scholarly journals A Review of Solar Radiation Models—Part I

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
A. K. Katiyar ◽  
C. K. Pandey
Keyword(s):  
Renewable Energy ◽  
Solar Radiation ◽  
Solar Energy ◽  
Energy Demand ◽  
Socioeconomic Development ◽  
Global Solar Radiation ◽  
Point Of View ◽  
Climate Conditions ◽  
Energy Devices ◽  
The World

Energy is considered as a key source for the future and plays a pivotal role in its socioeconomic development by raising the standard of living and the quality of life, not only for India but also for the world. In view of the scarce fossil fuel reserves, solar energy is one of the important sources of renewable energy used in India because of the suitable climate conditions. It receives about 5485.17 Wh/m2day of solar insolation with an annual total of about 19, 74, 661.2 Wh/m2. Except for the monsoon months, solar radiation incidence is very encouraging, from the application point of view. For the efficient functioning and better performance of solar energy device, the information of solar radiation and its components at particular location is very essential for designing the solar energy devices. Therefore, over the years, several empirical correlations have been developed in order to estimate the more appropriate solar radiation in India as well as around the world. Here we present a review of different solar radiation models which predict global solar radiation and discussed the long-term plan to meet future energy demand with renewable energy due to economy growth.

scholarly journals Ångström-Prescott Models of Solar radiation over Earth surface

2021 ◽  
Vol 2135 (1) ◽  
pp. 012005
Author(s):  
Gloria MarinaGloria Marina Bautista-Rodríguez ◽  
César Alexander Chacón-Cardona
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Energy Demand ◽  
Construction Projects ◽  
Environmental Variability ◽  
Geographical Location ◽  
Global Solar Radiation ◽  
Cost Overruns ◽  
Energy Needs ◽  
Solar Resource

Abstract The current energy demand increases every day and the deficit of electricity generation in Colombia due to technical aspects such as the lack of generation infrastructure, cost overruns in the construction projects of new plants and environmental variability as a consequence of climate change, entail a high risk of energy rationing; for this reason some of the users, whether industrial or residential, have decided to seek multiple alternatives to reduce the costs of their billing in interconnected areas and even supply their energy needs. Among these alternatives is found solar energy in its thermal and photovoltaic use, a resource that must be characterized in order to determine the technical and budgetary aspects involved in the implementation of profitable energy generation projects. This article seeks to provide technical tools for the design and implementation of generation projects based on solar energy, providing physical-mathematical approach based in the classical Angström-Prescott model that allow engineers and researchers to model the global solar radiation on the Earth’s surface in order to maximize the use of this resource in a specific geographical location. Although there are different ways to characterize the solar resource on the earth’s surface, this paper presents a review study focused on the most important global solar radiation estimation models present in the literature.

scholarly journals Evaluation of distributional solar radiation parameters of Cacak using long-term measured global solar radiation data

2007 ◽  
Vol 11 (4) ◽  
pp. 125-134 ◽  
Author(s):  
Snezana Dragicevic ◽  
Nikola Vuckovic
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Energy Demand ◽  
Energy Production ◽  
Global Solar Radiation ◽  
Primary Energy ◽  
Horizontal Surface ◽  
Energy Potential ◽  
Radiation Data

Serbia is becoming more dependent on imported primary energy to meet its increasing energy demand. The ratio of indigenous primary energy production to primary energy consumption is decreasing. Therefore, it is of great importance for Serbia to make use of its indigenous energy resources more effectively, including its solar energy potential. Knowledge of global solar radiation is essential in the prediction, study, and design of the economic viability of systems which use solar energy. In this paper, the solar radiation data on Cacak (lat 43.87?N, long 20.33?E) are analyzed based on 4 years of global solar radiation data measured on a horizontal surface. The distributional solar radiation parameters are derived from the available data and analyzed. The available solar radiation data on a horizontal surface are converted to that of various tilt angles and the yearly and monthly optimum tilt angles are determined.

scholarly journals Deep Learning Neural Networks Trained with MODIS Satellite-Derived Predictors for Long-Term Global Solar Radiation Prediction

Energies ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2407 ◽  
Author(s):  
Ghimire ◽  
Deo ◽  
Raj ◽  
Mi
Keyword(s):  
Neural Networks ◽  
Feature Selection ◽  
Renewable Energy ◽  
Deep Learning ◽  
Solar Radiation ◽  
Solar Energy ◽  
Deep Neural Networks ◽  
Global Solar Radiation ◽  
Hidden Layer

