Solar Resource Assessment Research Articles

Quantifying the spatial scale mismatch between satellite-derived solar irradiance and in situ measurements: A case study using CERES synoptic surface shortwave flux and the Oklahoma Mesonet

The spatial scale mismatch between gridded irradiance products and in situ measurements is perhaps the least understood topic in solar resource assessment. However, it has a profound impact on virtually all solar applications that involve satellite-derived or reanalysis irradiance data. This paper investigates spatial scale mismatch through a kriging-based upscaling method. Point-location measurements from a monitoring network are upscaled to the size of a satellite-derived irradiance footprint. Subsequently, satellite-derived irradiance is validated against both the nearest point-location measurements and the upscaled areal averages, and the error reduction can, thus, be used to quantify the amount of spatial scale mismatch. In that, a new measure is proposed. The empirical part of the paper considers a synoptic scale satellite-derived irradiance product, namely, National Aeronautics and Space Administration's Clouds and the Earth's Radiant Energy System synoptic surface shortwave flux, and a mesoscale monitoring network, namely, the Oklahoma Mesonet. Based on two years of hourly data and the proposed measure, the spatial scale mismatch is found to be 45% for the U.S. state of Oklahoma.

Intercomparison of Satellite-Derived Solar Irradiance from the GEO-KOMSAT-2A and HIMAWARI-8/9 Satellites by the Evaluation with Ground Observations

Solar irradiance derived from satellite imagery is useful for solar resource assessment, as well as climate change research without spatial limitation. The University of Arizona Solar Irradiance Based on Satellite–Korea Institute of Energy Research (UASIBS-KIER) model has been updated to version 2.0 in order to employ the satellite imagery produced by the new satellite platform, GK-2A, launched on 5 December 2018. The satellite-derived solar irradiance from UASIBS-KIER model version 2.0 is evaluated against the two ground observations in Korea at instantaneous, hourly, and daily time scales in comparison with the previous version of UASIBS-KIER model that was optimized for the COMS satellite. The root mean square error of the UASIBS-KIER model version 2.0, normalized for clear-sky solar irradiance, ranges from 4.8% to 5.3% at the instantaneous timescale when the sky is clear. For cloudy skies, the relative root mean square error values are 14.5% and 15.9% at the stations located in Korea and Japan, respectively. The model performance was improved when the UASIBS-KIER model version 2.0 was used for the derivation of solar irradiance due to the finer spatial resolution. The daily aggregates from the proposed model are proven to be the most reliable estimates, with 0.5 km resolution, compared with the solar irradiance derived by the other models. Therefore, the solar resource map built by major outputs from the UASIBS-KIER model is appropriate for solar resource assessment.

Site-Adaptation of Modeled Solar Radiation Data: The SiteAdapt Procedure

The adaptation of modeled solar radiation data with coincident ground measurements has become a standard practice of the industry, typically requested by financial institutions in the detailed solar resource assessments of solar projects. This practice mitigates the risk of solar projects, enhancing the adequate solar plant design and reducing the uncertainty of its yield estimates. This work presents a procedure for improving the accuracy of modeled solar irradiance series through site-adaptation with coincident ground-based measurements relying on the use of a regression preprocessing followed by an empirical quantile mapping (eQM) correction. It was tested at nine sites in a wide range of latitudes and climates, resulting in significant improvements of statistical indicators of dispersion, distribution similarity and overall performance: relative bias is reduced on average from −1.8% and −2.3% to 0.1% and 0.3% for GHI and DNI, respectively; relative root mean square deviation is reduced on average from 17.9% and 34.9% to 14.6% and 29.8% for GHI and DNI, respectively; the distribution similarity is also improved after the site-adaptation (KSI is 3.5 and 3.9 times lower for GHI and DNI at hourly scale, respectively). The methodology is freely available as supplementary material and downloadable as R-package from SiteAdapt.

