Integrated Solar-Wind Hydrogen Production System for Sustainable Green Mobility

Abstract

The transportation sector’s decarbonization represents one of the most critical challenges in achieving global climate targets. This study presents a comprehensive analysis of an integrated renewable energy system that produces green hydrogen through a hybrid solar photovoltaic (PV) and wind power configuration. The proposed system combines a 1.2 MWp solar array with 800 kW wind turbines, feeding a 1 MW proton exchange membrane (PEM) electrolyzer for hydrogen production. The hydrogen is subsequently compressed, stored at 350 (for trucks and buses) and 700 bar (for cars), and then utilized either directly for fuel cell electric vehicles (FCEVs) or reconverted to electricity via a 250 kW stationary PEM fuel cell to support electric vehicle (EV) charging infrastructure. Through detailed techno-economic simulation using HOMER Pro and MATLAB/Simulink 2022a, we demonstrate that the hybrid configuration achieves a 71% electrolyzer capacity factor, producing 55.8 tonnes of hydrogen annually with a levelized cost of 5.82 €/kg. The system ensures over 60 h of grid-independent operation while reducing CO₂ emissions by 1656 tones annually compared to conventional grid-powered alternatives. Results indicate that hybrid renewable hydrogen systems can provide economically viable solutions for sustainable mobility infrastructure, with projected cost reductions making them competitive with fossil fuel alternatives by 2030.

1. Introduction

The global energy transition towards carbon neutrality by 2050 necessitates fundamental transformations across all economic sectors, with transportation presenting particularly complex challenges. According to the International Energy Agency’s latest reports, the transport sector accounts for approximately 24% of global energy-related CO₂ emissions, totaling over 8 gigatons annually [1]. This substantial contribution to greenhouse gas emissions, combined with the sector’s projected growth in developing economies, underscores the urgent need for sustainable alternatives to fossil fuel-based mobility systems.

Hydrogen has emerged as a pivotal energy vector in decarbonization strategies, offering unique advantages for long-term energy storage and sector coupling applications. The concept of “green hydrogen,” produced through water electrolysis powered exclusively by renewable energy sources, represents the most environmentally sustainable pathway for hydrogen production [2]. Unlike conventional hydrogen production methods, which rely predominantly on steam methane reforming and contribute approximately 830 million tonnes of CO₂ annually, green hydrogen production generates zero direct emissions, positioning it as a cornerstone technology for achieving climate neutrality [3].

The integration of renewable energy sources with electrolysis systems presents both opportunities and challenges. Solar photovoltaic and wind energy have experienced dramatic cost reductions over the past decade, with levelized costs of electricity reaching grid parity in many regions globally [4]. However, the inherent intermittency of these resources poses significant challenges for continuous hydrogen production, as electrolyzers typically require stable operating conditions to maintain efficiency and minimize degradation [5]. This intermittency challenge has motivated research into hybrid renewable energy systems that combine complementary generation profiles to enhance system reliability and economic assessment and viability.

The mobility sector’s evolution towards electrification presents a dual pathway: battery electric vehicles (BEVs) and fuel cell electric vehicles (FCEVs). While BEVs have gained significant market share in passenger vehicle segments, FCEVs offer compelling advantages for heavy-duty transport, long-range applications, and rapid refueling requirements [6]. The development of integrated infrastructure capable of supporting both technologies through renewable hydrogen production and flexible energy conversion represents a strategic approach to comprehensive transport decarbonization. Previous studies have explored various configurations of renewable hydrogen production systems, predominantly focusing on single-source generation coupled with electrolysis. Research by Zhang et al. demonstrated the technical feasibility of solar-driven PEM electrolysis, achieving system efficiencies of 12–15% under optimal conditions [7]. Similarly, wind-powered electrolysis systems have been investigated extensively, with projects such as the Mainzer Stadtwerke facility in Germany demonstrating commercial-scale operation [8]. However, limited research has addressed the synergistic potential of hybrid solar-wind configurations for hydrogen production, particularly in the context of integrated mobility infrastructure. The economic viability of green hydrogen production remains a critical consideration for widespread deployment. Current production costs range from 3 to 8 €/kg depending on renewable resource availability, electrolyzer technology, and system scale [9]. Achieving cost competitiveness with conventional hydrogen production methods (1.5–2.5 €/kg) requires optimization of system design, improved electrolyzer efficiency, and strategic utilization of complementary renewable resources [10].

This research addresses these challenges through a comprehensive techno-economic analysis of an integrated solar-wind hydrogen production system designed specifically for green mobility infrastructure. The primary objectives include the following: (a) optimizing the configuration of hybrid renewable generation to maximize electrolyzer utilization; (b) evaluating the technical performance of integrated hydrogen production, storage, and reconversion systems; (c) assessing the economic viability through detailed cost modeling and sensitivity analysis; (d) quantifying the environmental benefits compared to conventional grid-powered alternatives.

