the middle and southern China. Lower values of annual solar radiation were also found in northeastern China. Sunshine hours and solar radiation varied with time, especially from spring to summer and from summer to autumn. The accurate gridded datasets are expected to provide significant information on more efficient use of natural resources.     

Generation of typical solar radiation year for China

Applying the daily global solar radiation data measured at least 10 years, the typical solar radiation year for 30 meteorological stations in China is generated using the Finkelstein–Schafer statistical method. Based on the typical solar radiation data obtained, the geographical difference of solar energy resource of these 30 stations was also analyzed. The results in this paper will fill this gap that complete and detailed typical solar radiation data are not available for China, and will be useful to the designers of solar energy conversion and utilization devices.     

Building a bankable solar radiation dataset

A robust solar radiation dataset is essential for securing competitive financing for solar power projects. The majority of solar radiation datasets are derived from publically available data, though there are an increasing number of proprietary datasets being developed and marketed. Most of these new datasets represent models based on satellite images and validated with ground measured data. This paper focuses on the strengths and weaknesses of the existing publically available solar radiation databases, though the commentary is equally relevant to the newer commercial datasets. While the financing community generally views the solar resource as stable, it also views the material miscalculation of the solar resource as one of the biggest risks in a solar project. Therefore, lenders and rating agencies alike require verification of the solar resource dataset to be utilized at each project location as this translates directly into electric energy production forecasts and revenues. The variability of the solar resource as exhibited by the historical solar data and the accuracy of the dataset play significant roles in estimating the probability of future performance and influences the financial contract that the project is likely to receive.     

Solar energy resource assessment — Brazil

Appropriate information on solar resources is very important for a variety of technological areas, such as: agriculture, meteorology, forestry engineering, water resources and particularly for an innovating technology such as solar energy. In the market entry process of an innovating technology such as solar energy, the enlarged and sustained reproduction of this energy strongly depends on the economy and reliability of the demonstrative solar systems installed (within a restricted or wide scale). The economy and reliability of a system are the consequence of a well-prepared project, resulting from an accurate knowledge of the solar resource available. Therefore, knowing the potential of the solar resource accurately is not only a need, it is also an imperative for a larger diffusion and use of the solar energy.The existing sources of information on radiation in Brazil are quite varied, both at the institutional level and in different types of publications. At the institutional level these sources are: the National Institute of Meteorology, secretary of agriculture, research centers, universities, and electric power generating and distributing companies, among others. The publications with this information are project reports, internal reports of institutions or several magazines. Thus, the quality of the data varies considerably, the information presents spatial and temporal discontinuity and the instruments as well as the measurement units are not standardized.The general objective of this paper is to recover, qualify, standardize and make available the best information from the current existing solar resource in Brazil, either in the form of isoline charts of solar radiation, insolation, numeric tables or analytic summaries of a great part of the publications on the theme over the last forty years.     

Analysis of utilisation of renewable energies as heat sources for heat pumps in building sector in Poland

In this paper the emphasis is put on identification the problem how different renewable sources can be effectively used as heat sources for heat pumps in Poland. Main data of: ambient air, solar radiation, soil, ground and surface water are presented. Recommendations for heating systems with a heat pump are given.     

New methodologies to estimate the hourly global solar radiation; Comparisons with existing models

This paper describes two new friendly and reliable approaches to estimate hourly global solar radiation on a horizontal surface even with a pocket calculator.Such fast and reliable predictions for the hourly solar radiation are necessary for the real-time management of both the solar energy sources, like a PV generator output in the one hand and the power loads, on the other.The predicted global solar hourly radiation values are compared with estimates from two existing packages and the recorded solar radiation for the two biggest cities of Greece.The two methodologies presented in this paper can be applied to any other site.     

Clear-sky solar luminous efficacy determination using artificial neural networks

Under cloudless conditions, the effect of atmospheric variables, such as turbidity or water vapour, on luminous efficacy is an important source of variability, often limiting the use of simple empirical models to those sites where they were developed. Due to the complex functional relationship between these atmospheric variables and the luminous efficacy components, deriving a non-local model considering all these physical processes is nearly impossible if standard statistical techniques are employed. To avoid this drawback, the use of a new methodology based on artificial neural networks (ANN) is investigated here to determine the luminous efficacy of direct, diffuse and global solar radiation under cloudless conditions. In this purpose, a detailed spectral radiation model (SMARTS) is utilized to generate both illuminance and solar radiation values covering a large range of atmospheric conditions. Different input configurations using combinations of atmospheric variables and radiometric quantities are analyzed. Results show that an ANN model using direct and diffuse solar irradiance along with precipitable water is able to accurately reproduce the variations of the three components of luminous efficacy caused by solar zenith angle and the various atmospheric absorption and scattering processes. This proposed model is considerably simpler than the SMARTS radiation model it is derived from, but still can retain most of its predicting power and versatility. The proposed ANN model can thus be used worldwide, avoiding the need of using detailed atmospheric information or empirical models of the literature if radiometric measurements and precipitable water data (or temperature and relative humidity data) are available.     

