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.     

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.     

ESTIMATING REFERENCE EVAPORATION IN THE CENTRAL VALLEY OF CALIFORNIA USING THE LINACRE MODEL1

ABSTRACT: The Linacre (1988) model for calculating evaporation from open water or well-watered surfaces only requires inputs of air temperature, latitude and elevation, and windspeed if it is available. The model was developed using data collected at a large number of sites in different climatic regions of the world, while independent tests of the model have shown it to be suitable for estimating evaporation in a variety of locations. This study was intended to contribute to the broad goal of evaluating temperature-based evaporation models for use in California by testing the Linacre model in the agriculturally intensive Central Valley. Observed monthly mean reference evaporation (E_o) and meteorological data for periods ranging up to 72 months were obtained from 25 California Irrigation and Management Information System (CIMIS) stations distributed throughout the Central Valley. Uncalibrated and calibrated Linacre models were used to estimate monthly mean reference evaporation, and the performance of each model was evaluated using indices that quantified the random and systematic errors and overall model performance. The accuracy of the radiation and ventilation components of the model were evaluated separately. The uncalibrated model was found to systematically overestimate E_o with most of the model error being attributed to the ventilation component. Calibration of the radiation and ventilation components removed most of the systematic model errors, and the root mean square error for monthly mean E_o was 0.676 mm day^?1 (16.8 percent of the mean observed value). (KEY TERMS: reference evaporation; Linacre model; irrigation scheduling.)     

Prediction of diffuse solar radiation using satellite data

In the project of the solar systems, the values of the solar radiation of a region must be known. The global solar radiation measurements are performed by the Turkish Meteorological Service in Turkey, while the diffuse solar radiation measurements are unavailable. In this study, some new models for predicting the monthly average daily diffuse solar radiation on a horizontal surface for Erzincan, Turkey are developed using satellite data. The evaluation of the models is carried out with the statistical analysis methods of mean bias error (MBE), root mean square error (RMSE) and correlation coefficient (r). The results are proved that the correlation equations obtained in here can be used to forecast diffuse solar radiation reasonably well.     

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.     

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.     

Simulation and validation of a suitable model for thin layer drying of ginger rhizomes in an induced draft dryer

Variation in drying material and their biological differences, coupled with heat supply method in different dryers, makes mathematical modeling of drying complicated. Attempt was made to simulate a drying process and to identify best suitable model out of six selected drying models, for drying of ginger slices in a solar-biomass integrated drying system designed and developed for spice drying. Moisture content data were converted into the moisture ratio (MR) expressions and curve fitting with drying time for the selected drying models was analyzed. Sigma Plot software was used for nonlinear regression to the data obtained during drying and for modeling of drying curves. The suitability of the models was evaluated in terms of statistical parameters such as coefficient of determination (R²), mean percentage error (P), and standard error estimate. Drying air temperature was in the range of 47–55°C and air velocity was between 1.0 and 1.3 m s^?1. Ginger slices were dried from 88.13% to 7.65 ± 0.65% (wb) in 16 h. Trays were interchanged in a predetermined matrix sequence from 4 h onwards when moisture content was reduced to 60–70% (wb), for uniformity in drying. Highest value of R² (0.997), lowest value of SEE (0.020), and P value < 0.0001 established Page model as the best suitable model for the developed drying system. The predicted MRs were in good agreement with the experimental values and the effective moisture diffusivity for ginger was found to be 2.97 × 10^–7 m² s^?1.     

Validation of spectral gas radiation models under oxyfuel conditions. Part A: Gas cell experiments

Combustion of hydrocarbon fuels with pure oxygen results in a different flue gas composition as combustion with air. Standard CFD spectral gas radiation models for air combustion are out of their validity range. The series of three articles provides a common spectral basis for the validation of new developed models. In part A of the series gas cell transmissivity spectra in the spectral range of 2.4–5.4 μm of water vapor and carbon dioxide in the temperature range from 727 to 1500 ° C and at different concentrations were compared at a nominal resolution of 32 cm^?1 to line-by-line models from different databases, two statistical-narrow-band models and the exponential wide band model. The two statistical-narrow-band models EM2C and RADCAL showed a good agreement with a maximal band transmissivity deviation of 3%. The exponential-wide-band model showed a deviation of 6%. The new line-by-line database HITEMP2010 had the lowest band transmissivity deviation of 2.2% and was recommended as a reference model for the validation of simplified CFD models.     

