Measurements Of Global Solar Radiation Research Articles

Improving the operational forecasts of outdoor Universal Thermal Climate Index with post-processing

The Universal Thermal Climate Index (UTCI) is a thermal comfort index that describes how the human body experiences ambient conditions. It has units of temperature and considers physiological aspects of the human body. It takes into account the effect of air temperature, humidity, wind, radiation, and clothes. It is increasingly used in many countries as a measure of thermal comfort for outdoor conditions, and its value is calculated as part of the operational meteorological forecast. At the same time, forecasts of outdoor UTCI tend to have a relatively large error caused by the error of meteorological forecasts. In Slovenia, there is a relatively dense network of meteorological stations. Crucially, at these stations, global solar radiation measurements are performed continuously, which makes estimating the actual value of the UTCI more accurate compared to the situation where no radiation measurements are available. We used seven years of measurements in hourly resolution from 42 stations to first verify the operational UTCI forecast for the first forecast day and, secondly, to try to improve the forecast via post-processing. We used two machine-learning methods, linear regression, and neural networks. Both methods have successfully reduced the error in the operational UTCI forecasts. Both methods reduced the daily mean error from about 2.6∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{\\circ }$$\\end{document}C to almost zero, while the daily mean absolute error decreased from 5∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{\\circ }$$\\end{document}C to 3∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{\\circ }$$\\end{document}C for the neural network and 3.5∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{\\circ }$$\\end{document}C for linear regression. Both methods, especially the neural network, also substantially reduced the dependence of the error on the time of the day.

Estimation of Global Solar Radiation using Angstrom and Gopinathan Model on Sunshine Hour and Temperature in Highland, Nepal

In developing countries like Nepal, the direct measurement of global solar radiation (GSR) is difficult. So, the estimation of GSR is carried out at Jumla (29°16′ N, 82° 11′ E and about 2347 m altitude) for the year 2015 and 2017 using regression technique to the meteorological parameters on Angstrom model, Gopinathan and Olomiyesan- Oyedum models. Among three models, Olomiyesan and Oyedum model is better than other models. Its empirical constants a=0.38, b=0.10 and c=0.09 are found. The values of statistical errors MBE, MPE and RMSE are smaller than other models. Similarly, the coefficient of determination (R2=0.89) is greater than other models. Finally, the finding empirical constants and meteorological parameters sunshine hour, and temperature are used to estimate the GSR for the year 2017. In addition to this, the annual average GSR for the year 2015 and 2017 are found to be 18.86 MJ/m2/day and 17.50 MJ/m2/day respectively. It is concluded that the finding empirical constants are used to estimate the GSR and solar energy at similar geographical location of Nepal.

Analysis of global and net radiation fluxes in relation to surface albedo at DACCIWA site in Ile-Ife, southwest Nigeria

Measurements of global solar radiation (RG) and net radiation (RN) fluxes were made above the grass-covered surface at DACCIWA site, Ile-Ife, southwest Nigeria, from 2017 to 2019. The datasets were obtained from a four-component net radiometer (model NR01, Hukseflux Thermal Sensors B.V., the Netherlands). Observations were made and separated for cases of clear sky and cloudy conditions during the measurement period. The results showed considerable fluctuations for both radiation fluxes. For clear sky conditions, the magnitudes of RG and RN were higher than those observed for cloudy conditions due to attenuation. For the period of observation, LWup fluxes were higher in the dry season than in the wet season due to dry and hotter surface conditions while LWd dominated the wet season at the site. The highest radiation values occurred in 2018, while the lowest were observed in 2017. Daily surface albedo (α) ranged from 0.16 to 0.22. Empirical relationships obtained for RG and RN are RN = 0.754 RG – 17.4 Wm−2 and RN = 0.657 RG – 32.7 Wm−2 for wet and dry seasons, respectively. Based on the empirical relationships, daily RN and RG can be obtained when measurements like these are not available. Linear relationships between RN and RG show that for all days (cloudy and clear sky conditions), daily average RN is about 0.75 RG, and about 0.60 RG for clear sky conditions at the location. However, the results reflect the characteristics of the site and can be applied for gap-filling or careful extension of the measurement period.