Development and validation in a 2D-GIS environment of a 3D shadow cast vector-based model on arbitrarily orientated and tilted surfaces

This paper presents a systematic GIS-based methodology to obtain the shadow cast profile of a group of buildings on arbitrarily orientated and tilted surfaces. The model is integrated in the widely-employed 2D-GIS environment. Given its scalability, the methodology can be easily applied from a local level up to a district, city or even regional level. This work is of interest for a wide range of applications such as for instance in Solar Resource Assessments (SRA) in urban environments.The starting point is to use cadastral cartography and LiDAR altimetric data to obtain a 3D vector-based model of the buildings using high robust mode estimators. Once the geometry of the buildings is defined, analytical models are applied to calculate the shadow cast profile on any arbitrarily orientated and tilted surface of the surroundings.The model has been implemented in the R programming language. An extensive validation has been carried out for several buildings of Valencia (Spain) using CAD elevation views of the buildings and the SketchUp’s shadow tool. The error of the vector-based city model is lower than 1% in all LiDAR datasets. The maximum error of the overall methodology, including both height and shadow models, is lower than 2%.

Development of a clear-sky model to determine circumsolar irradiance using widely available solar radiation data

Accurate assessment of the solar irradiance reaching the absorber of concentrating solar power (CSP) systems is crucial for accurate energy generation estimates as well as for power plants design and operation. Due to a larger aperture angle, direct normal irradiance (DNI) measurements taken by pyrheliometers include circumsolar normal irradiance (CSNI), i.e., the diffuse radiance from the vicinity of the sun disk, which in some cases is not totally captured by the CSP systems because of their lower aperture angles. This work reports the modelling of DNI and CSNI using a radiative transfer model and atmospheric measurements and aims to develop a fast and simple model to estimate the CSNI based on more common solar irradiance measurements such as the DNI, global horizontal irradiance (GHI) and diffuse horizontal irradiance (DHI). The proposed model performs better than other models available in the literature for the six locations analysed (scattered around the globe), thus contributing to a more accurate solar resource assessment and CSP systems design and operation.

Worldwide validation of 8 satellite-derived and reanalysis solar radiation products: A preliminary evaluation and overall metrics for hourly data over 27 years

Gridded solar radiation products, namely satellite-derived irradiance and reanalysis irradiance, are key to the next-generation solar resource assessment and forecasting. Since their accuracies are generally lower than that of the ground-based measurements, providing validation of the gridded solar radiation products is necessary in order to understand their qualities and characteristics. This article delivers a worldwide validation of hourly global horizontal irradiance derived from satellite imagery and reanalysis. The accuracies of 6 latest satellite-derived irradiance products (CAMS-RAD, NSRDB, SARAH-2, SARAH-E, CERES-SYN1deg, and Solcast) and 2 latest global reanalysis irradiance products (ERA5 and MERRA-2) are verified against the complete records from 57 BSRN stations, over 27 years (1992–2018). This scope of validation is unprecedented in the field of solar energy. Moreover, the importance of using distribution-oriented verification approaches is emphasized. Such approaches go beyond the traditional measure-oriented verification approach, and thus can offer additional insights and flexibility to the verification problem.

Evaluation of the reanalysis surface solar radiation from NCEP, ECMWF, NASA, and JMA using surface observations for Balochistan, Pakistan

Solar radiation from reanalysis datasets can be used to estimate solar energy potential in the absence of long-term surface measured data. Comprehensive validation of reanalysis data against short-term measurements of solar radiation is necessary to find uncertainties. The evaluation of the performance of seven reanalysis datasets (ERA-5, MERRA-2, ERA-Interim, JRA-55, NCEP-NCAR, NCEP-DOE, and CFSR) for Balochistan against high-quality surface measured data was performed using statistical analysis. The relative mean bias error (rMBE), relative mean absolute error (rMAE), and relative root mean square error of reanalysis solar radiation range from −4 to 7%, 8 to 14%, and 16 to 21%, respectively, using sub-daily data of six datasets except for NCEP-NCAR. Seasonal statistical analysis was performed to study seasonal variation of performance of datasets, which reveals the significant variation of errors in different seasons. Analysis of monthly mean data shows that rMBE and rMAE are less than 3 and 5% for ERA-5, respectively. The performance of the dataset changes by changing the temporal resolution of the data used for comparison. The monthly mean values of data show better performance, but the accuracy of data is compromised. The solar radiation data of ERA-5 can be used for preliminary solar resource assessment and power estimation.

