• New & Renewable Energy
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• v.19 no.4
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• pp.98-107
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• 2023

A study was conducted to analyze data from 1981 to 2020 for understanding the impact of climate on solar energy generation. A significant increase of 104.6 kWhm^-2 was observed in the annual cumulative solar radiation over this period. Notably, the distribution of solar radiation shifted, with the solar radiation in Busan rising from the seventh place in 1981 to the second place in 2020 in South Korea. This study also examined the correlation between long-term temperature trends and solar radiation. Areas with the highest solar radiation in 2020, such as Busan, Gwangju, Daegu, and Jinju, exhibited strong positive correlations, suggesting that increased solar radiation contributed to higher temperatures. Conversely, regions like Seosan and Mokpo showed lower temperature increases due to factors such as reduced cloud cover. To evaluate the impact on solar energy production, simulations were conducted using climate data from both years. The results revealed that relying solely on historical data for solar energy predictions could lead to overestimations in some areas, including Seosan or Jinju, and underestimations in others such as Busan. Hence, considering long-term climate variability is vital for accurate solar energy forecasting and ensuring the economic feasibility of solar projects.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.221-228
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• 2019

The effects of wind speed on the temperature change during day time could be insignificant in a region with a complex terrain. The objective of this study was to derive empirical relationship between solar radiation and hourly temperature under a windy condition for the period from sunrise to sunset in order to improve hourly air temperature at a site-specific scale. The deviation of the temperature measurements was analyzed along with the changes of the hourly sunlight at weather observation sites located on the east and west slopes under given wind speed. An empirical model where wind speed use used as an independent variable was obtained to quantify the solar effects on the temperature change (MJ/㎡). This model was verified estimating the hourly temperature during the daytime (0600-1900 h) at 25 weather observation sites located in the study area that has complex topography for the period from January to December 2018. The mean error (ME) and root mean square error (RMSE)of the estimated and measured values ranged from -0.98 to 0.67 ℃, and from 0.95 to 2.04 ℃, respectively. The daytime temperature at 1500 h were estimated using new and previous models. It was found that to the model proposed in the present study reduced the measurement errors of the hourly temperature in the afternoon in comparison with the previous model. For example, the ME and RMSE of the previous model were (ME -0.91 ℃ and 1.47 ℃, respectively. In contrast, the values of ME and RMSE were -0.45 ℃ and 1.22 ℃ for the new model, respectively. Our results suggested that the reliability of hourly temperature estimates at a specific site could be improved taking into account the effect of wind as well as solar radiation.

• Journal of Korean Society of Environmental Engineers
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• v.39 no.5
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• pp.255-264
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• 2017

To evaluate the water quality changes in agricultural reservoir covered with floating photovoltaic solar-tracking systems, the water quality variations with time and depth were monitored on both six sites for light blocking zones and four sites for light penetration zones after the installation of floating photovoltaic solar-tracking systems in Geumgwang reservoir at Anseong-si, Kyeonggi province. For one year with 16 monitoring events, water quality parameters [i.e., water temperature, pH, dissolved oxygen (DO), chlorophyll-a (Chl-a), and blue-green algae (BGA)] were monitored at depths of 0.3 m, 1 m, 3 m, and 5 m, while chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) were monitored at depths of 0.3 m. Statistically, the difference in all water quality parameters was not significantly different (p > 0.05) at the level of significance of 0.05. Based on these results, the water quality data from light blocking zones (site 1~6) and light penetration zones (site 7~10) were clustered, and were compared with time and depth. As a result, the difference in water temperature, pH, DO, COD, TN, TP, Chl-a, and BGA between light blocking zones and light penetration zones was not significant (p > 0.05) with different time and depth. For Chl-a and BGA, some data from light blocking zones greater than light penetration zones were temporary observed due to the severe drought, low water storage rate, and over growth of periphyton. However, this temporal phenomenon did not impact the water quality. Considering the small water surface area (${\leq}0.5%$) covered by floating photovoltaic solar-tracking systems, the mixing effect of whole Geumgwang reservoir caused by Ekman current and continuous discharge were more dominant than the effect of reduced solar irradiance. Further study is warranted to monitor the changes in water quality and aquatic ecosystems with greater water surface area covered by floating photovoltaic solar-tracking systems for a long time.

