Selection of an Information Source and Methodology for Calculating Solar Resources of the Kyrgyz Republic

2021 ◽  
pp. 578-615
Author(s):  
Alisher F. Narynbaev ◽  
Baatai M. Maksatov ◽  
Alexey Gennad'evich Vaskov ◽  
Galina V. Deryugina ◽  
Roman V. Pugachev
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Information Source ◽  
Global Solar Radiation ◽  
Climatic Conditions ◽  
Empirical Models ◽  
Kyrgyz Republic ◽  
Detailed Data ◽  
Grid Systems ◽  
Selection Of

Detailed data on incoming solar radiation are needed in the design of solar energy systems of any scale: from large PV plants to small off-grid systems. However, in most cases, obtaining data on measurements of solar radiation is connected with difficulties due to financial or technical restrictions. Often, ground-based measurements of solar radiation are either not carried out at all or only the value of the global horizontal intensity of solar radiation is measured. The aim of the present study is to review and to verify some existing empirical models of the global solar radiation and its components for the climatic conditions of Kyrgyzstan as well as to estimate the applicability of Meteonorm database model for the available solar radiation in the territory of Kyrgyzstan. The necessity to select the most suitable models of the solar radiation is called by the lack of similar studies on this direction for the conditions of the country.

Selection of an Information Source and Methodology for Calculating Solar Resources of the Kyrgyz Republic

2020 ◽  
pp. 236-272
Author(s):  
Alisher F. Narynbaev ◽  
Baatai M. Maksatov ◽  
Alexey Gennad'evich Vaskov ◽  
Galina V. Deryugina ◽  
Roman V. Pugachev
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Information Source ◽  
Global Solar Radiation ◽  
Climatic Conditions ◽  
Empirical Models ◽  
Kyrgyz Republic ◽  
Detailed Data ◽  
Grid Systems ◽  
Selection Of

Detailed data on incoming solar radiation are needed in the design of solar energy systems of any scale: from large PV plants to small off-grid systems. However, in most cases, obtaining data on measurements of solar radiation is connected with difficulties due to financial or technical restrictions. Often, ground-based measurements of solar radiation are either not carried out at all or only the value of the global horizontal intensity of solar radiation is measured. The aim of the present study is to review and to verify some existing empirical models of the global solar radiation and its components for the climatic conditions of Kyrgyzstan as well as to estimate the applicability of Meteonorm database model for the available solar radiation in the territory of Kyrgyzstan. The necessity to select the most suitable models of the solar radiation is called by the lack of similar studies on this direction for the conditions of the country.

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 Global solar radiation modeling using different machine learning and empirical models in Northeast China

2021 ◽  
Author(s):  
Yue Jia ◽  
Yongjun Su ◽  
Fengchun Wang ◽  
Pengcheng Li ◽  
Shuyi Huo
Keyword(s):  
Machine Learning ◽  
Solar Radiation ◽  
Solar Energy ◽  
Northeast China ◽  
Sunshine Duration ◽  
Meteorological Data ◽  
Global Solar Radiation ◽  
Empirical Models ◽  
Learning Models ◽  
Machine Learning Models

Abstract Reliable global solar radiation (Rs) information is crucial for the design and management of solar energy systems for agricultural and industrial production. However, Rs measurements are unavailable in many regions of the world, which impedes the development and application of solar energy. To accurately estimate Rs, this study developed a novel machine learning model, called a Gaussian exponential model (GEM), for daily global Rs estimation. The GEM was compared with four other machine learning models and two empirical models to assess its applicability using daily meteorological data from 1997–2016 from four stations in Northeast China. The results showed that the GEM with complete inputs had the best performance. Machine learning models provided better estimates than empirical models when trained by the same input data. Sunshine duration was the most effective factor determining the accuracy of the machine learning models. Overall, the GEM with complete inputs had the highest accuracy and is recommended for modeling daily Rs in Northeast China.

scholarly journals Empirical models for estimation of global solar radiation using the monthly average daily sunshine hours data for Makurdi, Benue State

2020 ◽  
Vol 12 (1) ◽  
pp. 32-39
Author(s):  
R.S. Sa’id ◽  
S.I. Akor ◽  
U.M. Gana
Keyword(s):  
Solar Radiation ◽  
Diffuse Radiation ◽  
Global Solar Radiation ◽  
Climatic Conditions ◽  
Empirical Models ◽  
Coefficient Of Determination ◽  
Linear Quadratic ◽  
Diffuse Fraction ◽  
Correlation Models ◽  
Sunshine Hours

This paper proposes empirical correlation models for estimating global solar radiation using data of sunshine hours for the location of Makurdi in Benue State of Nigeria. The paper suggests extrapolation of the empirical models for other locations with similar climatic conditions. The proposed models are: Linear, Quadratic, Cubic, Exponential, Power and Logarithmic models. Each of the models is based on Angstrom-Prescott equations for estimating global solar radiation. Any of the models can ease the use of sophisticated equipments, which are expensive, delicate and sometimes develop faults during measurement. The results of the models show that the cubic model is the best with slightly higher coefficient of  determination. The coefficient of  determination of each of the models was found to be 0.952, 0.965, 0.967, 0.965, 0.948& 0.924 respectively, while the absolute correlation was found to be unity. Errors evaluated include MBE, RMSE and MPE with minimal values. The percentage diffuse and direct solar radiations, clearness index and the diffuse fraction were also estimated using the models. The results of the estimations done using the proposed models indicate that there is an estimated average annual global solar radiation of 6056MJm-2, monthly value of 505MJm-2 and daily insolation of 16.82MJm-2 sufficient enough for maximum solar radiation exploitation. Keywords: Solar Radiation, Empirical Models, Diffuse Radiation, Direct Radiation

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.

