Monthly Average Daily Global Radiation Research Articles

Evaluation of different sunshine-based models for predicting global solar radiation – case study: New Borg El-Arab city, Egypt

The unavailability of the solar radiation measurements for different locations around the world leads to develop various empirical models to estimate the global solar radiation. In this consider, this study aims to investigate the performance of different solar radiation models to predict the monthly average daily global solar radiation on a horizontal surface. To achieve this, the measured global solar radiation data for a case study location are used. The model predictions are compared with the measured data to introduce the most accurate model for estimating the global solar radiation. The performance of each model is evaluated based on the different statistical indicators. The results show that the Robaa model has the best performance among the other models. Consequently, it can be used for estimating global solar radiation on a horizontal surface in the location under consideration. The accurate estimations of the global solar radiation using this approach can be used in the design and evaluation of performance for different solar applications.

Solar radiation exergy and quality performance for Iraq and Turkey

The present study is conducted with two primary objectives: First, a new formulation for the maximum efficiency of the solar radiation conversion is developed by considering the radiative energy transfer between two surfaces at different temperatures for a constant volume system. Second, a new methodology is introduced for estimating the exergy value of the monthly average daily horizontal global radiation, including many parameters, such as monthly average daily value of the horizontal extraterrestrial radiation, the number of sunny hours, the day length, the mean temperature and the mean wind velocity. Seven statistical parameters are used to validate the accuracy of all models. The results of the two new models are found to be more reliable than the results obtained from other models. This study, which was conducted for four locations in Iraq and Turkey. The findings would help in predicting the maximum availability of solar radiation based on weather parameters.

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

ABSTRACTThis 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.

Economic feasibility of decentralized hybrid photovoltaic-diesel technology in Saudi Arabia: A way forward for sustainable coastal development

In view of growing concerns of global warming and depleting oil/gas reserves, many nations are considering use of hybrid photovoltaic-diesel technology as an option for power generation The Kingdom of Saudi Arabia has higher level of solar radiation and is a prospective candidate for deployment of solar photovoltaic systems. Literature indicates that commercial/residential buildings in the Kingdom consume about 10-45% of the total electric energy generated. The aim of this study is to analyze solar radiation data in city of Yanbu to assess the technoeconomic feasibility of utilizing hybrid photovoltaic-diesel-battery power systems to meet the load of a typical residential building. The monthly average daily solar global radiation ranges from 3.61 to 7.90 kWh/m2 . National Renewable Energy Laboratory?s HOMER software has been used in the study. The simulation results indicate that for a hybrid system, composed of 4 kWp photovoltaic system together with 10 kW diesel system, and a battery storage of 3 hours of autonomy (average load), the photovoltaic penetration is 21%. The cost of generating energy from that hybrid system has been found to be 0.180 $/kWh. With use of this hybrid system, about 2 tons per year of carbon emissions can be avoided entering into the local atmosphere. Also, for a given hybrid configuration, the operational time of diesel generators has been found to decrease with increase in photovoltaic capacity. The investigation examines impact of photovoltaic penetration on: carbon emissions, diesel fuel consumption, net present cost, cost of energy, etc.

Empirical modeling of solar radiation exergy for Turkey

In this study, three different empirical models are developed to predict the monthly average daily global solar radiation exergy on a horizontal surface for some provinces in different regions of Turkey by using meteorological data from Turkish State Meteorological Services. To indicate the performance of the models, the following statistical test methods are used: the coefficient of determination (R2), mean bias error (MBE), mean absolute bias error (MABE), mean percent error (MPE), mean absolute percent error (MAPE), root mean square error (RMSE) and the t-statistic method (tsta). By the improved empirical models in this paper do not need exergy-to-energy ratio (ψ) and monthly average daily global solar radiation to calculate solar radiation exergy. Consequently, the average exergy-to-energy ratio (ψ) for all provinces are found to be 0.93 for Turkey. The highest and lowest monthly average daily values of solar radiation exergy are obtained at 23.4MJ/m2day in June and 4MJ/m2day in December, respectively. The empirical models providing the best results here can be reliably used to predict solar radiation exergy in Turkey and in other locations with similar climatic conditions in the world. The predictions of solar radiation exergy from regression models could enable the scientists to design the solar-energy systems precisely.

