• The Transactions of the Korean Institute of Power Electronics
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• v.14 no.4
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• pp.261-267
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• 2009

Due to the measurement noise or system noise, the performance of photovoltaic power generation system can be degraded. If this noise is contained in the solar array voltage measurement signal, the correct operation of the maximum power point tracker can not be guaranteed. The application of the extended Kalman filter to the photovoltaic system can obtain enhanced states estimation result. The Kalman filter provides a recursive solution to optimally estimate from random noise signals. Additionally, as a consequence of Kalman filter, the unmeasurable state such as inductor current can be estimated without current sensor. The methods for system modeling and extended Kalman filter design are presented and the experimental results verify the validity of the proposed system.

• Journal of Sensor Science and Technology
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• v.9 no.1
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• pp.70-75
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• 2000

The recycled single crystal silicon wafers have been fabricated into solar cells. It can be a solution for the high cost in materials for solar cells and recycling of materials. So, p-type (100) single crystal silicon wafers with high resistivity of $10-14\;{\Omega}cm$ and the thickness of $650\;{\mu}m$ were used for the fabrication of solar cells. Optimistic conditions of formation of back surface field, surface texturing and anti-reflection coating were studied for getting high efficiency. In addition, thickness variation of solar cell was also studied for increase of efficiency. As a result, the solar cell with efficiency of 10% with a curve fill factor of 0.53 was fabricated with the wafers which have the area of $4\;cm^2$ and thickness of $300\;{\mu}m$. According to above results, recycling possibility of wasted wafers to single crystal silicon solar cells was confirmed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.1
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• pp.74-82
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• 2019

The revolution of industry 4.0 is enabling us to build an intelligent connection society called smart cities. The use of renewable energy in particular solar energy is extremely important for modern society due to the growing power demand in smart cities, but its difficult to monitor and manage in each buildings since need to be deploy low energy sensors and information need to be transfer via wireless sensor network (WSN). The Internet of Things (IoT) / low-power wide-area (LPWA) is an emerging WSN technology, to collect and monitor data about environmental and physical electrical / electronics devices conditions in real time. However, providing power to IoT sensor end devices and other public electrical loads such as street lights, etc is an important challenging role because the sensor are usually battery powered and have a limited life time. In this paper, we proposes an efficient solar energy-based power management scheme for smart city based on IoT technology using LoRa wide-area network (LoRaWAN). This approach facilitates to maintain and prevent errors of solar panel based energy systems. The proposed solution maximizing output the power generated from solar panels system to distribute the power to the load and the grid. In this paper, we proved the efficiency of the proposed system with Simulink based system modeling and real-time emulation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.326-328
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• 2015

Function of the window of the building is an environment of the room through the entry of solar radiation. It is vulnerable to significant energy conservation off the thermal efficiency. Also this summer, cooling costs are weighted because of excessive solar radiation. In this paper, we develop a windows automatic control system to use the indoor environmental information, such as home temperature, humidity, light intensity, solar radiation. The system collects the indoor environment information using a variety of sensor, using the collected information, and controls the motor to the system to control the window.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.26 no.8
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• pp.351-356
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• 2014

Typical trouble patterns in solar thermal systems include working fluid leakage and freezing other than breakdown of pump. A fluid sensor for measuring electric resistance of fluid was developed and installed at the top of the collector piping in order to check the fault of solar system. Working fluid level in the pipe was determined by measuring electric resistance from a fluid sensor. On the base of this, it was confirmed that the fluid sensor diagnoses leakage of fluid. Electric resistance of propylene glycol aqueous solution was measured in the range of $0{\sim}70^{\circ}C$ and 0~40% of concentration. The response surface analysis was performed by using a central composite design, and the regression equation was derived from the relationship between electric resistance, temperature, and concentration. Through the experiment in a real solar system, we can estimate a concentration of working fluid when a pump is not operating and predict a possibility of freezing. Finally, an effective algorithm for trouble shooting was proposed to operate and maintain the solar system.

• Journal of the Korean Solar Energy Society
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• v.38 no.6
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• pp.65-72
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• 2018

Since data-driven building technologies have been widely applied to building energy systems, the accuracy of building sensors has more impacts on the building performance and system performance analysis. Various building sensors, however, can have typical errors including a random error (noise) and a systematic error (bias). The systematic error is indicated by the difference between the mean of measurements and their true value. It may occur due to the sensor's physical condition, measured phenomena, working environments inside the systems. Unfortunately, a conventional calibration method has limitations in calibrating the systematic errors because of the difference between working environments and calibration conditions. In such situations, a novel sensor calibration method is needed to handle various sensor errors, especially for systematic errors, in building energy systems having various thermodynamic environments. This study proposes a building sensor calibration method named Virtual In-situ Calibration (VIC) and shows how it is applied into a real building system and how it solves the sensor errors.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2009.04a
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• pp.471-474
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• 2009