scholarly journals Identification of solar radiation effect on climatic indicators of the territory of Ukraine

2018 ◽  
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Air Temperature ◽  
Temperature Regime ◽  
Atmospheric Pressure ◽  
Weather Conditions ◽  
Climatic Conditions ◽  
Practical Significance ◽  
Statistical Dependence ◽  
Physical Processes

Formulation of the problem. Understanding that solar energy is the main source of the majority of biological, chemical and physical processes on Earth, investigation of its influence on different climatic fields allows us to define the features of its space and hour fluctuations. To define radiation and temperature regime of the territory it is necessary to determine climatic features of the spreading surface, which absorbs and will transform solar energy. Considering the fact that modern climatic changes and their consequences cover all components of the system, today there is a problem of their further study for comprehension of atmospheric processes, modeling weather conditions on different territories depending on the properties. The purpose of the article is to determine interrelations between indexes of solar radiation (the Wolf's number) and air temperature, atmospheric pressure on the territory of Ukraine during 1965-2015, their change in space and time. Methods. Correlative method is one of the main methods of a statistical analysis which allows us to receive correlation coefficients of solar radiation variability indexes, air temperature, atmospheric pressure on the territory of the research. This technique estimates the extent of solar radiation influence on temperature regime of the territory and distribution of atmospheric pressure. Results. Coefficients of correlation, which characterize variability of solar radiation indexes, air temperature and atmospheric pressure on the explored territory have been received by means of statistical correlation analysis method. This technique allows us to estimate the degree and nature of solar radiation influence on a temperature regime of the territory and distribution of atmospheric pressure. It has been defined that direct correlative connection between indexes of solar radiation is characteristic of air temperature and atmospheric pressure fields. Significant statistical dependence between incoming solar radiation on the territory of Ukraine and atmospheric pressure has been noted during the spring and autumn periods mainly at the majority of stations. Between indexes of solar radiation and air temperature the inverse correlative connection in winter will be transformed to a direct connection during the spring and summer periods. Scientific novelty and practical significance. Physical processes, which happen in the atmosphere, are characterized by complex interrelations. For further research it is important to define solar radiation value and the extent of influence on climatic conditions.

scholarly journals Developing mathematical models for global solar radiation intensity estimation at Shakardara, Kabul

2021 ◽  
Vol 4 (2) ◽  
pp. 133-138
Author(s):  
Abdul Basit Da’ie
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Mathematical Models ◽  
Radiation Intensity ◽  
Global Solar Radiation ◽  
Suitable Model ◽  
Intensity Estimation ◽  
Solar Radiation Intensity ◽  
Sunshine Hours ◽  
Atmospheric Data

Solar energy properties such as Global Solar Radiation (GSR) intensity could be determined in either methods, experimentally or theoretically. Unfortunately, in most countries including Afghanistan, the first method which is more acceptable, but due to the high cost, maintenance and calibration requirements is not available. Therefore, an alternative widely used way is the second one which is model developments based on the meteorological (atmospheric) data; specially the sunny hours. The aim of this study at Shakardara area is to estimate atmospheric transparency percentage on 2017, determining the angstrom model coefficients and to introduce a suitable model for global solar radiation prediction. The hourly observed solar radiation intensity H (WHm-2 ) and sunshine hours S (

scholarly journals Parametrization of Models and Use of Estimated Global Solar Radiation Data in the Irrigated Rice Yield Simulation

2018 ◽  
Vol 33 (2) ◽  
pp. 238-246
Author(s):  
João Rodrigo de Castro ◽  
Santiago Vianna Cuadra ◽  
Luciana Barros Pinto ◽  
João Marcelo Hoffmann de Souza ◽  
Marcos Paulo dos Santos ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Air Temperature ◽  
Rice Yield ◽  
Simulation Models ◽  
Global Solar Radiation ◽  
Empirical Models ◽  
Potential Yield ◽  
Irrigated Rice ◽  
Radiation Data ◽  
The Impact

Abstract The objective of this study was to evaluate the use of estimated global solar radiation data in the simulations of potential yield of irrigated rice. Global solar radiation was estimated by four empirical models, based on air temperature, and a meteorological satellite derivated. The empirical models were calibrated and validated for 10 sites, representative of the six rice regions of the State of Rio Grande do Sul - Brazil. To evaluate the impact of the radiation estimates on irrigated rice yield simulations, the CERES-Rice model, calibrated for four cultivars, was used. The estimates of global solar radiation of the empirical models based on the air temperature showed deviations, from the observed values, of 20 to 30% and the estimated by satellite deviations of more than 30%. The global solar radiation data estimated by the Hargreaves and Samani, Donatelli and Campbell and derived satellite (PowerNasa) type air temperature-based empirical models can be used as input data in simulation models of crop growth, development and productivity of irrigated rice.

scholarly journals A Modified Method to Generate Typical Meteorological Years from the Long-Term Weather Database

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Haixiang Zang ◽  
Qingshan Xu ◽  
Pengwei Du ◽  
Katsuhiro Ichiyanagi
Keyword(s):  
Relative Humidity ◽  
Solar Radiation ◽  
Solar Energy ◽  
Atmospheric Pressure ◽  
Energy Systems ◽  
Global Solar Radiation ◽  
Weather Data ◽  
Radiation Data ◽  
Modified Method

A modified typical meteorological year (TMY) method is proposed for generating TMY from practical measured weather data. A total of eleven weather indices and novel assigned weighting factors are applied in the processing of forming the TMY database. TMYs of 35 cities in China are generated based on the latest and accurate measured weather data (dry bulb temperature, relative humidity, wind velocity, atmospheric pressure, and daily global solar radiation) in the period of 1994–2010. The TMY data and typical solar radiation data are also investigated and analyzed in this paper, which are important in the utilizations of solar energy systems.

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