Indirect forced solar drying of banana slices: phenomenological explanation of non-isotropic shrinkage and color changes kinetics

Solar drying technology is a noteworthy technique as it uses the renewable solar energy. In this study, thin slices of banana were dried by using an indirect forced solar dryer at air mass flow rates of 0.016, 0.041, and 0.082 kg s^?1. In order to assess the kinetics of shrinkage and color changes, image processing technique was applied for determining area, volume, density, total color difference and browning index. Shrinkage factor of the samples was less than 1 during drying indicating non-isotropic shrinkage with contraction of inner voids. Furthermore, product shrinkage showed two descending drying steps in which the volume change was more than the evaporated water volume in the first step and equal to that in the second step. The dimensionless evaporated water volume with respect to the dimensionless volume difference of the product also revealed that two steps of volume change existed during drying separated at critical moisture ratio 0.23. The area and volume changes were only related to the product moisture content and were independent of the air mass flow rate, and hence air temperature. In contrary to the browning index, the total color difference was not influenced by air mass flow rate and the least change in browning index occurred at mass flow rate of 0.041 kg s^?1.     

Real‐Time Analysis of Energy Generation of a Photovoltaic System Installed in the City of Lajeado,Rio Grande do Sul

Considering successive and costly increases in electricity rates, this article evaluates the generation of electricity from a photovoltaic system using solar energy, a renewable source. The solar photovoltaic system is installed at UNIVATES University Center, a public university in the state of Rio Grande do Sul, Brazil, and it is also connected to the electrical grid. Data related to the climatic conditions of the location, such as incident solar radiation, rainfall, and mean temperature, were obtained during the system's evaluation period and used along with bibliographic research on similar systems installed in southern Brazil. Our study quantified the energy produced over one calendar year (2014) and related it to the climatic variables and the conversion efficiency achieved by the system's photovoltaic modules. Our results show that there is both a strong relationship between the production of energy and climatic conditions and that the city, Lajeado, and the Brazilian state of Rio Grande do Sul, have good potential to supply energy using photovoltaic systems connected to the electrical grid. The horizontal global solar radiation average obtained in the study location was 4.14 kilowatts per square meter per day (kWh/m²/day), and the average monthly production of energy reached 243.93 kWh/m²/month, with a total of 2,927.10 kWh produced in 2014, achieving a monthly average conversion efficiency of 11.07%. This conversion efficiency is close to the value of 12.6% obtained in 2013 in a similar study of the same solar photovoltaic system conducted over a shorter time period.     

A basin-scale approach to estimating stream temperatures of tributaries to the lower Klamath River, California

Stream temperature is an important component of salmonid habitat and is often above levels suitable for fish survival in the Lower Klamath River in northern California. The objective of this study was to provide boundary conditions for models that are assessing stream temperature on the main stem for the purpose of developing strategies to manage stream conditions using Total Maximum Daily Loads. For model input, hourly stream temperatures for 36 tributaries were estimated for 1 Jan. 2001 through 31 Oct. 2004. A basin-scale approach incorporating spatially distributed energy balance data was used to estimate the stream temperatures with measured air temperature and relative humidity data and simulated solar radiation, including topographic shading and corrections for cloudiness. Regression models were developed on the basis of available stream temperature data to predict temperatures for unmeasured periods of time and for unmeasured streams. The most significant factor in matching measured minimum and maximum stream temperatures was the seasonality of the estimate. Adding minimum and maximum air temperature to the regression model improved the estimate, and air temperature data over the region are available and easily distributed spatially. The addition of simulated solar radiation and vapor saturation deficit to the regression model significantly improved predictions of maximum stream temperature but was not required to predict minimum stream temperature. The average SE in estimated maximum daily stream temperature for the individual basins was 0.9 +/- 0.6 degrees C at the 95% confidence interval.     

Regional and Local Scale Modeling of Stream Temperatures and Spatio-Temporal Variation in Thermal Sensitivities

