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Energy Management Strategies for Electric Aircraft Charging Leveraging Active Landside Vehicle-to-Grid

Finn Vehlhaber, Mauro Salazar

TL;DR

The paper tackles the energy burden of charging electric aircraft by leveraging the energy-buffering capacity of parked electric vehicles via vehicle-to-grid (V2G) at airports. It develops a modeling-and-optimization framework that couples aggregated landside fleet dynamics, represented by partial differential equations (PDEs), with a linear-programming (LP) formulation to minimize airport grid costs while coordinating aircraft charging and landside V2G. The approach is validated on a KLM hub-and-spoke network using real electricity prices and synthetic parking data, revealing up to 32% cost savings with substantial V2G participation and notable peak-shaving effects. The results illustrate the interdependence of flight networks and energy markets and highlight the practical viability of V2G-enabled airport energy management, while outlining future work on aging, emissions, broader deployment, and real-time control.

Abstract

The deployment of medium-range battery electric aircraft is a promising pathway to improve the environmental footprint of air mobility. Yet such a deployment would be accompanied by significant electric power requirements at airports due to aircraft charging. Given the growing prevalence of electric vehicles and their bi-directional charging capabilities--so-called vehicle-to-grid (V2G)--we study energy buffer capabilities of parked electric vehicles to alleviate pressure on grid connections. To this end, we present energy management strategies for airports providing cost-optimal apron and landside V2G charge scheduling. Specifically, we first formulate the optimal energy management problem of joint aircraft charging and landside V2G coordination as a linear program, whereby we use partial differential equations to model the aggregated charging dynamics of the electric vehicle fleet. Second, we consider a shuttle flight network with a single hub of a large Dutch airline, real-world grid prices, and synthetic parking garage occupancy data to test our framework. Our results show that V2G at even a single airport can indeed reduce energy costs to charge the aircraft fleet: Compared to a baseline scenario without V2G, the proposed concept yields cost savings of up to 32%, depending on the schedule and amount of participating vehicles, and has other potential beneficial effects on the local power grid, e.g., the reduction of potential power peaks.

Energy Management Strategies for Electric Aircraft Charging Leveraging Active Landside Vehicle-to-Grid

TL;DR

The paper tackles the energy burden of charging electric aircraft by leveraging the energy-buffering capacity of parked electric vehicles via vehicle-to-grid (V2G) at airports. It develops a modeling-and-optimization framework that couples aggregated landside fleet dynamics, represented by partial differential equations (PDEs), with a linear-programming (LP) formulation to minimize airport grid costs while coordinating aircraft charging and landside V2G. The approach is validated on a KLM hub-and-spoke network using real electricity prices and synthetic parking data, revealing up to 32% cost savings with substantial V2G participation and notable peak-shaving effects. The results illustrate the interdependence of flight networks and energy markets and highlight the practical viability of V2G-enabled airport energy management, while outlining future work on aging, emissions, broader deployment, and real-time control.

Abstract

The deployment of medium-range battery electric aircraft is a promising pathway to improve the environmental footprint of air mobility. Yet such a deployment would be accompanied by significant electric power requirements at airports due to aircraft charging. Given the growing prevalence of electric vehicles and their bi-directional charging capabilities--so-called vehicle-to-grid (V2G)--we study energy buffer capabilities of parked electric vehicles to alleviate pressure on grid connections. To this end, we present energy management strategies for airports providing cost-optimal apron and landside V2G charge scheduling. Specifically, we first formulate the optimal energy management problem of joint aircraft charging and landside V2G coordination as a linear program, whereby we use partial differential equations to model the aggregated charging dynamics of the electric vehicle fleet. Second, we consider a shuttle flight network with a single hub of a large Dutch airline, real-world grid prices, and synthetic parking garage occupancy data to test our framework. Our results show that V2G at even a single airport can indeed reduce energy costs to charge the aircraft fleet: Compared to a baseline scenario without V2G, the proposed concept yields cost savings of up to 32%, depending on the schedule and amount of participating vehicles, and has other potential beneficial effects on the local power grid, e.g., the reduction of potential power peaks.
Paper Structure (7 sections, 12 equations, 5 figures)

This paper contains 7 sections, 12 equations, 5 figures.

Table of Contents

  1. Introduction
  2. Methodology
  3. Airports and Flight Network
  4. Aggregated Landside Fleet Charging Dynamics
  5. Optimization Problem
  6. Numerical Results
  7. Conclusion

Figures (5)

  • Figure 1: Representation of the energy system at an airport with V2G capabilities.
  • Figure 2: Airports served by KLM within 800 km range of EHAM.
  • Figure 3: Cost comparison for three selected days.
  • Figure 4: Number of aircraft on the apron, distribution of EVs, and power breakdown at Schiphol assuming no V2G (top), 2000 (middle) and 6000 (bottom) electric parking spots and 80 MW grid connection for applicable KLM flights on January 22, 2025.
  • Figure 5: SoC evolution for two selected aircraft with different amounts of bi-directional chargers available in the parking lot with an 80 MW grid connection on January 22, 2025 with energy prices at EHAM vs. those at other airports.