KEPCO Journal on Electric Power and Energy

Korea Electric Power Corporation (한국전력공사)
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A Research on the Energy Data Analysis using Machine Learning

머신러닝 기법을 활용한 에너지 데이터 분석에 관한 연구

  • Kim, Dongjoo (KEPCO Research Institute, Korea Electric Power Corporation) ;
  • Kwon, Seongchul (KEPCO Research Institute, Korea Electric Power Corporation) ;
  • Moon, Jonghui (KEPCO Research Institute, Korea Electric Power Corporation) ;
  • Sim, Gido (KEPCO Research Institute, Korea Electric Power Corporation) ;
  • Bae, Moonsung (KEPCO Research Institute, Korea Electric Power Corporation)
  • Received : 2021.07.12
  • Accepted : 2021.09.27
  • Published : 2021.12.30
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Abstract

After the spread of the data collection devices such as smart meters, energy data is increasingly collected in a variety of ways, and its importance continues to grow. However, due to technical or practical limitations, errors such as missing or outliers in the data occur during data collection process. Especially in the case of customer-related data, billing problems may occur, so energy companies are conducting various research to process such data. In addition, efforts are being made to create added value from data, which makes it difficult to provide such services unless reliability of data is guaranteed. In order to solve these challenges, this research analyzes prior research related to bad data processing specifically in the energy field, and propose new missing value processing methods to improve the reliability and field utilization of energy data.

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Acknowledgement

본 연구는 국토교통부 국토교통과학기술진흥원의 스마트시티 혁신성자동력 프로젝트 지원으로 수행되었음 (과제번호 21NSPS-B149869-04)

References

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