반도체디스플레이기술학회지 (Journal of the Semiconductor & Display Technology)

한국반도체디스플레이기술학회 (The Korean Society Of Semiconductor & Display Technology)
권호 표지

랜덤 환경조건 기반의 태양광 모듈 인공신경망 모델링

Artificial Neural Network Modeling for Photovoltaic Module Under Arbitrary Environmental Conditions

  • 백지혜 (상명대학교 시스템반도체공학과) ;
  • 이종환 (상명대학교 시스템반도체공학과)
  • Baek, Jihye (Department of System Semiconductor Engineering, Sangmyung University) ;
  • Lee, Jonghwan (Department of System Semiconductor Engineering, Sangmyung University)
  • 투고 : 2022.12.01
  • 심사 : 2022.12.13
  • 발행 : 2022.12.31
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초록

Accurate current-voltage modeling of solar cell systems plays an important role in power prediction. Solar cells have nonlinear characteristics that are sensitive to environmental conditions such as temperature and irradiance. In this paper, the output characteristics of photovoltaic module are accurately predicted by combining the artificial neural network and physical model. In order to estimate the performance of PV module under varying environments, the artificial neural network model is trained with randomly generated temperature and irradiance data. With the use of proposed model, the current-voltage and power-voltage characteristics under real environments can be predicted with high accuracy.

키워드

과제정보

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. 2022R1I1A3064285).

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