Solar energy predictive models designed to emulate the long-term (e.g., monthly) global solar radiation (GSR) trained with satellite-derived predictors can be employed as decision tenets in the exploration, installation and management of solar energy production systems in remote and inaccessible solar-powered sites. In spite of a plethora of models designed for GSR prediction, deep learning, representing a state-of-the-art intelligent tool, remains an attractive approach for renewable energy exploration, monitoring and forecasting. In this paper, algorithms based on deep belief networks and deep neural networks are designed to predict long-term GSR. Deep learning algorithms trained with publicly-accessible Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data are tested in Australia’s solar cities to predict the monthly GSR: single hidden layer and ensemble models. The monthly-scale MODIS-derived predictors (2003–2018) are adopted, with 15 diverse feature selection approaches including a Gaussian Emulation Machine for sensitivity analysis used to select optimal MODIS-predictor variables to simulate GSR against ground-truth values. Several statistical score metrics are adopted to comprehensively verify surface GSR simulations to ascertain the practicality of deep belief and deep neural networks. In the testing phase, deep learning models generate significantly lower absolute percentage bias (≤3%) and high Kling–Gupta efficiency (≥97.5%) values compared to the single hidden layer and ensemble model. This study ascertains that the optimal MODIS input variables employed in GSR prediction for solar energy applications can be relatively different for diverse sites, advocating a need for feature selection prior to the modelling of GSR. The proposed deep learning approach can be adopted to identify solar energy potential proactively in locations where it is impossible to install an environmental monitoring data acquisition instrument. Hence, MODIS and other related satellite-derived predictors can be incorporated for solar energy prediction as a strategy for long-term renewable energy exploration.

scholarly journals A Linear Regression Model for Global Solar Radiation on Horizontal Surfaces at Warri, Nigeria

2013 ◽  
Vol 2 (3) ◽  
pp. 121-126 ◽  
Author(s):  
Michael S. Okundamiya ◽  
Israel E. Okpamen
Keyword(s):  
Renewable Energy ◽  
Linear Regression ◽  
Solar Radiation ◽  
Solar Energy ◽  
Regression Model ◽  
Linear Regression Model ◽  
Global Solar Radiation ◽  
Mean Bias Error ◽  
Accurate Estimation ◽  
Radiation Data

The growing anxiety on the negative effects of fossil fuels on the environment and the global emission reduction targets call for a more extensive use of renewable energy alternatives. Efficient solar energy utilization is an essential solution to the high atmospheric pollution caused by fossil fuel combustion. Global solar radiation (GSR) data, which are useful for the design and evaluation of solar energy conversion system, are not measured at the forty-five meteorological stations in Nigeria. The dearth of the measured solar radiation data calls for accurate estimation. This study proposed a temperature-based linear regression, for predicting the monthly average daily GSR on horizontal surfaces, at Warri (latitude 5.020N and longitude 7.880E) an oil city located in the south-south geopolitical zone, in Nigeria. The proposed model is analyzed based on five statistical indicators (coefficient of correlation, coefficient of determination, mean bias error, root mean square error, and t-statistic), and compared with the existing sunshine-based model for the same study. The results indicate that the proposed temperature-based linear regression model could replace the existing sunshine-based model for generating global solar radiation data. Keywords: air temperature; empirical model; global solar radiation; regression analysis; renewable energy; Warri

scholarly journals Evaluation and Comparison of Temperature-Based Models for The Prediction of The Monthly Average of Daily Global Solar Radiation for Baghdad City- Iraq

2020 ◽  
pp. 533-539
Author(s):  
Awras H. Ajil
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Meteorological Data ◽  
Global Solar Radiation ◽  
Radiation Model ◽  
Climate Conditions ◽  
First Order ◽  
Monthly Average ◽  
Suitable Climate ◽  
Solar Radiation Model

The solar energy is the major source of power for the future and an important source of renewable energy in Iraq and the world. Suitable climate conditions for solar energy are available in Iraq, especially the high temperature in the summer season which extends for more than six months in the year. Hence, the global solar radiation is abundant with high intensity, which is very essential in applicable models for researchers and solar applications. Therefore, nine first-order regression empirical equations of Angstrom-type correlations were used to estimate the more appropriate global solar radiation model for Baghdad city. Two equations were developed empirically in this work, using the most available and easy to get meteorological data, which is the temperature value in various forms. The results of the comparison between the real and calculated values showed reasonable agreement for most equations (including the development of R2- at 99%) as well as the least values of types of errors RMSE and MBE. As an exception, two equations of models failed in this study because of inability to apply to such climate conditions of Baghdad city.

scholarly journals Detrended Multiple Cross-Correlation Coefficient applied to solar radiation, air temperature and relative humidity

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Andrea de Almeida Brito ◽  
Heráclio Alves de Araújo ◽  
Gilney Figueira Zebende
Keyword(s):  
Relative Humidity ◽  
Solar Radiation ◽  
Solar Energy ◽  
Correlation Coefficient ◽  
Air Temperature ◽  
Cross Correlation ◽  
Global Solar Radiation ◽  
Meteorological Variables ◽  
Hourly Data ◽  
Cross Correlations