Research of the variable natural potential of the wind and energy energy in the northern strip of the ukrainian carpathians

The expediency of studying the varying potential of wind and solar energy in the northern strip of the Ukrainian Carpathians is substantiated. The technique of conducting experiments to determine the natural potential of wind and solar energy is proposed and a model for determining the relative volumes of electricity generation by wind farms and solar electrical installations is developed. Based on the conducted research, according to the Drohobych meteorological station, an energy assessment of wind and solar energy resources in the northern strip of the Ukrainian Carpathians was performed. It is substantiated that the theoretical curves of distribution of wind velocity in separate quarters of the year in the territory of the northern strip of the Ukrainian Carpathians are described by the Weibull distributions. Based on the calculations, it is established that the highest total daily solar radiation is in the summer months. Daily graphs of the relative generation of electricity by wind farms and solar electric installations have been constructed. The expediency of formation of combined systems of energy supply of objects from wind and solar energy in the northern strip of the Ukrainian Carpathians has been established. The substantiated patterns of change in the natural potential of wind and solar energy, as well as the graphs of the relative generation of electricity from them, will significantly speed up managerial decisions and improve their quality.

Site-specific tailoring of an optimal design of renewable energy system for remote water supply station in Silchar, India

Solar energy is considered as a potential solution for meeting the electrical needs in remote areas having no access to utility grid. However, its intermittent nature and dependence on geographical location possess a major challenge to design renewable energy system for sustainable utilization of solar energy. In this study, site-specific solar resource assessment using statistical parameters, HOMER based techno-economic assessment, and environmental impact analysis are done to design an optimal solar PV-battery based system for water supply station of a remote area of Silchar, India. The results show that two years’ average daily accumulated global solar radiation is 3.67 kWh/m2-day and the clearness index reveals that 73.5% of the days have partly clear or complete clear sky conditions. The Linke turbidity factor ranges from 3.5 to 5.5. The HOMER simulation results show that 257,014 kWh of energy is produced annually by the PV-battery system and the per-unit cost of energy is found to be $0.307/kWh. The environmental analysis shows that a maximum 98.16% reduction in CO2 emission can be achieved when compared to conventional fuel-based plant. This study provides a realistic approach using site specific solar resource data to optimize a renewable energy system design for remote area application.

Solar resource assessment of modern parking machines in an urban environment

This study presents a methodology for assessing the potential solar resource available at solar-powered parking machines installed in a typical city center. It is based on capturing fisheye images through an appropriate camera/lens. These images are then processed to classify the sky and non-sky pixels using a semi-automated sky detection method, also developed in this study. The processed images are then used to calculate the diffuse and beam solar potential of the site by estimating the visible fraction of the sky and the hours of the year during which the sun can be seen from the site, respectively. For the case study, 15 existing parking machines were analyzed in the central business district of Auckland (New Zealand). It was found that most of these machines were able to capture less than 50% of the available solar potential. Only two machines crossed the yearly irradiation threshold that represents the criterion for solar panel installation. If modern high-power solar-powered machines are used, selecting suitable locations for installation is crucial.

Analysis and research on quality control method of global radiation observation data

Radiation observation data are important basic data for assessment and research of climate change and solar energy resources. Quality control of radiation observation data is an important guarantee for accurate and reliable observation. First, the global radiation data collection method and the quality control process are introduced, and the differences and similarities between different quality control standards are compared in detail. Then, the quality control contents of the upper and lower limits and the rate of change are analysed theoretically and verified by experiments. Theoretical analysis and experimental results showed that the lower limit of the global radiation irradiance quality control should be −20 W/m2, the upper limit should be 2221 W/m2 or based on solar position, and the wrong change rate of sampling value should be 1000 W/m2. Through the unification of the global radiation quality control standards, the difference caused by the inconsistent quality control methods can be avoided, thus improving the effectiveness of the radiation observation data and ensuring the accuracy and consistency of the radiation observation data.

