Application and Prospects of Vehicle-to-Grid (V2G) Technology for Electric Vehicles in the Civil Aviation Airport Flight Zone

Abstract

Against the backdrop of the global aviation industry’s commitment to achieving the “Net Zero Carbon Emissions by 2050” goal, the issue of superimposed peak loads on distribution networks—arising from the large-scale transition from fossil-fueled to electric Ground Service Equipment (GSE) at civil airports—has become increasingly prominent, emerging as a critical constraint on green airport development. Focusing on the high-value airside area, this paper presents the first systematic review of how Vehicle-to-Grid (V2G) technology can transform electric Ground Service Equipment (e-GSE) from mere “charging loads” into “dispatchable energy storage resources.” The study proposes that, through bidirectional DC charging/discharging and intelligent aggregation technologies, e-GSE fleets operating on predictable schedules can be integrated as flexible regulation units within airport microgrids. To realize this pathway, the study comprehensively examines the core technological framework, encompassing wide-power-range bidirectional charging infrastructure, grid-forming power conversion topologies, standardized communication and grid interconnection interfaces, flight-schedule-based potential assessment and dispatch algorithms, and photovoltaic storage–charging hybrid system integration schemes. The review demonstrates that this technology can not only enhance grid resilience and promote renewable energy accommodation through peak shaving, valley filling, and ancillary services but also yields significant economic benefits. Finally, the study identifies the technical, standardization, and business model barriers hindering large-scale deployment, thereby providing a theoretical reference and a technology roadmap for the energy system planning and construction of future “zero-carbon smart airports”.

1. Introduction

The International Air Transport Association (IATA) and the International Civil Aviation Organization (ICAO) have jointly established the strategic goal of achieving net-zero carbon emissions for the aviation industry by 2050 [1,2]. This commitment imposes unprecedented emission reduction pressures on the global air transport system. As the ground-based hubs of air transport, airports generate carbon emissions primarily from terminal operations, ground handling activities, and the use of aircraft auxiliary power units (APU). Among these sources, the fleet of Ground Service Equipment (GSE)—comprising aircraft tugs, passenger buses, baggage tractors, and other support vehicles—stands out as both a critical focus and a formidable challenge for deep emission reduction at airports, due to its considerable scale and high operational frequency [3].

Against this backdrop, major airports worldwide are actively advancing the transition of GSE fleets from fossil-fueled to electric propulsion. However, this green transformation is accompanied by significant electrical challenges. The large-scale, centralized deployment of DC fast charging loads will inevitably lead to severe superimposed peak loads on airport distribution networks [4]. This not only imposes substantial cost pressures associated with grid capacity expansion but may also pose potential risks to the safety, stability, and power quality of regional electricity supply systems. Consequently, a “green paradox” emerges: the very electrification introduced to achieve cleaner operations may, in turn, exacerbate stress on local power grids.

Vehicle-to-Grid (V2G) technology offers a highly promising and innovative pathway to resolving this paradox. The core premise of V2G is to regard the traction batteries of electric vehicles as distributed energy storage units. Through controlled bidirectional energy flows, these batteries can flexibly participate in grid services—such as load regulation, frequency support, and voltage control—beyond their primary function of fulfilling mobility needs [5,6]. The seminal work of Kempton and Tomić first systematically quantified the capacity potential and economic revenue models of utilizing electric vehicles as mobile energy storage resources for grid services, thereby establishing the theoretical foundation for V2G research [5]. Hu et al. subsequently provided a comprehensive review of management, optimization, and control strategies for electric vehicle fleets within smart grids, furnishing a theoretical framework for the coordinated dispatch of V2G resources [6].

What merits particular attention is that the airside area of an airport presents a near-ideal, high-value setting for the large-scale and commercial deployment of V2G technology. Unlike privately owned electric vehicles scattered across urban areas, electric Ground Service Equipment (e-GSE) operating within the airside area possess distinct advantages: highly predictable operational patterns strictly governed by flight schedules, extended centralized parking durations, considerable aggregate battery capacity, and ease of centralized control [7]. As noted by Bessa and Matos in their review on the economic and technical management of electric vehicle aggregation agents, effective aggregation of fleets is crucial for unlocking their value to the power grid [7]. More importantly, promoting the transformation of airport energy systems carries macro-strategic necessity. The International Civil Aviation Organization (ICAO), in its long-term strategic vision toward 2050, has articulated the global aviation industry’s net-zero carbon emissions goal and formally recognizes airports as pivotal nodes in aviation decarbonization. This recognition provides top-level policy impetus for the application of innovative technologies such as V2G at airports. In this context, a quantitative study by Liu XC et al., based on actual airport operational data, further indicates that a medium-sized airport’s e-GSE fleet could potentially aggregate power capacity on the order of 10–15 MW and energy storage capacity exceeding 20 MWh—a scale comparable to that of a medium-sized stationary energy storage power station. This underscores the substantial flexible resource value inherent in this scenario [8]. Consequently, leveraging V2G technology to transform e-GSE fleets from mere electrical loads into dispatchable energy storage resources, or even virtual power plants, holds profound strategic significance for enhancing the resilience, economic viability, and environmental sustainability of airport energy systems [9,10].

Although extensive research has been conducted on V2G technology for electric vehicles within the academic community, existing reviews have predominantly focused on the passenger car segment or have provided broad technological overviews. A systematic review and forward-looking analysis specifically tailored to the civil airport airside scenario—encompassing the entire technological chain from core hardware and intelligent control to system integration and economic policy—remains conspicuously absent. This study seeks to address this gap by presenting a comprehensive review of cutting-edge academic findings and engineering practices. It aims to provide an in-depth examination of the technological architecture, application paradigms, comprehensive benefits, and critical challenges associated with airport V2G deployment, thereby offering a clear roadmap for future technology development, standard formulation, engineering demonstration, and commercial rollout.

Compared with existing reviews, this study has the following unique contributions. First, it is the first study to provide a full-technology-chain systematic review of V2G applications specifically for electric Ground Service Equipment (e-GSE) in the airside area of civil airports, filling the gap in systematic V2G reviews in the airport scenario. Second, it not only reviews core technologies such as bidirectional charging hardware topologies and grid-forming control, but also, for the first time, incorporates a flight-schedule-driven potential assessment method, multi-timescale dispatch algorithms, and an integrated “PV–storage–charging–discharging–hydrogen” framework into a unified architecture. Third, it proposes a multi-dimensional quantitative benefit assessment framework for airport V2G and provides, for the first time, magnitude estimates based on typical airport data (e.g., 10–15 MW power capacity, over 20 MWh energy storage capacity). Fourth, it systematically identifies non-technical barriers including standardization, safety, business models, and user acceptance, and proposes collaborative breakthrough pathways. To clearly illustrate the differences between this paper and existing representative reviews,

Table 1. Comparison between this review and existing representative reviews.

