• Journal of the Korean Association of Geographic Information Studies
• /
• v.17 no.3
• /
• pp.116-131
• /
• 2014

In this study, sunshine environment in an urban area is analyzed using a numerical model which considers sunshine-duration blocking by topography and buildings. The numerical model used in this study has an improvement in the algorithm detecting sunshine duration in the model domain. The main improvement in the algorithm is to detect sunshine duration using all the surfaces of any grid cell(the previous model uses the center of any grid cell). The improvement in the algorithm gives more accurate evaluation of sunshine duration at corner surfaces of buildings. Using the improvement model and geographic information system(GIS) data, sunshine environment is analysed at an building-congested area in Busan for a week in four seasons. The results show that sunshine duration can be much changed by apartment complexes, high-rise buildings, topography in the model domain.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2018.05a
• /
• pp.351-354
• /
• 2018

본 연구에서는 일 증발접시 증발량 모델링을 위한 다변량 적응 회귀 스플라인 (multivariate adaptive regression splines, MARS) 모델의 성능을 평가하였다. 모델 입력변수 집합은 부산 관측소 (기상청)로부터 수집된 기상자료를 활용하여 증발접시 증발량과의 상관성이 높은 변수들의 조합으로 구성되었으며, 일사량, 일조시간, 평균지상온도, 최대기온의 조합으로 구성된 세 가지 입력집합이 결정되었다. MARS 모델의 성능은 네 가지의 모델성능평가지표를 활용하여 정량적으로 산출되었으며, 그 결과를 인공신경망 (artificial neural network, ANN) 모델과 비교하였다. 입력변수로서 일사량 및 일조시간을 가지는 Set 1의 경우 MARS1 모델이 ANN1 모델보다 우수한 성능을 나타내었으며, Set 2 (일사량, 일조시간, 평균지상온도)의 경우 ANN2 모델, Set 3 (일사량, 일조시간, 평균지상온도, 최대기온)의 경우 MARS3 모델이 상대적으로 우수한 모델 성능을 나타내었다. 모든 분석 모델들을 비교하였을 때, MARS3, ANN2, ANN3, MARS2, MARS1, ANN1 모델의 순서로 우수한 모델 성능을 나타내었으며, 특히 MARS3 모델은 CE = 0.790, $r^2=0.800$, RMSE = 0.762, MAE = 0.587로서 가장 우수한 일 증발접시 증발량 모델링 성능을 나타내었다. 따라서 본 연구에서 적용한 MARS 모델은 지상관측 기상자료를 활용한 일 증발접시 증발량 모델링에서 효과적인 대안이 될 수 있을 것으로 판단된다.

• Journal of Advanced Navigation Technology
• /
• v.22 no.5
• /
• pp.478-484
• /
• 2018

This study predicts solar radiation, solar radiation, and solar power generation using hourly weather data such as temperature, precipitation, wind direction, wind speed, humidity, cloudiness, sunshine and solar radiation. I/O pattern in supervised learning is the most important factor in prediction, but it must be determined by repeated experiments because humans have to decide. This study proposed four input and output patterns for solar and sunrise prediction. In addition, we predicted solar power generation using the predicted solar and solar radiation data and power generation data of Youngam solar power plant in Jeollanamdo. As a experiment result, the model 4 showed the best prediction results in the sunshine and solar radiation prediction, and the RMSE of sunshine was 1.5 times and the sunshine RMSE was 3 times less than that of model 1. As a experiment result of solar power generation prediction, the best prediction result was obtained for model 4 as well as sunshine and solar radiation, and the RMSE was reduced by 2.7 times less than that of model 1.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.25 no.2
• /
• pp.165-175
• /
• 2007

Nowadays, architecture in urban areas is dominated by the goal of spanning wide spaces and creating openings large enough to distribute daylight to building interiors. Daylight availability of building in city strongly depends not only on the building's height but also on spaces between buildings. Recently numbers of disputes over the daylight availability are increasing in high density developed areas because residents' demand for pleasant residential environment is getting stronger. Therefore in this study we constructed the three-dimensional information of buildings using LiDAR data connected with digital map and then suggested conclusions by applying it to daylight availability analysis. This study presents an approach to judge accurately the violation of a right to enjoy sunshine by using altitude and azimuths of the sun, simulating three-dimensional urban space precisely, and classifying the total duration of sunshine and the continuous duration of sunshine each householder. We expect that local government performs precisely the confirmation and permission business about urban planning and design by advising this approach.