• Journal of the Korean Institute of Landscape Architecture
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• v.42 no.5
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• pp.22-30
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• 2014

The purpose of this study was to compare the Solar Radiation(SR) and the Mean Radiant Temperature(MRT) under the shades of the three landscaping trees in clear summer daytimes. The trees were Lagerstroemia indica, Quercus palustris and Ulmus parvifolia. The solar radiation, the globe temperature and the air temperature were recorded every minute from the $1^{st}$ of April to the $30^{th}$ of September 2013 at a height of 1.1m above on the four monitoring stations, with four same measuring system consisting of a solar radiation sensor, two resistance temperature detectors(Pt-100), a black brass globe (${\phi}50mm$) and data acquisition systems. At the same time, the sky view photos were taken automatically hourly by three scouting cameras(lens angle: $60^{\circ}$) fixed at each monitoring station. Based on the 258 daily sky view photos and 6,640 records of middays(10 A.M.~2 P.M.) from the $1^{st}$ of June to the $30^{th}$ of August, the time serial differences of SR and MRT under the trees were analysed and compared with those of open sky, The major findings were as follows; 1. The average ratio of sky views screened by the canopies of Quercus palustris, Lagerstroemia indica and Ulmus parvifolia were 99%, 98% and 97%, and the SR were $106W/m^2$, $163W/m^2$ and $202W/m^2$ respectively, while the SR of open sky was $823W/m^2$. Which shows the canopies blocked at least 70% of natural SR. 2. The average MRT under the canopies of Quercus palustris, Lagerstroemia indica and Ulmus parvifolia were $30.34^{\circ}C$, $33.34^{\circ}C$ and $34.77^{\circ}C$ respectively, while that of open sky was $46.0^{\circ}C$. Therefore, it can be said that the tree canopies can reduce the MRT around $10{\sim}16^{\circ}C$. 3. The regression test showed significant linear relationship between the SR and MRT. In summary, the performances of the landscaping shade trees were very good at screening the SR and reducing the MRT at the outdoor of summer middays. Therefore, it can be apparently said that the more shade trees or forest at the outdoor, the more effective in conditioning the outdoor space reducing the MRT and the useless SR for human activities in summertime.

• Journal of the Korean earth science society
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• v.40 no.2
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• pp.135-148
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• 2019

Although the technology for the observation of solar radiation is rapidly developing worldwide, in Korea the guidelines for comparing observations of solar radiation are only now under preparation. In this study, a procedure for intercomparison observations of solar radiation was established which accounts for meteorological and geographical conditions. The intercomparisons among observations by national reference pyranometers were carried out at the Asia Regional Radiation Center, Japan, in 2017. Recently, the result of the calibration of the reference pyranometer of the Korean Meteorological Administration (KMA) has been reported. Using the KMA pyranometer as a reference, comparisons between observations and calibrations were carried out for the standard (B to J) pyranometers of the KMA, and for the reference (A) and the standard pyranometers of the Gangneung-Wonju National University. The intercomparisons were carried out between October 24 and October 25, 2018. The sensitivity constants were adjusted according to the results of the data analysis performed on October 24. On October 25, a post-comparison observation was also performed, and the data of the participating pyranometers were verified. The sensitivity constants were calculated using only data corresponding to a solar radiation of $450.0W\;m^{-2}$ or higher. The B and I pyranometers exhibited a small error (${\pm}0.50W\;m^{-2}$), and the applied sensitivity constants were in the range $0.08-0.16{\mu}V(W\;m^{-2})^{-1}$. For the C pyranometer, the adjustment of the sensitivity constant was the largest, i.e., $-0.16{\mu}V(W\;m^{-2})^{-1}$. As a result, the nine candidate pyranometers could be calibrated with an average error of $0.06W\;m^{-2}$ (0.08%) with respect to the KMA reference, which falls within the allowed tolerance of ${\pm}1.00%$ (or ${\pm}4.50W\;m^{-2}$).

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1607-1622
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• 2022

The purpose of this study is to determine the actual performance of cool roof in preventing absorbed solar radiation. The spatial correlation between surface temperature and absorbed solar radiation is the method by which the performance of a cool roof can be understood and evaluated. The research area of this study is the vicinity of Jangyu Mugye-dong, Gimhae-si, Gyeongsangnam-do, where an actual cool roof is applied. FLIR Vue Pro R thermal infrared sensor, Micasense Red-Edge multi-spectral sensor and DJI H20T visible spectral sensor was used for aerial photography, with attached to the drone DJI Matrice 300 RTK. To perform the spatial correlation analysis, thermal infrared orthomosaics, absorbed solar radiation distribution maps were constructed, and land cover features of roof were extracted based on the drone aerial photographs. The temporal scope of this research ranged over 9 points of time at intervals of about 1 hour and 30 minutes from 7:15 to 19:15 on July 27, 2021. The correlation coefficient values of 0.550 for the normal roof and 0.387 for the cool roof were obtained on a daily average basis. However, at 11:30 and 13:00, when the Solar altitude was high on the date of analysis, the difference in correlation coefficient values between the normal roof and the cool roof was 0.022, 0.024, showing similar correlations. In other time series, the values of the correlation coefficient of the normal roof are about 0.1 higher than that of the cool roof. This study assessed and evaluated the potential of an actual cool roof to prevent solar radiation heating a rooftop through correlation comparison with a normal roof, which serves as a control group, by using high-resolution drone images. The results of this research can be used as reference data when local governments or communities seek to adopt strategies to eliminate the phenomenon of urban heat islands.

