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지평식(Pyeong-Shik Ji),임재윤(Jae-Yoon Lim) 대한전기학회 2015 전기학회논문지 P Vol.64 No.2
With the improvement of living standards and economic development, electricity consumption continues to grow. The electricity is a special energy which is hard to store, so its supply must be consistent with the demand. The objective of electricity demand forecasting is to make best use of electricity energy and provide balance between supply and demand. Hence, it is very important work to forecast electricity demand with higher precision. So, various forecasting methods have been developed. They can be divided into five broad categories such as time series models, regression based model, artificial intelligence techniques and fuzzy logic method without considering special-day effects. Electricity demand patterns on holidays can be often idiosyncratic and cause significant forecasting errors. Such effects are known as special-day effects and are recognized as an important issue in determining electricity demand data. In this research, we developed the power demand forecasting method using ELM(Extreme Learning Machine) for special day, particularly, lunar new year and Chuseok holiday.
인가전압의 특성을 고려한 주거용 부하의 전류성분 추정기법 개발
지평식(Pyeong-Shik. Ji) 대한전기학회 2011 전기학회논문지 P Vol.60 No.4
Due to the increasing of nonlinear loads such as converters and inverters connected to the electric power distribution system, and extensive application of harmonic generation sources with power electronic devices, disturbance of the electric power system and its influences on industries have been continuously increasing. Thus, it is difficult to construct accurate load model for active and reactive power in environments with harmonics. In this research, we develop current harmonics estimation method based on Extreme Learning Machine (ELM) with fast learning procedure for residential loads. Using data sets acquired from various residential loads, the proposed method has been intensively tested. As the experimental results, we confirm that the proposed method makes it possible to effective estimate current harmonics for various input voltage.
뉴로-퍼지 추론 시스템 기반 주거용 부하의 모델링 기법
지평식(Pyeong-Shik Ji),이종필(Jong-Pil Lee),이대종(Dae-Jong Lee),임재윤(Jae-Yoon Lim) 대한전기학회 2011 전기학회논문지 P Vol.60 No.1
In this study, we proposed a residential load modeling method based on neuro-fuzzy inference system by considering of various harmonics. The developed method was implemented by using harmonic information, fundamental frequency and voltage which are essential input factors in conventional method. Thus, the proposed method makes it possible to effectively estimate load characteristics in power lines with harmonics. To show the effectiveness, the proposed method has been intensively tested with various dataset acquired under the different frequency and voltage and compared it with a conventional method based on neural networks.
ZigBee기술을 이용한 태양광 발전 모듈의 원격 모니터링 시스템 개발
지평식(Pyeong-Shik Ji),이종필(Jong-Pil Lee),이대종(Dae-Jong Lee),변상준(Sang-Jun Byeon),임재윤(Jae-Yoon Lim) 대한전기학회 2011 대한전기학회 학술대회 논문집 Vol.2011 No.11
본 연구에서는 임베디드 타입의 무선 모듈을 갖는 데이터 취득 장치 개발, 태양전지 고장진단 알고리즘, 실시간 모니터링 프로그램 개발 등을 수행하였으며 사례연구를 통해 그 타당성을 입증하였다. Zigbee 기술을 적용한 태양광 발전모듈의 원격 모니터링 시스템개발로 센서네트워크를 통한 태양광 발전설비에 많이 응용될 것으로 기대되며, Zigbee 기술에 의한 전력설비 제어 및 기존 태양광 발전설비에 적용 방안 연구에 응용한 실용화 연구를 수행되어야 할 것으로 판단된다.
지평식(Pyeong-Shik Ji),문종필(Jong-Fil Moon) 대한전기학회 2012 전기학회논문지 P Vol.61 No.2
Recently, due to the expansion of electric power demands, nonlinear load such as converters and inverters connected to the electric power distribution system, and extensive application of harmonic generation sources with power electric devices, disturbance of the electric power system and its influences on industries have been continuously increasing. In this research, power quality was analyzed for 11 extra-high voltage customers by considering voltage unbalance condition, power factor, THD and TDD. This research will be utilized as fundamental data to improve power quality for power utility.
주거용 부하에 대한 고조파 영향 분석 및 개선된 부하모델 개발
池平植(Pyeong-Shik Ji),李大鍾(Dae-Jong Lee),李鍾弼(Jong-Pil Lee),朴在原(Jae-Won Park),林栽尹(Jae-Yoon Lim) 대한전기학회 2008 전기학회논문지 P Vol.57 No.4
In this study, we developed RBFN(Radial Basis Function Networks) based load modeling method with harmonic components. The developed method considers harmonic information as well as fundamental frequency and voltage considered as essential factors in conventional method. Thus, the proposed method makes it possible to effectively estimate load characteristics in power lines with harmonics. RBFN has some advantage such as simple structure and rapid computation ability compared with multi-layer perceptorn which is extensively applied for load modeling. To verify the effectiveness, the proposed method has been intensively tested with various dataset acquired under the different frequency and voltage and compared it with conventional methods such as polynomial method, MLPN and RBFN with no harmonic components.
FCM과 ELM을 이용한 전력용 변압기의 모니터링 알고리즘
지평식(Pyeong-Shik Ji),임재윤(Jae-Yoon Lim) 대한전기학회 2012 전기학회논문지 P Vol.61 No.4
In power system, substation facilities have become too complex and larger according to an extended power system. Also, customers require the high quality of electrical power system. However, some facilities become old and often break down unexpectedly. The unexpected failure may cause a break in power system and loss of profits. Therefore it is important to prevent abrupt faults by monitoring the condition of power systems. Among the various power facilities, power transformers play an important role in the transmission and distribution systems. In this research, we develop intelligent diagnosis technique for monitoring of power transformer by FCM(Fuzzy c-means) and ELM(Extreme Learning Machine). The proposed technique make it possible to diagnosis the faults occurred in transformer. To demonstrate the validity of proposed method, various experiments are performed and their results are presented.