건물 공조·조명 설비의 운영 및 유지관리 개선을 위한 디지털 트윈 기반 환경 적응 프레임워크 개발 = Digital Twin-based Environmental Adaptation Framework for Enhanced Operations and Maintenance of Building HVAC and Lighting Systems

다국어 초록 (Multilingual Abstract)

The operations and maintenance (O&M) phase, which spans the longest period in a building’s lifecycle, accounts for a substantial share of overall costs, energy consumption, and carbon emissions. As global climate change intensifies and buildings account for a substantial share of worldwide energy consumption and greenhouse gas emissions, addressing challenges during the O&M phase has become increasingly urgent. Traditional O&M practices often fail to continuously account for dynamic environmental factors such as equipment anomalies and aging, occupant behavior patterns, and climate variability. Over time, this can lead to accumulated issues such as degraded performance, reduced service reliability, and increased costs and carbon emissions.
To overcome these limitations, this research proposes a digital twin-based environmental adaptation framework for building energy systems. The framework integrates heterogeneous data into a digital twin environment, including monitoring and actuator signal data acquired from building systems, as well as external data sources such as energy pricing, weather conditions, and event schedules through APIs. This structure enables continuous recognition of and response to complex environmental changes affecting O&M processes. In contrast to conventional, static O&M methods, the proposed framework leverages a self-learning mechanism that dynamically adapts to environmental changes by integrating three key functions required across O&M phase.
During the operational phase, the framework employs a self-optimizing control strategy to optimally manage equipment and respond to short-term environmental changes. For the maintenance phase, it utilizes a self-monitoring strategy to prevent and diagnose equipment degradation and failures. Additionally, a self-evolving strategy is introduced to derive directions for long-term facility improvements by energy auditing. By integrating these comprehensive strategies—covering equipment utilization, maintenance, and enhancement—into the digital twin environment, building energy systems can achieve the potential to continuously adapt to changing environments.
This research focuses on designing the framework for HVAC and lighting systems, which account for a significant portion of energy consumption and are directly influenced by environmental changes. Through case studies, the framework was applied and validated, with each of its core functionalities examined. As a result, under dynamic environmental conditions, this approach demonstrated the ability to reduce thermal and air-quality discomfort and lower energy costs during the operation stage when compared to traditional static methods. During the maintenance stage, the framework enhanced fault detection performance, enabled timely responses to unknown faults, and provided updated improvement strategies reflecting changes in environmental conditions. The digital twin-based environmental adaptation framework is expected to contribute to establishing more sophisticated and sustainable O&M strategies in buildings and the built environment, where variability continues to intensify. Furthermore, it is anticipated to serve as a key component in improving occupant comfort, reducing O&M costs, and ultimately achieving carbon reduction targets in the building sector.

목차 (Table of Contents)

• 제 1 장 서 론 1
• 1.1 연구 배경 및 목적 1
• 1.1.1 연구 배경 1
• 1.1.2 연구 목적 4
• 1.2 연구 범위 및 방법 6
• 1.2.1 연구 범위 6
• 1.2.2 연구 방법 6
• 1.3 용어의 정의 9
• 제 2 장 운영 및 유지관리 과정에서의 환경 변화 대응 12
• 2.1 환경 변화 대응의 필요성 12
• 2.1.1 운영 및 유지관리 개요 12
• 2.1.2 환경 변화의 영향 13
• 2.2 배경 기술 및 연구 동향 16
• 2.2.1 제어 최적화 16
• 2.2.2 고장 검출 및 진단 21
• 2.2.3 에너지진단 24
• 2.3 디지털 트윈의 활용 잠재력 27
• 2.3.1 디지털 트윈 개요 27
• 2.3.2 환경 적응 메커니즘 31
• 제 3 장 디지털 트윈 기반 환경 적응 프레임워크 제안 33
• 3.1 적용 목적 및 범위 33
• 3.1.1 목적 및 기능적 요구사항 33
• 3.1.2 적용 대상 및 범위 34
• 3.2 작동 메커니즘 36
• 3.2.1 디지털 트윈 구조 36
• 3.2.2 변화 인지 프로세스 38
• 3.2.3 변화 대응 프로세스 51
• 3.3 적용 절차 58
• 3.3.1 운영 최적화 기능 적용 절차 58
• 3.3.2 유지관리 지원 기능 적용 절차 62
• 제 4 장 디지털 트윈 기반 환경 적응 프레임워크 적용 67
• 4.1 사례 연구 개요 67
• 4.1.1 적용 목적 67
• 4.1.2 대상 건물 및 설비 시스템 67
• 4.2 공조 설비에 대한 프레임워크 적용 73
• 4.2.1 검증용 물리 모델 구축 73
• 4.2.2 데이터셋 구축 80
• 4.2.3 프레임워크 적용 83
• 4.3 조명 설비에 대한 프레임워크 적용 100
• 4.3.1 사전 정보 구축 100
• 4.3.2 현장 데이터 수집 102
• 4.3.3 프레임워크 적용 104
• 제 5 장 공조·조명 설비의 환경 적응 효과 평가 108
• 5.1 평가 방법 108
• 5.1.1 평가 절차 108
• 5.1.2 평가 지표 111
• 5.2 환경 변화 시나리오 114
• 5.2.1 재실자 행동 변화 114
• 5.2.2 에너지 요금 변화 118
• 5.2.3 설비 상태 변화 118
• 5.3 환경 적응 효과 120
• 5.3.1 운영 최적화 120
• 5.3.2 유지관리 지원 130
• 제 6 장 결 론 136
• 6.1 연구 요약 및 결론 136
• 6.2 한계점 및 향후 연구 139
• 참고문헌 141
• Abstract 161
• Appendix 164