The main contributions and differences compared to recent similar publications and projects highlighted in the introduction are summarized in

Table 1. Comparison with similar publications.

Feature	Our Study	Kopp M. (Energy Park Mainz)	Rizk	Djilali. Nouredin	Wang	Bad Lauchstädt (Germany)
System Configuration	Integrated Hybrid Solar PV (1.2 MWp) and Wind (800 kW) feeding a 1 MW PEM electrolyzer. Includes both H2 storage and a 250 kW stationary PEM fuel cell for EV charging.	6 MW PEM electrolysis project.	Optimal standalone Wind-PV Power Plant system sizing for H2 generation.	Green H2 supply chain based on Hybrid Solar PV/Wind for transport and village supply.	Integration of PV-generated H2 production, compression, and storage, and a dynamic model of a H2 fueling station.	Large-scale dedicated Wind Farm (50 MW).
Primary Focus/Output	Techno-economic simulation (HOME Pro/MATLAB) demonstrating viability for Sustainable Green Mobility (FCEVs and EV support).	Analysis of operating experience of large-scale PEM electrolysis and grid services.	Optimal sizing and economic impacts for a Hydrogen Refueling Station and wastewater treatment.	Assessment of geographical, technical, economic, and environmental potential for wind-to-hydrogen in Algeria.	Advancements in green hydrogen storage stations and dynamic modeling for heavy-duty vehicles.	Comparison and benchmarking of large-scale wind-to-hydrogen projects
Unique Contribution /Difference	Demonstrates the synergistic use of H2 for both FCEV refueling (77% usage) and Fuel Cell to Grid (FC2G) reconversion to support EV infrastructure, providing a holistic green mobility solution.	Practical validation of large-scale (MW-level) PEM electrolysis operation, providing ancillary services to the local grid.	Focuses heavily on optimal sizing and environmental sustainability integrated with ancillary services (wastewater treatment).	Macro-level analysis focused on vast resource potential and supply chain needs across a specific geography (Algeria).	Focuses on detailed control strategies, dynamic performance, and stationary storage optimization.	lower LCOH due to economies of scale from a 50 MW dedicated wind farm, contrasting with the proposed decentralized hybrid approach.

.

In summary, the main contribution of this paper is the detailed simulation and techno-economic validation of a specific, medium-scale hybrid PV-wind system designed for dual-mobility support (FCEVs and EVs via FC2G), yielding a high capacity factor and a precise Levelized Cost of Hydrogen through the integration of multiple subsystems using HOMER Pro and MATLAB. This hybrid configuration significantly surpasses the performance and economic viability of typical single-source systems, providing a blueprint for resilient, decentralized mobility

2. Infrastructure of Hydrogen Production Systems

2.1. Hydrogen Production Technologies

The landscape of hydrogen production technologies has evolved significantly over recent decades, with electrolysis emerging as the most promising pathway for renewable integration. Three primary electrolysis technologies dominate current research and commercial deployment: alkaline electrolysis (AEL), proton exchange membrane electrolysis (PEMEL), and solid oxide electrolysis (SOEC) [11]. Alkaline electrolyzers represent the most mature technology, with over 100 years of industrial application and current global capacity exceeding 2 GW. These systems operate using a liquid alkaline electrolyte (typically 25–30% KOH solution) and demonstrate robust performance with efficiencies ranging from 60 to 75% (based on higher heating value). Recent advances in electrode materials and cell design have improved current densities to 0.4–0.6 A/cm², though dynamic response remains limited compared to newer technologies [12]. The capital costs of alkaline systems have decreased to approximately 500–1000 €/kW, making them economically attractive for large-scale applications with stable power input. PEM electrolyzers have gained significant attention due to their superior dynamic response characteristics, making them particularly suitable for integration with intermittent renewable sources. These systems utilize a solid polymer electrolyte membrane, enabling operation at higher current densities (1–3 A/cm²) and rapid load-following capabilities (0–100% in seconds) [13]. The absence of corrosive liquid electrolytes simplifies system design and maintenance, though the requirement for precious metal catalysts (platinum and iridium) contributes to higher capital costs (800–1500 €/kW). Recent research has focused on reducing catalyst loading and developing alternative materials to improve economic competitiveness. Solid oxide electrolysis cells operate at elevated temperatures (700–900 °C), enabling higher electrical efficiency through favorable thermodynamics and electrode kinetics. Laboratory demonstrations have achieved efficiencies exceeding 85% when coupled with waste heat recovery [14]. However, material challenges related to thermal cycling and long-term stability have limited commercial deployment, with current installations primarily at demonstration scale. The potential for reversible operation as fuel cells presents unique opportunities for integrated energy systems, though technical maturity remains lower than AEL and PEMEL alternatives.