Solar irradiance time series derived from high-quality measurements, satellite-based models, and reanalyses at a near-equatorial site in Brazil

This study analyzes five years of 1-min solar global horizontal irradiance (GHI) and direct normal irradiance (DNI) observations obtained at Petrolina (northeast Brazil). Quality-assured hourly and daily averages are obtained after applying filters and methodologies based on a Baseline Solar Radiation Network (BSRN) quality-control procedure. To calculate correct hourly averages, a minimum fraction of 20% of valid GHI or DNI minutely data is needed, as well as at least 60% of valid days to calculate correct daily-mean monthly values. An asymmetric diurnal pattern is found in GHI and DNI during all months, attributed to consistently higher cloudiness in the morning. The quality-assured hourly and monthly-mean GHI and DNI time series are compared to estimates from 11 solar databases regularly used in solar resource assessment studies: CAMS, CERES, ERA5, INPE, MERRA-2, Meteonorm, NASA-POWER, NSRDB, SARAH, SWERA-BR, and SWERA-US. For hourly GHI values, a range of RMS differences is found between the best (CAMS, 17.3%) and the worst (MERRA-2, 38.9%) results. The latter database is also affected by a larger bias (18.7%) than CAMS (4%). Larger RMS differences are found with hourly DNI, in a range extending from 37% (CAMS) to 63.4% (ERA5). Biases are all above 12%, except for CERES (−1%). For long-term mean-monthly GHI results, low biases of less than 1% are obtained with CAMS, CERES and NASA-POWER, whereas MERRA-2 overestimates (13%). Larger biases are found for mean-monthly DNI, spanning between CAMS (3%) and Meteonorm (−18.4%). Overall, CAMS appears the most consistent solar database for long-term irradiance time series at Petrolina. The significant differences found here between modeled databases are larger than expected, and underline the importance of regional validation studies like this one to decrease the incidence of uncertainties in solar resource assessments on the design and performance of solar energy projects.

Solar Irradiation Data Processing using estimator MatriceS (SIMS) validated for Portugal (southern Europe)

Accurate solar resource assessment is essential in all the different phases of solar energy systems design and implementation. On a local scale, the solar resource is best assessed from ground measurements and, if available, with the existence of complete time-series of hourly values for the long-term resource estimation. However, these usually suffer from the occurrence of data gaps that can be as large as several months for remote and/or less maintained stations. Such gaps hinder the correct assessment of solar availability and, for that matter, their filling is a crucial first step to perform an appropriate assessment. In this context, a method for Solar Irradiation Data Processing using estimator MatriceS (SIMS) has been developed and is presented here. The algorithm allows to determine long-term linear correlations between a network of spatially distributed stations and, with these, to identify possible outliers and to fill data gaps through the selection of the median value from the obtained estimations. The method is validated against global horizontal irradiation (GHI) data from a network that comprises 89 ground-measuring stations, being maintained by the Portuguese Meteorology Service (IPMA - Instituto Português do Mar e da Atmosfera), considering a period of 17 years (from 2001 to 2017). Two important assertions are made for coefficients between stations: (1) coefficients only decrease slightly with the distance between stations (with a median reduction of ∼0.0003 km−1), for the considered network; (2) asymptotic long-term coefficients are reached with only one year of data. Taking advantage of the SIMS method, GHI assessment is presented here in the form of availability maps over the Portuguese mainland, with the respective values being listed in a table for future reference. The present assessment confirms that Portugal is a suitable region for the implementation of solar energy systems, with GHI having availabilities up to 2028.4 kWh/m2/year ±3.4% in Sagres (southernmost part of Portugal).

High-resolution assessment of solar energy resources over the Arabian Peninsula

This study presents a high-resolution spatial and temporal assessment of the solar energy resources over the Arabian Peninsula (AP) from 38 years (1980–2017) reanalysis data generated using an assimilative Weather Research and Forecasting Solar model. The simulations are performed based on two, two-way nested domains with 15 km and 5 km resolutions using the European Centre for Medium-Range Weather Forecasts as initial and boundary conditions and assimilating most of available observations in the region. Simulated solar energy resources, such as the Global Horizontal Irradiance (GHI), Direct Normal Irradiance (DNI), and the Diffusive Horizontal Irradiance (DHI), are first validated with daily observations collected at 46 in-situ radiometer stations over Saudi Arabia for a period of four years (2013–2016). Observed and modelled data are in good agreement with high correlation coefficients, index of agreements, and low normalized biases.The total mean annual GHI (DNI) over the AP ranges from 6000 to 8500 Wh m−2 (3000 to 6500 Wh m−2) with significant seasonal variations. The diffuse fraction (the ratio of the DHI to the GHI) is high (low) over the northern (southern) AP in winter whereas it is high (low) over the central to southern (northern) AP during summer, indicating a significant modulation of the sky clearness over the region. Clouds over the northern AP in winter and the aerosol loading due to desert dust over the central and southern AP in summer are the major factors driving the variability of the DHI. The effects of dust and clouds are more pronounced in the diurnal variability of the solar radiation parameters. Our analysis of various solar radiation parameters and the aerosol properties suggest a significant potential for solar energy harvesting in the AP. In particular, the southeastern to northwestern Saudi Arabia are identified as the most suitable areas to exploit solar energy with a minimum cloud coverage over the region.