Interannual variability of solar energy generation in Australia

Australia has an abundant solar energy resource that is likely to be used for energy generation on a large scale. Variable sources of electricity generation require knowledge of the nature of their variability at all time scales. This study examines the effect that El Niño Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) have on solar radiation in Australia, in order to establish the role for seasonal forecasting of solar power. Calendar years are classified into their ENSO state using a sea surface temperature index. The ERA-Interim and NCEP reanalysis products are then used to estimate the effect of ENSO on global horizontal solar irradiance over the continent. A bootstrap technique is used to obtain confidence regions for the effect in both winter and summer. The main impact of ENSO occurs during winter over a large part of eastern Australia. Little impact was observed over the continent during summer. A similar analysis is conducted for the Indian Ocean Dipole (IOD) to ensure that the observed ENSO effect is not a manifestation of the IOD. This study indicates that the ENSO phenomenon may account for solar energy changes of more than 10% in some locations on a seasonal basis. We show that the solar radiation analysis is directly applicable to solar energy yield. Knowledge of this variability may influence the location of large solar generation plants. Also, there is a potential to predict solar energy a few months ahead by means of seasonal forecasting systems, which would help to assist with planning for electricity grid.     

A comparison of daily solar radiation estimates for the Northeastern United States using the Northeast Regional Climate Center and National Renewable Energy Laboratory models

Observed solar radiation data at three sites in the northeastern United States are compared with values estimated for nearby airport locations using the National Renewable Energy Laboratory (NREL) and Northeast Regional Climate Center (NRCC) models. A tendency toward considerable overestimation of relatively low values of observed solar radiation is evident in the NREL model. This bias is apparently regardless of season. A similar bias is not detected in the NRCC model. For moderate to high values of solar radiation both models produce estimates with similar accuracy for most practical applications. However, these models both tend to underestimate observed solar radiation on days when near maximum possible radiation levels are received. The tendency for the NREL model to overestimate low solar radiation values appears to be linked to the use of total sky cover, rather than the combination of cloud coverage and cloud base height information. Although total sky coverage data may be superior for estimates of moderate to high daily solar radiation values, it appears that information regarding the height of low overcast layers and the presence of obstructions to visibility, such as fog or haze, is required to accurately estimate low daily solar radiation totals.     

Atmospheric aerosol influence on the Brazilian solar energy assessment: Experiments with different horizontal visibility bases in radiative transfer model

The radiative transfer model BRASIL-SR is used by Brazilian Institute for Space Research for the assessment of the solar irradiation in Brazil. The model parameterizes the influence of aerosols in the solar radiation transmittance using climate averages of horizontal visibility, which does not represent the actual atmospheric condition in Brazil, especially during dry season. In clear sky conditions, aerosols are a major source of bias in solar radiation models. Their concentration have large spatial and temporal variability particularly in the Brazilian Midwestern region from April until October, due to forest fires, and in Southeastern region due to pollution from megacities. In this study, meteorological data from METAR comprising the years of 2006, 2007 and 2008 were analyzed to evaluate the seasonal variability of the horizontal visibility in Brazil to better represent the influence of aerosols on the model estimations of surface solar irradiation. New horizontal visibility values was generated to each month simulated, to provide input data to the BRASIL-SR model and site specific ground data were used to validate the model estimates. The global, direct beam and diffuse solar irradiation estimates obtained by making use of the new horizontal visibility data presented an overall lower BIAS and RMSE deviations.     

Output variation of photovoltaic modules with environmental factors — II: seasonal variation

This study investigated how seasonal changes in cell temperature and spectral solar radiation effect the seasonal variation in photovoltaic (PV) module conversion efficieny for CdS–CdTe and two-layer tandem-amorphous silicon (for simplicity referred to as CdS and 2L A Si, respectively). First, using the measured data, the ratio of the spectral solar radiation available for solar cell utilization to the global solar radiation (denoted hereafter as “available spectral ratio”), the mean cell temperature, and the conversion efficiency for each month were obtained, and seasonal variations were analyzed. Mean cell temperature and available spectral ratio seasonal changes were found to be 9% for CdS and 16% for 2L A Si.The CdS conversion efficiency increased during summer by 7%, whereas 2L A Si exhibited a more substantial 14% variation. During summer, although the spectral ratio available to CdS increases, the conversion efficiency does not increase by the same amount, because of an increase in cell temperature. Similarly, although 2L A Si, experienced a much greater increase in available spectral ratio and had a better overall performance, there was still only a 2% variation, because of the cell temperature increases.If the basic characteristics of solar cell output for various types are compared with the variation in environmental factors, such as irradiance, cell temperature and spectral solar radiation, it is possible to calculate the precise output of a solar cell. Accordingly, it is possible to evaluate the seasonal variation in conversion efficiency for each solar cell type and utilize this information to optimize the PV power system.     