2.2. Hybrid Renewable Energy Systems

The concept of hybrid renewable energy systems has evolved from simple complementary generation to sophisticated integrated platforms incorporating advanced control strategies and energy storage. The fundamental principle leverages the statistical independence and often inverse correlation of different renewable resources to enhance overall system reliability and capacity factor [15]. Solar–wind hybrid systems have been extensively studied in microgrid applications, demonstrating improved reliability metrics compared to single-source configurations. Because the intermittence, performance, and storage problems associated with renewable energy systems are not all solved, even with smart grids and high RE penetration.

Research by Ahmed et al. analyzed over 50 hybrid installations globally, identifying average capacity factor improvements of 35% through resource complementarity [16]. The optimization of component sizing represents a critical design challenge, with various methodologies proposed, including linear programming, genetic algorithms, and particle swarm optimization techniques. The integration of energy storage with hybrid renewable systems introduces additional complexity and opportunity. While battery energy storage systems (BESS) have dominated short-term applications, hydrogen storage offers unique advantages for seasonal and long-duration storage requirements. The round-trip efficiency of hydrogen storage systems (30–40%) remains lower than that of batteries (85–95%), but the decoupling of power and energy capacity enables cost-effective scaling for large-scale applications. Recent techno-economic analyses suggest that hydrogen becomes economically favorable for storage durations exceeding 8–12 h, depending on local conditions and application requirements [17].

2.3. Integration with Mobility Infrastructure

The evolution of sustainable mobility infrastructure requires consideration of diverse vehicle technologies and refueling/recharging requirements. The parallel development of battery electric and fuel cell electric vehicles has created demand for flexible energy supply systems capable of supporting both paradigms [18]. Technically, any DC charger over 22 kW can be classified as a fast charger. Current EV charging infrastructure predominantly relies on grid electricity, with fast-charging stations requiring power levels of 50–350 kW per unit. The simultaneous charging of multiple vehicles can create significant grid stress, particularly in distribution networks not designed for such loads. Integration of local renewable generation and energy storage can mitigate grid impacts while improving the carbon intensity of charging operations, as illustrated in Figure 1. Hydrogen refueling infrastructure presents different technical requirements, with compression to 700 bar standards for passenger vehicles and 350 bar for buses and trucks. The energy requirement for compression represents approximately 10–15% of the hydrogen’s energy content, necessitating careful system optimization [19]. Recent advances in ionic liquid compression and metal hydride storage offer potential improvements in efficiency and safety.

2.4. Existing Projects and Demonstrations

Several pioneering projects have demonstrated the feasibility of renewable hydrogen production at various scales. The Fukushima Hydrogen Energy Research Field (FH2R) in Japan represents one of the largest operational facilities, combining 20 MW of solar PV with a 10 MW electrolyzer to produce up to 1200 Nm³/h of hydrogen [20]. The facility demonstrates grid-balancing capabilities while supplying hydrogen for mobility and stationary power applications. The HyBalance project in Denmark integrates 1.2 MW PEM electrolysis with wind power, producing hydrogen for industrial applications and fuel cell vehicles. The project has demonstrated the technical feasibility of providing grid services through flexible electrolyzer operation, generating additional revenue streams to improve economic viability [21]. In Australia, the Western Sydney Green Gas project combines 500 kW of solar PV with electrolysis to inject hydrogen into the natural gas network, demonstrating the potential for sector coupling applications. The project has validated blending ratios up to 10% hydrogen by volume without requiring modifications to existing infrastructure [22].

During the last three years, six major green hydrogen development projects, with a capacity greater than 100 MW, have received a final investment decision according to a 10 GW action plan [23]. Meanwhile, several experimental infrastructures of hydrogen have been studied and evaluated. In 2022, Wang presented a study on the integration of renewable hydrogen for mobile and stationary fuel cells. The paper integrates PV-generated hydrogen production, compression, and storage, enhancing grid stability and maximizing PV utilization, showing advancements in green hydrogen storage stations. The author also presented a dynamic model of a green hydrogen fueling station for heavy-duty vehicles, integrating solar PV for hydrogen production and storage, emphasizing renewable energy utilization. Another comprehensive study conducted by Rizk in 2023 outlined the economic impacts of large-scale hydrogen production, indicating that costs could fall below $4 per kg due to ongoing technological innovations and scale. He developed an optimal wind-photovoltaic power plant system for green hydrogen generation, emphasizing sustainability, energy production for a hydrogen refueling station, and wastewater treatment. The annual generation production is 6997,990 kWh of electrical energy and 85,595 kg of green hydrogen [24]. Other researchers in Algeria developed in 2023 a green hydrogen supply chain based on the use of hybrid solar energy (wind/photovoltaic) for the production and storage of hydrogen dedicated to transport and the supply of the village of Ouergla, with a refueling station. The results show that transport requires 16.7 million tonnes of hydrogen/year to fuel 34 million vehicles. This transformation will reduce fossil energy consumption by 52.2 million tonnes of oil equivalent and avoid nearly 170 million tonnes of greenhouse gases. Table 2 gives more details about industrial projects in the field of green hydrogen production and use.