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.5
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• pp.75-83
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• 2019

In order to fulfill the obligation to voluntarily reduce greenhouse gas emissions under the Paris Climate Agreement, the proportion of coal and nuclear power generation is reduced worldwide and national efforts are being made to spread renewable energy including solar power generation. Korea also intends to increase the proportion of renewable energy generation to 30~35% by 2040 by introducing laws and regulations. In addition, while the country is trying to apply solar power generation to sidewalks and roads, there is no research related to it in Korea. Therefore, as a precedent study to develop solar power generation roads, solar power generation concrete blocks applicable to sidewalks and plazas were developed and the applicability was evaluated by constructing them on the site. As a result of indoor experiment, compressive strength was measured by 25.5~35.7MPa and flexural strength was measured by 5.1~10.5MPa, which showed that all domestic standards were satisfied. However, the higher the unit cement amount, the lower the strength was measured according to the mixing of the broken fine aggregate. The absorption rate was 5.7%, which satisfied the domestic standard of 7% or less. As a result of the freeze-thawing test, the reduction rate of the compressive strength after 100 cycles was up to 6.3%. As a result of measuring the settlement amount after construction, the maximum of 2.498mm was measured and irregular settlement occurred in the overall area, which is because the resolution of the sand layer was poor during construction. Maintenance techniques of sidewalk concrete block and solar panel need to be established more efficiently through long-term operation in the further.

• New & Renewable Energy
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• v.8 no.2
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• pp.14-23
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• 2012

The TMY (Typical Meteorological Year) for the solar energy study is generated using observation data with 22 solar sites from KMA (Korea Meteorological Administration) during 11 years (2000-2010). The meteorological data for calculation the TMY are used solar radiation, temperature, dew point temperature, wind speed and humidity data. And the TMY is calculated to apply the FS (Finkelstein and Schafer) statistics and RMSE (Root Mean Squared Error) methods. FS statistics performed with each point and each variable and then selected top five candidate TMM months with statistical analysis and normalization. Finally TMY is generated to select the highest TMM score with evaluation the average errors for the 22 whole points. The TMY data is represented average state and long time variations with 22 sites and meteorological data. When TMY validated with the 11-year daily solar radiation data, the correlation coefficient was about 0.40 and the highest value is 0.57 in April and the lowest value is 0.23 in May. Mean monthly solar radiation of TMY is 411.72 MJ which is 4 MJ higher than original data. Average correlation coefficient is 0.71, the lowest correlation is 0.43 in May and the highest correlation is 0.90 in January. Accumulated annual solar radiation by TMY have higher value in south coast and southwestern region and have relatively low in middle regions. And also, differences between TMY and 11-year mean of is distributed lower 100 MJ in Kyeongbuk, higher 200 MJ in Jeju and higher 125 MJ in Jeonbuk and Jeonnam, respectively.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.8
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• pp.977-983
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• 2013

Based on the consideration of the hourly patterns of the electricity power consumption, this study predicted the effectiveness of hybrid power generation system, which is composed with wind power generator and photovoltaic generator. And this case study is performed at Konrido, which is a affiliated island of Kyeongsangnam-do. As the results, it is obvious that it is not efficient to cover the whole electricity power consumption only with any single power generating system, because the hourly patterns of electricity power consumption, wind power generation and photovoltaic generation are quite different. And because the wind is being through almost 24 hours, it is also found out that wind power generating system with storage battery is the most efficient combination for this case study.

• Journal of Advanced Navigation Technology
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• v.23 no.6
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• pp.561-569
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• 2019

Solar photovoltaic can provide electrical energy with only radiation, and its use is expanding rapidly as a new energy source. This study predicts the short and long-term PV power generation using actual converter output data of photovoltaic system. The prediction algorithm uses multiple linear regression, support vector machine (SVM), and deep learning such as deep neural network (DNN) and long short-term memory (LSTM). In addition, three models are used according to the input and output structure of the weather element. Long-term forecasts are made monthly, seasonally and annually, and short-term forecasts are made for 7 days. As a result, the deep learning network is better in prediction accuracy than multiple linear regression and SVM. In addition, LSTM, which is a better model for time series prediction than DNN, is somewhat superior in terms of prediction accuracy. The experiment results according to the input and output structure appear Model 2 has less error than Model 1, and Model 3 has less error than Model 2.