• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.7
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• pp.99-109
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• 2012

Sub-station, key equipment in electric power infrastructure, are being exposed to increasing risk of hacking. For this, soft redundancy sub-station system needs to be formulated with automatic restoration mechanism. For this it is important to assess the reliability of the applicable range of data that are used in actual system operation, as well as the methods and findings of the tests. At the same time performance of soft redundancy system and total security mechanism, which are aligned for the protection of the sub-station, need to be tested. For testing the above-mentioned, this paper presented a viable formation of a soft redundancy practical VPN system within a panel to protect the latter from hacking or cracking incidences, and conducts a test to check if the considered system actually serves the protection function in the actual operation setting, gathering evidence from the data from the testing of the actual performance of the system as well as of emergency scenario simulation operations. Because tested soft-redundancy & restorative sub-station system is expected to be widely applicable for various cases such as Smart-grid or electricity IT system, where VPN with enhanced level of security is required.

• New & Renewable Energy
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• v.18 no.1
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• pp.1-16
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• 2022

Climatic characteristics were described using the LiDAR (Light Detection and Ranging) and the met-mast on Dongbok·Bukchon region. The influences of meteorological conditions on the power performance of wind turbines were presented using the data of Supervisory Control And Data Acquisition (SCADA) and met-mast of the Dongbok·Bukchon Wind Farm (DBWF) located in Jeju Island. The stability was categorized into three parameters (Richardson number, Turbulence intensity, and Wind shear exponent). DBWF was dominant in unstable atmospheric conditions. At wind speeds of 14 m/s or more, the proportion of slightly unstable conditions accounted for more than 50%. A clear difference in the power output of the wind turbine was exhibited in the category of atmospheric stability and turbulence intensity (TI). Particularly, a more sensitive difference in power performance was showed in the rated wind speeds of the wind turbine and wind regime with high TI. When the flow had a high turbulence at low wind speeds and a low turbulence at rated wind speeds, a higher wind energy potential was produced than that in other conditions. Finally, the high-efficiency of the wind farm was confirmed in the slightly unstable atmospheric stability. However, when the unstable state become stronger, the wind farm efficiency was lower than that in the stable state.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.174-179
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• 2015

Failure Mode and Effects Analysis (FMEA) has been used by Dynamic Positioning (DP) system for risk and reliability analysis. However, there are limitations associated with its implementation in offshore project. 1) since the failure data measured from the SCADA system is missing or unreliable, assessments of Severity, Occurrence, Detection are based on expert's knowledge; 2) it is not easy for experts to precisely evaluate the three risk factors. The risk factors are often expressed in a linguistic way. 3) the relative importance among three risk factors are rarely even considered. To solve these problems and improve the effectiveness of the traditional FMEA, we suggest a Fuzzy-FMEA method for risk and failure mode analysis in Dynamic Positioning System of offshore. The information gathered from DP FMEA report and DP FMEA Proving Trials is expressed using fuzzy linguistic terms. The proposed method is applied to an offshore Dynamic Positioning system, and the results are compared with traditional FMEA.

• Journal of Digital Contents Society
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• v.19 no.4
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• pp.789-799
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• 2018

This article presents machine learning based approach on Big data to analyzing time series data for anomaly detection in such industrial complex system. Long Short-Term Memory (LSTM) network have been demonstrated to be improved version of RNN and have become a useful aid for many tasks. This LSTM based model learn the higher level temporal features as well as temporal pattern, then such predictor is used to prediction stage to estimate future data. The prediction error is the difference between predicted output made by predictor and actual in-coming values. An error-distribution estimation model is built using a Gaussian distribution to calculate the anomaly in the score of the observation. In this manner, we move from the concept of a single anomaly to the idea of the collective anomaly. This work can assist the monitoring and management of Smart Factory in minimizing failure and improving manufacturing quality.

• Journal of the Korea Society of Computer and Information
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• v.21 no.8
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• pp.57-64
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• 2016

Initial prevention activities and rapid propagation conditions is the most important to prevent diffusion of water pollution. If water pollutants flow into streams river or main stresm located in environmental conservation area or water intake facilities, we must predict immediately arrival time and the diffusion concentration to the proactive. National Institute of Environmental Research developed water pollution incident response prediction system linking dam and movable weir. the system is mathematical model which is updated daily. Therefore it can quickly predict the arrival time and the diffusion concentration when there are accident of oil spills and hazardous chemicals. Also we equipped with mathematical model and toxicity model of EFDC(Environmental Fluid Dynamics Code) to calculate the arrival time and the diffusion concentration. However these systems offer the services of an offline manner than real-time control services. we have ensured the reliability of data collection and have developed a real-time water quality measurement data transmission device by using the data linkage utilizing a mode bus communication and a commercial SCADA system, in particular, we implemented to be able to do real-time water quality prediction through information infrastructure of the water quality integrated management business created by utilizing the construction of the real-time prediction system that utilizes the data collected, the Open map, the visual representation using charts API and development of integrated management system development based on web maps.