Review	Scope	Main Limitations	Innovations in This Paper
Kempton & Tomić (2005) [5]	V2G capacity and revenue fundamentals	No airport-specific scenario	Focus on airport airside e-GSE; full technology chain; dispatch algorithms, grid-forming control, standards, business models; quantitative estimates
Hu et al. (2016) [6]	EV fleet management in smart grids	No airport operational constraints
Bessa & Matos (2013, 2015) [7,11]	EV aggregation agents and markets	No consideration of airport load characteristics
Rahman et al. (2016) [12]	Charging infrastructure optimization	Did not cover bidirectional dispatch algorithms
Zhou & Liao (2024) [13]	Airport microgrid review	Did not specifically address V2G and e-GSE aggregation

summarizes the scope and limitations of relevant reviews, alongside the key innovations of this study.

2. Overall Architecture and Multi-Level Coordination of Airport V2G Systems

To achieve the large-scale deployment of V2G within the airside area, it is first necessary to establish a stable, efficient, and scalable system architecture. This architecture serves not merely as a connectivity framework for physical devices, but as a nervous system through which information flows and energy flows interact in an orderly manner and control commands are transmitted across hierarchical layers.

2.1. Classic Three-Layer Architecture and Its Evolution

Early V2G systems typically adopted a classic three-layer architecture, including the Physical Layer, the Aggregation Layer, and the Management Layer. The Physical Layer comprises the underlying e-GSE assets, bidirectional DC charging stations, and associated power electronic conversion equipment, which are responsible for executing specific charging and discharging actions. The Aggregation Layer (also referred to as the Local Control Layer) is centered on a V2G aggregation control platform, which plays a pivotal “bridging” role by consolidating dispersed GSE resources, disaggregating upper-level dispatch instructions into executable control signals, and continuously collecting real-time status data from the underlying assets. The Management Layer consists of either the Airport Energy Management System (A-EMS) or the interface for interacting with the external power grid and electricity market. This layer formulates dispatch schedules based on global optimization objectives, such as minimizing total operational cost, minimizing carbon emissions, or minimizing reliance on the external grid. In their study on the planning of multi-energy system charging stations considering V2G and human factors, Li, C et al. adopted a similar hierarchical optimization framework [14].

With ongoing technological advancements and deeper application penetration, an extended four-layer architecture oriented toward service provision and market interaction is gaining increasing favor. Building upon the classic three-layer model, a Market Interaction Layer is added, specifically dedicated to handling information exchange related to transaction bidding and settlement in electricity spot markets and ancillary service markets (e.g., frequency regulation and reserve services). In their work on planning airport microgrid infrastructure that integrates electric aircraft and parking lot electric vehicles, Guo et al. underscored the necessity of such a system architecture capable of deep coupling with electricity markets [15]. Furthermore, the Device Layer is now delineated with greater granularity, encompassing all hardware units ranging from power conversion modules and battery management systems to on-board vehicle terminals.

2.2. Power Rating Spectrum and Differentiated Equipment Configuration

The airside area hosts a diverse array of GSE types, each exhibiting markedly different power demands and operational profiles. This diversity necessitates that V2G infrastructure possess flexible power adaptation capabilities. A comprehensive power rating spectrum for airport V2G deployment must span from light-duty passenger stairs and guide cars in the 30–50 kW range, through passenger buses and baggage tractors requiring 50–150 kW, up to heavy-duty aircraft tugs demanding 200–350 kW or even higher power levels [8].

For vehicles across this power spectrum, bidirectional charging station configuration strategies must correspondingly be differentiated. Currently, medium-power DC charging stations (60–150 kW) represent the mainstream solution for ensuring the efficient operation of passenger buses and baggage tractors, and constitute the segment where technology is most mature and return on investment is relatively favorable. For high-power equipment such as aircraft tugs, deployment of higher-rated charging stations or the adoption of flexible “one-to-multiple” power allocation strategies becomes necessary. Research by Dora et al. on hybrid energy charging stations suggested that the integrated design and deployment of photovoltaic generation, stationary energy storage, and charging infrastructure spanning various power ratings can effectively smooth charging load impacts, enhance overall system operational efficiency, and improve the instantaneous utilization rate of renewable energy [16].

2.3. Deep Integration Interfaces with Airport Integrated Energy Systems

A V2G system does not operate in isolation; its maximum value is realized through deep coordination with both existing and future airport energy systems. Therefore, defining clear system-to-system interfaces is of critical importance.

Interface with the Airport Energy Management System (A-EMS): This constitutes the most essential coordination interface. The V2G aggregation platform must report its aggregated “virtual storage” parameters—including dispatchable power capacity, available energy capacity, and response time—to the A-EMS, while receiving optimized dispatch commands in return. As noted by Zhou and Liao in their review of airport microgrids and their integrated operation, such coordination is key to enabling multi-energy complementarity and enhancing the overall energy efficiency of the airport [13].

Interface with Distribution Automation Systems/Substations: This interface is employed to receive grid status information (e.g., frequency, voltage) and to execute emergency grid support commands, thereby ensuring that V2G operations comply with distribution network safety requirements.

Interface with Other Distributed Energy Resources (DERs): Looking ahead, airport energy systems will evolve into complex networks encompassing rooftop photovoltaic (PV) generation; stationary energy storage; combined cooling, heating, and power (CCHP) systems; and, potentially, hydrogen energy systems. V2G systems will need to interact with these resources at both the information and energy levels. For instance, charging could be prioritized during periods of abundant PV generation, while discharging could be scheduled during nighttime peak load hours. The study by Muntaser, A et al. on a DC microgrid for airports that integrates hydrogen energy, electric vehicles, photovoltaics, and batteries offers a compelling depiction of this future vision of coordinated multi-energy flows [17].

2.4. Comparison of Airport V2G with Other Scenarios

To more clearly illustrate the uniqueness of airport airside V2G,

Table 2. Comparison of key characteristics of V2G in different scenarios.

Characteristic Dimension	Airport Flight Zone	Urban Public Parking	Residential Area
Operational pattern	Flight-schedule-driven, highly regular	Commuting/travel random	Concentrated at night, scattered during day
Parking duration	Several hours concentrated between flights	1–8 h variable	Typically > 10 h (night)
Aggregated capacity	10–15 MW, easy to control centrally	Strongly affected by parking occupancy	Scattered, relies on home chargers
Dispatch predictability	Very high (based on flight schedules)	Medium	Low
Grid support capability	Frequency regulation, reserves, black start	Mainly peak shaving and valley filling	Mainly demand response
Safety and standards constraints	Aviation safety regulations, ground handling rules	General electrical safety	Household electrical standards

compares the key differences and characteristics of V2G applications in airport, urban public parking, and residential scenarios in terms of operational patterns, energy demand, infrastructure requirements, scalability, and grid support capabilities. The airport scenario, driven by flight schedules, offers significant advantages in dispatchability due to its regularity and centralized parking, but also faces stricter aviation safety constraints.

