• Proceedings of the KIPE Conference
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• 2011.07a
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• pp.95-96
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• 2011

최근 자동차와 같이 움직이는 장치에 부착된 태양광 모듈에 대한 연구가 활발히 이루어지고 있다. 이러한 이동식 태양광모듈 장치는 건물이나 기타 수목 그림자에 수시로 노출되는바 그에 따른 효율감소가 발생한다. 이에 본 논문은 어떠한 환경에서도 Maximum Power를 빠른 속도로 찾아 효율감소를 저감하는 방안을 강구하고자 한다. 제안된 알고리즘은 일사량에 따른 태양광 모듈의 V I곡선에서 MPPT를 함에 V 인자와 I 인자로 구분하여 트래킹 타임 스텝을 가변 설정하여 기존의 방식보다 우수한 동특성을 갖는 알고리즘을 제안한다. 본 논문에서는 시뮬레이션을 통해 제안된 구조의 타당성과 우수성을 검증하였다.

• 한국신재생에너지학회:학술대회논문집
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• 2011.05a
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• pp.108-108
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• 2011

공동주택에서 2025년 정부가 추진하고 있는 Zero Energy 건축물 구현과 친환경에 대한 탄소배출 저감 문제로 재생에너지 생산시스템의 추가 적용은 반드시 필요하다. 따라서 공동주택 적용 및 활용성을 높일 수 있는 BIPV시스템 개발을 통하여 설치면적 확보와 세대 활용성을 높일 수 있도록 하는 것이 필요하다. 특히 거실 창호의 경우 주방향이 남향, 남동 또는 남서향으로 배치되어 태양광을 적용하기에 적합한 특성을 가지고 있다. 그러나 창호는 건물외피의 역할과 재실자가 조망과 정보취득을 얻을 수 있는 중요한 통로가 되기 때문에 단열 문제나 시야 차폐의 문제는 발생하지는 않도록 하는 것이 필요하다. 본 연구에서는 a-si타입 모듈 2개를 10% 투과율로 Bsck Coating 색상을 달리한 모듈과 c-si BIPV 모듈을 커튼월 창호시스템으로 개발, 일반 2중 창호시스템과 비교 평가를 위해 실제 Test bed 건물에 시공하여 시환경 및 실내 창측면 온도변화 측정 분석을 진행하였다. 현재 국내외 출시되고 있는 a-si see through 모듈은 10~30%의 투과율로 창 마감재로 대체가 가능하나 건축 환경(시환경,열환경)에 대한 분석은 전무한 상태이다. 본 연구에서는 시환경과 창유리면의 열 부하, 자외선, 적외선 차폐 및 가시광선의 투과율에 대한 평가와 Back Coating에 따른 색온도 평가를 통해서 a-si BIPV의 공동주택 세대 발코니 창호 적합성에 대한 검토를 진행하였다. 연구결과는 아래와 같다. ${\bullet}$ 실내조도는 청천공 정오기준 가시성 확보 모듈의 경우 2,300 ~ 3,500lx를 나타내고 있어 대비 현상이나 창측의 급격한 조도 변화가 적은 시환경 구축이 가능 ${\bullet}$ 12시경 휘도는 창측면, 실내 벽체, 코너 바닥면을 대상으로 a-si BIPV 모듈을 적용한 경우 휘도비가 12:1로 KS나 IESNA의 광원과 근접면의 비 20:1 범위에 모두 존재, 적합한 것으로 분석되었으나 c-si의 경우는 그림자로 인한 대비 현상이 발생, 작업 시환경 문제 발생. ${\bullet}$ 이중시스템 창호와 비교하여 단열 성능 떨어짐. 발전시간대 창유리 면 온도 상승 으로 하절기 냉방부하 증가. ${\bullet}$ 자외선은 100% 가까이 차단, 적외선은 13~42%만 투과되고 가시광선은 13% 투과율을 나타내어 일반 창에 칼라 코팅을 적용하는 것과 유사한 경향을 나타냄.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.77-83
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• 2020

The technologies of 3D spatial information, such as Smart City and Digital Twins, are developing rapidly for managing land and solving urban problems scientifically. In this construction of 3D spatial information, an object using aerial photo images is built as a digital DB. Realistically, the task of extracting a texturing image, which is an actual image of the object wall, and attaching an image to the object wall are important. On the other hand, occluded areas occur in the texturing image. In this study, the ResNet algorithm in deep learning technologies was tested to solve these problems. A dataset was constructed, and the street tree was detected using the ResNet algorithm. The ability of the ResNet algorithm to detect the street tree was dependent on the brightness of the image. The ResNet algorithm can detect the street tree in an image with side and inclination angles.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.655-661
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• 2020

SGM (Semi Global Matching) can be used to find all the conjugate points between stereo images. Therefore, it enables high-density DSM (Digital Surface Model) production from high-resolution satellite images. However, water, shadows, and occlusion areas cause mismatching of the surrounding points in this method. Particularly, in buildings with large-parallax and elongated-shapes such as a Korean style apartment, it is difficult to reconstruct the 3D building even if the SGM method is applied to a high-resolution 50cm satellite image. This study proposed and performed the SGM technique with a classified image and an edge image from the IKONOS-2 satellite stereo-image with a 1m resolution to produce DSM. It was compared with the DSMs from the general SGM and the high-density ABM (Area Based Matching) matching of ERDAS software. The results of the apartment DSM by the proposed method were the best in the test area. As a result, despite the image having a resolution of 1m, the outline of the building DSM could be expressed more clearly than the existing method.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.1
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• pp.1-5
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• 2013

The number of pedestrians is considered essential information which can be used to control a person who makes a entrance or a exit into a building. The number of pedestrians, also, can be used to help to manage pedestrian traffic and the volume of pedestrian flow within the building. Due to the fact there is incorrect detection by occluded, shadows, and illumination, however, difficulty can arise in existing system which is for detection and counts of a person who makes a entrance or a exit into a building. In this paper, it is minimized that the change of illumination and the effect of shadow through the transmitted image from camera which is created and processed with great adaptability. The accuracy of the calculations can be increase as well by using Kalman Filter and Mean-Shift Algorithm in order to avoid overlapped counts. As a result of the test, it is proved that the count method that shows the accuracy of 95.4% should be effective for detection and counts.