• Journal of Korean Society on Water Environment
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• v.36 no.6
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• pp.535-545
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• 2020

This study aims to conserve and monitor energy use in public sewage treatment plants by utilizing data from the SCADA system and by controlling the aeration rate required for maintaining effluent water quality. Power consumption in the sewage treatment process was predicted using the equipment's uptime, efficiency, and inherent power consumption. The predicted energy consumption was calibrated by measured data. Additionally, energy efficiency indicators were proposed based on statistical data for energy use, capacity, and effluent quality. In one case study, a sewage treatment plant operated via the SBR process used ~30% of energy consumed in maintaining the bioreactors and treated water tanks (included decanting pump and cleaning systems). Energy consumption analysis with the K-ECO Tool-kit was conducted for unit processing. The results showed that about 58.7% of total energy consumed was used in the preliminary and biological treatment rotating equipment such as the blower and pump. In addition, the energy consumption rate was higher to the order of 19.2% in the phosphorus removal process, 16.0% during sludge treatment, and 6.1% during disinfection and discharge. In terms of equipment energy usage, feeding and decanting pumps accounted for 40% of total energy consumed following 27% for blowers. By controlling the aeration rate based on the proposed feedback control system, the DO concentration was reduced by 56% compared pre-controls and the aeration amount decreased by 28%. The overall power consumption of the plant was reduced by 6% via aeration control.

• Progress in Superconductivity and Cryogenics
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• v.19 no.1
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• pp.5-8
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• 2017

A series of high gradient superconducting magnetic separator (HGMS) for kaolin has been developed. It is used for processing kaolin to increase the brightness or whiteness whether it is for paper or ceramic applications. The HGMS system mainly consists of a solenoid magnet with a zero boil-off helium cryostat, a double reciprocating canisters system, and a PLC (Process Logic Controller) fully automatic control system based on SCADA (Supervisory Control and Data Acquisition) system. We have successfully developed CGC-5.5/300 and CGC-5.0/500 HGMS systems in the recent years, and now three sets of them are on-site operation in different customers. This paper will present recent progress of the HGMS system, the results of some experiments on processing kaolin clay used HGMS, and the on-site operation.

• Proceedings of the KIEE Conference
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• 2008.10a
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• pp.75-76
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• 2008

전력거래소는 전격계통 안정된 운영과 공정한 전력시장 운영을 주요 임무로 하며, 이를 위하여 전국의 80여개의 발전소와 600여개 변전소로부터 발전량, 전압, 조류, 자단기 상태정보 등 다양한 전력계통 자료를 취득하고 있다 전력거래소의 중앙급전소에는 이와 같은 계통자료 취득은 물론 발전량 제어기능을 수행하기 위한 에너지관리시스템(이하 EMS 라 한다)을 운영하고 있으며, 발,변전소에는 현장의 전력설비와 연결되어 계통자료를 취득하여 EMS로 전송하는 원격소장치 (이하 RTU 라한다)를 운영하고 있다. 자료취득 경로는 모든 발전소와 34skv급 이상의 변전소의 경우 EMS와 RTU가 직접 연결되어 자료를 취득하며 154Kv급 이하 변전소는 12개 지역급전소의 자료취득제어시스템(이하 SCADA라 한다)를 경유하여 자료를 취득하고 있다. 전력계통의 대형화와 복잡화에 따라 계통해석기능 자동발전제어기능에 의한 계류운영으로 정보기술에 대한 의존도가 증가하고 있으며, 변동비 반영시장의 개선운영에 따라 공정한 전력시장 운영과 안정된 전력계통 운영을 위해 전력계통 취득자료의 신뢰도가 요구되고 있다. 따라서 EMS를 비롯한 RTU, 통신망 등 전력계통 자료취득 설비의 운영실적을 분석하여 각 시스템별 고장 고장원인 고장유형 등을 고찰하므로써 시스템 성능개선을 위한 설비투자와 운영개선에 반영하고자 한다.

• Proceedings of the KIEE Conference
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• summer
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• pp.541-544
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• 2004

지난 99년 이후 친환경적이며 경제적이고 효율적인 대체 교통수단의 개발이라는 목표 하에, 차세대 근거리 교통수단으로 각광받고 있는 경량전철 시스템 적용을 목표로 무인 변전소 기반의 전력감시제어 시스템(SCADA)을 개발하였다. 차세대 변전소 기술 적용이라는 취지 하에 각종 IED들과의 연계는 모두 통신으로 처리하여 시스템의 고기능화를 추구하였고, Network 이중화를 통하여 시스템의 신뢰성을 제고하였으며, CCTV 및 각종 보안센서를 적용하여 배전반의 무인화 운전 및 원격 상시 감시 기능을 구현하였다. 이로써 신뢰성 있는 시스템 기반의 무인 변전소 기술 확립이라는 측면에서 현재 진행되고 있는 변전소 자동화 기술에 일조하며, 나아가 향후 에너지 IT산업기술의 기반이 되리라 사료된다.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.63 no.2
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• pp.89-94
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• 2014

Tidal generation has become one of environmentally friendly new and renewable future sources of energy. The Sihwa Tidal Power Plant in South Korea, which was imported from abroad by turnkey type in 2011, connected to the power system in 2012, and is currently under commercial operation. However, leading companies are reluctant to disclose their technologies associated with the control systems and are not cooperative in technology transfers, making it a high priority to develop core technologies in South Korea. In order to develop a start stop control system for tidal generation, this paper presents the optimal algorithm for decision making and prototype of hardware design. First, control systems in tidal power, such as plant operation control, data interfaces between systems, monitoring and control points of the control system, are analyzed. The software development and PC based emulator processes for optimization algorithm processing are described. Finally, verification of the algorithm implementation, hardware platform for start stop control device, and implementation of prototype control system were discussed.