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논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2025.11
- 수록면
- 2,306 - 2,311 (6page)
이용수
초록· 키워드
As electric vehicles (EVs) gain traction as energy resources, Vehicle-to-Building (V2B) technology enables parked EVs to participate in building-level energy management by performing both charging and discharging. This paper proposes a scheduling framework for optimizing EV charging and discharging over a 48-hour horizon using a Mixed-Integer Quadratic Programming (MIQP) model. The scenario assumes unified ownership of the building, chargers, and EVs. The model aims to maximize economic value through energy arbitrage based on time-of-use pricing while minimizing building demand charges by suppressing peak power. Unlike previous MILP-based approaches, which control peak demand using linear penalties or slack variables, the proposed MIQP formulation introduces a quadratic penalty term to more accurately penalize peak demand excursions. The model incorporates real-world constraints including EV state-of-charge (SoC), arrival/departure schedules, charger limits, and building load profiles. Simulation results demonstrate that the MIQP-based strategy outperforms conventional MILP models in both cost savings and peak reduction robustness, providing a practical basis for treating EVs as flexible energy assets in building operations.
#EMS(energy management system)
#optimization
#VPP(virtual power plant)
#V2G(vehicle to grid)
#V2B(vehicle to building)
#MIP(mixed integer programming)
#MILP(mixed integer linear programming)
#MIQP(mixed integer quadratic programming)
#EV(Electric Vehicle)
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목차
- Abstract
- 1. 서론
- 2. 본론
- 3. 결론
- References
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