KEPCO Journal on Electric Power and Energy

Korea Electric Power Corporation (한국전력공사)
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Development of Comparative Verification System for Reliability Evaluation of Distribution Line Load Prediction Model

배전 선로 부하예측 모델의 신뢰성 평가를 위한 비교 검증 시스템

  • Lee, Haesung (KEPCO Research Institute, Korea Electric Power Corporation) ;
  • Lee, Byung-Sung (KEPCO Research Institute, Korea Electric Power Corporation) ;
  • Moon, Sang-Keun (KEPCO Research Institute, Korea Electric Power Corporation) ;
  • Kim, Junhyuk (KEPCO Research Institute, Korea Electric Power Corporation) ;
  • Lee, Hyeseon (KEPCO Research Institute, Korea Electric Power Corporation)
  • Received : 2020.09.16
  • Accepted : 2020.10.20
  • Published : 2021.06.30
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Abstract

Through machine learning-based load prediction, it is possible to prevent excessive power generation or unnecessary economic investment by estimating the appropriate amount of facility investment in consideration of the load that will increase in the future or providing basic data for policy establishment to distribute the maximum load. However, in order to secure the reliability of the developed load prediction model in the field, the performance comparison verification between the distribution line load prediction models must be preceded, but a comparative performance verification system between the distribution line load prediction models has not yet been established. As a result, it is not possible to accurately determine the performance excellence of the load prediction model because it is not possible to easily determine the likelihood between the load prediction models. In this paper, we developed a reliability verification system for load prediction models including a method of comparing and verifying the performance reliability between machine learning-based load prediction models that were not previously considered, verification process, and verification result visualization methods. Through the developed load prediction model reliability verification system, the objectivity of the load prediction model performance verification can be improved, and the field application utilization of an excellent load prediction model can be increased.

Keywords

Acknowledgement

본 연구는 한국전력공사 전력연구원의 2017년 자체과제로 수행한 '상태추론 기반 배전설비 예지 기술 및 엔진 개발' 연구과제의 기술개발 결과임.

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