Development of new monthly global and diffuse solar irradiation estimation methodologies and comparisons

In assessing and deciding the prediction schemes of solar irradiation countrywide, better the accuracy means better the management of energy transition toward renewables. Consequently, the present study is on the development of new models to make the most accurate possible estimations of the global and diffuse solar irradiation based on ground measurements. Such analysis produces the most accurate estimations for the input of solar energy systems. This is utmost significant for deciding the investments on solar energy systems and their design periods. Turkey is a high-potent country whose solar energy market has been growing rapidly. She doesn’t have adequate reliable measurement network and there is no estimation methodology developed for each and every point within its territory. Moreover, installing such a measurement system network doesn’t seem to be economically feasible and technically possible, inter alia. Accordingly, this study defines a methodology to make the most accurate estimations of monthly mean daily solar irradiation on horizontal surface and its diffuse and beam components. For the global and diffuse estimations, new methodologies in linear and quadratic forms are developed, compared, and discussed. The comparison is applied by using mean bias error and root mean square error statistical comparison methods. The measured data values used for modeling and comparisons are provided from the State Meteorological Service of Turkey responsible authority for solar irradiation measurements. The results revealed that the methodologies explained in this study give very high accurate values of total solar irradiation on a horizontal surface and its diffuse component.     

Comparisons and critical assessment of global and diffuse solar irradiation estimation methodologies

Defining better methodologies of accurate predictions of the amount of monthly mean daily global and diffuse solar irradiation exposed is of utmost importance in order to determine the potential for utilizing the solar energy. This study compares and discusses the main methodologies, databases, and software that are used in estimating the solar irradiation to be used for the short- and long-term performances and feasibilities of solar energy systems, especially photovoltaic power plants in Turkey, and addresses the best one to be used to make the most accurate estimations. The comparisons are carried out between the recent methodologies developed by the authors, some models taken from the related literature that are concluded to be better, a widely used database, namely Meteonorm, and a widely used software, namely EU PVGIS. The reference data to develop the methodologies and to make comparison are provided from the State Meteorological Service of Turkey, which is the responsible body in Turkey to make measurements of solar irradiation. The comparisons are based on monthly mean daily values of global and diffuse solar irradiation and are carried out by statistical errors: mean bias error and root mean square error. The results showed that the methodology developed by the authors has shown better performances in estimating the monthly mean daily global and diffuse solar irradiation amount for Turkey.     

The global solar radiation estimation and analysis of solar energy: Case study for Osmaniye,Turkey

This paper investigates the prediction of solar radiation model and actual solar energy in Osmaniye, Turkey. Four models were used to estimate using the parameters of sunshine duration and average temperature. In order to obtain the statistical performance analysis of models, the coefficient of determination (R²), mean absolute percentage error (MAPE), mean absolute bias error (MABE), and root mean square error (RMSE) were used. Results obtained from the linear regression using the parameters of sunshine duration and average temperature showed a good prediction of the monthly average daily global solar radiation on a horizontal surface. In order to obtain solar energy, daily and monthly average solar radiation values were calculated from the five minute average recorded values by using meteorological measuring device. As a result of this measurement, the highest monthly and yearly mean solar radiation values were 698 (April in 2013) and 549 (2014 year) W/m² respectively. On an annual scale the maximum global solar radiation changes from 26.38 MJ/m²/day by June to 19.19 MJ/m²/day by September in 2013. Minimum global solar radiation changes from 14.05 MJ/m²/day by October to 7.20 MJ/m²/day by January in 2013. Yearly average energy potential during the measurement period was 16.53 MJ/m²/day (in 2013). The results show that Osmaniye has a considerable solar energy potential to produce electricity.     

Comparison of the daily global solar radiation from different data sources in Northwest China climate

The solar radiation data are of high importance to the solar energy systems. Conventional methods to obtain the solar radiation data are from weather stations, solar radiation models, commercial software databases, and field measurements. In the present study, a new daily global solar radiation model is proposed, by combining the quadratic function of sunshine fraction and sine function of the day of the year. The solar radiation model calculated data are then compared with China Meteorological Data Sharing System (CMDSS) data, TRNSYS data, and field-measured data in Northwest China climate. It is found that the newly proposed solar radiation model has better performance than the other nine solar radiation models in the literature. The solar radiation model calculated data fit well with the CMDSS annually average data. The TRNSYS data are a bit larger than the CMDSS annually average data in summer half year and a little smaller than those in winter half year. The solar radiation model and the CMDSS annually average data have the best correlation, whereas the TRNSYS data and the field-measured data have the worst correlation. The solar radiation model calculated data have the best correlation with the other three data sources.     