Table 2. European projects dealing with the hydrogen production and storage chain.

Projects	Problematic	Goals	Proposed Solutions	Results Obtained
HyDeal Ambition (Spain) [25]	- Need for large-scale green hydrogen vector	- Production of 3.6 million tonnes of green hydrogen by 2030 and integration of several European countries. - Use of 95 GW of photovoltaic energy and 67 GW of electrolysis capacity.	- Integration of renewable energy sources on a large scale - largest green hydrogen project by IRENA.	- Transnational collaboration to maximize and increase the production rate of green hydrogen.
H2V (France) [26]	- mass production of green H2, reduction in costs and develop a network of service stations to supply the entire territory)	- Construction of several giga-factories. - Reach more than 3 GW of capacity by 2030. - Production of green hydrogen from renewable electricity.	- Efficient storage and distribution. - Reduction in CO2 emissions. - Replacement of gray hydrogen with green hydrogen.	- E-fuels synthesis. - methanation - Powering heavy mobility such as trucks, buses, or garbage trucks.
INGRID Project (Italy) [27]	- Energy exploitation	- Industrial demonstration of hydrogen production by water electrolysis. - Solid storage of hydrogen. - Use of hydrogen in several varied applications.	- Production of hydrogen from renewable sources - Efficiency of solid hydrogen storage - Efficient solid storage.	- hydrogen reuse.
H2BER (Germany) [28]	- Large-scale renewable energy storage	- Large-scale renewable energy storage. - Production and use of green hydrogen in the industrial sector and various applications.	- Contribution to the industrial sector for the reduction of carbon footprint. - Efficient storage of renewable energy. - H2 distribution networks.	- Large High-Pressure Hydrogen Storage to Meet Renewable Energy Demand.
Hy Trac Project (France)	- Motorization of heavy vehicles with hydrogen	- Universal alternative for the motorization of heavy vehicles. - Integration of local hydrogen production solutions. - Use of renewable electricity. - Decarbonized solutions	- Motorization of heavy vehicles by a decarbonized technique. - Integration of local hydrogen production. - Use of renewable electricity.	- High-power refueling and charging station.
Abdullah Al- Sharafi Saudi Arabia [29]	- Wind speed changes and solar radiation	- Analysis of hybrid systems with solar panels, wind turbines, and energy storage.	- Battery storage and electrolysers.	- Identification of the most common configurations for energy production.
Djilali, M. Nouredin S (Algeria) [30]	- Production of hydrogen for transport from solar energy	- Assessment of area suitability, identification of optimal locations.	- Use of solar energy for the production of hydrogen.	- Significant reduction in fossil fuel consumption.
Kopp M, (Germany) Energie Park Mainz [31,32]	- Study of the potential of large-scale PEM electrolysis	- Analysis of the operating experience of a 6 MW PEM electrolysis project in Germany, investigating the potential of large-scale PEM electrolysis technology while providing additional services to a local electricity grid.	- Analysis of the operation of the initial phase of a 6 MW PEM electrolysis project.	- Three electrolysis units of 6 MW of electricity, producing hydrogen injected into the gas network and refueling stations.

Table 2. European projects dealing with the hydrogen production and storage chain.