Understanding variation in stream thermal regimes becomes increasingly important as the climate changes and aquatic biota approach their thermal limits. We used data from paired air and water temperature loggers to develop region-scale and stream-specific models of average daily water temperature and to explore thermal sensitivities, the slopes of air–water temperature regressions, of mostly forested streams across Maryland, USA. The region-scale stream temperature model explained nearly 90 % of the variation (root mean square error = 0.957 °C), with the mostly flat coastal plain streams having significantly higher thermal sensitivities than the steeper highlands streams with piedmont streams intermediate. Model R ² for stream-specific models was positively related to a stream’s thermal sensitivity. Both the regional and the stream-specific air–water temperature regression models benefited from including mean daily discharge from regional gaging stations, but the degree of improvement declined as a stream’s thermal sensitivity increased. Although catchment size had no relationship to thermal sensitivity, steeper streams or those with greater amounts of forest in their upstream watershed were less thermally sensitive. The subset of streams with three or more summers of temperature data exhibited a wide range of annual variation in thermal sensitivity at a site, with the variation not attributable to discharge, precipitation patterns, or physical attributes of streams or their watersheds. Our findings are a useful starting point to better understand patterns in stream thermal regimes. However, a more spatially and temporally comprehensive monitoring network should increase understanding of stream temperature variation and its controls as climatic patterns change.     

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.     

The effect of environmental conditions on the ability of a constructed wetland to disinfect municipal wastewaters

Constructed wetlands are widely used all over the world for the treatment of municipal wastewaters, which are characterized by high concentrations of pathogens. The objectives of this study were (1) to study the effect of solar radiation and temperature on the ability of a constructed wetland to reduce the concentration of total coliforms (TC), and (2) to evaluate the relationship between the presence of Salmonella spp. in the outflow and the concentration of TC. The results of this study showed that under Mediterranean environmental conditions, the percentage reduction in coliforms was lower during winter compared to all other seasons. Maximum removal of coliforms was achieved under conditions of high solar radiation and temperature. In addition, solar radiation was found to play a greater role in coliform die-off at low temperatures than at high temperatures. Finally, it was found that the probability of Salmonella spp. appearance in the outflow of the wetland was related to the concentration of TC. The increase in coliform bacteria in the effluents also increased the chances of Salmonella appearance. The risk of Salmonella spp. appearance in the outflow is minimized when the concentration of TC is below 10²/100 mL.     

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.     

Temperature and relative humidity distributions in a medium-size administrative town in southwest Nigeria

This study was carried out in one of the medium-sized public administrative towns in the southwestern part of Nigeria. Its aim is to highlight the effect of spatial distribution of settlements, population, and socio-economic activities on urban air temperature and humidity in the town. Temperature and relative humidity data from 1992 to 2001 were obtained from three meteorological stations in Akure, the Administrative Capital of Ondo State, Nigeria. The stations are located within the Federal Ministry of Aviation, Akure Airport (FMA), Federal University of Technology, Akure (FUTA) and Federal School of Agriculture (SOA). Air temperature and relative humidity measurements were also obtained from 27 points, which were cited to include road junctions, markets, built up areas, etc., using sling psychrometer. The data were subsequently analysed for spatial and temporal variations using statistical packages (SPSS and Microsoft Excel) and isolines. Actual vapour pressure and dew point temperature were computed using Magnus conversion formulae. The results obtained showed that spatial variation was insignificant, in terms of the temperature and humidity variables. The annual mean temperature (Tmean) ranged between 21.9 and 30.4 degrees C while minimum (Tmin) and maximum (Tmax) temperatures varied from 13 to 26 and 21.5-39.6 degrees C, respectively. Relative humidity (RH), actual vapour pressure (Es) and dew point temperature (Td) values also varied from 39.1% to 98.2%, 19.7-20.8 gm(-3), and 17.3-17.8 degrees C, respectively. A significant relationship (p>0.6; r<0.05) between Tmin, Es and Td was observed while the daytime 'urban heat island' intensity (UHI) ranged between 0.5 and 2.5 degrees C within the study period. The study concluded that there is influence of urban canopy on the microclimate of Akure, and hypothesizes that the urban dwellers may be subjected to some levels of weather related physiological disorderliness.     

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.     

Wintertime Surface Heat Exchange for the Inner Mongolia Reach of the Yellow River

This study analyzed the wintertime surface heat exchange for the Inner Mongolia reach of the Yellow River, China, based on the data from the nearby weather station at Wulateqianqi. In this analysis, the solar radiation is based on the observed data. Other components of the surface heat flux, that is, long‐wave radiation, and evaporative and conductive heat fluxes, are calculated. The relative importance of the contributions of long‐wave radiation, conductive, and evaporative heat fluxes are in descending order. The air temperature is the most important meteorological factor to the total heat flux. Although the wind speed influences evaporative and conductive heat fluxes, it has the least correlation with the total heat budget. The heat exchange coefficient for the linearized surface heat exchange equation is 21.87 W/(m² °C), which is comparable with published values in the regions of United States and Canada with similar latitudes.     

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.