A simple method for partitioning total solar radiation into diffuse/direct components in the United States

Solar radiation is a major sustainable and clean energy resource, and use of solar radiation is expected to increase. The utilization efficiency of solar energy varies with the relative proportions of the direct and diffuse components that compose total solar radiation and with the slope and aspect of the irradiated surface. The purpose of this paper is to develop a simple method for estimating diffuse and direct solar radiation at sites with observation of only total solar radiation. An existing model for estimating diffuse radiation, i.e., a linear relationship between the diffuse fraction (the ratio of diffuse radiation to total solar radiation) and the clearness index (the ratio of total solar radiation to extraterrestrial radiation), is applied to 7 sites across the continental United States with observations of diffuse and total radiation. The linear model shows good monthly performance. The model parameters (slope and interception) show a strong seasonal pattern that exhibits small variation across the 7 sites; therefore, the average values of the two monthly parameters may be used for estimating diffuse radiation for other locations with observations of total radiation.     

Evaluation of various global solar radiation models for Nigeria

This study assessed the performance of six solar radiation models. The objective was to determine the most accurate model for estimating global solar radiation on a horizontal surface in Nigeria. Twenty-two years meteorological data sets collected from the Nigerian Meteorological agency and the National Aeronautics and Space Administration for the three regions, covering the entire climatic zones in Nigeria were utilized for calibrating and validating the selected models for Nigeria. The accuracy and applicability of various models were determined for three locations (Abuja, Benin City, and Sokoto), which spread across Nigeria using seven viable statistical indices. This study found that the estimation results of considered models are statistically significant at the 95% confidence level, but their accuracy varies from one location to another. However, the multivariable regression relationship deduced in terms of sunshine ratio, air temperature ratio, maximum air temperature, and cloudiness performs better than other relationships. The multivariable relationship has the least root mean square error and mean absolute bias error, not exceeding 1.0854 and 0.8160 MJ m^?2 day^?1, respectively, and monthly relative percentage error in the range of ± 12% for the study areas.     

Comparison of ANN,MVR, and SWR models for computing thermal efficiency of a solar still

In this paper, the viability of modeling the instantaneous thermal efficiency (η_ith) of a solar still was determined using meteorological and operational data with an artificial neural network (ANN), multivariate regression (MVR), and stepwise regression (SWR). This study used meteorological and operational variables to hypothesize the effect of solar still performance. In the ANN model, nine variables were used as input parameters: Julian day, ambient temperature, relative humidity, wind speed, solar radiation, feed water temperature, brine water temperature, total dissolved solids of feed water, and total dissolved solids of brine water. The η_ith was represented by one node in the output layer. The same parameters were used in the MVR and SWR models. The advantages and disadvantages were discussed to provide different points of view for the models. The performance evaluation criteria indicated that the ANN model was better than the MVR and SWR models. The mean coefficient of determination for the ANN model was about 13% and14% more accurate than those of the MVR and SWR models, respectively. In addition, the mean root mean square error values of 6.534% and 6.589% for the MVR and SWR models, respectively, were almost double that of the mean values for the ANN model. Although both MVR and SWR models provided similar results, those for the MVR were comparatively better. The relative errors of predicted η_ith values for the ANN model were mostly in the vicinity of ±10%. Consequently, the use of the ANN model is preferred, due to its high precision in predicting η_ith compared to the MVR and SWR models. This study should be extremely beneficial to those coping with the design of solar stills.     

Drying of salted silver jewfish in a hybrid solar drying system and under open sun: Modeling and performance analyses

This study investigated the thin-layer drying kinetics of salted silver jewfish in a hybrid solar drying system and under open sun. Ten drying models were compared with experimental data of salted silver jewfish drying. A new model was introduced, which is an offset linear logarithmic (offset modified Page model). The fit quality of the models was evaluated using the coefficient of determination (R²), root mean square error (RMSE), and sum of squared absolute error (SSAE). The result showed that Midilli et al. model and new model were comparable with two or three-term exponential drying models. This study also analyzed energy and exergy during solar drying of salted silver jewfish. Energy analysis throughout the solar drying process was estimated on the basis of the first law of thermodynamics, whereas exergy analysis during solar drying was determined on the basis of the second law of thermodynamics. At an average solar radiation of 540 W/m² and a mass flow rate of 0.0778 kg/sec, the collector efficiency and drying system efficiency were about 41% and 23%, respectively. Specific energy consumption was 2.92 kWh/kg. Moreover, the exergy efficiency during solar drying process ranged from 17% to 44%, with an average value of 31%. The values of improvement potential varied between 106 and 436 W, with an average of 236 W.     