Evaluating the Applicability of Data on Total Solar-Radiation Intensity Derived from Various Sources of Actinometric Information

In designing generating solar-engineering devices, the first priority is the predesign study of the potential of local resources of solar energy at the places where they may be located. Currently, actinometric information is obtained in several ways. They include direct measurement of solar-radiation characteristics at meteorological stations or from satellites and analytical methods for calculating intensity of solar radiation. Despite the significant number of sources of actinometric information, it seems impossible to evaluate the potential of incoming solar energy in the region, to substantiate the composition and parameters of solar-power-plant equipment, and to predict its operation at the initial stage. Using the example of the town of Kamyshin in Volgograd oblast, the sufficiency of required actinometric information is analyzed for further solar-engineering calculations and the data accuracy and limits of their applicability are estimated.     

Trends in solar radiation in NCEP/NCAR database and measurements in northeastern Brazil

The database from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) re-analysis project available for the period from 1948 to 2009 was used for obtaining long-term solar radiation for northeastern Brazil. Measurements of global solar radiation (R_s) from data collection platform (DCP) for four climatic zones of northeastern Brazil were compared to the re-analysis data. Applying cluster analysis to R_s from database, homogeneous sub-regions in northeastern Brazil were determined. Long times series of R_s and sunshine duration measurements data for two sites, Petrolina (09°09′S, 40°22′W) and Juazeiro (09°24′S, 40°26′W), exceeding 30 years, were analyzed. In order to exclude the decadal variations which are linked to the Pacific Decadal Oscillation, high-frequency cycles in the solar radiation and sunshine duration time series were eliminated by using a 14-year moving average, and the Mann-Kendall test was employed to assess the long-term variability of re-analysis and measured solar radiation. This study provides an overview of the decrease in solar radiation in a large area, which can be attributed to the global dimming effect. The global solar radiation obtained from the NCEP/NCAR re-analysis data overestimate that obtained from DCP measurements by 1.6% to 18.6%. Results show that there is a notable symmetry between R_s from the re-analysis data and sunshine duration measurements.     

太湖地区光合有效辐射(PAR)的基本特征及其气候学计算

光合有效辐射（Photosynthetically Availble Radiation,简称PAR）是植物进行光合作用的重要能量来源。利用太湖湖泊生态系统研究站1998年1－12月一年的气象辐射观测资料，分析了该地区有效辐射以及占太阳总辐射比例的变化特征，并分析了光合有效辐射的极值及对应的光合有效辐射占总辐射的比例和它与云量的的关系，最后提出了适合本地区的光合有效辐射的气候学计算方法。     

The effect of model generated solar radiation data usage in hybrid (wind–PV) sizing studies

Wind speed and solar radiation characteristics belonging to past years of a region are the main input parameters in wind–photovoltaic hybrid system (WPHS) sizing studies. Classically, these data are fed to several scenarios with different solar panel, wind turbine, and storage battery number combinations. The solutions with minimal cost which also satisfy the desired maximum loss of energy probability are selected. Since the utilized data have random fluctuations because of atmospheric phenomenon, past years’ data are unlikely to appear in a similar manner in future years. Hence, using a robust model that characterizes the general behavior of the data instead of directly using past data should yield more accurate sizing solutions. In order to compare the sizing accuracy obtained by directly using the data to the accuracy obtained by indirect modeling from data, an analytical solar radiation model is first explained. Using this model, 3-year solar radiation data of three geographical sites are analyzed. It was observed that the differences between sample-by-sample hourly recordings corresponding to different years are significantly larger than the difference between these recordings and the data model obtained from an arbitrary year. This provides a hint that a sizing approach carried out using the data of a previous year would not be accurate in producing the same Loss of Load Probability (LLP) for a future year. On the contrary, the accuracy would improve if a generic analytical model of the solar radiation is used in the sizing process. This foresight is tested by comparing the LLPs obtained in the two ways mentioned above. Results obtained using available data are in accordance with the aforementioned propositions.