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전자기과도해석을 위한 설계서 기반의 고정밀 HVDC 모델 개발
고백경(Baekkyeong Ko),정솔영(Solyoung Jung),송지영(Jiyoung Song),이재걸(Jaegul Lee),김용학(Yonghak Kim),전동훈(Donghoon Jeon) 대한전기학회 2019 전기학회논문지 Vol.68 No.3
Special equipment such as HVDC and FACTS is increasing for expansion of power system scale and stable power supply. The increase of such special facilities is expected to be a combined system of AC facilities such as conventional generators and AC-DC where power electronics based DC facilities are operated simultaneously in the power system. Special equipment such as HVDC and FACTS devices is very fast because it consists of switching elements. Therefore, RMS Value based analysis tools such as PSS/E have limited analysis with a long time step. Therefore, PSCAD or RTDS, which is an instantaneous value-based analysis tool capable of sophisticated analysis, should be used. KEPCO has been developed a software model based on design documents for the HVDC facility, which will be operated for the first time in the land system. It is confirmed that the characteristics of the basis of the simulation result are well reflected in the developed single model. When the Replica controller of the HVDC facility is introduced, the developed HVDC system model will be upgraded very sophisticatedly. In addition, this model is applied to real-time large-scale system, and real-scale application analysis will be carried out to identify various problems in advance and prepare countermeasures.
시각동기 위상측정데이터를 이용한 FACTS 동적 모델 제정수 추정에 관한 연구
고백경(Baekkyeong Ko),남수철(Suchul Nam),구본길(Bongil Koo),강성범(Sungbum Kang) 대한전기학회 2020 전기학회논문지 Vol.69 No.8
FACTS is an important facility for stable power system operation by controlling the voltage of the power system. Recently, large-scale FACTS are in operation to increase the reliability of power supply, and system analysis is performed with the UWM model related to this. Although it is most accurate to perform with UWM model with high precision of analysis results, it is a good way to use a general model that can be quickly simulated for power system planning, etc. When the UWM model does not exist, general dynamic models were used for considering the dynamic characteristics of FACTS. If it is possible to estimate the parameters for the dynamic model through measurement data, the parameters in this model are considered to be more realistically applicable than before. Therefore, we developed an algorithm that estimates the parameters of FACTS using PMU data and verified the validity of the algorithm by internally verifying it through PSS/E and EMT simulations.
765㎸ 루트 고장 대비 모터부하를 고려한 다단계 부하차단량 및 차단시간 산정에 관한 연구
고백경(Baekkyeong Ko),이병준(Byongjun Lee),김태균(Taegyun Kim),남수철(Su-chul Nam),신정훈(Jeong-hoon Shin) 대한전기학회 2012 대한전기학회 학술대회 논문집 Vol.2012 No.5
국내 계통은 심각한 고장에 따른 고장파급을 방지하기 위하여 부하차단 시스템을 운영하고 있다. 고장파급방지시스템을 설계하기 위해서는 차단되어야 할 부하 및 용량, 차단 지연시간을 선정하여야 한다. 차단 부하후보지 및 용량은 정상상태 해석을 통하여 선ㆍ산정할 수 있으며, 차단 지연시간은 동적해석을 통하여 적정시간을 선정하게 된다. 현행 UVLS시스템은 정상상태해석을 통해 산정된 부하차단량을 1단계에 전량 차단하고 있다. 하지만 계통상황이 실시간으로 변하고 있는 만큼 다단계 부하차단계획을 통해 부하차단량을 기존보다 감소할 수 있을 것이다. 이러한 배경에서 모터부하의 비율은 매우 중요한 역할을 한다. 이에 따라 모터부하의 비율에 따른 다단계 부하차단량 및 차단시간을 검토한다. 본 논문에서 검토된 결과는 향후 다단계 부하차단계획 및 차단시간을 산정하기 위한 자료로 활용될 수 있다.
사용자 편의성을 고려한 전력계통 해석 프로그램 개발 연구
고백경(Baekkyeong Ko),송지영(Jiyoung Song),한상욱(Sangwook Han),이재걸(Jaegul Lee),신정훈(Jeonghoon Shin),안용호(Youngho An) 대한전기학회 2016 전기학회논문지 Vol.65 No.1
Power system engineers use power systems solution programs such as PSS/E, DSATool, Power World simulators for power system analysis. In this reason, KEPCO has begun to develop independent power system program, KW-PSS(KEPCO World Power system Solution) since 2002 and KW-PSS ver2.0 development was completed in 2011. However, it did not have much better functions compared with other programs. Therefore, we focused on the development of the practical and specialized functions. Consequently, PAZ(Power system AnalyZer) ver3.0 has been developed and it realized a differentiation than previous version. In other words, previous version focused on the basic function of power system analysis, PAZ ver3.0 has implemented many automated functions for power system operators were driven maximize operational efficiency. The unique feature of the implementation is as follows : Automated check for exceeding the breaker capacity, Scheduled outage automation, Control-file wizard for various voltage stability analysis, Scenario-based multiple transient stability analysis and Auto calculation of transmission line impedance. As shown in these functions, Those functions provide to use power system analysis easily by automation and simplification for power system engineers. We will secure national expertise through PAZ ver3.0. In addition it will be able to gain competitive edge through the steady development in the world market.
김용학,남수철,고백경,강성범,심관식,Kim, Yonghak,Nam, Suchul,Ko, Baekkyeong,Kang, Sungbum,Shim, Kwansik 한국전력공사 2020 KEPCO Journal on electric power and energy Vol.6 No.3
It is very important to evaluate on/off-line stability to operate the power system stably and economically. Until now, we have continuously secured the operation reliability of the power system through the evaluation of transient, voltage and small signal stability. This paper proposes that it is possible to operate in KWAMS by applying the multi-section analysis and subspace methods and verifying the reliability of the algorithms to directly estimate the dominant oscillation mode of the power system from the signal waveform acquired from the phasor measurement units. In addition, this paper shows that the dominant oscillation mode can be detected from real-time measurement data in power systems. Therefore, if we can monitor the state of the power system in real time, it is possible to avoid a large-scale power outage by knowing the possibility of the power system accident in advance.
강성범(Sungbum Kang),고백경(Baekkyeong Ko),남수철(Suchul Nam),최영도(Youngdo Choi),김용학(Yonghak Kim),전동훈(Donghoon Jeon) 대한전기학회 2019 전기학회논문지 Vol.68 No.9
Recently, innovative techniques in artificial intelligence such as machine learning have emerged to efficiently process huge amounts of big data delivered from PMUs to WAMS. Through processing raw data and analyzing big data, It delivers highly useful and valuable system status information to system operators. The types of machine learning vary depending on the usage, but the CNN (Convolution Neural Network) model is mainly used for the post analysis and fault detection(classification) in the power system. In this paper, based on PMU big data, we study the power system fault classification model by using CNN Model. Using Convolution neural network model based on KERAS, the database for each fault type was built and supervised learning was conducted for the model. The constructed model was verified with test data and the validity of the model was verified by inputting the actual power system fault data for the trained model. As a result, developed model classified correctly for the actual fault.