Current energy mix and techno-economic analysis of concentrating solar power (CSP) technologies in Malaysia

This study performs a techno-economic analysis of concentrating solar power (CSP) technologies for Malaysia. The solar resource assessment was done by analyzing various rural and regional locations using NASA Surface Meteorology and Solar Energy database. Three different technologies, parabolic trough collector (PTC), solar power tower (SPT) and solar parabolic dish (SPD) were assessed under different economic criterions. Results based on the analysis show that PTC and SPT type plants are particularly suitable for locations at East and Peninsular Malaysia. However, considering simple payback, the net present value (NPV) and internal rate of return (IRR), it is found that PTC type CSP plant will be the most eligible for CSP plant development. Sensitivity analysis is performed to investigate the effect of the levelized cost of electricity (LCOE) on the various project discount rate. Regional renewable energy policy development and regulatory reform in feed-in-tariff (FiT), hybrid technology (PTC with biogas, solar PV and biomass) implementation, project financing under clean development mechanism (CDM) and lesson learned from international experience in local PTC equipment manufacturing are some of the crucial future policy outlooks that need to be applied for CSP technology implementation, as well as long-term sustainable renewable energy system development in the country.

Climate-specific and global validation of MODIS Aqua and Terra aerosol optical depth at 452 AERONET stations

Aerosol optical depth (AOD) is a highly influential variable in solar resource assessment and clear-sky radiation modelling. Hence, the accuracy of solar energy estimates ultimately depends on the accuracy of the measured or assumed AOD. Gridded satellite information is often used for solar modelling due to its geographical coverage, and so a global validation of commonly utilised AOD products is imperative. Here, all Level-3 Moderate Resolution Imaging Spectroradiometer (MODIS) daily observations of AOD (at 470, 550 and 660 nm, noted AOD470, AOD550 and AOD660, respectively) from the Aqua and Terra satellites (of 1° × 1° spatial resolution) from 2000 to 02/2018 are compared and validated against all of NASA’s ground sensing Aerosol Robotic NETwork (AERONET) V3 Level 2 AOD daily averages from sites that reported at least one year of observations during 2000–2018 (452 sites representing at least 653,000 observations per variable). Furthermore, sub-categorisation by Köppen-Geiger climate regions enables a novel climate-specific validation to ascertain any distinct climatic influence. The results demonstrate significant climatological influences that impact the derived AOD product at all three wavelengths. It is found that blending the two Aqua and Terra products results in a higher accuracy of daily estimates of all AOD products. Each AOD product is validated similarly and separately. AOD550, which is most commonly used in solar resource assessment, is found worst in the equatorial climate (absolute root mean square error (RMSE) of 0.194) and best in the temperate climate (RMSE of 0.126). Globally, the combined Aqua + Terra AOD550 experiences an absolute RMSE of 0.106 and a mean absolute error of 0.109. The most common MODIS AOD retrievals are between 0.01 and 0.25, suggesting that the MODIS daily AOD products may introduce a significant source of uncertainty in modelled irradiance estimates, and that other sources of input data should be used instead whenever their applications demand high accuracy.

Towards the Development of a Low-Cost Irradiance Nowcasting Sky Imager

Solar resource assessment is fundamental to reduce the risk in selecting the solar power-plants’ location; also for designing the appropriate solar-energy conversion technology and operating new sources of solar-power generation. Having a reliable methodology for solar irradiance forecasting allows accurately identifying variations in the plant energy production and, as a consequence, determining improvements in energy supply strategies. A new trend for solar resource assessment is based on the analysis of the sky dynamics by processing a set of images of the sky dome. In this paper, a methodology for processing the sky dome images to obtain the position of the Sun is presented; this parameter is relevant to compute the solar irradiance implemented in solar resource assessment. This methodology is based on the implementation of several techniques in order to achieve a combined, fast, and robust detection system for the Sun position regardless of the conditions of the sky, which is a complex task due to the variability of the sky dynamics. Identifying the correct position of the Sun is a critical parameter to project whether, in the presence of clouds, the occlusion of the Sun is occurring, which is essential in short-term solar resource assessment, the so-called irradiance nowcasting. The experimental results confirm that the proposed methodology performs well in the detection of the position of the Sun not only in a clear-sky day, but also in a cloudy one. The proposed methodology is also a reliable tool to cover the dynamics of the sky.

