• Journal of The Korean Astronomical Society
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• v.36 no.spc1
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• pp.83-91
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• 2003

There are terrestrial signatures of the solar activity cycle in ice core data (Ram & Stoltz 1999), but the variations in the sun's irradiance over the cycle seem too small to account for the signature (Lean 1997; Goode & Dziembowski 2003). Thus, one would expect that the signature must arise from an indirect effect(s) of solar activity. Such an indirect effect would be expected to manifest itself in the earth's reflectance. Further, the earth's climate depends directly on the albedo. Continuous observations of the earthshine have been carried out from Big Bear Solar Observatory since December 1998, with some more sporadic measurements made during the years 1994 and 1995. We have determined the annual albedos both from our observations and from simulations utilizing the Earth Radiation Budget Experiment (ERBE) scene model and various datasets for the cloud cover, as well as snow and ice cover. With these, we look for inter-annual and longer-term changes in the earth's total reflectance, or Bond albedo. We find that both our observations and simulations indicate that the albedo was significantly higher during 1994-1995 (activity minimum) than for the more recent period covering 1999-2001 (activity maximum). However, the sizes of the changes seem somewhat discrepant. Possible indirect solar influences on the earth's Bond albedo are discussed to emphasize that our earthshine data are already sufficiently precise to detect, if they occur, any meaningful changes in the earth's reflectance. Still greater precision will occur as we expand our single site observations to a global network.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.2
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• pp.134-140
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• 2021

Global solar radiation consists of direct and diffuse radiations. Both components are necessary for not only atmospheric science and solar energy domains but also agricultural applications. In this study, the data of direct and diffuse radiations are uploaded to Github. It was observed in Naju during May 2019 to November 2020. Using this data, the previous empirical equations using the relation between clearness index and diffuse ratio were validated. All coefficients of determination (R²) and RMSE were similar as 0.79~0.80 and 0.13~0.15. However, to get the lower RMSE, other non-linear approaches will be required with more observation data.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.358-365
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• 2019

An agrivoltaic systems (AVS) is mixed systems associating photovoltaic panels (PVPs) and crop cultivation at the same time on the given land area. It is receiving attention to improve rural economy. However, it is likely that, the crop yield should be decreased due to the reduced absorption of solar radiation by leaves. Thus, before popularizing the AVS, it is necessary to comprehend the degree of shading by PVPs in AVS. In this study, the change of radiation condition under AVS mimic shading net was investigated. The minimum and maximum of difference of photosynthetically active radiation (PAR) between under and outside shading net were 3.03 mol/㎡/day on a cloudy day and 17.08 mol/㎡/day on a sunny day. This difference decreased when the ratio of diffuse irradiance to global irradiance increased. Such a shading effect resulted in the increase of rice height and decrease of rice tillering.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.3
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• pp.299-305
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• 2015

Global environmental concerns and the ever increasing need of energy, coupled with steady progress in renewable energy technologies, are opening up new opportunities for utilization of renewable energy resources. Distributed electricity generation is a suitable option for sustainable development thanks to the load management benefits and the opportunity to provide electricity to remote areas. Solar energy being easy to harness, non-polluting and never ending is one of the best renewable energy sources for electricity generation in present and future time. Due to the random and intermittent nature of solar source, PV plants require the adoption of an energy storage and management system to compensate fluctuations and to meet the energy demand during night hours. This paper presents an efficient, economic and technical model for the design of a MPPT based grid connected PV with battery storage and management system. This system satisfies the energy demand through the PV based battery energy storage system. The aim is to present PV-BES system design and management strategy to maximize the system performance and economic profitability. PV-BES (photovoltaic based battery energy storage) system is operated in different modes to verify the system feasibility. In case of excess energy (mode 1), Li-ion batteries are charged using CC-CV mechanism effectively controlled by fuzzy logic based PID control system whereas during the time of insufficient power from PV system (mode 2), batteries are used as backup to compensate the power shortage at load and likewise other modes for different scenarios. This operational mode change in PV-BES system is implemented by State flow chart technique based on SOC, DC bus voltages and solar Irradiance. Performance of the proposed PV-BES system is verified by some simulations study. Simulation results showed that proposed system can overcome the disturbance of external environmental changes, and controls the energy flow in efficient and economical way.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.4
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• pp.185-191
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• 2009

Few studies have attempted to analyze variations of daily maximum temperature in the summer whereas many studies have analyzed warming trends in other seasons with respect to greenhouse gases or urban heat islands. We analyzed daily maximum temperature data for the summer season (June to August) at 18 locations in South Korea from 1983 to 2007. Compared to the climatic normal (from 1971 to 2000), an average increase of $0.1^{\circ}C$ was found for the summer daily maximum temperature along with an increase of $0.61MJ\;m^{-2}$ in daily solar radiation. Approximately 65% of the annual variations of the summer daily maximum temperature could be explained by the solar radiance alone. Higher atmospheric transmittance due to lower aerosol concentration (especially of sulfur dioxide) is believed to have caused the recent increase in solar irradiance. Daily maximum temperature of the summer is expected to keep rising if the clean air activities are maintained in the future.

