• KIEAE Journal
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• v.14 no.2
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• pp.3-10
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• 2014

Impact by estimation error of hourly horizontal global solar radiation in a weather file on building energy performance was investigated in this study. There are a number of weather parameters in a given weather file, such as dry-bulb, wet-bulb, dew-point temperatures; wind speed and direction; station pressure; and solar radiation. Most of them except for solar radiation can be easily obtained from weather stations located on the sites worldwide. However, most weather stations, also including the ones in South Korea, do not measure solar radiation because the measuring equipment for solar radiation is expensive and difficult to maintain. For this reason, many researchers have studied solar radiation estimation models and suggested to apply them to predict solar radiation for different weather stations in South Korea, where the solar radiation is not measured. However, only a few studies have been conducted to identify the impact caused by estimation errors of various solar radiation models on building energy performance analysis. Therefore, four different weather files using different horizontal global solar radiation data, one using measured global solar radiation, and the other three using estimated global solar radiation models, which are Cloud-cover Radiation Model (CRM), Zhang and Huang Model (ZHM), and Meteorological Radiation Model (MRM) were packed into TRY formatted weather files in this study. These were then used for office building energy simulations to compare their energy consumptions, and the results showed that there were differences in the energy consumptions due to these four different solar radiation data. Additionally, it was found that using hourly solar radiation from the estimation models, which had a similar hourly tendency with the hourly measured solar radiation, was the most important key for precise building energy simulation analysis rather than using the solar models that had the best of the monthly or yearly statistical indices.

• Journal of Korea Water Resources Association
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• v.52 no.12
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• pp.1033-1046
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• 2019

To evaluate the utilization suitability of solar radiation models, estimated solar radiation from 13 solar radiation models were verified by comparing with measured solar radiation at 5 study stations in South Korea. Furthermore, for the evaluation of evaporation estimates according to solar radiation models, 5 different evaporation estimation equations based on Penman's combination approach were applied, and evaporation estimates were compared with pan evaporation. Some solar radiation models require only meteorological data; however, some other models require not only meteorological data but also geographical data such as elevation. The study results showed that solar radiation model based on the ratio of the duration of sunshine to the possible duration of sunshine, maximum temperature, and minimum temperature provided the estimated solar radiation that most closely match measured solar radiation. Accuracy of estimated solar radiation also greatly improved when Angstrőm-Prescott model coefficients are adjusted to the study stations. Therefore, when choosing the solar radiation model for evaporation estimation, both data availability and model capability should be considered simultaneously. When applying measured solar radiation for estimating evaporation, evaporation estimates from Penman, FAO Penman-Monteith, and KNF equations are most close to pan evaporation rates in Jeonju and Jeju, Seoul and Mokpo, and Daejeon respectively.

• Journal of the Korean Solar Energy Society
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• v.33 no.5
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• pp.9-17
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• 2013

Hourly horizontal global solar radiation has been used as one of significant parameters in a weather file for building energy simulations, which determines the quality of building thermal performance. However, as about twenty two weather stations in Korea have actually measured the horizontal global sola radiation, the weather files collected in other stations requires solar data simulation from the other meteorological parameters. Thus, finding the reliable complicated method that can be used in various weather conditions in Korea is critically important. In this paper, three solar simulation models were selected and evaluated through the reliability test with the simulated hourly horizontal global solar radiation against the actually measured solar data to find the most suitable model for the south east area of Korea. Three selected simulation models were CRM, ZHM, and MRM. The first two models are regression type models using site-fitted coefficients which are derived from the correlation between measured solar data and local meteorological parameters from the previous years, and the last model is a mechanistic type model using the meteorological data to calculate conditions of atmospheric constituents that cause absorption and scattering of the extraterrestrial radiation on the way to the surface on the Earth. The evaluation results show that ZHM is the most reliable model in this area, yet a complicated hybrid simulation methods applying the advantages of each simulation method with the monthly-based weather data is needed.

• Journal of the Korean Solar Energy Society
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• v.34 no.1
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• pp.39-47
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• 2014

Solar applications analysis and building energy performance depend on the quality of the solar resource data available. Unfortunately, most of the weather stations do not measure solar radiation data in Korea, as a reason many researchers have studied different solar radiation estimation models and suggested to apply them to various locations in Korea. In addition, they also studied the impact of hourly global solar radiation on energy performance of an office building by comparing the simulated building energy consumptions using four different weather files, one using measured, and three estimated solar radiation from different models, which are Cloud-cover Radiation Model (CRM), Zhang and Huang Model (ZHM), and Meteorological Radiation Model (MRM), and concluded that there was some impact on energy performance of the building due to the using different solar radiation models. However, the result cannot be applied to all other buildings since the simulated office building for that study only used limited building characteristics such as using fixed values of solar heat gain coefficient (SHGC) and window-to-wall ratio (WWR), which are significant parameters related to solar radiation that affect to the building energy consumptions. Therefore, there is a need to identify how the building energy consumption will be changed by varying these building parameters. In this study, the impact of one measured and three estimated global solar radiation on energy performance of the office building was conducted taking account of SHGC and WWR. As a result, it was identified that the impact of four different solar radiation data on energy performance of the office building was evident regardless SHGC and WWR changes, and concluded that the most suitable solar models was changed from the CRM/ZHM to the MRM as SHGC and WWR increases.

