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계통 사고시 6.6kV 전동기 모선의 안정적 절체를 위한 계전기 Logic 연구
조영식(Yeong-Sik Cho),문원식(Won-Sik Moon),김재철(Jae-Chul Kim) 한국조명·전기설비학회 2016 조명·전기설비학회논문지 Vol.30 No.5
Recently at many industrial factories, distribution buses for critical loads are installed redundancy system. This system is divided from main Transformer to distribution buses. Generally this bus arrangement is in a incoming-tie-incoming arrangement. If the loss of the power is happened, that bus must be transferred to the alternate bus without damaging the equipment, and ideally, without interrupting the facilities process. This paper explains the conditions for fast transferring without damaging the equipment, without uncontrolled operating in emergency situations. And it describes the relay logic including these conditions and checks the duration time for transferring. The duration time is key of fast transferring without any problem. The system voltage stabilities using this transfer duration time is also included.
제조업 전력량 예측 정확성 향상을 위한 Double Encoder-Decoder 모델
조영창 ( Yeongchang Cho ),고병길 ( Byung Gill Go ),성종훈 ( Jong Hoon Sung ),조영식 ( Yeong Sik Cho ) 한국정보처리학회 2020 정보처리학회논문지. 소프트웨어 및 데이터 공학 Vol.9 No.12
This paper investigated methods to improve the forecasting accuracy of the electricity consumption prediction model. Currently, the demand for electricity has continuously been rising more than ever. Since the industrial sector uses more electricity than any other sectors, the importance of a more precise forecasting model for manufacturing sites has been highlighted to lower the excess energy production. We propose a double encoder-decoder model, which uses two separate encoders and one decoder, in order to adapt both long-term and short-term data for better forecasts. We evaluated our proposed model on our electricity power consumption dataset, which was collected in a manufacturing site of Sehong from January 1st, 2019 to June 30th, 2019 with 1 minute time interval. From the experiment, the double encoder-decoder model marked about 10% reduction in mean absolute error percentage compared to a conventional encoder-decoder model. This result indicates that the proposed model forecasts electricity consumption more accurately on manufacturing sites compared to an encoder-decoder model.