This study presents an optimization model for battery scheduling in Advanced Air Mobility (AAM) operations considering congested (peak-hour) flight periods. Peak-hour demand concentration causes bottlenecks in vertiport charging/swapping facilities and accelerates battery degradation, reducing operational efficiency. A Mixed-Integer Linear Programming (MILP) model is developed, incorporating battery states (SoC, SoH), charger and swap-bay constraints, and power peak limits. Simulation results under peak and off-peak scenarios show that the proposed model reduces both delay time and total operating cost compared to average-demand scheduling. This study provides a quantitative decision-making basis for enhancing resource efficiency in AAM operations. The findings offer practical implications for improving AAM infrastructure efficiency and resource management policies.

Abstract
1. 서 론
2. 관련 이론 및 선행 연구 고찰
    2.1. AAM 및 eVTOL 에너지 인프라
    2.2 배터리 교환 스테이션 운영 및 스케줄링 관련연구
    2.3 수요예측 및 시뮬레이션 기반 연구
3. 모델링 및 수학적 정식화
    3.1 모델 개요 및 구성 요소
    3.2 목적함수 정립
    3.3 모델 해석 및 계산
4. 결과 및 고찰
    4.1 시뮬레이션 환경 및 변수 설정
    4.2 시뮬레이션 결과
5. 결 론
    5.1. DER + ESS 통합 운용의 효과
    5.2. 부하 평준화와 안전성 확보
    5.3. 시사점 및 향후 연구
후 기
References

• 정의태(Division of Unmanned Aerial Vehicles, Kyungwoon University, Professor) | Euitae Jeong
• 이우람(Division of Unmanned Aerial Vehicles, Kyungwoon University, Professor) | Wooram Lee Corresponding author
• 유현수(Head of Business Strategy and Director of the Corporate Research Institute at a software development firm) | Hyunsoo Yoo