• 한국태양에너지학회:학술대회논문집
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• 2008.04a
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• pp.142-147
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• 2008

Limited fossil fuels and unstable energy supply are considered as one of the critical problems in architecture requiring large amounts of energy. In order to this challenge, environment-friendly architecture design is required. Especially, Application of solar energy as a clean energy source and one kind of renewable energy. Many sites however are mainly concentrated in the developed countries, and are scarcer within the developing world. Simple radiation estimation models using meteorologically observed input parameters are often used in the applications requiring rough estimations of solar radiation. In this paper, measurements of global solar radiation and cloud data hours in climatological locations in South Korea are used to develop an estimation in solar radiation. The results of measured data are compared with the results obtained from equations, internationally accepted correlations.

• Advances in Energy Research
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• v.6 no.2
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• pp.131-143
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• 2019

Global Solar Radiation (GSR) is the key element for performance estimation of any Solar Power Plant (SPP). Its forecasting may help in estimation of power production from a SPP well in advance, and may also render help in optimal use of this power. Seasonal Auto-Regressive Moving Average (SARMA) and Artificial Neural Network (ANN) models are combined in order to develop a hybrid model (SARMA-ANN) conceiving the characteristics of both linear and non-linear prediction models. This developed model has been used for prediction of GSR at Gorakhpur, situated in the northern region of India. The proposed model is beneficial for the univariate forecasting. Along with this model, we have also used Auto-Regressive Moving Average (ARMA), SARMA, ANN based models for 1 - 6 day-ahead forecasting of GSR on hourly basis. It has been found that the proposed model presents least RMSE (Root Mean Square Error) and produces best forecasting results among all the models considered in the present study. As an application, the comparison between the forecasted one and the energy produced by the grid connected PV plant installed on the parking stands of the University shows the superiority of the proposed model.

• KCID journal
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• v.19 no.1
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• pp.87-96
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• 2012

Information of local solar radiation is essential for many field, including water resources management, crop yield estimation, crop growth model, solar energy systems and irrigation and drainage design. Unfortunately, solar radiation measurements are not easily available due to the cost and maintenance and calibration requirements of the measuring equipment and station. Therefore, it is important to elaborate methods to estimate the solar radiation based on readily available meteorological data. In this study, two empirical equations are employed to estimate daily solar radiation using Cheongju Regional Meteorological Office data. Two scenarios are considered: (a) sunshine duration data are available for a given location, or (b) only daily cloudiness index records exist. Simple linear regression with daily sunshine duration and cloudiness index as the dependent variable accounted for 91% and 80%, respectively of the variation of solar radiation(H) at 2011. Daily global solar radiation is highly correlated with sunshine duration. In order to indicate the performance of the models, the statistical test methods of the mean bias error(MBE), root mean square error(RMSE) and correlation coefficient(r) are used. Sunshine duration and cloudiness index can be easily and reliably measured and data are widely available.

• Journal of the Korean Solar Energy Society
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• v.28 no.3
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• pp.1-6
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• 2008

It is necessary to estimate empirical constants in order to predict the monthly mean daily global radiation on a horizontal surface in the developing areas for alternative energy. Therefore many different equations have proposed to evaluate them for certain areas. In this work a new correlation has been made to predict the solar radiation for any areas over Korea by calculating the regression models taking into account latitude, percentage of possible sunshine, and cloud cover. Results clearly demonstrates the reliability of the single linear equation for the estimation of global radiation, which is proposed by using percentage of possible sunshine method. When compared with the measured values, the average annual deviation falls between -3.1 to +0.6%.

• 한국신재생에너지학회:학술대회논문집
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• 2011.05a
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• pp.67.2-67.2
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• 2011

It is necessary to estimate empirical constants in order to predict the monthly mean daily global radiation on a horizontal surface in the developing areas for alternative energy. Therefore many different equations have proposed to evaluate them for certain areas. In this work a new correlation has been made to predict the solar radiation for any areas over Korea by calculating the regression models taking into account latitude, percentage of possible sunshine, and cloud cover. From the results, the single linear equation proposed by using percentage of possible sunshine method shows reliable results for estimating the global radiation with average annual deviation of -3.1 to +0.6 % from measured values.

• Journal of Korea Water Resources Association
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• v.55 no.3
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• pp.229-243
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• 2022

The effects of monthly meteorological data measured at 11 stations in South Korea on pan coefficient were analyzed to develop the four types of multiple linear regression models for estimating pan coefficients. To evaluate the applicability of developed models, the models were compared with six previous models. Pan coefficients were most affected by air temperature for January, February, March, July, November and December, and by solar radiation for other months. On the whole, for 12 months of the year, the effects of wind speed and relative humidity on pan coefficient were less significant, compared with those of air temperature and solar radiation. For all meteorological stations and months, the model developed by applying 5 independent variables (wind speed, relative humidity, air temperature, ratio of sunshine duration and daylight duration, and solar radiation) for each station was the most effective for evaporation estimation. The model validation results indicate that the multiple linear regression models can be applied to some particular stations and months.