• Atmosphere
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• v.32 no.4
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• pp.277-295
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• 2022

The global weather prediction model, Korean Integrated Model (KIM), has been in operation since April 2020 by the Korea Meteorological Administration. This study assessed the performance of heat waves (HWs) in Korea in 2020. Case experiments during 2018-2020 were conducted to support the reliability of assessment, and the factors which affect predictability of the HWs were analyzed. Simulated expansion and retreat of the Tibetan High and North Pacific High during the 2020 HW had a good agreement with the analysis. However, the model showed significant cold biases in the maximum surface temperature. It was found that the temperature bias was highly related to underestimation of downward shortwave radiation at surface, which was linked to cloudiness. KIM tended to overestimate nighttime clouds that delayed the dissipation of cloud in the morning, which affected the shortage of downward solar radiation. The vertical profiles of temperature and moisture showed that cold bias and trapped moisture in the lower atmosphere produce favorable conditions for cloud formation over the Yellow Sea, which affected overestimation of cloud in downwind land. Sensitivity test was performed to reduce model bias, which was done by modulating moisture mixing parameter in the boundary layer scheme. Results indicated that the daytime temperature errors were reduced by increase in surface solar irradiance with enhanced cloud dissipation. This study suggested that not only the synoptic features but also the accuracy of low-level temperature and moisture condition played an important role in predicting the maximum temperature during the HWs in medium-range forecasts.

• Current Photovoltaic Research
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• v.10 no.3
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• pp.77-83
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• 2022

Renewable energy is receiving attention again as a way to realize carbon neutrality to overcome the climate change crisis. Among renewable energy sources, the installation of Photovoltaic is continuously increasing, and as of 2020, the global cumulative installation amount is about 590 GW and the domestic cumulative installation amount is about 17 GW. Accordingly, O&M technology that can analyze the power generation and fault diagnose about PV plants the is required. In this paper, a study was conducted to diagnose fault using I-V curves of PV strings and deep learning. In order to collect the fault I-V curves for learning in the deep learning, faults were simulated. It is partial shade and voltage mismatch, and I-V curves were measured on a sunny day. A two-step data pre-processing technique was applied to minimize variations depending on PV string capacity, irradiance, and PV module temperature, and this was used for learning and validation of deep learning. From the results of the study, it was confirmed that the PV fault diagnosis using I-V curves and deep learning is possible.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.5
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• pp.415-426
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• 2015

Solar radiation under a clear sky is a important factor in the process by which meteorological satellite images are converted into solar radiation maps, and the quality of estimations depends on the accuracy of clear sky models. Therefore, it is important to select models appropriate to the purpose of the study and the study area. In this instance, complex models were applied using Linke turbidity, including ESRA, Dumortier, and MODTRAN, in addition to simple models such as Bourges and PdBV, which consider only the solar elevation angles. The presence of cloud was identified using the Communication, Ocean, and Meteorological Satellite and the Meteorological imager (COMS MI), and reference data were then selected. In order to calculate the accuracy of the clear sky models, the concepts of RMSE and MBE were applied. The results show that Bourges and PdBV produced low RMSE values, while PdBV had relatively steady RMSE values. Also, simple models tend to underestimate global solar irradiation during spring and early summer. Conversely, in the winter season, complex methods often overestimate irradiation. In future work, the cause of overestimation and other factors will be analyzed and the clear sky models will be adjusted in order to make them suitable for the Korean Peninsula.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.2
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• pp.511-520
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• 2020

Owing to global warming, heat waves have become stronger in the summer, and research on improving the thermal environment of green spaces, such as urban parks, is being conducted. On the other hand, studies on improving the urban thermal environment, which is changing due to the greening pattern and the intensity of the wind, are still insufficient. This study analyzed the temperature of the green spaces on campus to understand the factors affecting the temperature changes. After investigating the covering condition and planting form of the site, factors, such as temperature, humidity, wind direction, wind speed, and illuminance, were measured. The most influential factors on the temperature distribution are evapotranspiration and wind - induced heat transfer. The other major factors affecting the temperature change were the type of cover, wind velocity/wind direction, type of planting, shade / solar irradiance. In the type of cover, the plant was classified as low temperature, and the asphalt pavement was classified as high temperature. In wind speed, instantaneous temperature was reduced by 1.2 ℃ in southern wind, 0.7 ℃ in the westerly wind, 0.4 ℃ in the north wind and 0.5 ℃ in the east wind when a wind of 3.5m/s or more was blown.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.2
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• pp.74-87
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• 2016

Potato phenology, growth, and yield are projected to be highly affected by global warming in the future. The objective of this study was to examine the responses of potato growth and yield to environmental elements like temperature, solar radiation, and daylength. Planting date experiments under open field condition were conducted using three cultivars differing in maturity group (Irish Cobbler and Superior as early; Atlantic as mid-late maturing) at eight different planting dates. In addition, elevated temperature experiment was conducted in four plastic houses controlled to target temperatures of ambient temperature (AT), $AT+1.5^{\circ}C$, $AT+3^{\circ}C$, and $AT+5^{\circ}C$ using cv. Superior. Tuber initiation onset was found to be hastened curve-linearly with increasing temperature, showing optimum temperature around $22-24^{\circ}C$, while delayed by longer photoperiod and lower solar radiation in Superior and Atlantic. In the planting date experiments where the average temperature is near optimal and solar radiation, rainfall, pest, and disease are not limiting factor for tuber yield, the most important determinant was growth duration, which is limited by the beginning of rainy season in summer and frost in the late fall. Yield tended to increase along with delayed tuber initiation. Within the optimum temperature range ($17^{\circ}-22^{\circ}C$), larger diurnal range of temperature increased the tuber yield. In an elevated temperature treatment of $AT+5.0^{\circ}C$, plants failed to form tubers as affected by high temperature, low irradiance, and long daylength. Tuber number at early growth stage was reduced by higher temperature, resulting in the decrease of assimilates allocated to tuber and the reduction of average tuber weight. Stem growth was enhanced by elevated temperature at the expense of tuber growth. Consequently, tuber yield decreased with elevated temperature above ambient and drop to almost nil at $AT+5.0^{\circ}C$.