The Importance of the Chosen Technique to Estimate Diffuse Solar Radiation by Means of Regression

The Ordinary Least Squares (OLS) is one of the widely used methods which is used for estimating the diffuse solar radiation. However, in order to use the OLS method in the estimation, the dataset must provide certain assumptions. In this study, alternative robust methods have been described and they were compared with the OLS method, which is used for estimating diffuse radiation frequently in an application. At the end of the analysis, the R² value obtained by the OLS method is less than the values obtained by M regression models. In other words, the explanation of the dependent value is weak when the OLS method is used. Finally, it can be said that the most appropriate method is Andrews for estimating the diffuse solar radiation.     

Available solar energy for flat-plate solar collectors mounted on a fixed or tracking structure

The solar energy received by a flat plate collector is calculated for various tracking modes: fixed, inclination depending on the season or the month; variable inclination with fixed azimuth, variable azimuth with fixed inclination and double tracking. At first, we take into account only the sun position and then, we use validated radiation models for estimating the ground solar radiation. Using a tracker is questionable particularly if the additional costs are taken into account. A good solution to increase the available solar energy is to change seasonally the inclination, that is, 4 times per year.     

Global solar radiation and energy yield estimation from photovoltaic power plants for small loads

Daily global solar radiation on a horizontal surface and duration of sunshine hours have been determined experimentally for five meteorological stations in Saudi Arabia, namely, Abha, Al-Ahsa, Al-Jouf, Al-Qaisumah, and Wadi Al-Dawaser sites. Five-years of data covering 1998–2002 period have been used. Suitable Angstrom models have been developed for the global solar radiation estimation as a function of the sunshine duration for each respective sites. Daily averages of monthly solar PV power outputs have been determined using the Angstrom models developed. The effect of the PV cell temperature on the PV efficiency has been considered in calculating the PV power output. The annual average PV output energy has been discussed in all five sites for small loads. The minimum and maximum monthly average values of the daily global solar radiation are found to be 12.09 MJ/m²/d and 30.42 MJ/m²/d for Al-Qaisumah and Al-Jouf in the months of December June, respectively. Minimum monthly average sunshine hours of 5.89 hr were observed in Al-Qaisumah in December while a maximum of 12.92 hr in Al-Jouf in the month of June. Shortest range of sunshine hours of 7.33–10.12 hr was recorded at Abha station. Minimum monthly average Solar PV power of 1.59 MJ/m²/day was obtained at Al-Qaisumah in the month of December and a maximum of 3.39 MJ/m²/day at Al-Jouf in June. The annual PV energy output was found to be 276.04 kWh/m², 257.36 kWh/m², 256.75 kWh/m², 245.44 kWh/m², and 270.95 kWh/m² at Abha, Al-Ahsa, Al-Jouf, Al-Qaisumah, and Wadi Al-Dawaser stations, respectively. It is found that the Abha site yields the highest solar PV energy among the five sites considered.     

Prediction of global solar radiation using support vector machines

This article utilizes Support Vector Machines (SVM) for predicting global solar radiation (GSR) for Sharurha, a city in the southwest of Saudi Arabia. The SVM model was trained using measured air temperature and relative humidity. Measured data of 1812 values for the period from 1998–2002 were obtained. The measurement data of 1600 were used for training the SVM, and the remaining 212 were used for comparison between the measured and predicted values of GSR. The GSR values were predicted using the following four combinations of data sets: (i) Daily mean air temperature and day of the year as inputs, and global solar radiation as output; (ii) daily maximum air temperature and day of the year as inputs, and GSR as output; (iii) daily mean air temperature and relative humidity and day of the year as inputs, and GSR as output; and (iv) daily mean air temperature, day of the year, relative humidity, and previous day’s GSR as inputs, and GSR as output. The mean square error was found to be 0.0027, 0.0023, 0.0021, and 7.65 × 10^?4 for case (i), (ii,), (iii), and (iv) respectively, while the corresponding absolute mean percentage errors were 5.64, 5.08, 4.48, and 2.8%. Obtained results show that the SVM method is capable of predicting GSR from measured values of temperature and relative humidity.     