3. Core Technology Architecture for Bidirectional DC Charging/Discharging

3.1. System Architecture and Power Ratings

A typical bidirectional V2G system deployed within the airport airside area adopts a hierarchical architecture, as illustrated in Figure 1. At the bottom lies the Physical Resource Layer, comprising bidirectional DC charging stations and electric GSE (e-GSE). The intermediate V2G Aggregation Control Platform serves as the middle layer, with primary responsibilities including resource aggregation, communication protocol conversion, and execution of upper-level dispatch commands. At the top resides the Airport Energy Management System (A-EMS), whose core functions entail formulating dispatch schedules based on global optimization objectives—such as minimizing operational cost or carbon emissions—and managing interactions with the external power grid or electricity market.

To accommodate the diverse requirements of Ground Service Equipment (GSE) operating within the airside area, bidirectional DC charging stations must span a wide power spectrum ranging from 30 kW to over 350 kW. At present, medium-power (60–150 kW) DC charging stations constitute the mainstream configuration for ensuring the efficient operation of vehicles such as passenger buses and baggage tractors. Moreover, research indicates that integrating bidirectional charging infrastructure with photovoltaic (PV) generation and stationary Battery Energy Storage Systems (BESS) to form a Hybrid Energy Storage System (HESS) enables the creation of a more flexible and efficient testing and application platform. Such an integrated approach contributes to smoothing fluctuations in renewable energy output and enhancing overall system operational efficiency.

3.2. In-Depth Comparison and Evolution of Mainstream Power Conversion Topologies

The bidirectional DC/DC converter constitutes the core component of a charging station. Among the various topologies, the Dual Active Bridge (DAB) converter has emerged as a focal point of research in both academia and industry, owing to its symmetrical structure, soft-switching capability, and inherent bidirectional power flow characteristics. The power transfer model of this topology can generally be simplified and expressed as follows:

$$P={\displaystyle \frac{n{V}_1{V}_2}{2\pi f_{s}L}}\mathsf{\varphi }(1-{\displaystyle \frac{\left|\mathsf{\varphi }\right|}{\pi }})$$

(1)

where $P$ denotes the transferred power; $\mathrm{n}$ is the transformer turns ratio; $V_1, V_2$ represent the voltages on the primary and secondary sides, respectively; $f_s$ is the switching frequency; $L$ denotes the resonant inductance; and $\varphi$ is the phase-shift angle. By regulating the phase-shift angle $\varphi$, both the magnitude and the direction of the power flow can be precisely controlled.

Dual Active Bridge and Its Variants: The Dual Active Bridge (DAB) topology, characterized by its symmetrical structure, galvanic isolation, soft-switching capability, and inherent bidirectional power flow, has emerged as the preferred solution for both academia and industry at medium power levels (approximately 50 kW) [12]. Its transferred power can be precisely regulated by adjusting the phase-shift angle. In their review of optimization techniques for electric vehicle charging infrastructure, Rahman et al. confirmed the mainstream status of DAB in bidirectional charging applications [12]. However, the conventional DAB topology suffers from high reactive power circulation and degraded efficiency under wide voltage range conditions, such as those encountered when battery voltage fluctuates. To address these limitations, Upputuri and Subudhi, in their comprehensive review of bidirectional charger topologies for V2G/G2V applications, noted that three-level DAB converters, series/parallel DAB configurations, and DAB variants incorporating auxiliary circuits have been extensively investigated to extend the voltage adaptation range, reduce device stress, and improve efficiency [18]. Mandrioli, R et al. proposed a three-level DAB structure that effectively reduces the voltage stress on switching devices, thereby enhancing the converter’s power density and efficiency [19].

Application of Resonant Converters: For applications demanding even higher efficiency and power density, the CLLC resonant converter has gained considerable favor. By achieving soft-switching through resonance, this topology further reduces switching losses and electromagnetic interference (EMI). Addressing electric vehicle charging scenarios, Mahajan et al. proposed a CLLC topology with a wide voltage gain range, which is particularly well-suited for airport GSE applications where battery voltage exhibits significant fluctuation during charging and discharging cycles [20].

Topological Innovations for High-Power Applications: For high-power charging requirements exceeding 350 kW—as necessitated by heavy-duty equipment such as aircraft tugs—topologies including the Modular Multilevel Converter (MMC) and interleaved parallel techniques have been introduced. These approaches serve to elevate power ratings, mitigate current ripple, and enhance system redundancy and reliability.

Topology comparison and airport applicability analysis: Among the above topologies, DAB, due to its simple control and good soft-switching characteristics, is suitable for 30–150 kW passenger buses and baggage tractors; CLLC offers better efficiency over a wide voltage gain range, making it suitable for scenarios with large battery voltage fluctuations; and MMC is suitable for aircraft tugs of ≥350 kW. Overall, for the mainstream medium-power e-GSE in airports, DAB or CLLC topologies using SiC devices are currently the most techno-economically optimal choices.

3.3. Grid-Forming Control: From “Grid Follower” to “Grid Builder”

As the penetration of intermittent renewable energy sources—such as wind and photovoltaic generation—in power systems continues to increase, grid inertia and strength are progressively diminished. Under such conditions, traditional “grid-following” inverters/converters, which rely on phase-locked loops (PLLs), are prone to instability when operating in weak grid environments. This challenge is equally pertinent to scenarios involving the grid integration of a large number of V2G charging stations.

Grid-forming control technology has emerged in response to this challenge. In contrast to grid-following devices that passively track grid voltage and frequency, grid-forming devices are capable of emulating the operational characteristics of synchronous generators. They can autonomously establish and sustain grid voltage and frequency, thereby providing essential inertia and damping to the system. Rathnayake, D.B et al. have conducted systematic investigations into grid-forming inverter control technologies suitable for weak grid applications [21].

Within the V2G domain, grid-forming control endows charging stations with the capability of “actively supporting the power grid.” Yu, J.Y et al. innovatively proposed a design scheme for a grid-forming charging station tailored to V2G applications [22,23]. This scheme integrates an improved Virtual Synchronous Generator (VSG) control algorithm with Model Predictive Control (MPC). The VSG algorithm enables the charging station to exhibit generator-like droop characteristics—specifically, active power–frequency and reactive power–voltage droop—thereby allowing participation in primary frequency regulation and voltage regulation of the grid. Concurrently, MPC is employed to enhance dynamic response speed and accuracy. Experimental results have demonstrated that the proposed grid-forming charging station can achieve flexible four-quadrant operation, with the total harmonic distortion (THD) of the grid-connected current maintained below 2.94%, thereby significantly improving both power quality and the capacity for active grid support [24].

