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순환여과식 양식장 해수 열원 히트펌프 시스템의 전력 소비량 예측을 위한 인공 신경망 모델

Power consumption prediction model based on artificial neural networks for seawater source heat pump system in recirculating aquaculture system fish farm

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참고문헌

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주제분류수산학

초록

본 연구에서는 순환여과식 시스템의 해수 열원 히트펌프의 전력 소비량 예측을 위한 인공신경망(ANN) 모델의 적용을 다룬다. 히트펌프 시스템을 적용한 순환여과식 시스템의 전력 소비량 예측을 위한 ANN 모형의 입출력 자료를 얻기 위해 TRNSYS 프로그램을 이용하여 통합 동적 시뮬레이션 모델을 구축하였다. TRNSYS 프로그램에서 얻은 자료는 선형회귀분석을 이용하여 분석한 후, 정규화를 통해 ANN 모델에 필요한 최적의 데이터로 변환하였다. ANN 기반의 전력 소비량 예측 모델을 최적화하기 위해 베이지안 최적화를 이용하여 ANN의 하이퍼 파라미터를 결정하였다. 하이퍼 파라미터가 최적화된 ANN 모델의 예측 결과는 ASHRAE 기준을 충족하며 예측 정확도가 매우 높음을 확인하였다.

Abstract

This study deals with the application of an artificial neural network (ANN) model to predict power consumption for utilizing seawater source heat pumps of recirculating aquaculture system. An integrated dynamic simulation model was constructed using the TRNSYS program to obtain input and output data for the ANN model to predict the power consumption of the recirculating aquaculture system with a heat pump system. Data obtained from the TRNSYS program were analyzed using linear regression, and converted into optimal data necessary for the ANN model through normalization. To optimize the ANN-based power consumption prediction model, the hyper parameters of ANN were determined using the Bayesian optimization. ANN simulation results showed that ANN models with optimized hyper parameters exhibited acceptably high predictive accuracy conforming to ASHRAE standards.

참고문헌 (23)

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