A Calibrated,High‐Resolution GOES Satellite Solar Insolation Product for a Climatology of Florida Evapotranspiration1

Paech, Simon J., John R. Mecikalski, David M. Sumner, Chandra S. Pathak, Quinlong Wu, Shafiqul Islam, and Taiye Sangoyomi, 2009. A Calibrated, High‐Resolution GOES Satellite Solar Insolation Product for a Climatology of Florida Evapotranspiration. Journal of the American Water Resources Association (JAWRA) 45(6):1328‐1342. Abstract: Estimates of incoming solar radiation (insolation) from Geostationary Operational Environmental Satellite observations have been produced for the state of Florida over a 10‐year period (1995‐2004). These insolation estimates were developed into well‐calibrated half‐hourly and daily integrated solar insolation fields over the state at 2 km resolution, in addition to a 2‐week running minimum surface albedo product. Model results of the daily integrated insolation were compared with ground‐based pyranometers, and as a result, the entire dataset was calibrated. This calibration was accomplished through a three‐step process: (1) comparison with ground‐based pyranometer measurements on clear (noncloudy) reference days, (2) correcting for a bias related to cloudiness, and (3) deriving a monthly bias correction factor. Precalibration results indicated good model performance, with a station‐averaged model error of 2.2 MJ m^?2/day (13%). Calibration reduced errors to 1.7 MJ m^?2/day (10%), and also removed temporal‐related, seasonal‐related, and satellite sensor‐related biases. The calibrated insolation dataset will subsequently be used by state of Florida Water Management Districts to produce statewide, 2‐km resolution maps of estimated daily reference and potential evapotranspiration for water management‐related activities.     

Guidelines for Riparian Vegetative Shade Restoration Based Upon a Theoretical Shaded‐Stream Model1

Abstract: Guidelines for riparian vegetative shade restoration were developed using a theoretical model of total daily radiation received by a shaded stream. The model assumed stream shading by nontransmitting, vertical or overhanging, solid vegetation planes in infinitely long reaches. Radiation components considered in the model were direct beam shortwave on the stream centerline, diffuse atmospheric shortwave, shortwave reflected by vegetation, atmospheric longwave, and longwave emitted by vegetation. Potential or extraterrestrial shortwave irradiation theory was used to compute beam shortwave radiation received at the stream centerline, and view factor theory was used to compute diffuse radiation exchange among stream, vegetation, and atmospheric planes. Model shade effects under clear skies were dominated by reductions in receipt of direct beam shortwave radiation. Model shade effects with cloudy skies were dominated by the “view factor effect” or the decreases in diffuse shortwave and longwave radiation from the atmosphere balanced against increases in longwave radiation from vegetation. Model shade effects on shortwave radiation reflected by vegetation were found to be negligible. The model was used to determine the vegetation height (H) to stream width (W) ratios needed to achieve 50, 75, and 90 % shade restoration for mid‐latitude conditions on clear and cloudy days. Ratios of vegetation height to stream width, for dense nontransmitting vegetation, generally ranged from 1.4 to 2.3 for 75% shade restoration at a mid‐latitude site (40°N). The model was used to show H/W needed for E‐W vs. N‐S stream azimuths, varying stream latitudes between 30° and 50°N, channels with overhanging vegetation, channels undergoing width changes, as well as the limits to shade restoration on very wide channels.     

Using LiDAR Data Analysis to Estimate Changes in Insolation Under Large‐Scale Riparian Deforestation1

Greenberg, Jonathan Asher, Erin L. Hestir, David Riano, George J. Scheer, and Susan L. Ustin, 2012. Using LiDAR Data Analysis to Estimate Changes in Insolation Under Large‐Scale Riparian Deforestation. Journal of the American Water Resources Association (JAWRA) 48(5): 939‐948. DOI: 10.1111/j.1752‐1688.2012.00664.x Abstract: Riparian vegetation provides shade from insolation to stream channels. A consequence of removing vegetation may be an increase in insolation that can increase water temperatures and negatively impact ecosystem health. Although the mechanisms of riparian shading are well understood, spatially explicit, mechanistic models of shading have been limited by the data requirements of precisely describing the three‐dimensional structure of a riparian corridor. Remotely acquired, high spatial resolution LiDAR data provide detailed three‐dimensional vegetation structure and terrain topography over large regions. By parameterizing solar radiation models that incorporate terrain shadowing with LiDAR data, we can produce spatially explicit estimates of insolation. As a case study, we modeled the relative change in insolation on channels in the Sacramento‐San Joaquin River Delta under current conditions and under a hypothesized deforested Delta using classified LiDAR, rasterized at a 1‐m resolution. Our results suggest that the removal of levee vegetation could result in a 9% increase in solar radiation incident on Delta waters, and may lead to water temperature increases. General, coarse‐scale channel characteristics (reach width, azimuth, levee vegetation cover, and height) only accounted for 72% of the variation in the insolation. This indicates that the detailed information derived from LiDAR data has greater explanatory power than coarser reach‐scale metrics often used for insolation estimates.     