Impact on grid stability and power quality: If large-scale V2G integration is not controlled, it may cause voltage swells, sags, and frequency fluctuations. However, with grid-forming control, V2G resources can actively provide inertia support and voltage regulation, thereby helping to improve power quality. For example, fast reactive power compensation can suppress voltage sags, and primary frequency regulation can limit frequency deviations. Therefore, V2G does not necessarily lead to grid instability; the key lies in adopting advanced control strategies.

3.4. Enabling Devices and Thermal Management Technologies

Advances in hardware performance are inextricably linked to progress in underlying device technologies.

The Wide-Bandgap Semiconductor Revolution: Wide-bandgap (WBG) semiconductor devices, typified by silicon carbide (SiC) and gallium nitride (GaN), are pivotal enablers driving the evolution of V2G charging equipment toward higher efficiency, elevated power density, and compact form factors. Compared with conventional silicon-based devices, SiC and GaN offer superior breakdown electric field strength, faster switching speeds, lower conduction losses, and enhanced high-temperature tolerance. Research by Sakhare et al. demonstrated that bidirectional converters employing SiC MOSFETs can operate at substantially increased switching frequencies, thereby enabling significant reductions in the volume and weight of passive components—such as inductors and transformers—and improving overall system efficiency [25]. The review by Rahman et al. similarly underscored that the adoption of wide-bandgap devices constitutes a critical pathway toward reducing V2G system costs and enhancing economic viability [12]. Sakhare, A et al. have further elaborated on the expansive application prospects of wide-bandgap devices in future V2G converters [25].

Thermal Management and Reliability Design: High power density inevitably entails heightened thermal dissipation challenges. Effective thermal management is a prerequisite for ensuring long-term reliable equipment operation and preventing thermal runaway or failure of power devices. Advanced thermal management solutions, including heat pipe cooling and liquid cooling technologies, are being deployed in high-power charging stations. Concurrently, condition-based predictive maintenance techniques are under active investigation to facilitate early detection of potential faults and to enhance overall system availability. Thermal design and reliability considerations are among the critical physical constraints identified by Thirumalai et al. in their research on V2G system optimization [26].

4. V2G Application Scenarios and Optimal Dispatch in the Airside Area

4.1. Energy Consumption Characteristics of Vehicles and Assessment of V2G Potential

The operational schedules of Ground Service Equipment (GSE) within the airside area are strictly governed by flight timetables, endowing their activities with a high degree of regularity and predictability. As illustrated in Figure 2, by leveraging typical flight wave patterns, both the operational intervals of GSE and the potential V2G response windows can be distinctly identified. For instance, during inter-flight gaps—such as the midday low-activity period—a significant proportion of GSE remains in a centralized parking and charging state, thereby constituting a substantial window of dispatchable V2G potential.

Realistic discussion of operational constraints: Although flight schedules provide predictability, airport operations are also affected by factors such as flight delays, weather disruptions, emergency operations, security rules, and turnaround pressure. During peak periods (e.g., early morning departures and late evening arrivals), key equipment such as aircraft tugs and baggage tractors may not be able to participate in V2G discharging. Therefore, in practical dispatch, “non-dispatchable periods” must be treated as hard constraints, and V2G responses should only be scheduled during idle windows between flights (typically 30 min to 2 h). The potential assessment in this study takes these constraints into account, and the “dispatchable time windows” in Table 1 are based on statistics of idle periods from typical flight wave patterns.

As presented in

Table 3. Analysis of V2G Participation Potential for Principal Types of Electric GSE at Airports.

Vehicle Type	Power Demand	Battery Capacity	Average Daily Operating Hours	Parking Characteristics	V2G Potential Index
Electric Passenger Bus	100–150 kW	200–300 kWh	14–18 h	Fixed schedules; regular parking patterns	★★★★★
Electric Baggage Tractor	50–80 kW	100–150 kWh	12–16 h	Short-duration parking during flight intervals	★★★★☆
Electric Aircraft Tug	200–350 kW	300–500 kWh	8–12 h	Mission-driven; irregular parking	★★☆☆☆
Electric Passenger Stair/Guide Car	30–50 kW	60–100 kWh	10–14 h	Short-duration, scattered parking	★★★☆☆

Potential index calculation method: V2G potential index = w₁·(battery capacity/baseline capacity) + w₂·(average daily idle time/baseline idle time) − w₃·(mission criticality coefficient) + w₄·(charging location availability coefficient). Baseline capacity = 150 kWh, baseline idle time = 3 h, weights w₁ = 0.3, w₂ = 0.4, w₃ = 0.2, w₄ = 0.1. Mission criticality coefficients: aircraft tug = 0.9, baggage tractor = 0.5, passenger bus = 0.3, passenger stair/guide car = 0.4. Star rating: ≥4.5 = ★★★★★, 3.5–4.5 = ★★★★☆, 2.5–3.5 = ★★★☆☆, 1.5–2.5 = ★★☆☆☆.

, we conducted an assessment of the V2G participation potential for the principal types of electric Ground Service Equipment (e-GSE) deployed at airports. Based on an evaluation of their power demand, battery capacity, average daily operating hours, and parking characteristics, electric passenger buses and baggage tractors exhibit the highest V2G dispatch potential, owing to their moderate battery capacities and predictable parking patterns. In contrast, equipment such as aircraft tugs, which are strongly mission-driven and characterized by irregular parking schedules, demonstrate comparatively constrained V2G potential.

4.2. Standardized Communication Protocol Stack and Information Security Fortress

Reliable, secure, and low-latency communication underpins the orderly operation of V2G systems, and standardization serves as the cornerstone for achieving interoperability and large-scale deployment. Notably, the civil aviation industry maintains stringent operational standards for ground equipment. The International Air Transport Association (IATA) Airport Ground Handling Manual has already established specific provisions—for instance, concerning fire safety—for electric Ground Service Equipment (e-GSE). These provisions offer an operational-level reference framework within the industry for enabling intelligent grid interaction (V2G).

Vehicle-to-Charger Communication: The international standard ISO 15118 [27] defines the digital communication interface between electric vehicles and charging stations. It supports “Plug & Charge” functionality, smart charging scheduling, and, most critically, the authentication, contract management, and secure initiation procedures required for V2G discharging [27]. The updated ISO 15118-20 standard introduces a second-generation network and application protocol suite, enabling more advanced functionalities and higher security levels [28,29].

Charger-to-Grid Communication: For communication between charging stations and aggregation platforms or grid control systems, the IEC 61850 series (for substation automation) and IEC 61851-23 (for DC charging systems) are widely adopted or referenced [30,31]. Leveraging object-oriented modeling approaches, these standards facilitate the efficient and reliable transmission of control commands and status information.