• Journal of Korean Society for Geospatial Information Science
• /
• v.24 no.3
• /
• pp.67-73
• /
• 2016

The present study evaluated the blocking effect of natural and artificial topography on sunshine duration in the southern coastal area of Haui-do. The geospatial data for the target area was constructed by geographic information system(GIS) data. Three-dimensional modeling based on solar azimuth and altitude angles was conducted for the assessment of sunshine environment. The sunshine area was evaluated over 80~90% of the target area in the daytime, especially in summer. The blocking effect of mountainous terrain on sunshine duration was presented at the northern residential area in the late afternoon. There was also the effect of artificial topography by construction of fill-up bank on sunshine environment at the southern residential area early in the morning and the south-western part of salt field in the late afternoon.

• Korean Journal of Remote Sensing
• /
• v.34 no.5
• /
• pp.749-762
• /
• 2018

In this study, the changes of the sunshine environment due to the construction of buildings were analyzed by season. Using a geographic information system (GIS) data, the topography and the buildings were constructed around Pukyong National University (PKNU) in Busan. The numerical model was performed for a week in each season, before and after the construction of buildings. Even before the construction of the high-rise building complex, the area of sunshine block is wide due to the apartment complex located in the southeast of the PKNU campus and the mountain in the south. After the construction, the sunshine-blocked area became wider after the sunrise and before the sunset. The area of sunshine block after 1 hour at sunrise increased by 1.60%, 1.50%, 1.58% and 1.36% in the vernal equinox, summer solstice, autumnal equinox and winter solstice, respectively. The building complex in the east (south) of the PKNU campus made shadow in more than 1,000 m (750 m) toward the west (east) just before the sunrise (sunset). Especially, the sunshine duration in PKNU campus decreased by 46.61%, 22.75%, 58.56%, and 11.31% in the vernal equinox, summer solstice, autumnal equinox and winter solstice, respectively. The analysis of the sunshine duration for a dormitory building showed that the construction of the building complex in the south of the PKNU campus reduced the sunshine area of the western (southern) wall of the dormitory by 30.91% (49.45%) for a winter week.

• Journal of Advanced Navigation Technology
• /
• v.22 no.3
• /
• pp.233-239
• /
• 2018

Since solar power generation is intermittent depending on weather conditions, it is necessary to predict the accurate generation amount of solar power to improve the efficiency and economical efficiency of solar power generation. This study proposes a short - term deep learning prediction model of solar power generation using meteorological data from Mokpo meteorological agency and generation data of Yeongam solar power plant. The meteorological agency forecasts weather factors such as temperature, precipitation, wind direction, wind speed, humidity, and cloudiness for three days. However, sunshine and solar radiation, the most important meteorological factors for forecasting solar power generation, are not predicted. The proposed model predicts solar radiation and solar radiation using forecast meteorological factors. The power generation was also forecasted by adding the forecasted solar and solar factors to the meteorological factors. The forecasted power generation of the proposed model is that the average RMSE and MAE of DNN are 0.177 and 0.095, and RNN is 0.116 and 0.067. Also, LSTM is the best result of 0.100 and 0.054. It is expected that this study will lead to better prediction results by combining various input.

• Journal of Korea Water Resources Association
• /
• v.52 no.12
• /
• pp.1033-1046
• /
• 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 Association of Geographic Information Studies
• /
• v.13 no.2
• /
• pp.146-156
• /
• 2010

The objective of this study was to improve the accuracy of calculation and estimation of solar radiation and duration of sunshine, which are the most important variables of photovoltaic power generation in deciding the location of photovoltaic facilities efficiently. With increasing interest in new and renewable energies, research on solar energy is also being conducted actively, but there have not been many studies on the location of photovoltaic facilities. Thus, this study calculated solar duration and solar radiation based on geographical factors, which have the most significant effect on solar energy in GIS environment, and corrected the results of analysis using diffuse radiation. Moreover, we performed ordinary kriging, a spatial statistical analysis method, for estimating values for parts deviating from the spatial resolution of input data, and used variogram, which can determine the spatial interrelation and continuity of data, in order to estimate accurate values. In the course, we compared the values of variogram factors and estimates from applicable variogram models, and selected the model with the lowest error rate. This method is considered helpful to accurate decision making on the location of photovoltaic facilities.

• Solar Energy
• /
• v.14 no.2
• /
• pp.17-28
• /
• 1994

It is necessary to estimate enpirical 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 propoed to evaluate them for certain areas. In this work a new corrlation has been made to predict the solar radiation for any areas over Korea by cululating 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 rdiation with average annual deviation of -4 to +2% from measured values.