Global Solar Radiation Modelling using an Artificial Neural Network for Kazaure, Jigawa State, Nigeria

This research presents an algorithm based on Artificial Neural Networks (ANN), for estimating monthly mean daily and hourly values of solar global radiation. To effectively investigate solar energy consumption and estimate solar renewable energy resources, the Hourly Global Solar Radiation measurements are necessary. In order to predict monthly average daily global sun irradiance on a horizontal area of Kazaure- Nigeria, this study creates a model utilizing ANN to solve the problem of solar energy distribution. Five empirical correlations are developed using the data from 42 months to aid in the prediction of the solar energy distribution pattern. The software is constructed around the Multilayer Perceptron under categorized tabs, with Multilayer perception in neural network Toolbox in MATLAB 9.7 version as a feed forward ANN that maps sets of input data into a set of suitable output. It differs from conventional linear perception by employing three or more layers of neurons (nodes) with nonlinear activation functions. It is also more effective than perceptrons in identifying input that is not linearly separable by a linear hyper-plane. Results obtained utilizing the suggested structure reveals good agreement between the calculated and measured levels of global solar irradiation. The ANN model is shown to be superior when compared to empirical models, due to negligible noise margin.

Spatial estimation of the optimum PV tilt angles in China by incorporating ground with satellite data

Tilt angle is a key parameter that affects solar photovoltaic (PV) power generation. Traditional empirical model based on latitude may fail to estimate the optimum tilt angle in regions with large climatic differences. In this study, we propose a framework that incorporates ground with satellite data to determine the optimum tilt angle at any location. We collect global solar radiation measurements of 133 stations in China and estimate the diffuse fraction through Boland–Ridley–Lauret model. Hourly PV power generation is modelled by considering photoelectric conversion process and PV system losses. The results show that the optimum tilt angles are highly correlated with latitude and diffuse fraction with an R of 0.86 and 0.80, respectively. Empirical models reconciled by diffuse fraction allow for spatial estimates of the optimum tilt angle from satellite data to reflect the climatic influence. Furthermore, we explore the benefit from periodically adjusting the tilt angle in China. PV panels fixed at the optimum tilt angle increase the annual power yield by 13.7% compared with horizontally fixed panels. Seasonal adjustment largely increases power yield in winter; additional yield gain of monthly adjustment is very limited; while tracking systems provide the option of achieving double or even triple gains.

Global solar radiation predictions in Fiji Islands based on empirical models

Many difficulties associated with Global Solar Radiation (GSR)’ variability in space and time and with the angular position in sky hemisphere hamper its accurate knowledge. Fiji Islands, with a tropical maritime climate without great extremes of heat or cold, have GSR measurement limited by a small number of stations due to the technical and financial restricts. Yet there are various options of available empirical models to select the most suitable one(s) for estimating GSR accurately using weather-related variables available for each location. This paper, therefore, focuses on evaluation of the performances of twenty (20) empirical models in predicting GSR between 1984 and 2018 in six (6) meteorological stations within Fiji Islands. Simulations were performed for 35-year period (1984–2018) and results were compared with the National Aeronautics and Space Administration (NASA)’s MERRA (Modern-Era Retrospective Analysis for Research and Applications) observational datasets after bias corrections. Model performance indices such as Mean Error (ME), Nash-Sutcliffe Efficiency coefficient (NSE), Percentage Mean Error (PME), Root Mean Square Error (RMSE) and correlation coefficient (r) were adopted. Obtained coefficients of determination from the regression analysis (0.415 ≤ R2 ≤ 0.988; at 95% confidential level) performed for the models’ calibration between 1984 and 2018 suggest that the models’ potentials to simulate GSR varies across the stations and among the models. About 33% of the models in group I, which relate GSR to the sunshine duration, monthly average day length and/or extra-terrestrial radiation performed favourably well in predicting GSR while 75% of models in group II (with air temperature as additional predictor) and 100% in group III (humidity) performed very well. It is concluded that inclusion of air temperature and humidity as two principal predictors alongside with sunshine duration, day length and extra-terrestrial radiation produce the best GSR prediction (RMSE ≤ 5 MJ m−2) over Fiji Islands.

Potential of Grid-Connected Photovoltaic Systems in Brazilian Dairy Farms

The insufficient supply of electrical energy, in addition to frequent disturbances and interruptions, has motivated the inclusion of solar, biogas, biomass or wind energy systems in many Brazilian farms. However, there are few studies that have addressed the technical and economic impacts of renewable sources for generating electricity in rural applications, leading farmers not to invest in these technologies for fear of financial losses. This study was carried out to evaluate the potential of grid-connected photovoltaic systems for supplying the electricity demand in dairy farms located at Minas Gerais State, Brazil. The electricity generated by grid-connected photovoltaic systems was estimated from global solar radiation measurements, considering six municipalities of Minas Gerais State, Brazil. Electricity consumption was monitored monthly during one year in 12 farms. The average percentages of electricity consumption in the main operations executed at farms were 4, 27, 12, 33 and 24% for lighting, milking, cleaning/disinfection (water heating and pumping), milk cooling/refrigeration and miscellaneous, respectively. The monthly differences between the electricity generation and consumption for the studied municipalities demonstrated the technical feasibility of grid-connected systems installed directly in the dairy farms, helping to achieve energy sustainability.

