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Triboelectric Energy Harvesting for Self-powered Antibacterial Applications
서인용,김상우 한국센서학회 2023 센서학회지 Vol.32 No.4
Triboelectric nanogenerators (TENGs) have emerged as a highly promising energy harvesting technology capable of harnessing mechanical energy from various environmental vibrations. Their versatility in material selection and efficient conversion of mechanical energy into electric energy make them particularly attractive. TENGs can serve as a valuable technology for self-powered sensor operation in preparation for the IoT era. Additionally, they demonstrate potential for diverse applications, including energy sources for implanted medical devices (IMDs), neural therapy, and wound healing. In this review, we summarize the potential use of this universally applicable triboelectric energy harvesting technology in the disinfection and blocking of pathogens. By integrating triboelectric energy harvesting technology into human clothing, masks, and other accessories, we propose the possibility of blocking pathogens, along with technologies for removing airborne or waterborne infectious agents. Through this, we suggest that triboelectric energy harvesting technology could be an efficient alternative to existing pathogen removal technologies in the future.
서인용,신호철,박문규,김성준,Seo, In-Yong,Shin, Ho-Cheol,Park, Moon-Ghu,Kim, Seong-Jun 한국시뮬레이션학회 2009 한국시뮬레이션학회 논문지 Vol.18 No.3
In a nuclear power plant (NPP), periodic sensor calibrations are required to assure sensors are operating correctly. However, only a few faulty sensors are found to be calibrated. For the safe operation of an NPP and the reduction of unnecessary calibration, on-line calibration monitoring is needed. In this paper, principal component-based Auto-Associative support vector regression (PCSVR) was proposed for the sensor signal validation of the NPP. It utilizes the attractive merits of principal component analysis (PCA) for extracting predominant feature vectors and AASVR because it easily represents complicated processes that are difficult to model with analytical and mechanistic models. With the use of real plant startup data from the Kori Nuclear Power Plant Unit 3, SVR hyperparameters were optimized by the response surface methodology (RSM). Moreover the statistical techniques are integrated with PCSVR for the failure detection. The residuals between the estimated signals and the measured signals are tested by the Shewhart Control Chart, Exponentially Weighted Moving Average (EWMA), Cumulative Sum (CUSUM) and generalized likelihood ratio test (GLRT) to detect whether the sensors are failed or not. This study shows the GLRT can be a candidate for the detection of sensor drift.
국민DR 100만 kW를 위한 스마트가전 수요반응 시범사업 실적분석 및 경제성 전망
서인용,이창희,이태일,손성용 대한전기학회 2020 전기학회논문지 Vol.69 No.8
With a gradual increase of electricity demand and high penetration of renewable energy resources to electrical power grid, the demand response (DR) program is emerging as an alternative to reduce peak power and increase the power system stability. This study provides an analysis of data from a DR pilot project in which 140 appliances were participated. We proposed a customer baseline load (CBL) estimation method without historic power consumption data, and calculated peak reduction effects of smart appliances. Moreover, we analyzed the average respond success rate, and investigated the effectiveness respond signal. In addition, an economic assessment of smart appliances (S/A) DR for 1GW peak reduction is performed based on the data from the pilot project. We evaluate the benefits from the application of S/A DR in the utility and participant perspective. While participant’s benefit is an incentive from the reduction of power consumption, the utility’s benefits can include deferral effects of the generation capacity and delay of transmission and distribution infra construction. Also sensitivity analysis according to various factors that affect the benefit cost ratio of the project is performed. Finally, we proposed a moderate incentive program which can attract the customer to participate the DR project.
배전자동화시스템의 전류계측 오차 보정을 통한 정확성 향상에 관한 연구
서인용(In-Yong Seo),이정인(Jeong-In Lee),하복남(Bok-Nam Ha),이성우(Sung-Woo Lee),박소영(So-Young Park) 대한전기학회 2010 대한전기학회 학술대회 논문집 Vol.2010 No.7
배전자동화시스템(DAS)용 기기는 주로 리크로져, 가스절연부하개폐기가 사용되고 있으며, 현재 한전에서는 DAS 정보와 연계한 배전선로 상관리시스템을 개발하여 시범적용 중에 있으나, 자동화용기기의 전류계측 오차 때문에 정확한 구간별 불평형 부하전류 시정작업이 곤란하고 불편한 실정이다. 선로고장 발생시에도 DAS용 계통도 화면에서 보여주는 고장표시기 FI(Fault Indicator)의 고장전류 계측값이 자동화기기별로 크게 상이하여 고장 발생시 DAS 운영자가 고장원인 분석에 어려움이 있다. 기존 DAS용 기기의 전류계측 정밀도를 높이기 위한 BCT 교체하는 것은 많은 비용이 소요 될 뿐 아니라, 정전작업 및 자동화기기의 운전 정지를 수반하여야 한다. 본 논문에서는 기존 DAS용 부싱변류기를 교체하지 않고, 자동화기기의 운전정지 없이도 부싱변류기(BCT) 및 FRTU 내부 2차 CT의 전류계측정밀도를 0.5급 이상으로 보정하기 위해 DAS의 통신 프로그램 수정하였고, 이를 사업소의 DAS에 설치 후 현장 개폐기에 대해 시험하여 오차가 정확히 보정됨을 확인하였다. 이는 CT 교체비 절감 및 부하불평형 고압선 손실 측면에서 큰 경제적 이득을 줄 것으로 기대된다.