Uncertainty Analysis of Energy Production for a 3 × 50 MW AC Photovoltaic Project Based on Solar Resources

Access to solar energy is a prerequisite to remedy CO2 and improve the standard of human living. Green solar energy is only an immediate solution to add its zero emission profile and provide carbon footprint reduction benefits. This energy does not emit greenhouse gases which means it is a renewable free source of energy when producing electricity. The purpose of this paper is to investigate the accurate annul energy production data reducing uncertainty in solar energy estimates. This work investigated the solar energy assessment taking into account a detailed solar resource and energy production assessment for a 3 × 50 MW PV project with uncertainty analysis. The authors defined a total uncertainty of energy production which is estimated at 9.5% for one year and 8.9% for ten years as well as future variability of 3.4% for one year and 1.1% for ten years. The annual power degradation and expected energy production over the plant lifespan at dissimilar 99%, 90%, 75%, 60%, 50%, and 25% probability of surplus are also observed in this paper.

Probabilistic prediction of direct normal irradiance derived from global horizontal irradiance over the Korean Peninsula by using Monte-Carlo simulation

Solar resource assessment is carried out in a feasibility study using reliable meteorological elements including solar irradiance. In concentrating solar power plants, the direct normal irradiance is the key variable in the system operation. However, direct normal irradiance is rarely measured as compared to global horizontal irradiance. There are several models that can be used to derive the direct normal irradiance from global horizontal irradiance. In this study, the Engerer model is used as a decomposition model, then evaluated against in situ observations at three ground stations: Seoul, Buan, and Jeju ground stations. The relative root mean square errors between the observed and direct normal irradiance estimated by the Engerer model are 15.0%, 19.4%, and 17.1% at Seoul, Buan, and Jeju ground stations, respectively. The uncertainty of estimates is represented by the prediction interval from probabilistic prediction through Monte-Carlo simulation that employs the bias between estimation and ground truth for training datasets. The prediction interval for 90% confidence level is 117.9 W m−2 at the Seoul station, resulting from Monte-Carlo simulation. The prediction interval coverage probability is 92.8%, implying that the probability that observed DNI is not included in the prediction interval is 7.2%. The error metrics for probabilistic prediction indicates that Monte-Carlo simulation provides both valid and more informative estimations.

High Wind Power Penetration Large-Scale Hybrid Renewable Energy System Design for Remote Off-Grid Application

This study looks into the resource assessment, technology economics and modeling of different energy alternatives and proposes a rechargeable battery storage-based large-scale wind/photovoltaic hybrid power system to meet an average electrical load demand of 2.4 MW and peak load of 2.9 MW for a remote rural district in Ethiopia called Geladin. The district is 682 km away from nearby grid. The site enjoys high solar and wind resources that can be harnessed for electric power generation to electrify the community. HOMER simulation software is used for optimal sizing and techno-economic analysis. The diesel generator is used as back up to fill the gaps in case both resources are out. Average monthly solar irradiation data of 6.2 kWh/m2 is determined from measured sunshine duration data by implementing a suitable specific model for the site. NASA satellite based estimated wind speed data of 10 years average at hub height of 50 m for the site in question is extracted from the SWERA (Solar and Wind Energy Resource Assessment) database (with annual average of 6.1 m/s) and its weigh-bull distribution parameter, k of 1.98 is estimated which indicates a fair wind speed distribution of the site to generate electric power using wind turbine. The proposed optimal system results electricity generation indicates that 92% from wind turbine, 3% from photovoltaic, 5% from diesel generator and managed to obtain a much lower cost of energy (COE = 0.11USD/kWh) than other alternatives investigated in this study such as grid extension and diesel generator.