New Temperature-based Models for Predicting Global Solar Radiation

This study presents new ambient-temperature-based models for estimating global solar radiation as alternatives to the widely used sunshine-based models owing to the unavailability of sunshine data at all locations around the world. Seventeen new temperature-based models are established, validated and compared with other three models proposed in the literature (the Annandale, Allen and Goodin models) to estimate the monthly average daily global solar radiation on a horizontal surface. These models are developed using a 20-year measured dataset of global solar radiation for the case study location (Lat. 30°51′N and long. 29°34′E), and then, the general formulae of the newly suggested models are examined for ten different locations around Egypt. Moreover, the local formulae for the models are established and validated for two coastal locations where the general formulae give inaccurate predictions. Mostly common statistical errors are utilized to evaluate the performance of these models and identify the most accurate model. The obtained results show that the local formula for the most accurate new model provides good predictions for global solar radiation at different locations, especially at coastal sites. Moreover, the local and general formulas of the most accurate temperature-based model also perform better than the two most accurate sunshine-based models from the literature. The quick and accurate estimations of the global solar radiation using this approach can be employed in the design and evaluation of performance for different solar applications.

Artificial neural network optimisation for monthly average daily global solar radiation prediction

The availability of reliable climatologic data is essential for multiple purposes in a wide set of anthropic activities and operative sectors. Frequently direct measures present spatial and temporal lacks so that predictive approaches become of interest. This paper focuses on the prediction of the Monthly Average Daily Global Solar Radiation (MADGSR) over Italy using Artificial Neural Networks (ANNs). Data from 45 locations compose the multi-location ANN training and testing sets. For each location, 13 input parameters are considered, including the geographical coordinates and the monthly values for the most frequently adopted climatologic parameters. A subset of 17 locations is used for ANN training, while the testing step is against data from the remaining 28 locations. Furthermore, the Automatic Relevance Determination method (ARD) is used to point out the most relevant input for the accurate MADGSR prediction. The ANN best configuration includes 7 parameters, only, i.e. Top of Atmosphere (TOA) radiation, day length, number of rainy days and average rainfall, latitude and altitude. The correlation performances, expressed through statistical indicators as the Mean Absolute Percentage Error (MAPE), range between 1.67% and 4.25%, depending on the number and type of the chosen input, representing a good solution compared to the current standards.

PREDICTING SOLAR RADIATION FOR TROPICAL ISLANDS FROM RAINFALL DATA

There are many correlations developed to predict incident solar radiation at a given location developed based on geographical and meteorological parameters. However, all correlations depend on accurate measurement and availability of weather data such as sunshine duration, cloud cover, relative humidity, maximum and minimum temperatures etc, which essentially is a costly exercise in terms of equipment and labour. Sri Lanka being a tropical island of latitudinal change of only 30 along the length of the country, the meteorological factors govern the amount of incident radiation. Considering the cloud formation and wind patterns over Sri Lanka as well as the seasonal rainfall patterns, it can be observed that the mean number of rainy days can be used to predict the monthly average daily global radiation which can be used for calculations in solar related activities conveniently.

PREDICTING SOLAR RADIATION FOR TROPICAL ISLANDS FROM RAINFALL DATA

There are many correlations developed to predict incident solar radiation at a given location developed based on geographical and meteorological parameters. However, all correlations depend on accurate measurement and availability of weather data such as sunshine duration, cloud cover, relative humidity, maximum and minimum temperatures etc, which essentially is a costly exercise in terms of equipment and labour. Sri Lanka being a tropical island of latitudinal change of only 30 along the length of the country, the meteorological factors govern the amount of incident radiation. Considering the cloud formation and wind patterns over Sri Lanka as well as the seasonal rainfall patterns, it can be observed that the mean number of rainy days can be used to predict the monthly average daily global radiation which can be used for calculations in solar related activities conveniently.

An Evaluation of Global Solar Radiation Empirical Formulations in Isparta, Turkey

Global solar radiation data are very essential for the design, evaluation, and simulation of solar energy systems. For this purpose, various empirical models for computing have been used to predict the monthly average daily global solar radiation on a horizontal surface around the world. The main objective of this article is to investigate 46 existing models and develop 4 models for estimating daily global solar radiation on a horizontal surface in Isparta, Turkey (37.47 N, 30.34 E). The collected existing models and developing models are compared on the basis of statistical error tests. According to the results, the developing model (Model 49) is showed the best estimation of the global solar radiation on a horizontal surface of Isparta by means of the R = 99.42, MPE = –0.254%, MBE = 0.00052 MJ/m2, and RMSE = 1.3284 MJ/m2.

