기화 설비의 토출 온도 예측을 위한 인공지능 모델 개발

• 영문명: Development of Artificial Intelligence Model for Outlet Temperature of Vaporizer
• 발행기관: 한국산업경영시스템학회
• 저자명: 이상현(Sang-Hyun Lee) 조기정(Gi-Jung Cho) 신종호(Jong-Ho Shin)
• 간행물 정보: 『산업경영시스템학회지』제44권 제2호, 85~92쪽, 전체 8쪽
• 주제분류: 공학 > 산업공학
• 파일형태: PDF
• 발행일자: 2021.06.30

영문 초록

Ambient Air Vaporizer (AAV) is an essential facility in the process of generating natural gas that uses air in the atmosphere as a medium for heat exchange to vaporize liquid natural gas into gas-state gas. AAV is more economical and eco-friendly in that it uses less energy compared to the previously used Submerged vaporizer (SMV) and Open-rack vaporizer (ORV). However, AAV is not often applied to actual processes because it is heavily affected by external environments such as atmospheric temperature and humidity. With insufficient operational experience and facility operations that rely on the intuition of the operator, the actual operation of AAV is very inefficient. To address these challenges, this paper proposes an artificial intelligence-based model that can intelligent AAV operations based on operational big data. The proposed artificial intelligence model is used deep neural networks, and the superiority of the artificial intelligence model is verified through multiple regression analysis and comparison. In this paper, the proposed model simulates based on data collected from real-world processes and compared to existing data, showing a 48.8% decrease in power usage compared to previous data. The techniques proposed in this paper can be used to improve the energy efficiency of the current natural gas generation process, and can be applied to other processes in the future.

목차

1. 서 론

2. 공기식 기화기

3. 데이터 수집

4. 모델 개발

5. 결론 및 토의

키워드

AI AAV Multiple Regression Analysis Deep Neural Network Vaporizer