EVAPOTRANSPIRATION MEASUREMENTS AND MODELING FOR THREE WETLAND SYSTEMS IN SOUTH FLORIDA1

ABSTRACT: At the Everglades Nutrient Removal project in south Florida, three lysimeters were installed to measure daily evapotranspiration (ET) rates from cattails (Typha domingensis), mixed marsh vegetation, and an open water/algae system. The cattail lysimeter began operation in February 1993. The mixed marsh vegetation lysimeter began operation in January 1994, and the open water lysimeter with occasional algae cover began operation in December 1993. The mean measured ET rate was 3.6 mm, 3.5 mm, and 3.7 mm per day for the cattail, mixed marsh vegetation, and open water/algae system, respectively. High resolution weather data were continuously measured at the site. Six models were applied to estimate daily ET rates of the three systems. The Penman-Monteith equation best estimated ET of cattail and mixed marsh vegetation, and the Penman Combination equation was most suitable for the open water/algae system. Empirical equations based on solar radiation and maximum temperature produced estimates of daily ET from the three systems that are comparable to models that require many more parameters. In cases where limited data is available, the calibrated simple models can be used to estimate ET from wetlands in south Florida.     

Thermal modeling and analysis of novel twin-chamber community solar cooker as a replacement of biomass-based cooking

A novel design of twin-chamber community solar (TCCS) cooker is presented as a replacement of biomass-based cooking. The novelty of separating a single rectangular cooking chamber into separate twin chambers (of 1-m² aperture area each) improves the cooking performance as opening of one chamber for unloading of food cooked in lesser time (rice) does not disturb the stagnation temperature of the other chamber (pulses and meat) needing more time to cook besides resulting in reduction in side heat loss coefficient due to common wall. Aperture area and cooking volume of TCCS cooker are 9.54 and 35.33 times more as compared to single-chamber domestic solar (SCDS) cooker which makes it a community-scale large-capacity solar cooker. The developed solar radiation capture model and overall heat loss coefficient (U_l) computed for TCCS cooker have been used in a thermal model developed between various interactive components. First (F₁) and second figures of merit (F₂) values are 0.13 and 0.42, respectively, for TCCS cooker at par with ‘A’ grade category SCDS cooker. Techno-economic analysis shows that the net present value of TCCS cooker is Rs. 83,253 with break-even point occurring after cooking 43,461 meals with payback period of only 25, 50, and 72 months if used as a replacement for LPG, cow dung cakes, and wood-based cooking, respectively. Environmental impact analysis shows that the use of the proposed cooker can mitigate 2, 5.9, and 4.1 tonnes of CO₂ emissions every year by not burning LPG, cow dung cakes, and wood respectively.     

Modeling urban solar energy with high spatiotemporal resolution: A case study in Toronto,Canada

This research presents a method to determine the maximum potential for the capturing of solar radiation on the rooftop of buildings in an urban environment. This involves the modeling of solar energy potential and comparison to historical building energy demand profiles through the use of 3-D solar simulation software tools and geographic information systems (GIS). The objective is to accurately identify the amount of surface area that is suitable for solar photovoltaic (PV) installations and to estimate the hourly PV electricity generation potential of existing building rooftops in an urban environment. This study demonstrates a viable approach for modeling urban solar energy and offers valuable information for electricity distributors, policy makers, and urban energy planners to facilitate the substantial design of a green built environment. The developed methodology is comprised of three main sections: (1) determination of suitable rooftop area, (2) determination of the amount of incident solar radiation available per rooftop, and (3) estimation of hourly solar PV electricity generation potential. A case study was performed using this method for Ryerson University, located in Toronto, Canada. It was found that solar PV could supply up to 19% of the study area’s electricity demands during peak consumption hours. The potential benefits of solar PV was also estimated based upon hourly greenhouse gas emission intensity factors as well as Time-of-Use (TOU) savings through the Ontario Feed-in-Tariff (FIT) program, which allows for better representation of the positive impacts of solar technologies.     

高原气候环境对涂层材料性能的影响研究

太阳辐射是引起有机涂层老化的最主要原因。由于高原拉萨地区的太阳辐射年总量比内地同纬度高出约一倍，分别将3种同基材同镀层但不同底漆和面漆的6类常用防护涂层在高原气候条件下自然暴露试验一年。经过对比，能较快速优选出性能相对稳定的涂层。