현대 사회는 유비쿼터스와 함께 Intelligent Bridge와 녹색 뉴딜개념의 Energy Birdge 같은 신개념의 교량연구에 주력하고 있다. 따라서 교량 안전관리는 무선 센서노드로 데이터를 송신하고 있으나 센서 전력에 수명제한 베터리와 기후제한 태양열로 공급 문제가 있다. 이에 본 논문에서는 외력에 의해 bending vibration이 일어나면서 판 양면에 양 음의 전하가 띄어 전압, 전류가 발생하는 압전소자를 이용 하였다. 이 압전소자에 발생하는 정현파로 인한 축전 문제와 발전된 전력이 다른 압전소자에게 흘러 전력생산량의 감소 문제는 Bridge Diode를 사용한 R-C회로도를 구성하여 보완하였다. 이 설계를 통하여 차량 하중(외력)의 크기에 변수를 두어 전압발생 차이를 측정하고 일정시간 외력 통해 Capacitor 축전된 양을 검토하였다.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1640-1641
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• 2011

다양한 환경에서 USN 시스템이 적용됨에 따라 해당 시스템의 효율적인 전력 운용 및 통신 방식이 중요해 지고 있다. 이에 본 논문에서는 태양전지를 사용하여 획득한 전력을 효율적으로 배터리에 충전시키기 위해 히스테리시스 스위치를 사용한 에너지 획득모듈, 센서노드의 효율적인 전력운영을 위해 아이디 기반의 웨이크업 모�뺐� 센싱정보를 전송후 자체적으로 전력을 차단하는 동적전력관리 모듈을 제안 및 구현을 통해 센서노드의 효율적인 전력 운용을 검증했다.

• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.422.1-422.1
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• 2014

E-textile과 같은 웨어러블 전자소자는 휴대용 전자소자, 의료센서 및 디스플레이 등을 포함하는 다기능 직물등의 적용가능 응용분야에서의 잠재력으로 인하여 많은 관심을 가지고 있다. 따라서 본 논문에서는 이같은 응용분야에 적용하기 위하여 전기방사를 이용한 나노크기의 나일론 섬유를 제작하고 reduced graphene oxide를 섬유에 코팅하여 전도성을 가지는 나노섬유를 제작하였다. 나일론 알갱이를 포름산에 녹인 용액을 이용하여 전기방사를 통해 약 100 nm 두께를 가지는 나노섬유를 제작하였다. 제작된 나일론 섬유와 그래핀 옥사이드 사이의 결합력을 향상시키기 위하여 BSA(bovine serum albumin)으로 표면 처리를 하였다. 마지막으로 나일론 섬유에 코팅된 그래핀 옥사이드를 hydrazine을 이용하여 환원하여 전도성을 가지는 섬유를 제작하였다. 제작된 전도성을 가지는 섬유는 약 10 kohm 정도의 저항을 가지는 것을 확인하였으며, 물리적인 외부 변형에서도 안정적으로 전도성을 가지는 것을 확인하였다. 이러한 전도성을 가지는 나노섬유는 웨어러블 전자소자를 제작하는데 응용 가능할 뿐만 아니라, 전기방사를 통한 나노구조물 제작 기술을 가스센서, 바이오센서, 태양전지, 나노소자등 다양한 분야에 적용 가능한 우수한 기술이라고 생각한다.

• Proceedings of the KIPE Conference
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• 2019.07a
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• pp.216-218
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• 2019

태양광발전시스템은 최대의 전력을 생산하기 위하여 PV 패널의 운전을 최대전력점에서 동작하게 하는 MPPT(Maximum Power Point Tracking) 제어가 필요하다. 그중 대표적인 방법인 P&O(Perturb and Observe) 알고리즘은 전류와 전압을 측정하여 계산된 전력의 값이 최대가 되는 전압의 운전점을 찾는다. 그러나 센서의 측정오차로 인하여 발전전력의 계산 및 전압의 제어에 불규칙한 오차가 발생하여 정확한 MPP 운전점을 찾지 못하는 문제가 발생한다. 본 논문에서는 전형적인 맑은 날씨와 흐린 날씨에서 취득한 일사량 데이터와 전류 및 전압 센서의 오차를 고려하여 P&O 알고리즘에 의한 전력 생산량을 시뮬레이션 한다. 시뮬레이션 분석을 통해 실제 날씨 및 센서허용오차 조건에서 MPPT 목표 효율을 극대화할 수 있는 최적의 MPPT 제어주기와 변량전압의 크기를 제시한다.