Performance Analysis of Solar Water Pumping System at Nawabshah

Performance of solar photovoltaic water pumping units relies on available solar radiations of the area, geographical conditions and system configurations. This study was conducted to analyze the influence of solar radiation, motor speed and water head on water discharge of a solar water pumping systems (SWPS). For that, a SWPS was installed, configured and its performance was examined at Sadiqabad Colony, Nawabshah for two consecutive months from 12:00 to 13:00 hours. Light meter, Model- HDS 2302.0, Delta OHM was used for measurement of global solar radiation, PROVA-RM 1000 tachometer for motor pump speed and stopwatch for recording of elapsed time for filling up of 30 liters capacity water can. Results revealed that the average minimum solar radiations were 776 W/m2 at 12:00 hours in the month of May and maximum 902 W/m2 at 13:00 hours in the month of June during experimental work. The maximum average motor speed and flow rate were noted at L1 and minimum at L4, whereas, the maximum time taken by the solar water pumping system for filling up of water can at L4 and minimum at L1. The time taken to provide one liter of water was found inversely proportional with motor speed and directly with the water head.

Determination of Angstrom Coefficients for Masvingo and Makoholi Stations, Zimbabwe

Coefficients of the first order and second order Angstrom model were obtained for Masvingo and Makoholi stations in Zimbabwe. Long term average ground measurements of sunshine hours and global horizontal solar radiation from the meteorological services were used as input data. Monthly average values of the clearness index, and the fraction of sunshine hours, were determined. Regression analysis was used to obtain the first and second order coefficients of the Angstrom model for the two locations. The estimates from the developed models were tested against measured values and results obtained were in agreement to within +/- 5%. The results also showed that the models performed better with these coefficients compared with coefficients suggested in previous researches. Also the first order model was found to perform better than the second order model for Makoholi station while the second order model works well for Masvingo.

Study of Atmospheric Turbidity in a Northern Tropical Region Using Models and Measurements of Global Solar Radiation

Radiative transfer in the Earth’s atmosphere under clear-sky conditions strongly depends on turbidity due to aerosols and hydrometeors. It is therefore important to know its temporal radiative properties for a given site when the objective is to optimize the solar energy that is collected there. Turbidity can be studied via measurements and models of the global solar radiation reaching the ground in cloudless conditions. These models generally depend on two parameters, namely the Angström turbidity coefficient and the Linke factor. This article aims to do a comparative study of five models of global solar radiation, all dependent on the Linke factor, based on real data. The measurements are provided by the Tamanrasset Meteorological Center (Algeria), which has a long series of global solar radiation data recorded between 2005 and 2011. Additional data from AERONET and MODIS onboard the TERRA satellite were also used to perform the comparison between the two estimated parameters and those obtained from AERONET. The study shows that the ESRA models are the most reliable among the five models for estimating the Linke factor with a correlation coefficient R of the data fits of 0.9995, a RMSE of 13.44 W/m2, a MBE of −0.64 W/m2 and a MAPE of 6.44%. The maximum and minimum statistical values were reached, respectively, in June and during the autumn months. The best correlation is also observed in the case of ESRA models between the Linke parameter and the joint optical thickness of aerosols and the total column-integrated water vapor. The Angström turbidity coefficient β, calculated from the Linke factor and MODIS data, has values less than 0.02 at 9% of the cases, and 76% present values ranging between 0.02 and 0.15 and 13% higher than 0.15. These β values are validated by AERONET measurements since a very good correlation (R≈0.87) is observed between the two datasets. The temporal variations of β also show a maximum in June. Satellite observations confirm more aerosols during the summer season, which are mostly related to the African monsoon.