Projects	Problematic	Goals	Proposed Solutions	Results Obtained
HyDeal Ambition (Spain) [25]	- Need for large-scale green hydrogen vector	- Production of 3.6 million tonnes of green hydrogen by 2030 and integration of several European countries. - Use of 95 GW of photovoltaic energy and 67 GW of electrolysis capacity.	- Integration of renewable energy sources on a large scale - largest green hydrogen project by IRENA.	- Transnational collaboration to maximize and increase the production rate of green hydrogen.
H2V (France) [26]	- mass production of green H2, reduction in costs and develop a network of service stations to supply the entire territory)	- Construction of several giga-factories. - Reach more than 3 GW of capacity by 2030. - Production of green hydrogen from renewable electricity.	- Efficient storage and distribution. - Reduction in CO2 emissions. - Replacement of gray hydrogen with green hydrogen.	- E-fuels synthesis. - methanation - Powering heavy mobility such as trucks, buses, or garbage trucks.
INGRID Project (Italy) [27]	- Energy exploitation	- Industrial demonstration of hydrogen production by water electrolysis. - Solid storage of hydrogen. - Use of hydrogen in several varied applications.	- Production of hydrogen from renewable sources - Efficiency of solid hydrogen storage - Efficient solid storage.	- hydrogen reuse.
H2BER (Germany) [28]	- Large-scale renewable energy storage	- Large-scale renewable energy storage. - Production and use of green hydrogen in the industrial sector and various applications.	- Contribution to the industrial sector for the reduction of carbon footprint. - Efficient storage of renewable energy. - H2 distribution networks.	- Large High-Pressure Hydrogen Storage to Meet Renewable Energy Demand.
Hy Trac Project (France)	- Motorization of heavy vehicles with hydrogen	- Universal alternative for the motorization of heavy vehicles. - Integration of local hydrogen production solutions. - Use of renewable electricity. - Decarbonized solutions	- Motorization of heavy vehicles by a decarbonized technique. - Integration of local hydrogen production. - Use of renewable electricity.	- High-power refueling and charging station.
Abdullah Al- Sharafi Saudi Arabia [29]	- Wind speed changes and solar radiation	- Analysis of hybrid systems with solar panels, wind turbines, and energy storage.	- Battery storage and electrolysers.	- Identification of the most common configurations for energy production.
Djilali, M. Nouredin S (Algeria) [30]	- Production of hydrogen for transport from solar energy	- Assessment of area suitability, identification of optimal locations.	- Use of solar energy for the production of hydrogen.	- Significant reduction in fossil fuel consumption.
Kopp M, (Germany) Energie Park Mainz [31,32]	- Study of the potential of large-scale PEM electrolysis	- Analysis of the operating experience of a 6 MW PEM electrolysis project in Germany, investigating the potential of large-scale PEM electrolysis technology while providing additional services to a local electricity grid.	- Analysis of the operation of the initial phase of a 6 MW PEM electrolysis project.	- Three electrolysis units of 6 MW of electricity, producing hydrogen injected into the gas network and refueling stations.

3. Materials and Methods

3.1. System Architecture and Components

The proposed integrated renewable hydrogen production system used for this techno-economic analysis comprises multiple subsystems designed to operate synergistically for optimal performance and reliability. The complete system architecture of Figure 2 integrates renewable power generation, power conditioning, electrolysis, gas storage, and end-user applications through sophisticated control and monitoring systems. The solar photovoltaic array consists of 1.2 MWp installed capacity using monocrystalline silicon modules with 21% cell efficiency. The array is configured with 3042 modules of 400 Wp. Two-axis tracking systems are implemented to maximize energy yield, providing approximately 30% increased annual generation compared to fixed-tilt installations. Wind generation capacity of 800 kW is provided by two 400 kW horizontal-axis wind turbines with 50 m rotor diameters and 80 m hub heights. The turbines employ variable-speed operation with full-power conversion, enabling optimal energy extraction across the full wind speed range (3–25 m/s operational range). The selection of medium-scale turbines balances economic considerations with land use constraints and maintenance requirements typical of distributed generation applications. The PEM electrolyzer system rated at 1 MW (DC input) represents the core hydrogen production component. The electrolyzer stack consists of 200 cells operating at current densities up to 2 A/cm² with an active area of 1500 cm² per cell. Operating pressure is maintained at 30 bar, eliminating the need for separate low-stage compression. The balance of plant includes deionized water treatment, thermal management systems maintaining stack temperature at 60–80 °C, and power electronics enabling variable operation from 10 to 80% rated capacity. Hydrogen purification and compression systems ensure product quality for fuel cell vehicle applications. Multi-stage diaphragm compressors raise pressure to 350 bar for intermediate storage, with final compression to 700 bar for vehicle dispensing.

The study quantifies the energy consumed by the compression process (350–700 bar):

-

Compression Energy Consumption: The energy consumed for compression is estimated at 0.54 MWh per day (or 198 MWh/year), highlighting its significance.

-

Storage Efficiency: The overall high storage efficiency (89%) and the produced hydrogen purity (99.99%) are reported.

Furthermore, the relatively high storage efficiency (88%) reflects the implementation of a security system with the following:

-

Appropriate sensors, control, and monitoring interface;

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Advanced design of the composite tank with minimal permeation and optimized pressure management strategies, which indirectly contributes to maintaining safe and efficient operation.

3.2. The Hydrogen Value Chain

The hydrogen value chain of Figure 3 includes several stages of production, storage, distribution and use of hydrogen. The hydrogen production part can be carried out either from the electrolysis of water, by the reforming of natural gas, or by the gasification of biomass. The storage can be gaseous at high pressure, a liquid storage at cryogenic temperatures, or a solid storage by the use of absorbent materials. The H2 transport chain is ensured by pipelines over long distances, either by tanker trucks or via maritime transport. Finally, the distribution of hydrogen is done through the refueling stations to supply hydrogen to H2-vehicles, or by the injection of gaseous H2 into the natural gas network. The end use could be as follows:

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Industrial sector, such as metallurgical, chemical, mining, oil, and pharmaceutical industries.