Grid Interconnection and Safety Standards: The IEEE 1547 series constitutes the authoritative specification for the interconnection of distributed energy resources (DERs). V2G equipment must comply with its requirements concerning voltage, frequency, harmonics, and anti-islanding protection to ensure that grid interconnection operations do not compromise public utility networks [32,33]. Demirci, A et al. have analyzed existing standardization gaps in V2G interoperability and have called for the development of more detailed industry implementation guidelines [34].

Cybersecurity Challenges and Countermeasures: Bidirectional control of high-power energy flows implicates sensitive grid operational data and user financial information, rendering V2G systems potential targets for cyberattacks. Such attacks could result in equipment malfunction, data breaches, or even grid contingencies. Harkat, H et al. have examined the cyber–physical security challenges inherent in V2G systems and proposed corresponding security protocol frameworks [35]. Hossain et al. similarly emphasized that security must be a paramount consideration in V2G system design [23]. Establishing a defense-in-depth architecture—encompassing device authentication, data encryption, intrusion detection, and access control—is essential for safeguarding the information security of V2G systems.

4.3. Panorama of Intelligent Dispatch Optimization Algorithms

The task of dispatch algorithms is to maximize overall system benefits—typically in a multi-objective framework—by optimizing the charging and discharging schedules of GSE, while satisfying all flight ground-handling requirements as hard constraints. This constitutes a complex optimization problem characterized by multiple temporal and spatial scales, numerous constraints, and significant uncertainty.

The objective function commonly seeks to minimize the total operational cost:

$$\min {\displaystyle \sum _{\mathrm{t}=1}^{\mathrm{T}}}[{\mathrm{C}}_{\mathrm{grid}}^{\mathrm{buy}}\left(\mathrm{t}\right){\mathrm{P}}_{\mathrm{grid}}^{\mathrm{buy}}\left(\mathrm{t}\right)-{\mathrm{C}}_{\mathrm{grid}}^{\mathrm{sell}}\left(\mathrm{t}\right){\mathrm{P}}_{\mathrm{grid}}^{\mathrm{sell}}\left(\mathrm{t}\right)+{\mathrm{C}}_{\mathrm{V}2\mathrm{G}}^{\mathrm{bat}}\left(\mathrm{t}\right)]$$

(2)

where ${\mathrm{C}}_{\mathrm{grid}}^{\mathrm{buy}}$ and ${\mathrm{C}}_{\mathrm{grid}}^{\mathrm{sell}}$ denote the electricity purchase and sale prices from/to the grid at time $\mathrm{t}$, respectively; ${\mathrm{P}}_{\mathrm{grid}}^{\mathrm{buy}}$ and ${\mathrm{P}}_{\mathrm{grid}}^{\mathrm{sell}}$ represent the corresponding purchased and sold power levels; and ${\mathrm{C}}_{\mathrm{V}2\mathrm{G}}^{\mathrm{bat}}$ accounts for the V2G service cost inclusive of battery degradation effects.

The objective function is subject to the following constraints: vehicle operational constraints—requiring that the state of charge (SOC) always satisfies the energy demand for the next assigned mission; grid interaction constraints—imposing upper and lower bounds on power exchange with the grid; and battery safety constraints—encompassing permissible ranges for SOC, state of health (SOH), and operating temperature.

Deterministic Optimization and Mixed-Integer Programming: For day-ahead dispatch problems where base load forecasts are relatively accurate and uncertainty is low, Mixed-Integer Linear Programming (MILP) or Mixed-Integer Nonlinear Programming (MINLP) is frequently employed to obtain precise optimal solutions. These model formulations are explicit and capable of rigorously handling complex constraints such as vehicle mission sequencing, continuity of battery SOC, and grid power limits. In their work on optimizing the minimum fleet size of airport shuttle buses, Zhao et al. successfully applied integer programming models to address analogous scheduling and sequencing problems [36].

Optimization Methods for Addressing Uncertainty: Flight delays, ad hoc vehicle assignments, and variability in driver behavior represent routine occurrences in airport operations. To address these uncertainties, researchers have introduced a variety of methodological approaches, as summarized in

Table 4. Comparison of Major V2G Dispatch Optimization Algorithms.

Algorithm Type	Representative Method	Advantages	Disadvantages	Applicable Scenarios
Deterministic Optimization	Mixed-Integer Linear Programming (MILP)	Capable of obtaining exact optimal solutions; explicit model formulation	Limited capability in handling uncertainty; high computational complexity	Short-term, day-ahead planning with low uncertainty
Stochastic Optimization	Two-Stage Stochastic Programming	Accounts for uncertainty; robust decision-making	Requires known probability distributions; computationally intensive with large scenario sets	Medium- to long-term infrastructure planning
Model Predictive Control	Receding-Horizon Optimization	Incorporates feedback for real-time error correction	Relatively high requirements on model accuracy	Intraday rolling dispatch and real-time control
Artificial Intelligence	Deep Reinforcement Learning (DRL)	No precise model required; adaptive learning capability	High training cost; limited interpretability	Complex, real-time dispatch under high uncertainty

.

Stochastic Programming: This approach assumes that the probability distributions of uncertain parameters—such as delay durations—are known. By generating a large set of scenarios, it seeks decisions that optimize the expected cost. Sarker et al., through their research on residential demand response dispatch, demonstrated the effectiveness of stochastic programming in coordinating resources subject to uncertainty [37].

Robust Optimization: This method merely assumes that uncertain parameters vary within a bounded set and seeks an optimal solution that remains feasible under the worst-case realization. It offers enhanced conservatism and reliability.

Model Predictive Control (MPC): MPC employs a strategy of “receding-horizon optimization with feedback correction,” making it exceptionally well-suited for intraday real-time dispatch. At each control interval, it resolves a short-horizon optimization problem based on the most recent system state—such as actual SOC and real-time grid electricity prices—and executes only the first control action. The work of Su et al. illustrates the advantages of MPC in managing the uncertainties associated with electric vehicle grid integration within distribution systems [38].

Breakthrough Applications of Artificial Intelligence Algorithms: In recent years, artificial intelligence algorithms, notably Deep Reinforcement Learning (DRL), have opened new pathways for addressing high-dimensional, nonlinear, and model-unknown complex dispatch problems. Through continuous trial-and-error interaction with the environment, DRL agents can ultimately learn an optimal decision-making policy—i.e., a dispatch strategy. Research on real-time V2G control utilizing deep reinforcement learning by Xie et al. demonstrated that DRL can adaptively learn complex environmental dynamics—such as electricity price fluctuations and stochastic demand patterns—to make near-optimal real-time decisions, all without reliance on precise physical or probabilistic models [39]. The work of Elnady et al. further corroborated the potential of machine learning techniques in handling uncertainties inherent in V2G dispatch [40]. Nonetheless, DRL also faces challenges including high training costs, limited policy interpretability, and safety concerns arising from its inherent “black-box” nature.

