반도체디스플레이기술학회지 (Journal of the Semiconductor & Display Technology)

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

태양광 시스템의 인공신경망 기반 I-V 특성 모델링 향상

Improved Modeling of I-V Characteristic Based on Artificial Neural Network in Photovoltaic Systems

  • 박지원 (상명대학교 시스템반도체공학과) ;
  • 이종환 (상명대학교 시스템반도체공학과)
  • Park, Jiwon (Department of System Semiconductor Engineering, Sangmyung University) ;
  • Lee, Jonghwan (Department of System Semiconductor Engineering, Sangmyung University)
  • 투고 : 2022.09.16
  • 심사 : 2022.09.21
  • 발행 : 2022.09.30
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초록

The current-voltage modeling plays an important role in characterizing photovoltaic systems. A solar cell has a nonlinear characteristic with various parameters influenced by the external environments such as the irradiance and the temperature. In order to accurately predict current-voltage characteristics at low irradiance, the artificial neural networks are applied to effectively quantify nonlinear behaviors. In this paper, a multi-layer perceptron scheme that can make accurate predictions is employed to learn complex formulas for large amounts of continuous data. The simulated results of artificial neural networks model show the accuracy improvement by using MATLAB/Simulink.

키워드

과제정보

This result is a study conducted by the Ministry of Environment and Korea Environmental Industry and Technology Institute's 2022 green convergence professional manpower training support project.

참고문헌

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