• Journal of the Semiconductor & Display Technology
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• v.11 no.2
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• pp.13-16
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• 2012

Zinc oxide (ZnO) films were deposited by an RF magnetron sputtering system with the RF power of 200W and 300W and flow rate of oxygen gases of 20 and 30 sccm, in order to research the growth of ZnO on carbon doped silicon oxide (SiOC) thin film. The reflectance of SiOC film on Si film deposited by the sputtering decreased with increasing the oxygen flow rate in the range of long wavelength. In comparison between ZnO/Si and ZnO/SiOC/Si thin film, the reflectance of ZnO/SiOC/Si film was inversed that of ZnO/Si film in the rage of 200~1000 nm. The transmittance of ZnO film increased with increasing the oxygen gas flow rate because of the transition from conduction band to oxygen interstitial band due to the oxygen interstitial (Oi) sites. The low reflectance and the high transmittance of ZnO film was suitable properties to use for the front electrode in the display or solar cell.

• Proceedings of the KIEE Conference
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• 2009.04b
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• pp.115-117
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• 2009

본 논문은 단일 디지털 제어기를 이용하여 독립형 태양광 발진 시스템에 사용되는 태양전지에서 발생한 전력을 수집하고 필요에 따라 에너지 저장 장치에 전력을 저장하는 Boost 컨버터가 최대전력점에서 동작하도록 제어하면서, 이 전압을 부하에 필요한 전압 값으로 변환하는 Buck 컨버터를 동시에 제어하는 방법을 제안한다. 제안된 독립형 태양광 발전 시스템의 구성은 에너지를 발생하는 태양전지, 최대전력 점을 추종(MPPT)하도록 하는 Boost 컨버터, 부하에 적합한 준위의 전압을 공급하는 Buck 컨버터가 직렬로 연결되어 있다. 제안된 방법은 디지털 제어기의 제어변수 값들을 바꿈으로써 전체시스템의 출력특성을 쉽게 제어할 수 있어, 사용되는 태양전지 어레이의 종류와 환경조건 변화에 따라 쉽게 제어변수 값들을 조정할 수 있다. 또한 하나의 디지털 제어기로 최대전력점 제어부 및 Buck과 Boost 컨버터의 피드백 제어부를 구성하여 시스템의 구조가 간단해지기 때문에 소형 및 경량화를 이룰 수 있다.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1241-1242
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• 2007

전세계가 고유가 시대로 들어서면서 각국은 에너지 확보에 전력을 기울이고 있다. 이에 대체 에너지 개발이 미래의 중요한 과제로 여겨지고 있다. 본 연구에서는 결정질 실리콘 태양전지의 대안으로 주목받고 있는 염료감응형 태양전지를 다루어 보았다. 유효면적 $8cm^2$의 염료감응형 태양전지의 직병렬 조합을 이용하여 DSSC 모듈을 만들어 얻은 출력을 전력변환 시킴으로써 상용전원을 얻고자 하였다. 염료감응형 태양전지모듈을 만들기 위해 먼저 DSSC의 단위 셀을 최적화 시키고 이를 실제 광원에서 다양한 직병렬 연결 시도 끝에 모듈로부터 약 5.7V, 3A의 출력을 얻을 수 있었다. 이를 Boost converter를 이용하여 전압을 12V까지 승압하고 이 출력을 고속 스위칭 소자인 MOSFET을 이용하여 스위칭한 Push-pull converter에서 DC 310V까지 승압시켰다. 그리고 그 출력을 DSP를 이용한 20[kHz]의 PWM신호를 만들어 제어한 결과, AC 220V의 상용전원을 얻었다. 그리고 이 전원을 부하에 연결하여 그 동작 특성을 연구하였다.

• Ceramist
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• v.21 no.4
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• pp.312-330
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• 2018

Energy storage/conversion has become crucial not only to meet the present energy demand but also more importantly to sustain the modern society. Particularly, electrical energy storage is critical not only to support electronic, vehicular and load-levelling applications but also to efficiently commercialize renewable energy resources such as solar and wind. While Li-ion batteries are being intensely researched for electric vehicle applications, there is a pressing need to seek for new battery chemistries aimed at stationary storage systems. In this aspect, Zn-ion batteries offer a viable option to be utilized for high energy and power density applications since every intercalated Zn-ion yields a concurrent charge transfer of two electrons and thereby high theoretical capacities can be realized. Furthermore, the simplicity of fabrication under open-air conditions combined with the abundant and less toxic zinc element makes aqueous Zn-ion batteries one of the most economical, safe and green energy storage technologies with prospective use for stationary grid storage applications. Also, Zn-ion batteries are very safe for next-generation technologies based on flexible, roll-up, wearable implantable devices the portable electronics market. Following this advantages, a wide range of approaches and materials, namely, cathodes, anodes and electrolytes have been investigated for Zn-ion batteries applications to date. Herein, we review the progresses and major advancements related to aqueous. Zn-ion batteries, facilitating energy storage/conversion via $Zn^{2+}$ (de)intercalation mechanism.

• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.77-87
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• 2021

In this study, a novel improved second order Radial Basis Function Neural Network based method with excellent scheduling capabilities is used for the dynamic prediction of short and long-term energy required applications. The effectiveness and the reliability of the algorithm are evaluated using training operations with New England-ISO database. The dynamic prediction algorithm is implemented in Matlab and the computation of mean absolute error and mean absolute percent error, and training time for the forecasted load, are determined. The results show the impact of temperature and other input parameters on the accuracy of solar Photovoltaic load forecasting. The mean absolute percent error is found to be between 1% to 3% and the training time is evaluated from 3s to 10s. The results are also compared with the previous studies, which show that this new method predicts short and long-term load better than sigmoidal neural network and bagged regression trees. The forecasted energy is found to be the nearest to the correct values as given by England ISO database, which shows that the method can be used reliably for short and long-term load forecasting of any electrical system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1777-1783
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• 2021

The use of drones is gradually increasing for the efficient maintenance of large-scale renewable energy power generation complexes. For a long time, photovoltaic panels have been photographed with drones to manage panel loss and contamination. Various approaches using artificial intelligence are being tried for efficient maintenance of large-scale photovoltaic complexes. Recently, semantic segmentation-based application techniques have been developed to solve the image classification problem. In this paper, we propose a classification model using semantic segmentation to determine the presence or absence of failures such as arcs, disconnections, and cracks in solar panel images obtained using a drone equipped with a thermal imaging camera. In addition, an efficient classification model was implemented by tuning several factors such as data size and type and loss function customization in U-Net, which shows robust classification performance even with a small dataset.

• Journal of Drive and Control
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• v.21 no.2
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• pp.65-71
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• 2024

In this study, we suggested a key-point detection method for robot harvesting of oriental melon. Our suggested method could be used to detect the detachment part and major composition of oriental melon. We defined four points (harvesting point, calyx, center, bottom) based on tomato with characteristics similar to those of oriental melon. The evaluation of estimated key-points was conducted by pixel error and PDK (percentage of detected key-point) index. Results showed that the average pixel error was 18.26 ± 16.62 for the x coordinate and 17.74 ± 18.07 for the y coordinate. Considering the resolution of raw images, these pixel errors were not expected to have a serious impact. The PDK score was found to be 89.5% PDK@0.5 on average. It was possible to estimate oriental melon specific key-point. As a result of this research, we believe that the proposed method can contribute to the application of harvesting robot system.

• Journal of Advanced Navigation Technology
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• v.23 no.6
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• pp.561-569
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• 2019

Solar photovoltaic can provide electrical energy with only radiation, and its use is expanding rapidly as a new energy source. This study predicts the short and long-term PV power generation using actual converter output data of photovoltaic system. The prediction algorithm uses multiple linear regression, support vector machine (SVM), and deep learning such as deep neural network (DNN) and long short-term memory (LSTM). In addition, three models are used according to the input and output structure of the weather element. Long-term forecasts are made monthly, seasonally and annually, and short-term forecasts are made for 7 days. As a result, the deep learning network is better in prediction accuracy than multiple linear regression and SVM. In addition, LSTM, which is a better model for time series prediction than DNN, is somewhat superior in terms of prediction accuracy. The experiment results according to the input and output structure appear Model 2 has less error than Model 1, and Model 3 has less error than Model 2.

• Bulletin of the Korean Space Science Society
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• 2009.10a
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• pp.28.4-29
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• 2009

The 'Amon-Ra' instrument of the proposed 'EARTHSHINE' satellite is a dual (i.e. imaging and energy) channel instrument for monitoring the total solar irradiance (TSI) and the Earth's irradiance at around the L1 halo orbit. Earlier studies for this instrument include, but not limited to, design and construction of breadboard Amon-Ra imaging channel, stray light suppression and system performance computation using Integrated Ray Tracing (IRT) technique. The Amon-Ra instrument is required to produce 0.3% in uncertainty for both Sunlight and Earthlight measurement. In this study, we report accurate estimation of the output electric signal derived from the orbital variation of radiant exitance from the Sun and the Earth arriving at the aperture and detector plane of the Amon-Ra. For this, orbital irradiance are computed analytically first and then confirmed by simulation using Integrated Ray Tracing (IRT) model. Specially, the results show the arriving power at the bolometer detector surface is $1.24{\mu}W$ for the Sunlight and $1.28{\mu}W$ for the Earthlight, producing the output signal pulses of 34.31 mV and 35.47 mV respectively. These results demonstrate successfully that the arriving radiative power is well within the bolometer detector dynamic range and, therefore, the proposed detector can be used for the in-orbit measurement sequence. We discuss the computational details and implications as well as the simulation results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.9
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• pp.2140-2146
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• 2014

Ocean buoys are operated for safe navigation and collecting ocean data. Recently, to reducing marine buoy's damage by ocean weather's bad condition and collision with vessels has been conducted in several field research. This paper's experiment is buoy condition monitoring about predefined data form by users. As a result using Wireless remote control board applying a radio signal processing algorithms, it can observe buoy's state at an interval of three minutes on the land. Acquired data type is changeable according to ocean weather condition or buoy's purpose of using in advance. Also, this paper conducted an experiment such as data-transmission's stability and wireless communication's availability. As results of the analysis of the transmitted data, the solar, wind and wave power indicates the maximum amount of power, 50 W, 20 W and 40 W respectively. The communication system proven through this research can apply to buoy or other ocean facility.