An Information Framework for Enhancing Coordination Between Aggregator and Grid-Interactive Efficient Buildings = Grid-Interactive Efficient Buildings과 어그리게이터 간 효율적 정보연계 체계

다국어 초록 (Multilingual Abstract)

Advancements in building energy management have enabled grid-interactive efficient buildings (GEBs) to provide multiple grid services, creating new coordination demands for aggregators responsible for integrating building-level flexibility into demand response (DR) programs. However, existing DR coordination mechanisms designed for earlier generations of single service, low-automation buildings are increasingly inadequate for processing the multi-service, multi-dimensional flexibility profiles produced by GEBs. To address this challenge, this study proposes an aggregation and coordination approach that restructures how aggregators interpret and utilize building-level flexibility information. By introducing a unified and scalable representation of coupled demand response and frequency regulation flexibility, the method reduces computational and operational complexity in the aggregator’s decision process. Simulation results demonstrate that the proposed approach enables more efficient, tractable multi-service scheduling and provides a viable pathway for integrating GEBs flexibility into modern DR programs.

목차 (Table of Contents)

• CHAPTER 1. Introduction 1
• 1.1 Introduction 1
• 1.2 Research Contributions 3
• 1.3 Related Work 6
• 1.3.1 Related Works 6
• 1.3.2 Research Gaps 10
• CHAPTER 2. Theoretical Background 13
• 2.1 Comparison of Building Models 13
• 2.1.1 Definition of Building Models 13
• 2.1.2 Grid-Interactive Efficient Buildings 18
• 2.1.3 Key Feature-Based Comparative Analysis 19
• 2.3 Demand response and Flexibility 26
• 2.3.1 Demand Response 26
• 2.3.2 Flexibility and Flexibility Potential 31
• CHAPTER 3. Methodology 35
• 3.1 Building to Aggregator Information 35
• 3.2 Binary Selection Cost Surface 40
• 3.3 Continuous Cost Surface Optimization 42
• 3.4 Lagrangian-Based Augmented Optimization 45
• 3.4.1 Lagrangian-Based Coordinated Optimization 45
• 3.4.2 Proposed Model 47
• CHAPTER 4. Simulation Results and Comparison Analysis 50
• CHAPTER 5. Conclusion 60
• References 62