• Korean Journal of Remote Sensing
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• v.18 no.4
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• pp.221-231
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• 2002

In this study we applied a DEM generation algorithm developed in-house to satellite images at various resolution and discussed the results. We tested SPOT images at l0m resolution, EOC images at 6.6m and IKONOS images at 1m resolution. These images include the same urban area in Daejeon city. For camera model, we used Gupta & Hartley's(1997) DLT model for all three image sets. We carried out accuracy assessment using USGS DTED for SPOT and EOC and 23 check points for IKONOS. The assessment showed that SPOT DEM had about 38m RMS error, EOC DEM 12m RMS error and IKONOS DEM 6.5m RMS error. In terms of image resolution, SPOT and EOC DEM error corresponds to 2∼4 pixels where as IKONOS DEM error 6∼7pixels. IKONOS DEM contains more errors in pixels. However, in IKONOS DEM, individual buildings, apartments and major roads are identifiable. All three DEMs contained errors due to height discontinuity, occlusion and shadow. These experiments show that our algorithm can generate urban DEM from 1m resolution and that, however, we need to improve the algorithm to minimize effects of occlusion and building shadows on DEMs.

• Korean Chemical Engineering Research
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• v.58 no.3
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• pp.416-423
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• 2020

Majority of over 100 kW capacity photo voltaic (PV) power generation system was constructed on the plate ground of soil. Rarely PV system installed on concrete or building but it usually be under 25 kW capacity. On the soil ground the weeds growen up and it's shadow influenced to decrease of amount of PV power generation. This work analysis the weeds shadow's effect to decrease of PV power generation with 100 kW capacity of real PV power generation system in Yeungnam University, Finally the weed shadow"s influence value through the real field monitoring Data is suggested for give a standard management time of weeds to avoid the negative influence on whole power plant. Moreover the hot spot which is generated by long term partial shallow on PV module also can detected with the result of this work. It also suggested as a standard value of monitoring Data.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.223-232
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• 2023

A widely used method for monitoring land cover using high-resolution satellite images is to classify the images based on the colors of the objects of interest. In urban areas, not only major objects such as buildings and roads but also vegetation such as trees frequently appear in high-resolution satellite images. However, the colors of vegetation objects often resemble those of other objects such as buildings, roads, and shadows, making it difficult to accurately classify objects based solely on color information. In this study, we propose a method that can accurately classify not only objects with various colors such as buildings but also vegetation objects. The proposed method uses the normalized difference vegetation index (NDVI) image, which is useful for detecting vegetation objects, along with the RGB image and classifies objects into subclasses. The subclass classification results are fused, and the final classification result is generated by combining them with the image segmentation results. In experiments using Compact Advanced Satellite 500-1 imagery, the proposed method, which applies the NDVI and subclass classification together, showed an overall accuracy of 87.42%, while the overall accuracy of the subchannel classification technique without using the NDVI and the subclass classification technique alone were 73.18% and 81.79%, respectively.

• Journal of Korean Society for Geospatial Information Science
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• v.11 no.2 s.25
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• pp.61-66
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• 2003

The change detection using the satellite imagery and airphotos has been carried out in the application of terrain mapping, environment, forestry, facility detection, etc. The low-spatial resolution data such as Landsat, NOAA satellite images is generally used for automatic change detection, while on the other hand the high-spatial resolution data is used for change detection by image interpretation. The research to integrate automatic method with manual change detection through the high-spatial resolution satellite image is performed. but the problem such as shadow, building 'lean' due to perspective geometry and precision geocorrection was found. In this paper we performed change detection using the IKONOS satellite images, and present the concerning problem.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.603-616
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• 2016

In this study, the effects of differential heating by land-use types on flow and air temperature at an Seoul Automated Synoptic Observing Systems (ASOS) located at Songwol-dong, Jongno-gu, Seoul was analyzed. For this, a computation fluid dynamics (CFD) model was coupled to the local data assimilation and prediction system (LDAPS) for reflecting the local meteorological characteristics at the boundaries of the CFD model domain. Time variation of temperatures on solid surfaces was calculated using observation data at El-Oued, Algeria of which latitude is similar to that of the target area. Considering land-use type and shadow, surface temperatures were prescribed in the LDAPS-CFD coupled model. The LDAPS overestimated wind speeds and underestimated air temperature compared to the observations. However, a coupled LDAPS-CFD model relatively well reproduced the observed wind speeds and air temperature, considering complicated flows and surface temperatures in the urban area. In the morning when the easterly was dominant around the target area, both the LDAPS and coupled LDAPS-CFD model underestimated the observed temperatures at the Seoul ASOS. This is because the Kyunghee Palace located at the upwind region was composed of green area and its surface temperature was relatively low. However, in the afternoon when the southeasterly was dominant, the LDAPS still underestimated, on the while, the coupled LDAPS-CFD model well reproduced the observed temperatures at the Seoul ASOS by considering the building-surface heating.