• Korean Journal of Construction Engineering and Management
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• v.20 no.6
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• pp.126-131
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• 2019

The estimation of available solar energy at particular locations is critical to find and assess suitable locations of PV sites. The amount of PV power generation is however affected by various geographical factors (e.g., weather), which may make it difficult to identify the complex relationship between affecting factors and power outputs and to apply findings from one study to another in different locations. This study thus undertakes a regression analysis using data collected from 172 PV plants spatially distributed in Korea to identify critical weather conditions and estimate the potential power generation of PV systems. Such data also include solar radiation, precipitation, fine dust, humidity, temperature, cloud amount, sunshine duration, and wind speed. The estimated PV power generation is then compared to the actual PV power generation to evaluate prediction performance. As a result, the proposed model achieves a MAPE of 11.696(%) and an R-squred of 0.979. It is also found that the variables, excluding humidity, are all statistically significant in predicting the efficiency of PV power generation. According, this study may facilitate the understanding of what weather conditions can be considered and the estimation of PV power generation for evaluating and determining suitable locations of PV facilities.

• Solar Energy
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• v.10 no.1
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• pp.47-56
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• 1990

The aerodynamic performances of Darrieus wind turbine were studied through the wind tunnel model tests and its analytical aerodynamic streamtube model. Hence, analytical streamtube model which is based on momentum and blade element theory is considered and the formulated model was generalized in non-dimensional type to predict the aerodynamic characteristics of Darrieus wind turbine. The analytical model was justified through the wind tunnel model tests for several experimental conditions but in the limited rages. These satisfactory comparative studies between the wind tunnel tests and the analytical predictions can be utilized for the basic reliable design of Darrieus wind turbine.

• Journal of the Korean Solar Energy Society
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• v.34 no.5
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• pp.1-9
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• 2014

Daylight is very useful to control the indoor environment, and can save energy in buildings. So it is necessary to evaluate the daylighting performance of buildings. We proposed a simplified equation that can be used in the early stages of design. And we verified the equation by using the measured illuminance data from the 1/5 scale model. We compared the calculated indoor illuminances and measured illuminance including Daylight Factors of scale model in order to verify the applicability of the simplified equation, and proved the analyzed values are acceptable. When we have a target value of the Daylight Factor, we just have to determine the window area, transmittance of the glazing system, and indoor surface reflectance, then can achieve it with this simplified equation.

• Journal of the Korean Solar Energy Society
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• v.36 no.3
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• pp.33-43
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• 2016

Daylight is an important factor which influences building energy efficiency and visual comfort for occupants. It is important to predict precise sky luminance at the early stages of design to reduce light energy in the building. This study predicted sky luminance distributions of standard sky model(CIE overcast sky, CIE clear sky) that was provided from the CIE(Commission internationale de $l^{\prime}{\acute{e}}clairage$). Afterward, result of sky luminance was compared and verified with simulation value of Radiance program. From the CIE overcast sky, zenith and horizon ratio is about 3:1. From the CIE clear sky, luminance value gets most high value around the sun. On the other hand, luminance value is the lowest in the opposite direction of the sun when angle is $90^{\circ}$ between the sun and sky element. As a result of comparing the calculation results with Radiance program, sky luminance prediction error rate is 0.4~1.3% when it is CIE overcast sky. Also, sky luminance prediction error rate is 0.3~1.5% when it is CIE clear sky. When compared with the results of radiance simulation, it was evaluated as fairly accurate.

• Journal of the Korean Solar Energy Society
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• v.33 no.3
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• pp.114-123
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• 2013

In these days, most of the office buildings are being required to save energy for maintenance. lighting system constitutes 20% to 30% of the total annual electrical energy consumption in office buildings. As an energy saving strategy for lighting system, dimming control system based on illuminance sensors came into use. But the system is accompanied with many illuminance sensors to control lighting and needs a lot of initial investment. In this study, the prediction equation for indoor daylighting illuminance distribution is proposed through the review for conventional research results and field measurements. The proposed equation was verified by the comparison between predicted results and field measurement results. The developed prediction equation for daylighting can be used to control the indoor illuminance level with the limited sensor when dimming control system is operated.