-

Transport sector: Electric, hydrogen, or hybrid cars, and buses and trains.

-

Electricity production and injection into the grid: Use of hydrogen fuel cells to generate electricity and then inject it into the network.

This value chain highlights the interconnection between different stages, from production to end use. Each link ensures a successful transition to a green circular economy, minimizing environmental impact and maximizing efficiency.

4. Modeling

4.1. Photovoltaic Array Model

The photovoltaic (PV) subsystem consists of multiple monocrystalline silicon modules aggregated into an equivalent array with a nominal capacity Y_PV (kW) under Standard Test Conditions (STC: irradiance = 1000 W/m², cell temperature T_C,STC = 25 °C, air mass 1.5). For system-level simulations and techno-economic optimization, the PV array is represented by a single-diode-equivalent efficiency model based on incident irradiance and cell temperature [33]. The instantaneous DC power output of the PV array P_PV(t) is expressed:

$$P_{PV}\left(\mathrm{t}\right)=Y_{PV}·f_{PV}·{\displaystyle \frac{G_T\left(t\right)}{G_{STC}}}· [1+{\alpha }_P·(T_C\left(\mathrm{t}\right)-T_{C,STC}\left(\mathrm{t}\right))]$$

(1)

where:

Y_PV is the installed PV capacity at STC (kW), to be optimized.

f_PV is the overall derating factor (dimensionless), accounting for soiling, wiring losses, mismatch, DC/connector losses, and MPPT imperfections. A value of f_PV = 0.88 is adopted, consistent with the following:

G_T(t) is the plane-of-array (POA) irradiance at time t (W/m²).

G_STC = 1000 W/m² is the STC irradiance reference.

α_P is the PV power temperature coefficient for monocrystalline silicon,

α_P = −0.0035 °C⁻¹

Tc(t) is the PV cell temperature (°C).

T_C,STC = 25 ° Cis the cell temperature at STC.

This formulation explicitly captures the linear degradation of PV power with increasing cell temperature and the proportionality to incident irradiance. To estimate the cell temperature Tc(t) from the ambient temperature T_a(t), the Nominal Operating Cell Temperature (NOCT) model is applied [33]:

$$T_C\left(\mathrm{t}\right)=T_a\left(\mathrm{t}\right)+\left(T_{NOCT}-T_{a,NOCT}\right)· {\displaystyle \frac{G_T\left(t\right)}{G_{NOCT}\left(t\right)}}$$

(2)

where:

Ta(t) is the ambient air temperature at time t (°C).

T_NOCT is the nominal operating cell temperature (°C), T_NOCT = 45°C

T_{a, NOCT} = 20 °C is the ambient temperature at which NOCT is defined.

G_NOCT = 800 W/m² is the irradiance at which NOCT is defined.

The PV generator is interfaced to the DC bus through a DC/DC converter implementing maximum power point tracking (MPPT). MPPT losses are included in f_PV; dynamic MPPT behavior is not explicitly modeled because the system is simulated on an hourly time step, for which steady-state MPPT operation is a valid assumption.This model provides a good compromise between accuracy and computational simplicity and is widely used in hybrid system simulations by MATLAB software and HOMER-based studies [34].

4.2. Wind Turbine Model

The wind generation subsystem is modeled in four steps: vertical extrapolation of the measured wind speed to hub height, aerodynamic/mechanical power computation, electrical power estimation through the manufacturer’s power curve, and correction for air density variations.

Wind speed at hub heigh: Measured wind speed is generally available at a reference height href (10–50 m). The hub-height wind speed v_hub(t) is obtained using the power-law profile [35]:

$$v_{hub}\left(\mathrm{t}\right)=v_{ref}\left(\mathrm{t}\right)·{\left({\displaystyle \frac{h_{hub}}{h_{ref}}}\right)}^2$$

(3)

where

v_ref(t) is the hourly wind speed at height href;

h_ref is the turbine hub height;

α is the wind shear exponent; for open and low-roughness terrain, we use α = 0.14.

• Aerodynamic/Mechanical Power

The mechanical power available at the rotor shaft is as follows:

$$P_{mech}\left(\mathrm{t}\right)={\displaystyle \frac{1}{2}}\rho \left(\mathrm{t}\right)·{A · v_{hub}}^3\left(\mathrm{t}\right)·C_P(\mathsf{\lambda },\mathit{\beta })$$

(4)

where:

ρ(t) is the air density (kg/m³);

A = πR² is the rotor swept area (m²);

C_p(λ,β) is the power coefficient, a function of tip–speed ratio λ and pitch angle β.

Typical modern turbines have a peak Cp in the range 0.40–0.48, below the Betz limit of 0.593.

