• Transactions of the Korean Society of Mechanical Engineers B
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• v.37 no.4
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• pp.331-341
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• 2013

In a solar domestic hot water (SDHW) system, solar energy is collected using collector panels, transferred to a circulating heat transfer fluid (brine), and eventually stored in a thermal storage tank (TST) as hot water. In this study, a computational fluid dynamics (CFD) model was developed to predict the solar thermal energy storage in a hybrid-type TST equipped with a helical jacket heater (mantle heat exchanger) and an immersed spiral coil heater. The helical jacket heater, which is the brine flow path attached to the side wall of a TST, has advantages including simple system design, low brine flow rate, and enhanced thermal stratification. In addition, the spiral coil heater further enhances the thermal performance and thermal stratification of the TST. The developed model was validated by the good agreement between the CFD results and the experimental results performed with the hybrid-type TST in SDHW settings.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.283-290
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• 2020

In this study, a floater was developed for a frame-type solar power plant. The floater supports the frame and the solar panels. A finite element analysis was performed to design its shape and thickness, and the floater was manufactured by a rotational molding method using linear low-density polyethylene. It was found that the floater did not cause collapse and it maintained its stiffness even at 4 times the maximum load of 322.7 kgf. To perform a long-term compression test, a weight-type load application device that uses gravity was designed and manufactured. The amount of compressive deformation was measured for 7 days, and a long-term deformation equation was obtained. Even under small loads, continuous deformation was observed. However, the 10-year deformation amount for a constant load of 100 kgf was predicted to be small at about 4.64 mm. As a result, it was found that the developed floater could be used in a solar power plant on a body of water.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.608-614
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• 2018

In addition to the diffusion of ICT technology, various protocols of short range wireless communication technology are being applied for efficient information operation. However, due to limitations of short-range wireless communication, communication is not smooth in places where frequency environment is poor, such as frequency confusion and warehouse type factory. When an alternative is needed. The development of LED technology and expansion of infrastructure through LED based visible light communication is attracting attention as an alternative and spreading the usage in wide range now a days. In addition, the infrastructure has been expanded with solar panels in response to the development of smarthome built-in with renewable energy. In this situation, visible light communication using PD has been limitedly applied in a near environment where the receiving angle of the PD and the ambient light ensure the LoS and the influence of the ambient light is small. In order to solve this problem, we have implemented visible light communication using LED lighting with large current infrastructure and solar panel with large receiving area, and proposed a circuit for restoring accurate data even in ambient light. Through this study results, it is expected that visible light communication can be more widely used and this result used as the base data for visible light communication research using the solar panel as the receiver.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.141-148
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• 2021

Agrivoltaic systems, also called solar sharing, stated from an idea that utilizes sunlight above the light saturation point of crops for power generation using solar panels. It is expected that agrivoltaic systems can realize climate smart agriculture by reducing evapotranspiration and methane emission due to the reduction of incident solar radiation and the consequent surface cooling effect and bring additional income to farms through solar power generation. In this study, to evaluate that agrivoltaic systems are suitable for realization of climate smart agriculture, we conducted agro-environmental observations (i.e., downward/upward shortwave/longwave radiations, air temperature, relative humidity, water temperature, soil temperature, and wind speed) in a rice paddy under an agrivoltaic system and compared with the environment outside the system using automated meteorological observing systems (AMOS). During the observation period, the spatially averaged incoming solar radiation under the agrivoltaic system was about 70% of that in the open paddy field, and clear differences in the soil and water temperatures between the paddy field under the agrivoltaic system and the open paddy field were confirmed, although the air temperatures were similar. It is required in the near future to confirm whether such environmental differences lead to a reduction in water consumption and greenhouse gas emissions by flux measurements.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.12
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• pp.1216-1221
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• 2008

A low earth orbit satellite with a fixed solar array always has a sun-pointing attitude during daylight, and changes into a nadir-pointing attitude for a imaging mission. Since external heating sources to the satellite panels are Earth　irradiation and Albedo during most of daylight in a sun-pointing attitude, the thermal environment condition is relatively stable. However, direct sunlight which is the greatest environmental heating has an affect on the satellite panels during a mission period (10% of one orbit) in a nadir-pointing attitude. In satellite thermal design, thermal effects of a nadir-pointing mission attitude due to this thermal environment change need to be evaluated although the duration of a nadir-pointing attitude is short. Therefore, a nadir-pointing attitude during a mission is incorporated into thermal model and by the thermal analysis result, thermal effects on the satellite are investigated.

• Korean Journal of Remote Sensing
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• v.40 no.3
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• pp.257-268
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• 2024