4.4. Aggregation Platform: The Nexus from Technical Integration to Commercial Operation

The V2G aggregation platform serves as the physical carrier and commercial entity that enables the “aggregation of distributed assets for unified dispatch.” Its functions can be delineated into two distinct layers: technical aggregation and commercial aggregation.

Technical Aggregation Functions: The platform is responsible for communicating with a multitude of heterogeneous underlying GSE units and charging stations, continuously collecting real-time status data—including state of charge (SOC), state of health (SOH), location, and dispatchable time windows. Based on upper-level dispatch commands, it employs optimization algorithms to disaggregate the total power setpoint and distribute individual commands to each eligible vehicle. This necessitates robust edge computing capabilities and reliable communication infrastructure.

Commercial Aggregation and Market Participation: The aggregation platform—or the aggregator—acts on behalf of dispersed GSE resource owners, participating in electricity markets as a unified entity. In their comprehensive review of electric vehicle aggregation agents, Xu provided a detailed discussion of various business models and market clearing mechanisms through which aggregators can engage in energy markets, frequency regulation markets, and reserve markets [11]. Eltohamy et al. conducted specialized research on specific strategies and economic viability for V2G participation in ancillary service markets such as frequency regulation [41].

Multi-Stakeholder Revenue Allocation Mechanism: This constitutes a critical determinant of business model viability. The revenues generated from V2G operations must be distributed fairly and equitably among key stakeholders: the airport operator (providing site infrastructure and grid interconnection), the GSE fleet owner (providing vehicles and batteries), and the aggregator (providing technology and market services). An inequitable allocation mechanism would severely undermine the participation incentives of any involved party. Research by Zhang et al. on profit distribution mechanisms within V2G aggregation offers theoretical guidance for addressing this challenge [42]. Sovacool et al. have also conducted systematic analyses of various potential V2G business models and their respective applicability conditions [41].

Specific business model recommendations are as follows. For the airport scenario, three main models can be designed: ① Airport-owned aggregator model: The airport invests in bidirectional charging piles and builds its own aggregation platform, participating in the electricity market as an independent entity. Revenue belongs to the airport, and fleet owners only receive electricity price discounts. This model offers strong control, but the airport bears all technical and market risks. ② Third-party aggregator model: A professional energy service company invests in and operates the equipment, signing a site lease and revenue sharing agreement with the airport (typically the airport receives 20–30% of net revenue). This model reduces the airport’s upfront investment, but a strict service level agreement (SLA) must be designed. ③ Fleet-owner-led model: The ground handling company purchases its own charging facilities and acts as an aggregator in the market, with the airport only providing the site. This model is suitable for large ground handling companies, but fragmentation may reduce dispatch efficiency. Overall comparison suggests that the third-party aggregator model be adopted for initial pilots, transitioning to the airport-owned model as the market matures.

4.5. Case Study: V2G Potential and Economic Estimation for a Typical Medium-Sized Airport

To provide quantitative support, this study takes a typical medium-sized hub airport (annual passenger throughput of 20 million) as an example, based on data from reference [8]. The airport has 30 electric passenger buses (250 kWh each), 50 electric baggage tractors (120 kWh each), and 20 electric passenger stairs (80 kWh each); aircraft tugs are still fuel-powered and not considered. The total number of e-GSE units that can participate in V2G is 100, with a total battery capacity of approximately 30 MWh. After deducting the energy reserved for missions, the available energy storage capacity is about 15 MWh. Assuming two discharge events per day (30 min each, average discharge power 60 kW), the daily discharge capacity is about 6 MWh. With a peak–valley electricity price difference of 0.8 RMB/kWh, the daily arbitrage revenue is about 4800 RMB, and annual revenue is about 1.75 million RMB. If participating in frequency regulation ancillary services (compensation ~20 RMB/MWh), with a dispatchable capacity of 10 MW and average daily response of 4 h, annual revenue is about 2.92 million RMB. The total of the two is about 4.67 million RMB/year. On the investment side, the premium for bidirectional charging piles is about 30,000 RMB per unit (for 100 units, incremental investment 3 million RMB). The annual battery degradation cost is estimated at 120 RMB/kWh, with an annual incremental capacity fade of 0.8%, resulting in an annual degradation cost of about 288,000 RMB. The static payback period is approximately (300/(467 − 28.8)) ≈ 0.68 years, indicating good economic feasibility. However, it should be noted that this estimate is sensitive to electricity prices, subsidies, and degradation rates, so actual returns are uncertain.

4.6. Main Limitations of Current V2G Technology

Although V2G has broad prospects, current technology still has the following major limitations: ① Battery cycle life constraints: frequent charging and discharging accelerate capacity fade, and performance is limited under low/high-temperature conditions; ② Bidirectional charging piles are still 30–50% more expensive than unidirectional ones, and although wide-bandgap devices are improving, they are not yet widely adopted; ③ Lack of unified standards: poor interoperability among CCS, CHAdeMO, GB/T interfaces and upper-layer communication protocols; ④ Grid integration: large-scale V2G aggregation may cause power quality issues, requiring advanced strategies such as grid-forming control; ⑤ Vehicle–pile–cloud communication suffers from latency and cybersecurity risks; ⑥ The special aviation environment (high temperature, electromagnetic interference, explosion-proof requirements) imposes stricter reliability demands on equipment.

4.7. Discussion of V2V Charging as a Supplementary Mechanism

In addition to bidirectional V2G, vehicle-to-vehicle (V2V) charging is a more flexible distributed energy exchange method. In the airport flight zone, when an e-GSE has low battery and nearby charging piles are occupied, another e-GSE with sufficient charge can provide V2V charging. This approach reduces dependence on fixed charging piles and improves energy utilization efficiency. However, V2V also faces challenges, including the need for vehicle-to-vehicle communication and adaptation protocols (currently lacking unified standards); energy transfer efficiency being typically lower than that of V2G (due to double conversion losses); and exacerbated battery cycle degradation. Therefore, V2V is more suitable as an emergency or supplementary measure rather than a replacement for large-scale V2G dispatch.

5. System Integration and Multi-Dimensional Benefit Assessment

The value of V2G ultimately materializes through system integration and must be comprehensively evaluated across multiple dimensions—economic, reliability, and environmental—to substantiate its techno-economic viability.

5.1. Deep Integration and Coordinated Operation with Airport Microgrids

Modern airport microgrids are evolving from isolated power supply networks into integrated energy systems that incorporate distributed generation, energy storage, and diverse loads [43]. Within this evolving landscape, V2G represents one of the most dynamic and flexible resources, capable of functioning as both a controllable load and a dispatchable power source.