For system-level simulation, instead of resolving (λ–β) control, the manufacturer’s power curve is used (next subsection), which implicitly incorporates the dependence of Cp on λ and β.

4.3. Electrical Power via Power Curve

The electrical output power of the turbine PW(t) is modeled with a standard piecewise power curve [35]:

$$P_W\left(v_{hub}\right)=0, \mathrm{i}\mathrm{f} v_{hub}< v_{ci}$$

$$P_W\left(v_{hub}\right)=P_r·{\displaystyle \frac{{ v_{hub}}^3-{ v_{ci}}^3}{{ v_r}^3-{ v_{ci}}^3}}, \mathrm{i}\mathrm{f} v_{ci}<v_{hub}<v_r$$

$$P_W\left(v_{hub}\right)=P_r, \mathrm{i}\mathrm{f} v_r\le v_{hub}\le v_{co}$$

$$P_W\left(v_{hub}\right)=0, \mathrm{i}\mathrm{f} v_{hub}>v_{co}$$

(5)

where:

Pr is the rated electrical power of the turbine;

vci, vr, and vco are the cut-in, rated, and cut-out wind speeds, respectively.

In this study, a generic medium-scale turbine is assumed with the following:

Pr = 800 kW, vci = 3.5 m/s, vr = 14 m/s, vco = 25 m/s.

The interval vci ≤ vhub < vr corresponds to the maximum power point tracking (MPPT) region, where the rotor speed is adjusted to maintain an optimal tip–speed ratio. The interval, vr ≤ vhub ≤ vco, corresponds to the rated region, where pitch control and/or generator torque limiting are used to cap the power at Pr.

4.4. Air Density Correction

Manufacturer power curves are provided at standard air density ρ₀ = 1.225 kg/m³ (at 25 °C, 1 atm). To account for site-specific temperature and pressure, the actual density is computed using the ideal gas relation:

$$\rho \left(\mathrm{t}\right)={\displaystyle \frac{P_{atm}}{{T\left(\mathrm{t}\right) ·R}_{air}}}$$

(6)

where

P_atm is the local atmospheric pressure;

R_air = 287.058 J/(kg\cdotpK);

T(t) is the ambient temperature in Kelvin.

The electrical power is then corrected as follows:

$$P_{W,corr}\left(t\right) =P_W\left(t\right)· {\displaystyle \frac{\rho \left(\mathrm{t}\right)}{{\rho }_0}}$$

(7)

This correction is particularly relevant in warm climates, where reduced air density can lower annual wind energy yield by several percent compared with standard conditions.

4.5. PEM Electrolyzer Model

The modeling of proton exchange membrane (PEM) electrolyzers is based on electrochemical equations that allow the dissociation of pure water. In the case of water electrolysis, the gas obtained under the action of electrical energy is molecular oxygen at the anode and molecular hydrogen at the cathode. Proton exchange membrane electrolysis is an electrolysis technology that has the advantage of being able to produce high-purity hydrogen directly under pressure, with compact systems requiring little maintenance. The performance of a PEM is often linked to the operating voltage of the converter and the current density passing through it; these parameters can be linked to the conversion efficiency and therefore to the electrical consumption of the electrolyzer during hydrogen production [34].

V_el(t) = V_in + V_anode(t) + V_cathode(t) +R_el(t) +I_el(t)

(8)

I_el(t) = V_anode1(t) + V_anode2(t) =V_cathode1(t) + V_cathode2(t)

(9)

Electrolysis yield:

$${\eta }_{el}={\displaystyle \frac{N_{H2}{·LH}_{H2}}{P_{el}}}$$

(10)

Electric power:

$$P_{el}(\mathrm{t})={\displaystyle \frac{N_{H2}{·HHV}_{H2}}{{\eta }_{el}}}$$

(11)

Quantity of H2 produced:

$$V_{H2}\left(\mathrm{t}\right)={\eta }_F ·{\displaystyle \frac{n_C{·I}_{el}}{2F}}$$

(12)

Yield:

$${\eta }_F=96.5 \mathrm{e}\mathrm{x}\mathrm{p}( {\displaystyle \frac{0.09}{I_{el}}}- {\displaystyle \frac{75.5}{{ I_{el}}^2}})$$

(13)

-

Lower Heating Value (LHV or LH): Represents the energy released by burning a fuel, assuming the water produced remains as vapor (steam).

-

Higher Heating Value (HHV): Represents the energy released, assuming all products of combustion are cooled back to the original pre-combustion temperature, meaning the water vapor produced is condensed back into liquid water, thus recovering the latent heat of vaporization.

According to Table 3 and Equations (8)–(13), the electrolyzer model is illustrated by Figure 4.