Half-hour global solar radiation forecasting based on static and dynamic multivariate neural networks

Precise global solar radiation (GSR) measurements in a given location are very essential for designing and supervising solar energy systems. In the case of rarity or absence of these measurements, it is important to have a theoretical or empirical model to compute the GSR values. Therefore, the main goal of this work is to offer, to designers and engineers of solar energy systems, an appropriate and accurate way to predict the half-hour global solar radiation (HHGSR) time series from some available meteorological parameters (relative humidity, air temperature, wind speed, precipitation, and acquisition time vector in half-hour scale). For that purpose, two intelligent models are developed: the first one is a multivariate dynamic neural network with feedback connection, and the second is a multivariate static neural network. The database used to build these models was recorded in Agdal’s meteorological station in Marrakesh, Morocco, during the years of 2013 and 2014, and it was divided into two subsets. The first subset is used for training and validating the models, and the second subset is used for testing the efficiency and the robustness of the developed models. The obtained results, in terms of the statistical performance indicators, demonstrate the efficiency of the developed forecasting models to accurately predict the HHGSR parameter in the city of Marrakesh, Morocco.

Estimation of Global Solar Radiation and Optimal Tilt Angles of Solar Panels for Pune, India

Solar panels can achieve the highest yield when they are oriented in the right way as the influence of the tilt angles can lead to a high impact on the performance. This paper demonstrates the effect of the tilt angle on the final yield and maximum utilization of solar energy. The annual optimal tilt angle of the solar panels for Pune was found out using the Liu and Jordan model. The optimal tilts yielding an increase of 7% was found out to be 0° on the months starting from April and lasting till September and 40° starting from October and holding at 40° till March. By changing the tilt angle every month, there was an increase in the yield by more than 8%. For better yield and maximum utilization of solar energy, optimizing the tilt angles of solar panels monthly or even twice a year is effective based on the study. Most of the panels are fixed at an angle equal to the latitude of the place and oriented towards the Southern sky in the northern hemisphere. Measurements of the monthly average global solar radiation, monthly average temperatures, and monthly average relative humidity were compared. Further ahead regression correlation for a linear model was carried and the regression coefficients a and b were found out to be 0.2804 and 0.3618 respectively.

Predicting Global Solar Radiation on A Horizontal Surface A Case Study For Zambia

Insolation models have been recognized for many years in solar energy systems as important tools to determine radiations for locations lacking insolation data base. Unfortunately, for most geographical areas in Zambia, the insolation data is not available. Correlations between the daily measurements of global solar radiation and the meteorological parameters were presented in tabular form for the selected locations. A common relationship to estimate global solar radiation for the all Zambia is also established. The values of correlation coefficients established varied from 53% to 97% and the errors of estimation were between 0.24 and 0.0.84.

Evaluation of heat transfer during the process of heating water in containers using a solar cooker box-type

This work presents the experimental results and the evaluation of the heat transfer mechanisms by conduction, convection, and radiation that occur during the water heating process inside four containers with volumes of 250, 500, 750, and 1000 ml. using as for this process a box-type solar cooker. For the experimental measurements, a type k thermocouple arrangement was used, located in the water, the exterior surfaces of the containers, and the glass that forms part of the solar cooker cover. For the acquisition of the data perceived by the thermocouples, a Compact Field Point from National Instruments was implemented and for the measurement of global solar radiation, an Eppley 8-48 radiometer was used. The results obtained from the evaluation show that the most important heat transfer mechanism is by conduction located in the exterior glass of the solar cooker cover and the convection heat transfer in this same glass is the one with the lowest values. The evaluation of the results achieved contributes to the knowledge of the operation of solar cookers, which can contribute to the design and improvements of these solar energy devices.

Study of Impact of Linke Turbidity on Solar Radiation over Kathmandu Valley

Population growth, mechanization, and industrialization have now made humanity the equivalent of other natural processes in its effect on air-pollution levels and associated climatic change. Link turbidity is an important parameter for assessing the air pollution of Kathmandu (Lat.:27.72oN, Long.: 85.32oE and Alt.: 1350 m. above sea level). The Because of the unavailability of spectral measurements, a model has been used to estimate the Linke turbidity factor (TL) from broadband measurements of Global Solar radiation on 2012 by using CMP6 paranometer. The average value of extinction coefficient (K) and Linke turbidity are 0.69 ± 0.03 and 5.53±0.23$ respectively, which can be compared with other sites around the world. Relationship between turbidity co-efficient with meterological parameters (humidity, temperature and water contained) have been investigated further.