• Electronics and Telecommunications Trends
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• v.23 no.6
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• pp.70-80
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• 2008

화석연료 사용에 따른 클린에너지 및 "carbon footprint" 절감을 위해 태양광발전과 같은 직접적인 에너지 대안기술에서부터 조명 및 표시소자로서의 LED 고효율화 기술, 레이저를 이용한 비접촉성, 고속, 초정밀 측정 기술을 바탕으로 하는 공정 관리기술, 그리고 오염원검출 및 추출기술 관련 등 그린 포토닉스 기술 활용에 관심이 급증하고 있다. OIDA 보고 2010년경 100억 달러 수준의 부품시장이 형성될 것으로 예측되는 그린 포토닉스 분야의 기술개발 동향을 설명한다.

• 한국태양에너지학회:학술대회논문집
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• 2009.04a
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• pp.184-189
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• 2009

In order to improve the operation of energy systems, it is necessary for the urban communities to have reliable optimization routines, both computerized and manual, implemented in their organizations. However, before a production plan for the energy system units can be constructed, a prediction of the energy systems first needs to be determined. So, several methodologies have been proposed for energy demand prediction, but due to uncertainties in urban community, many of them will fail in practice. The main topic of this paper has been the development of a method for energy demand prediction at urban community. Energy demand prediction is important input parameters to plan for the energy planing. This paper presents a energy demand prediction method which estimates heat and electricity for various building categories. The method has been based on artificial neural networks(ANN). The advantage of ANN with respect to the other method is their ability of modeling a multivariable problem given by the complex relationships between the variables. Also, the ANN can extract the relationships among these variables by means of learning with training data. In this paper, the ANN have been applied in oder to correlate weather conditions, calendar data, schedules, etc. Space heating, cooling, hot water and HVAC electricity can be predicted using this method. This method can produce 10% of errors hourly load profile from individual building to urban community.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.620-626
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• 2020

This research propose and simulate a solar power generation system monitoring system based on Modbus TCP communication using RaspberryPi, an IOT equipment, as a master and an inverter as a slave. In this model, various sensors are added to the RaspberryPi to add necessary information for monitoring solar power plants, and power generation prediction and monitoring information are transmitted to the smart phone through real-time power generation prediction. In addition, information that is continuously generated by the solar power plant is built on the server as big data, and a deep learning model for predicting power generation is trained and updated. As a result of the study, stable communication was possible based on Modbus TCP with the Raspberry Pi in the inverter, and real-time prediction was possible with the deep learning model learned in the Raspberry Pi. The server was able to train various deep learning models with big data, and it was confirmed that LSTM showed the best error with a learning error of 0.0069, a test error of 0.0075, and an RMSE of 0.0866. This model suggested that it is possible to implement a real-time monitoring system that is simpler, more convenient, and can predict the amount of power generation for inverters of various manufacturers.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.1
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• pp.33-39
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• 2007

This paper is aimed at the development of a software that predicts the surface temperature profiles of three-dimensional objects on the ground by considering the spectral solar radiation through the atmosphere. The spectral solar radiation through the atmosphere is modeled by using the well-known LOWTRAN7 code which analyzes the detailed spectral transmission characteristics by considering the atmospheric gas layers. In this paper, the transient temperature distribution over a cylinder is calculated by using the semi-implicit method. The spectral radiative surface properties such as the absorptivity and emissivity of the objects are used to model the effects of the solar irradiation and the surface emission. Both the detailed spectral modeling and the simple total modeling for the solar radiation absorption show fairly good agreement with each other by showing less than 3% difference in surface temperature.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.5
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• pp.1079-1085
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• 2012

Many researchers worldwide have been making a lot of effort to find sustainable clean energy source to replace the current fossil fuels. However, solar energy is considered as the ultimate energy solution to supply the world total power consumption. Light can be used for lighting, heating, wired and wireless communications, etc. Moreover, even light-driven motors which can directly convert optical energy into kinetic energy are studied recently. In this paper, we analyze optical energy delivery through multi-core optical fibers. Our estimation shows that an optical power of 2 kW can be transmitted through a multi-core fiber and an optical power of >10 MW can be transmitted through a bundle of optical fibers with a diameter of several centimeters. It seems competitive compared with the electric power delivery through a copper cable.