AbstractDue to the importance of generating energy sustainably, with the Sun being a large solar power plant for the Earth, we study the cross-correlations between the main meteorological variables (global solar radiation, air temperature, and relative air humidity) from a global cross-correlation perspective to efficiently capture solar energy. This is done initially between pairs of these variables, with the Detrended Cross-Correlation Coefficient, ρDCCA, and subsequently with the recently developed Multiple Detrended Cross-Correlation Coefficient, $${\boldsymbol{DM}}{{\boldsymbol{C}}}_{{\bf{x}}}^{{\bf{2}}}$$DMCx2. We use the hourly data from three meteorological stations of the Brazilian Institute of Meteorology located in the state of Bahia (Brazil). Initially, with the original data, we set up a color map for each variable to show the time dynamics. After, ρDCCA was calculated, thus obtaining a positive value between the global solar radiation and air temperature, and a negative value between the global solar radiation and air relative humidity, for all time scales. Finally, for the first time, was applied $${\boldsymbol{DM}}{{\boldsymbol{C}}}_{{\bf{x}}}^{{\bf{2}}}$$DMCx2 to analyze cross-correlations between three meteorological variables at the same time. On taking the global radiation as the dependent variable, and assuming that $${\boldsymbol{DM}}{{\boldsymbol{C}}}_{{\bf{x}}}^{{\bf{2}}}={\bf{1}}$$DMCx2=1 (which varies from 0 to 1) is the ideal value for the capture of solar energy, our analysis finds some patterns (differences) involving these meteorological stations with a high intensity of annual solar radiation.

Review of empirical solar radiation models for estimating global solar radiation of various climate zones of China

2019 ◽  
Vol 44 (2) ◽  
pp. 168-188
Author(s):  
Shaban G Gouda ◽  
Zakia Hussein ◽  
Shuai Luo ◽  
Qiaoxia Yuan
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Computational Cost ◽  
Energy Systems ◽  
Global Solar Radiation ◽  
Empirical Models ◽  
Dew Point ◽  
Machine Learning Techniques ◽  
Accurate Information ◽  
Input Parameters

Utilizing solar energy requires accurate information about global solar radiation (GSR), which is critical for designers and manufacturers of solar energy systems and equipment. This study aims to examine the literature gaps by evaluating recent predictive models and categorizing them into various groups depending on the input parameters, and comprehensively collect the methods for classifying China into solar zones. The selected groups of models include those that use sunshine duration, temperature, dew-point temperature, precipitation, fog, cloud cover, day of the year, and different meteorological parameters (complex models). 220 empirical models are analyzed for estimating the GSR on a horizontal surface in China. Additionally, the most accurate models from the literature are summarized for 115 locations in China and are distributed into the above categories with the corresponding solar zone; the ideal models from each category and each solar zone are identified. Comments on two important temperature-based models that are presented in this work can help the researchers and readers to be unconfused when reading the literature of these models and cite them in a correct method in future studies. Machine learning techniques exhibit performance GSR estimation better than empirical models; however, the computational cost and complexity should be considered at choosing and applying these techniques. The models and model categories in this study, according to the key input parameters at the corresponding location and solar zone, are helpful to researchers as well as to designers and engineers of solar energy systems and equipment.

scholarly journals PROSPECTS FOR RENEWABLE ENERGY FOR LOW-RISE BUILDINGS IN CRIMEA

2020 ◽  
pp. 85-93
Author(s):  
N. V. Tsopa ◽  
A. E. Dikarev
Keyword(s):  
European Union ◽  
Renewable Energy ◽  
Solar Energy ◽  
Power Supply ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
The European Union ◽  
Advantages And Disadvantages ◽  
The World ◽  
The Crimea

in the article provides a comparative analysis of the development of solar energy in the world, in the European Union, in Russia and in Crimea; the advantages and disadvantages of the use of solar energy, the features of the use of renewable energy sources are considered, the use of solar energy in the Crimea is justified; describes the mechanism of a feasibility study for the use of autonomous power supply for low-rise buildings in Crimea.

scholarly journals Photovoltaic power generation system

2018 ◽  
Vol 1 (1) ◽  
Author(s):  
Huang Huanhai
Keyword(s):  
Power Generation ◽  
Renewable Energy ◽  
Solar Energy ◽  
Social Life ◽  
Fossil Fuels ◽  
Solar Power ◽  
Environmentally Friendly ◽  
Energy Status ◽  
The World ◽  
New Energy

The potential crisis of energy and the deterioration of ecological environment make the world's cumbersomedevelopment of renewable energy including new energy, including solar energy. Traditional energy in the coal, oil andnatural gas are evolved from ancient fossils, it is collectively referred to as fossil fuels. As the world's energy needscontinue to increase, fossil fuels will also be depleted, it is necessary to fi nd a new energy to replace the traditionalenergy. Solar energy is a clean renewable energy with mineral energy incomparable superiority. Modern society shouldbe a conservation-oriented society, and social life should also be a life-saving energy. At the same time, Premier WenJiabao also proposed on June 30, 2005 and stressed the need to speed up the construction of a conservation-orientedsociety. And solar energy as an inexhaustible new environmentally friendly energy has become the world's energyresearch work in the world an important issue. Is the world in the economic situation to take a simpler, economical,environmentally friendly and reliable building heating and heating energy-saving measures. This paper summarizes thecurrent global energy status, indicating the importance of solar power and prospects. Details of the various solar powergeneration methods and their advantages, and made a comparison of this power generation parameters. At the sametime pointed out that the diffi culties faced by solar power and solutions, as well as China's solar power of the favorableconditions and diffi culties. The future of China's solar energy made a prospect.

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