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RISS 인기검색어
- 검색키워드
- 주제어 : Distribution asset condition prediction model (검색결과 2 건)
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배전 자산 상태예측 모델 성능 개선을 위한 기계학습 데이터 관리 시스템 개발
이해성(Hae-Sung Lee),이병성(Byung-Sung Lee) 대한전기학회 2021 전기학회논문지 Vol.70 No.9
The predictive information provided through the electric distribution asset failure prediction model is used as key information for transmission and distribution investment plans in consideration of new and renewable energy, distribution line capacity analysis, or distributed power location analysis. The predictive performance of the distribution asset failure prediction model is affected by the quality of the training data. Also, due to the characteristics of the highly volatile electrical distribution line, the electric distribution asset failure prediction model should maintain the predictive performance at a certain level by performing periodical machine learning on newly generated data. In this paper, we develop an automated system for machine learning data quality management in order to continuously manage machine learning data and efficiently improve electric distribution asset condition prediction model. As a result, our system make it possible to effectively shorten the development time and the cost of the electric distribution asset failure prediction model through the provision of high-quality data for training the prediction model. And the system developed in this paper will be able to improve the accuracy of electric distribution asset condition prediction model.
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저압 배전망에 접속된 분산전원이 고객 전압 관리에 미치는 영향 분석
이해성,임한민,이병성,김동섭 대한전기학회 2024 전기학회논문지 Vol.73 No.2
Voltage control has become more complex as distributed energy resources or electrical vehicles increase, but voltage control is essential to continuously increase the amount of power distribution lines connected to distributed energy resources. In this paper, we perform voltage measurement data analysis through AMI(Advanced Metering Infrastructure) to prevent voltage quality degradation due to connections of distributed energy resources through appropriate voltage control and to find ways to maintain a certain level of voltage quality. Through the analysis, it is possible to identify the correlation and voltage level of voltage changes due to the connection of distributed energy resources. Because OLTC(On Load Tap Changer) enables voltage regulation and phase shifting by varying the transformer ratio under load without interruption, OLTC is a representative voltage control method. Therefore, we attempt to understand the effect of applying OLTC which are representative voltage control method and the voltage quality management effect of distributed energy resource connection lines through the analysis of voltage volatility correlation for distributed energy resources. In addition, we attempt to find an appropriate control method to maintain the voltage quality of distribution lines connected to distributed energy resources.
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