Drone-mounted hyperspectral sensors (DHSs) have revolutionized remote sensing in agriculture by offering a cost-effective and flexible platform for high-resolution spectral data acquisition. Their ability to capture data at low altitudes minimizes atmospheric interference, enhancing their utility in agricultural monitoring and management. This study focused on addressing the challenges of radiometric and geometric distortions in preprocessing drone-acquired hyperspectral data. Radiometric correction, using the empirical line method (ELM) and spectral reference panels, effectively removed sensor noise and variations in solar irradiance, resulting in accurate surface reflectance values. Notably, the ELM correction improved reflectance for measured reference panels by 5-55%, resulting in a more uniform spectral profile across wavelengths, further validated by high correlations (0.97-0.99), despite minor deviations observed at specific wavelengths for some reflectors. Geometric correction, utilizing a rubber sheet transformation with ground control points, successfully rectified distortions caused by sensor orientation and flight path variations, ensuring accurate spatial representation within the image. The effectiveness of geometric correction was assessed using root mean square error(RMSE) analysis, revealing minimal errors in both east-west(0.00 to 0.081 m) and north-south directions(0.00 to 0.076 m).The overall position RMSE of 0.031 meters across 100 points demonstrates high geometric accuracy, exceeding industry standards. Additionally, image mosaicking was performed to create a comprehensive representation of the study area. These results demonstrate the effectiveness of the applied preprocessing techniques and highlight the potential of DHSs for precise crop health monitoring and management in smart agriculture. However, further research is needed to address challenges related to data dimensionality, sensor calibration, and reference data availability, as well as exploring alternative correction methods and evaluating their performance in diverse environmental conditions to enhance the robustness and applicability of hyperspectral data processing in agriculture.

• 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.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1693-1705
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• 2023

Rural areas, which account for about 90% of the country's land area, are increasing in importance and value as a space that performs various public functions. However, facilities that adversely affect residents' lives, such as livestock facilities, factories, and solar panels, are being built indiscriminately near residential areas, damaging the rural environment and landscape and lowering the quality of residents' lives. In order to prevent disorderly development in rural areas and manage rural space in a planned manner, detection and monitoring of hazardous facilities in rural areas is necessary. Data can be acquired through satellite imagery, which can be acquired periodically and provide information on the entire region. Effective detection is possible by utilizing image-based deep learning techniques using convolutional neural networks. Therefore, U-Net model, which shows high performance in semantic segmentation, was used to classify potentially hazardous facilities in rural areas. In this study, KOMPSAT ortho-mosaic optical imagery provided by the Korea Aerospace Research Institute in 2020 with a spatial resolution of 0.7 meters was used, and AI training data for livestock facilities, factories, and solar panels were produced by hand for training and inference. After training with U-Net, pixel accuracy of 0.9739 and mean Intersection over Union (mIoU) of 0.7025 were achieved. The results of this study can be used for monitoring hazardous facilities in rural areas and are expected to be used as basis for rural planning.

• The Korean Journal of Applied Statistics
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• v.36 no.1
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• pp.49-62
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• 2023

Solar energy, which is rapidly increasing in proportion, is being continuously developed and invested. As the installation of new and renewable energy policy green new deal and home solar panels increases, the supply of solar energy in Korea is gradually expanding, and research on accurate demand prediction of power generation is actively underway. In addition, the importance of solar radiation prediction was identified in that solar radiation prediction is acting as a factor that most influences power generation demand prediction. In addition, this study can confirm the biggest difference in that it attempted to predict solar radiation using medium-term forecast weather data not used in previous studies. In this paper, we combined the multi-linear regression model, KNN, random fores, and SVR model and the clustering technique, K-means, to predict solar radiation by hour, by calculating the probability density function for each cluster. Before using medium-term forecast data, mean absolute error (MAE) and root mean squared error (RMSE) were used as indicators to compare model prediction results. The data were converted into daily data according to the medium-term forecast data format from March 1, 2017 to February 28, 2022. As a result of comparing the predictive performance of the model, the method showed the best performance by predicting daily solar radiation with random forest, classifying dates with similar climate factors, and calculating the probability density function of solar radiation by cluster. In addition, when the prediction results were checked after fitting the model to the medium-term forecast data using this methodology, it was confirmed that the prediction error increased by date. This seems to be due to a prediction error in the mid-term forecast weather data. In future studies, among the weather factors that can be used in the mid-term forecast data, studies that add exogenous variables such as precipitation or apply time series clustering techniques should be conducted.

• International Journal of Advanced Culture Technology
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• v.3 no.1
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• pp.120-128
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• 2015

In this paper, Residential roof top photovoltaic system with 9.9 kW design is proposed. The system composed of 200 Watts solar array 33 panels connecting in series 10 strings and parallels 3 strings which have maximum voltage and current are 350 V and 23.8 A. The 10 kW sinusoidal grid-connected inverter with window voltage about 270-350 is selected to convert and transfer DC Power to AC Power at PCC (Point of Common Coupling) of power system following to utility standard. However the impact of fluctuation and uncertainty of weather condition of PV may decrease the voltage stability and voltage collapse of power system. In order to solve this problem the energy storage such 120 V 1200 Ah battery bank and 30 kVAR capacitor are designed for voltage stability control. The other expensed for installing the system such battery charger, cable, accessories and maintenance cost are concerned. The economic analysis by using investment from money loan with interest about 7% and use own money which loss income of deposit about 3% are calculated as 671,844 and 547,044 for PV system with energy storage and non energy storage respectively. The solar energy from PV is about 101,616 Bath per year which evaluated by using the value of $5kWh/m^2/day$ from average peak sun hour (PSH) of the Thailand and 6.96 Bath/kWh of Feed in Tariff Incentive. The payback periods of four scenarios are proposed follow as i) PV system with energy storage and use loan money is 15 years ii) PV system with no energy storage and use loan money is 10 years iii) PV system with energy storage and use deposit money is 9 years iv) PV system with energy storage and use deposit money is 7 years. In addition, the other scenarios of economic analysis such no FIT support and other type of economic analysis such NPV and IRR are proposed in this paper.