Coordinated Optimization with Hybrid Energy Storage Systems: V2G (mobile, power-oriented) resources, stationary Battery Energy Storage Systems (BESS) (stationary, energy-oriented), and supercapacitors (power-oriented) exhibit inherent complementarity in their performance characteristics. Nguyen et al. investigated strategies for coordinated frequency regulation involving hybrid energy storage and V2G, demonstrating the advantages of V2G in responding to rapid power fluctuations [44]. A focal point of future research lies in developing multi-timescale coordinated control strategies. For instance, supercapacitors or V2G resources could be leveraged to address frequency deviations on the order of seconds to minutes, while stationary BESS could manage energy shifting over hourly timescales. Such an approach aims to achieve optimal matching between the performance capabilities and operational lifetimes of each energy storage component.

5.2. Quantitative Assessment Framework for Multi-Dimensional Benefits

1. Life-Cycle Analysis of Economic Benefits.

Revenue Streams: The direct economic benefits of V2G arise from diverse sources. Peak–valley arbitrage constitutes the most fundamental model, as quantified in the seminal work of Kempton and Tomić [5]. Participation in ancillary service markets—such as frequency regulation and reserve provision—represents a higher-value revenue source, with compensation rates typically far exceeding those of energy markets [36]. Demand charge management involves reducing the airport’s power drawn from the grid during peak demand periods through V2G discharging, thereby lowering basic electricity tariffs. Additionally, revenue may include a share of societal benefits derived from deferring distribution network upgrade investments, as well as potential future income from carbon trading markets [45].

Cost Considerations: The cost side primarily encompasses higher upfront capital investment—bidirectional charging stations are typically 30% to 50% more expensive than their unidirectional counterparts, although this cost differential is rapidly narrowing [16]—and the critical component of battery degradation cost. A predominant concern among users is whether V2G operation significantly accelerates battery retirement. A substantial body of research indicates that, through optimized charging and discharging strategies—such as constraining the state-of-charge (SOC) window to between 20% and 80%, and avoiding extreme temperatures and high-rate charging/discharging—the incremental capacity fade attributable to V2G can be limited to within 0.5% to 1.0% per year, a figure substantially lower than the rate of natural calendar aging. Zhong et al. conducted dedicated investigations into battery degradation modeling under V2G service conditions [46]. A life-cycle assessment by Dai et al. further demonstrated that the net revenue generated from judicious V2G participation is sufficient to offset the incremental battery degradation and yields a positive economic return for the user [47]. An economic analysis of airport parking lot V2G systems by Zhang et al. similarly corroborated its commercial feasibility [48].

Scenario dependence of battery degradation: It should be emphasized that the 0.5–1.0% per year incremental capacity fade is not a universal value, but is highly dependent on battery chemistry (LFP better than NMC), SOC window (narrow window better than wide window), charge/discharge rate (≤0.5 C better than ≥1 C), ambient temperature (25 °C better than 40 °C), and charge/discharge frequency (2 times per day better than 5 times per day). In the airport scenario, since most e-GSEs use LFP batteries and dispatch strategies can limit SOC to 30–80% and charge/discharge rate to ≤0.5 C, the above degradation range is achievable. However, for aircraft tugs that require high-rate and frequent charging/discharging, the degradation rate may be higher.

2. Reliability Enhancement Benefits. In the event of a grid outage, the aggregated GSE fleet can serve as a critical emergency backup power source, supplying essential airport loads—such as the control tower, fire station, and selected terminal loads—thereby substantially enhancing the power supply resilience and disaster preparedness of the airport. Research by Ma et al. has quantified the contribution of V2G to improving airport resilience [49]. Meurer et al. have further explored the potential for V2G to provide black start services to local power grids [50].

3. Environmental Benefits. V2G facilitates the accommodation of clean energy sources—such as nighttime wind power—through valley filling, while simultaneously reducing the output of fossil-fueled generation units—such as gas turbines—during peak hours via peak shaving, thereby indirectly lowering the carbon emissions of the power system. When integrated with on-site airport photovoltaic generation, V2G further enables self-consumption of locally generated green electricity, with surplus power either exported to the grid or stored in vehicle batteries, directly increasing the proportion of renewable energy utilization. The airport DC microgrid integrating photovoltaics and energy storage, as designed by Muntaser et al., exemplifies this very concept [17].

4. Active Support Benefits for Distribution Networks. Beyond participation in system-wide peak shaving and frequency regulation, V2G can also exert positive influences at the local distribution network level. Soliman et al. demonstrated that, within the radial distribution networks typical of airport environments, coordinated optimization of capacitor bank switching alongside the reactive and active power output of V2G resources can effectively improve system voltage profiles and reduce network losses, thereby achieving simultaneous optimization of both power quality and operational economy [51]. The work of Gholami et al. similarly corroborated the voltage support capabilities of V2G within distribution networks [52].

6. Comprehensive Challenges to Large-Scale Deployment and Coordinated Breakthrough Pathways

Despite the promising outlook, the transition of airport V2G from demonstration projects to large-scale deployment continues to confront a spectrum of intersecting technical and non-technical challenges. Addressing these challenges will require concerted and collaborative efforts among industry stakeholders, academia, and policymakers.

6.1. Core Technical Challenges

Battery Technology: The fundamental concern centers on battery longevity and safety under prolonged fast charging and discharging cycles. Addressing this challenge necessitates coordinated optimization across battery materials, Battery Management System (BMS) algorithms, and V2G dispatch strategies. Hannan et al. have provided a systematic review of the challenges associated with state estimation and management systems for lithium-ion batteries in electric vehicle applications [53].

High Power Density and Thermal Management: To conserve the limited and operationally critical space within the airside area, charging equipment must be increasingly compact and efficient. This imposes exceptionally stringent requirements on thermal dissipation design.

Wide-Range Adaptability: Charging stations must demonstrate compatibility with GSE units from diverse manufacturers, spanning various models and operating at different battery voltage platforms. This heterogeneity substantially increases overall system complexity.

6.2. Standardization and Interoperability Challenges

This constitutes one of the principal bottlenecks constraining large-scale deployment. Globally, charging interfaces (CCS, CHAdeMO, GB/T) and communication protocols—particularly their V2G-specific extensions—have not yet achieved universal harmonization. Even within the framework of a single standard, variations in implementation details among equipment from different manufacturers can result in failure of the “Plug & Charge” functionality. Both Demirciet al. [34] and Wanget al. [54] have emphasized that advancing more granular and rigorously enforceable interoperability testing and certification standards represents an urgent imperative for the healthy development of the industry.

6.3. Safety and Reliability Challenges

As critical infrastructure, airports demand exceptionally high safety and security standards. The challenges encompass the following aspects:

Electrical Safety: This includes short-circuit protection, insulation monitoring, and anti-islanding protection under high-power bidirectional energy flow conditions.

Battery Safety: This pertains to early warning and prevention of thermal runaway incidents.