Analysis of Measurements of Direct Normal and Global Solar Radiation for Maceió, Alagoas State, Northeastern Brazil

Abstract Studying solar radiation is essential for human knowledge, since it is present in practically all its activities. Thus, the aim of this work was to analyze the climatic and seasonal variation of direct normal and global solar radiation in the region of Maceió, Alagoas State, Northeastern Brazil with sky conditions characterized by clearness index (Kt). The Kt was determined by the ratio between global solar irradiance and solar irradiance at the top of the atmosphere. The highest occurrences of daily direct normal solar irradiance under conditions of Kt ≥ 0.6 were recorded between 400 W m−2 and 700 W m−2 for all seasons. Under conditions of 0.4 ≤ Kt < 0.6, the daily direct normal solar irradiance occurred between 200 W m−2 and 500 W m−2 and for conditions of Kt < 0.4, its maximum value was 200 W m−2. It was observed that the levels of solar incidence in the study region depend on cloud cover conditions, with little influence of seasonality.

Daily spectral ocean surface albedo (OSA) parameterization in case of clearness index (Kt) and phytoplankton variability in Malacca Strait

In this study, we examined the albedo's dependence on clearness index (Kt) based on measured global radiation data and phytoplankton variability influence represented by chlorophyll (a) concentration at the upper layers over the Malacca Strait. Half-hourly global solar radiation (5°26′53″ N, 100°11′36″ E) measurement over the period from January to October 2017 was analyzed to investigate the correlation between clearness index and ocean surface albedo (OSA) in case of phytoplankton influence in Malacca Strait coastal waters. Three days (January 29, February 26 and March 22, 2017) with high irradiation values were selected for daily OSA variability study. The parameterization includes bio-optical analytical modelling based on apparent optical properties and photosynthetically active range (PAR) estimation. Daily timescale analysis of spectral albedo in Malacca Strait enables detail examination for the chlorophyll maximum absorption wavelength (λ = 440 nm) parameterization. OSA diurnal variability was estimated using Jin et al. scheme, which is based on the separation of albedo components (direct and diffuse). Hourly changes in radiation (including Kt) and solar position properties provide valuable information to investigate the pathways of daily spectral albedo in case of small concentrations of chlorophyll (a) and clearness index parameterization.

A novel method for fast sky conditions identification from global solar radiation measurements

Sky conditions, and the corresponding luminance and radiance distribution patterns are essential to daylighting, energy and thermal environmental studies. The CIE Standard Skies define the overcast, partly cloudy, and clear sky conditions intuitively by rigorous luminance distributions, which are, however, usually determined by sophisticated and uncommon measurements (e.g. radiation in multiple vertical directions). This study proposes a simple approach to identifying the hourly sky conditions from the global horizontal irradiance (EHG) that is most widely accessible in weather stations with basic radiation measurement facilities. The sophisticated measurements are, therefore, avoided for simple applications. The partly cloudy sky, especially, is identified by the notable disparity of its EHG measurement from the theoretical cloudless condition. The proposed approach interprets the ISO/CIE Standard Sky conditions and their diffuse luminance and radiance distributions successfully. From the datasets at two sites with different climates, the approach correctly identifies 7% more sky conditions than a previous work when the direct beam and diffuse radiation measurements were not accessible. The model can thus be essential to solar energy studies for places with ground-based solar radiation measurements only.

Measurement of global and direct normal solar energy radiation in Seri Iskandar and comparison with other cities of Malaysia

Potential solar data are an essential tool for successful solar design and application. However, because of the limited availability of solar radiation stations, spatial resolution is affected whenever an attempt to construct a solar radiation map is made. In this paper, actual solar data were acquired in Universiti Teknologi PETRONAS (UTP), Seri Iskandar, Malaysia (4°24′latitude, 100°58′E longitude, 24 m altitude). The measurements of global solar radiation and direct normal radiation were gathered and analyzed for the whole of 2018. In addition to solar data collection, real-time solar radiation, high accuracy, and related meteorological data were also obtained. With 1-min recorded average values the everyday and monthly solar radiation averages were determined. A record of 1068.10 W/m2 as maximum daily global solar radiation and 915 W/m2 for direct normal radiation was observed on 9 September 2018. Discussions on daily and monthly average clearness index differences are also elaborated in this paper. The acquired data were compared with corresponding data obtained from other selected Malaysian cities and the widely useable data resource, the NASA solar energy model and surface meteorology. Investigation of the data indicated that Seri Iskandar obtains an ample amount of global solar radiation, indicating the strong potential for the use of solar energy.

Prediction of Doses Biologically Active Ultraviolet Solar Radiation from Measurements of Global Solar Radiation

Prediction of Doses Biologically Active Ultraviolet Solar Radiation from Measurements of Global Solar Radiation