인공지능(AI) 기반 냉동시스템 제어를 통한 저온물류센터 에너지 효율화 방안 연구

다국어 초록 (Multilingual Abstract)

As the demand for cold chain logistics for the distribution of fresh food or medicine increased, the domestic cold chain logistics center increased rapidly. Due to the nature of managing low temperature, cold chain logistics requires a lot of energy consumption. In order to cope with the rise in global energy prices and carbon neutrality policies, the establishment of a platform for converting cold chain warehouses to energy efficiency and low energy consumption structures continues to be required. In this study, we focused on the energy efficiency of the refrigeration system with the largest energy load in the operation of the cold chain distribution center, and developed an energy management system operation model through two AI-based refrigeration system control algorithms for effective energy reduction; 1) 3 dimentional temperature mapping and unit-cooler control algorithm through AI learning; 2) AI based automatic defrosting algorithm. In order to verify the energy reduction effect of this control system, it was quantitatively analyzed through experiments in an area of 100? chamber; 1) By applying 3D temperature mapping and unit-cooler control algorithm, unit cooler power consumption is reduced by 19.8% (from 65.85 kWh to 51.97 kWh for 12 hours) ; 2) By applying AI-based automatic defrosting algorithm, 48% reduction in defrosting power consumption (from 532.2 kWh to 271.9 kWh for 24 hours). In the future, it is expected to contribute to reducing the national energy load and carbon neutrality by applying it to the actual cold chain distribution center.

목차 (Table of Contents)

• Abstract
• 서론
• 재료 및 방법
• 1. 에너지 저감 실험을 위한 저온물류창고 파일럿(Pilot)테스트 베드 구성
• 2. 적용된 인공지능(AI)기반 제어 알고리즘
• 3. 실험방법 및 환경 조건
• 4. 시험 결과
• 결론
• 감사의 글
• 참고문헌