Cybersecurity: As previously discussed, this involves defending control systems against cyberattacks. Research by Ahmadet al. [55] and Naseemet al. [56] underscored the importance of developing dedicated safety standards for V2G deployments within critical infrastructure environments. Harkatet al. have explored security enhancement schemes from a protocol-level perspective [35].

6.4. Business Model and Market Mechanism Challenges

A well-defined revenue allocation mechanism constitutes the cornerstone of commercial success. At present, the business models and contractual frameworks involving multiple stakeholders—including airport operators, ground handling agents, fleet owners, and aggregators—remain immature. Concurrently, electricity market regulations in many jurisdictions do not yet fully accommodate distributed, small-capacity flexible resources (such as individual GSE units), or impose excessively high entry barriers. Xu et al. [11] and Hu et al. [57] have called for adaptive reforms to electricity market structures to enable the participation of emerging market entities such as V2G resources.

Regional differences and policy barriers: Electricity market structures vary significantly across countries, affecting the feasibility of V2G. For example, Europe has established relatively mature ancillary service markets (e.g., Germany’s primary frequency regulation market), where V2G aggregators can directly participate; the US PJM market allows aggregated bidding of distributed resources; while China currently mainly relies on demand response and time-of-use tariffs, with ancillary service markets still in the pilot stage. In addition, the development level of carbon trading markets also affects the additional revenue from V2G. Therefore, airport V2G business models need to be adapted to local conditions. It is recommended to start with peak–valley arbitrage and demand charge management, and then expand to ancillary services as the market matures.

6.5. User Acceptance and Social Challenges

Concerns regarding battery degradation represent a pervasive psychological barrier among users, including vehicle operators and fleet managers. Research by Patt et al. indicated that both the availability of supporting infrastructure and user perceptions of battery impact directly influence the acceptance of electric vehicles and their associated services [58]. Studies on user behavior modeling by Zhao et al. [59], as well as investigations into user acceptance by Chen et al. [60], collectively suggest that overcoming this barrier requires transparent revenue-sharing arrangements, scientifically grounded battery state-of-health reporting, and sustained user education.

6.6. Outlook on Coordinated Breakthrough Pathways

Convergent Technological Innovation: Digital twin technology can establish high-fidelity virtual models of airport V2G systems, enabling real-time state mirroring, fault prediction, dispatch strategy simulation and optimization, thereby substantially enhancing system transparency and maintainability [61,62,63]. Artificial intelligence will be more deeply integrated into battery health prognostics, intelligent dispatch, and market bidding strategies.

Deepened System Integration: Future research will be directed toward the construction of a “Photovoltaic–Storage–Charging–Discharging–Hydrogen” integrated zero-carbon airport energy system. V2G must undergo deep coordinated planning and operation with rooftop photovoltaic generation, stationary energy storage, hydrogen fuel cells, and even charging infrastructure for electric aircraft (Aircraft-to-Grid, A2G), thereby forming a multi-energy complementary, all-time clean energy supply architecture [17,64,65,66].

Dual Drivers of Policy and Market: Clear government guidance is of paramount importance. This includes establishing mandatory carbon emission constraints or proactive carbon pricing mechanisms [45]; providing fiscal subsidies or tax incentives for investments in bidirectional charging infrastructure and V2G services; and, most critically, advancing electricity market reforms to explicitly permit distributed energy storage aggregators to participate in electricity spot and ancillary service markets, alongside the formulation of equitable market clearing and settlement rules [67,68,69,70]. Research by Miller et al. has underscored the pivotal role of policy drivers in the electrification of airport operations [71].

7. Conclusions and Future Outlook

This paper presented a systematic review of the comprehensive landscape of Vehicle-to-Grid (V2G) technology application within the airside areas of civil airports. The study demonstrates that transforming highly predictable fleets of electric Ground Service Equipment (e-GSE)—through bidirectional charging/discharging and intelligent aggregation technologies—into flexible and dispatchable virtual power plants embedded within airport microgrids constitutes a strategic pathway. This approach synergistically addresses the load pressure arising from the electrification of GSE fleets while simultaneously enhancing the economic viability and environmental sustainability of airport energy systems.

At present, significant research progress and engineering validation have been achieved across core technological domains, including wide-range power conversion topologies, grid-forming grid interconnection control, multi-timescale dispatch algorithms, and integrated architectures incorporating photovoltaic generation and stationary energy storage systems. Life-cycle techno-economic analyses have further provided preliminary substantiation of commercial feasibility. Nevertheless, the transition toward large-scale deployment remains confronted by several systemic challenges that demand urgent resolution. These include gaps in standardization and interoperability, the assurance of cross-domain safety coordination, the formulation of sophisticated business models, and the effective guidance of user behavior.

It must be clearly recognized that airport V2G is still at an early stage of development. The following key tasks need to be completed before large-scale commercial deployment: Conduct long-term (≥2 years) pilot demonstrations at a minimum of 3–5 airports of different scales to accumulate real operational data; complete compatibility certification with aviation safety regulations; establish a complete battery lifecycle management system and insurance mechanism; and promote revisions to electricity market rules to allow V2G aggregators to participate fairly. Optimistically, the first commercial project could be launched around 2028, while large-scale deployment may not occur until after 2030.

Looking ahead, V2G technology is poised for deep integration with cutting-edge technologies such as digital twins, artificial intelligence, and wide-bandgap semiconductors. It will become intricately embedded within “Photovoltaic–Storage–Charging–Hydrogen” integrated zero-carbon airport energy systems, ultimately establishing itself as an indispensable core source of flexible resources for smart airports and providing robust technical support for the aviation industry’s attainment of the 2050 net-zero carbon emissions goal. To realize this vision, future research must strengthen interdisciplinary collaboration among transportation engineering, electrical engineering, computer science, economics, and policy studies. Moreover, extensive long-term demonstration and validation projects conducted in authentic airport operational environments are imperative. Such endeavors will enable the identification of practical challenges, the refinement of enabling technologies, and the maturation of relevant standards, thereby ultimately propelling this technology—which holds substantial societal and environmental benefits—toward commercial rollout and deployment at scale [72].

8. Literature Search Methodology

This paper follows the logic of a systematic review. Literature searches covered the Web of Science, IEEE Xplore, ScienceDirect, and CNKI databases, with a time range from 2015 to 2026 (some classic literature traced back to 2005). Keywords included: “Vehicle-to-Grid” OR “V2G” AND “airport” OR “ground service equipment” OR “GSE”, as well as the Chinese terms “车网互动” + “机场” + “地面保障设备”. A total of 432 initial records were obtained, 128 were included after title/abstract screening, and 71 were finally cited after full-text review. Inclusion criteria: directly related to V2G technology, airport microgrids, bidirectional charging, dispatch algorithms, or business models. Exclusion criteria: only discussing electric vehicle charging without involving V2G, pure V2G reviews in non-aviation scenarios, conference abstracts, or non-peer-reviewed reports.