A Novel Intelligent Water Drops Optimization Approach for Estimating Global Solar Radiation

Measurement of the solar radiance requires utilization of expensive devices. To address this issue, estimator models are used to facilitate the measurement process. In this paper, a new method based on the empirical equations is introduced to estimate the monthly average of daily global solar radiation on a horizontal surface. The proposed method takes advantages of an intelligent water drops algorithm as a swarm-based nature-inspired optimization technique. This algorithm has been implemented in the MATLAB software. The best obtained coefficients of linear and nonlinear empirical models and global solar radiation are employed for the measurement of the six different climate regions of Iran. Performance of this approach has been compared to the other existing techniques. The result reveals the superiority of the proposed method in term of accuracy for estimating the monthly average daily global solar radiation.

Monthly average daily global and diffuse solar radiation based on sunshine duration and clearness index for Brasov, Romania

The main objective of this study is to develop single location appropriate models for the estimation of the monthly average daily global and diffuse horizontal solar radiation for Brasov, Romania. The study focuses particularly on models based on the sunshine duration and clearness index. The data used for the calibration of the models were collected during a period of 4 yr, between November 2008 and October 2012, at the Transilvania University of Brasov. The testing and validation of the models was carried out using data from the online SoDa database for Brasov for the year 2005. Different statistical error tests were applied to evaluate the accuracy of the models. The predicted values are also compared with values from three other known models concerning the global and diffuse solar radiation. A new mixed model was developed for the estimation of monthly average daily global horizontal solar radiation. The data processing was performed by means of a real-time interface developed with LabVIEW graphical programming language. The parameters taken into account were the relative sunshine, the clearness index, the extraterrestrial radiation, the latitude and the longitude. The methodology is simple and effective and may be applied for any region. Its effectiveness was proven through comparison with global models.

New technique for global solar radiation forecasting by simulated annealing and genetic algorithms using

In this paper, a novel approach based on simulated annealing algorithm as a meta-heuristic method is implemented in MATLAB software to estimate the monthly average daily global solar radiation on a horizontal surface for six different climate cities of Iran. A search method based on genetic algorithm is applied to accelerate problem solving. Results show that simulated annealing based on genetic algorithm search is a suitable method to find the global solar radiation.

A Temperature-Based Model for Estimating Monthly Average Daily Global Solar Radiation in China

Since air temperature records are readily available around the world, the models based on air temperature for estimating solar radiation have been widely accepted. In this paper, a new model based on Hargreaves and Samani (HS) method for estimating monthly average daily global solar radiation is proposed. With statistical error tests, the performance of the new model is validated by comparing with the HS model and its two modifications (Samani model and Chen model) against the measured data at 65 meteorological stations in China. Results show that the new model is more accurate and robust than the HS, Samani, and Chen models in all climatic regions, especially in the humid regions. Hence, the new model can be recommended for estimating solar radiation in areas where only air temperature data are available in China.

English

The solar radiation study have been undertaken at Pekan campus (3.5oN, 103.4oE), Faculty of Mechanical Engineering, University Malaysia Pahang to utilize solar energy in east coast of Malaysia. The knowledge of the daily variation of global solar radiation is a necessity at the particular locality to consider the feasibility of solar energy utilisation. Hence, the diurnal patterns of global solar radiation were obtained using measured data from weather station which was installed at the site for three years (2011 – 2013). The patterns have been divided into five conditions such as clear sky, partially cloudy, fully cloudy, afternoon rain, and northeast monsoon season day. It was observed that on a clear sky day in Pekan, the maximum solar insolation was 939 W/m 2 and total solar energy received was 6.51 kWhr/m 2 . In contrast, on a fully cloudy day the maximum solar insolation was only 30 W/m 2 and total solar energy received was 0.35 kWhr/m 2 . Besides that, the empirical models were developed to estimate the monthly average daily global solar radiation on a horizontal surface with Pekan meteorological station data. Subsequently, the models were evaluated using statistical analysis. Based on analysis results, Eq. (13) and Eq. (15) models are proposed to estimate monthly average daily global solar radiation for Pekan. The present paper describes on advance understanding of daily variation global solar radiation in east coast Malaysia whereby it has significance for designing a solar system. Lastly, the developed Angstrom’s modified linear models are highly recommended to be used to estimate the monthly average daily global solar radiation in Pekan, Pahang and location with similar solar radiation patterns in east coast Malaysia.

New correlations for estimation of monthly average daily solar radiation on a horizontal surface using meteorological data

This study deals with the estimation of monthly average daily global solar radiation incident on a horizontal surface at a location using meteorological data for different cities of Andhra Pradesh state. The regression equations of two types of models are developed for various locations of the state having varied climatic regions using measured meteorological parameters obtained from different measuring stations. Parameters such as the latitude and height of the location, maximum and minimum temperature and relative humidity are considered to develop linear and quadratic regression equations to estimate the monthly average daily global radiation. The estimated values are compared with measured data and with other theoretical models in terms of mean percent errors calculated using recognised statistical criteria of MBE, MABE, MPE and RMSE. The proposed quadratic model performs better than the proposed linear models and shows good agreement with the long-term pyranometer data of various locations with a deviation of less than 10%. In comparison with other theoretical models presented so far, the suggested models are expected to perform with a higher degree of accuracy.

