• Journal of international Conference on Electrical Machines and Systems
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• 제2권1호
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• pp.104-110
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• 2013

In this paper an application of centralized pitch angle controller for fixed speed wind turbines based wind farm to mitigate load frequency fluctuation is presented. Reference signal for the pitch angle of each wind turbine is calculated by using proposed centralized control system based on wind speed information. The wind farm in the model system is connected to a multi machine power system which is composed of 4 synchronous generators and a load. Simulation analyses have been carried out to investigate the performance of the controller using real wind speed data. It is concluded that the load frequency of the system can be controlled smoothly.

• KEPCO Journal on Electric Power and Energy
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• 제2권1호
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• pp.33-41
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• 2016

To verify that the friction damper used to high buildings as a kind of control technology of wind vibration can reduce dynamic behaviors of PTTs effectively, slip dampers in this paper are proposed to absorb the energy through relatively frictional movement of slip dampers applied to main post of a PTT (Power Transmission Tower) when dynamic displacement of a PTT occurs. The result of dynamic analysis is presented to determine the capacity of the damper system by controlling damping ratio on the resonance condition. It is observed that by installing slip dampers at a PTT the strain amplitudes of the main post caused by wind load are effectively reduced. Therefore it is shown that the proposed damper satisfies the strengthened wind-load design standards, and its efficacy was also validated experimentally by field testing.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 A
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• pp.359-361
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• 2005

This paper presents the method of countermeasures before voltage collapse by load encroachment(impedance of load ability on R-X locus decrease toward zero point) and describes a study of impedance relay(zone-3) operation and voltage instability caused by over load of neighborhood line at contingency of heavy load line.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.749-751
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• 1999

We acquired operating data in an existing steam turbine power plant using analog control system to investigate operation characteristics. We analyzed a load control logic to develop a digital turbine control system. The load control logic is constituted of load target, load reference, loading rate, load limit and admission mode transfer of valve. The result of this paper is utilized to implement a digital turbine control system.

• 전기학회논문지
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• 제65권6호
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• pp.934-939
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• 2016

This paper made short-term electric load forecasting by using temperature data at three-hour intervals (9am, 12pm, 3pm, and 6pm) provided by the Korea Meteorological Administration (KMA). In addition, the electric power pattern was created using existing electric power data, and temperature sensitivity was derived using temperature and electric power data. We made power load forecasting program using LabVIEW, a graphic language.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 A
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• pp.298-300
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• 2004

Arc-furnace facilities consume 9,895,165(MWh) which is about 69.6 Percent of electronic furnace power consumption. and interior of a country demand power have inclosed annual. but becaused of the problem of cost, power plant location, and environment have faced difficulty to electric power supply. In this paper, Examining Load cutting of Arc-furnace that is dominating high weight of industry electric power use. and it is expected to solve easily electric power supply and demand problem by highest Priority load cutting examination of Arc-furnace when electric power supply and demand problem happens to area electric power system when is urgent.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 춘계학술대회 논문집 전력기술부문
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• pp.201-205
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• 2001

This paper presents the load modeling process and bus load models for KEPCO power system. At first, load devices commonly used in KEPCO power systems were selected, and tested for measuring the voltage and frequency sensitivity of active and reactive power. From this test, about 40 voltage and frequency dependent load models have been obtained. The bus load composition rate for KEPCO power system has been determined using the various recent surveys and papers in order to develop the load model for a power system bus. To verify the accuracy of developed bus load models, the field test for measuring active and reactive power according to artificial variation of the bus voltage was performed at 8 substations for spring summer, autumn, winter cases. With data of this seasonal field test, more reliable bus load models for KEPCO power systems were developed.

• KEPCO Journal on Electric Power and Energy
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• 제2권1호
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• pp.61-69
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• 2016

Understanding load patterns and customer classification is a basic step in analyzing the behavior of electricity consumers. To achieve that, there have been many researches about clustering customers' daily load data. Nowadays, the deployment of advanced metering infrastructure (AMI) and big-data technologies make it easier to study customers' load data. In this paper, we study load clustering from the view point of yearly and daily load pattern. We compare four clustering methods; K-means clustering, hierarchical clustering (average & Ward's method) and DBSCAN (Density-Based Spatial Clustering of Applications with Noise). We also discuss the relationship between clustering results and Korean Standard Industrial Classification that is one of possible labels for customers' load data. We find that hierarchical clustering with Ward's method is suitable for clustering load data and KSIC can be well characterized by daily load pattern, but not quite well by yearly load pattern.

• KEPCO Journal on Electric Power and Energy
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• 제7권1호
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• pp.125-128
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• 2021

This paper presents the root cause failure analysis of the circulating water pump in the 560 MW thermal power plant. A fractured austenitic stainless-steel shaft operated for 24 years was examined. Fracture morphology was investigated by micro and macro-fractographic analysis. The metallurgical analyses including chemical analysis, metallography and hardness testing were performed. The analysis reveals that the pump shaft was fractured due to the reverse bending load with combination of rotating bending load. Corrective actions for plant operator was recommended based on the analysis.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제5권10호
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• pp.293-302
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• 2016

전기는 생산과 소비가 동시에 이루어지므로 필요한 전력 사용량을 예측하고, 이를 충족시킬 수 있는 충분한 공급능력을 확보해야만 안정적인 전력 공급이 가능하다. 특히, 대학 캠퍼스는 전력 사용이 많은 곳으로 시간과 환경에 따라 전력 변화폭이 다양하다. 이러한 이유로, 효율적인 전력 공급 및 관리를 위해서는 전력 사용량을 실시간으로 예측할 수 있는 모델이 요구된다. 국내외 대학 건물에 대해서는 전력 사용 패턴과 사례 분석을 통해 전력 사용에 영향을 주는 요인들을 파악하기 위한 다양한 연구가 진행되었으나, 전력 사용량의 정량적 예측을 위해서는 더 많은 연구가 필요한 상황이다. 본 논문에서는, 기계 학습 기법을 이용하여 대학 캠퍼스의 전력 사용량 예측 모델을 구성하고 평가한다. 이를 위해, 대학 캠퍼스의 주요 건물 클러스터에 대해 전력 사용량을 15분마다 1년 이상 수집한 데이터 셋을 사용한다. 수집된 전력 사용량 데이터는 수열 형태의 시계열 데이터로 기계 학습 모델에 적용 시 주기성 정보를 반영할 수 없으므로, 2차원 공간의 연속적인 데이터로 증강함으로써 주기성을 반영하였다. 이 데이터와 교육기관의 특성을 반영하기 위한 요일과 공휴일로 구성된 8차원 특성 벡터에 대해 주성분 분석(Principal Component Analysis) 알고리즘을 적용한다. 이어, 인공 신경망(Artificial Neural Network)과 지지 벡터 회귀분석(Support Vector Regression)을 이용하여 전력 사용량 예측 모델을 학습시키고, 5겹 교차검증(5-fold Cross Validation)을 통하여 적용된 기법의 성능을 평가하여, 실제 전력 사용량과 예측 결과를 비교한다.