New Technique for Global Solar Radiation Forecast using Bees Algorithm

A B S T R A C T Solar radiation estimation is integral part for various solar energy systems which requires precise and expensive devices to gage the solar radiation for a particular region. However, researches have proposed different techniques to estimate the solar radiation that hinder using such devices so far. Nonlinear nature and excessive dependence on the meteorological parameters of these methods forced researchers to look for quick and efficient techniques to solve related issues and find solar radiation for a particular region. In this paper, a new method based on the Angstrom model is introduced which estimates the monthly average daily global solar radiation on a horizontal surface by Bees Algorithm as a heuristic and population-based search technique implemented in MATLAB software. The experimental coefficients for Angstrom model are calculated for six different climate regions of Iran using proposed program written in the software. The obtained results proved the efficiency and predominance of the new method to find a more accurate level of solar radiation.

New technique for estimating the monthly average daily global solar radiation using bees algorithm and empirical equations

Measurement of solar radiance demands expensive devices to be used. Alternatively, estimator models are used instead. In this article, a new method based on the empirical equations is introduced to estimate the monthly average daily global solar radiation (GSR) on a horizontal surface. The proposed method uses Bees algorithm as a heuristic and population‐based search technique. The best coefficients of linear and nonlinear empirical models and GSR are calculated for seven different climate regions of Iran using proposed algorithm written in MATLAB software. The results of the proposed method are compared with other techniques. The result shows that the proposed method is more accurate in estimating the monthly average daily GSR. © 2013 American Institute of Chemical Engineers Environ Prog, 33: 1042–1050, 2014

Study of the Intensity of Global Solar Radiation Incident in Suan Sunandha Rajabhat University

Solar radiation is one of mains alternative energy, widely used in present day. Measure solar radiation accurately is an essential for planning in application of used. Universities are the places that have used significant of energy all year long. Therefore, long-term measured solar radiation data is important, for understand in both quantity and variation in time period, for application of the alternative energy in future. The main objective of this research is to investigate solar energy potentials of Suan Sunandha Rajabhat University, Bongkok, Thailand (Latitude 13.46°N, Longitude 100.31°E). A station for solar radiation was installed at Suan Sunandha Rajabhat University. The main equipment is composed of two parts: 1) a pyranometer from Kipp & Zonen Ltd., model CMP11, and 2) a digital data logger from Measurement Systems Ltd. model DX2000. The pyranometer is permanently installed on the top of a building. The data logger is keeping clean and safe inside the building. To analyze the values of the global solar radiations, the computer source code is written in Interactive Data Language version 6.1 (IDL6.1). The results show the variation of the average hourly global irradiance is about 800-900 W/m2 at 12:00 UTC. The maximum monthly average daily global radiation is 21.5 MJ/m2-day in April. The yearly average daily radiation at Suan Sunandha Rajabhat University is found to be 16.55 MJ/m2-day. The information from the monthly and yearly global radiation has relatively high solar energy potentials. Finally, the solar radiation database was also developed for use in solar energy applications in Suan Sunandha Rajabhat University and neighbor areas.

Estimation of horizontal diffuse solar radiation from common meteorological parameters: a case study for Jeddah, Saudi Arabia

The measured data of global and diffuse solar radiation on a horizontal surface, number of sunshine hours, mean daily ambient temperature, maximum and minimum ambient temperatures, relative humidity and amount of cloud cover, for Jeddah (latitude 21° 42′ 37″ N, longitude 39° 11′ 12″ E), Saudi Arabia for the period (1996–2006) are analysed. The data are employed to develop empirical correlations between the monthly average daily diffuse fraction (H d /H) or diffuse transmittance (H d /H 0) and various meteorological parameters such as relative number of sunshine hours (s/s 0), ambient temperature T, relative humidity R h and amount of cloud cover c w. The derived correlations are evaluated by making comparisons between measured and calculated values of monthly average daily diffuse radiation H d. All the proposed correlations are found to be able to predict the monthly and annual averages daily diffuse radiation with excellent accuracy. It is also inferred that, if the data of the monthly average daily global radiation H and number of bright sunshine hours s are not available, the values of H d for the hot-humid zone of Saudi Arabia can be estimated with a reasonable accuracy from the correlations between H d /H 0 and the mean daily ambient temperature T.