Figure 4. Electric model of the PEM electrolyzer. Where R1, C1: resistance and capacity of the anode; R2, C2: resistance and capacity of the cathode; Rm: resistance of the membrane; i: Electrolyzer current; E: Electrolyzer reversible voltage.

Figure 4. Electric model of the PEM electrolyzer. Where R1, C1: resistance and capacity of the anode; R2, C2: resistance and capacity of the cathode; Rm: resistance of the membrane; i: Electrolyzer current; E: Electrolyzer reversible voltage.

Table 3. Characteristics of the PEM electrolyzer [34].

Settings	Values
cell electrical power	400 W
Rated steak voltage	2 V
Stack current range	0–80 A
Operating temperature	298 °K
Hydrogen outlet pressure	35 bar
Cells numbers	3042
Total power	1000 kW

Table 3. Characteristics of the PEM electrolyzer [34].

Settings	Values
cell electrical power	400 W
Rated steak voltage	2 V
Stack current range	0–80 A
Operating temperature	298 °K
Hydrogen outlet pressure	35 bar
Cells numbers	3042
Total power	1000 kW

4.6. Compressor Model

The compressor is essential in a hydrogen gas storage station to be able to reduce the storage volume. The compressor is placed just after the low-pressure storage tank. Its role is to compress the gas, leaving it and sending it to the tank at the desired pressure [34]. The nominal power of the compressor is expressed by the following formula:

$$P_{comp}\left(t\right)=C_P \left( {\displaystyle \frac{T_{in} }{{\eta }_{comp}}}\right)·\left[ {\left( {\displaystyle \frac{P_{in} }{P_{out}}}\right)}^{ {\displaystyle \frac{r}{r-1}}} - 1\right]· {m^{\prime }}_{comp}\left(t\right)$$

(14)

where

r: The specific heat of hydrogen at constant pressure, (14.304 kJ/kg/°K);

T_in: The temperature of hydrogen at the compressor inlet (293 K);

η_comp: The mechanical efficiency of the compressor;

P_in et P_out: total inlet pressure (30 MPa) and outlet pressure (90 MPa) of the compressor;

C_p: The calorific ratio of hydrogen;

m’_comp: The mass flow rate of gas through the compressor [kg/s].

The energy consumption of the compressor can be calculated as follows:

$$E_{comp}\left(t\right)=\left({\displaystyle \frac{W_{comp}\left(t\right)· t_{jour}}{{\eta }_{el}}}\right)$$

(15)

with

t_jour is the daily operating time (Number of hours/day);

η_ele is the efficiency of the electric motor;

W_comp is the power of the compressor.

4.7. Hydrogen Storage Model

A hydrogen tank is a device used to store hydrogen, particularly in the form of hydrogen gas. This type of storage is used in particular to power fuel cells. The storage tank is used to store the amount of hydrogen produced by the electrolyzer and supply the amount required by the fuel cell to maintain the load demand. In order to ensure the safety and normal operation of the system, effective and critical control of high-pressure storage must be carried out. The dynamic changes in its pressure are expressed as follows [34]:

$$P=Z ·\left({\displaystyle \frac{m_{H2} {·R·T}_{tank}}{{M·V}_{tank}}}\right)+ P_{Initial}$$

(16)

V_tank: Total water volume of tanks [m³];

P: Gas pressure in pascals (Pa);

mH2: The mass of hydrogen;

R: Ideal gas constant;

Ttank: The absolute temperature of the gas in Kelvin (K);

Vtank: The gas volume in cubic meters (m³);

z: Compressibility factor;

M: Molar mass.

4.8. Fuel Cell Model

PEM fuel cells are innovative technologies that electrochemically convert hydrogen into electricity. Using a proton exchange polymer membrane, these cells are able to selectively move protonnes while blocking electrons, thereby generating an electric current. They stand out for their fast start-up, high efficiency and ability to respond quickly to load fluctuations, making them ideal for a variety of applications, including fuel cell vehicles and emergency power systems. The mathematical model of a PEMFC fuel cell can be given by the following equations. The output voltage of the fuel cell can be expressed as follows [36,37]:

V_FC = E_Nernst − Vact − Vohm − Vcon

(17)

The expression of the N ernst equation is as follows [36]:

E_Nernst = 1.23 − 0.85T⁻³ (T − 298) + 4.3 10⁻⁵ T [log(P_H2)+ 0.5 log (P_O2)]

(18)

P_H2 and P_O2 are respectively the pressures of hydrogen and oxygen at the inlet of the cell expressed in atmosphere (atm). According to Amphlett’s model:

Vact = ξ₁ + ξ₂ T + ξ₃ T log(C_O2) + ξ₄ T log(I_FC)

(19)

where

I_FC is the fuel cell current;

ξ₁, ξ₂, ξ₃ and ξ₄ are empirical parameters of the fuel cell;

C_O2 is the concentration of Oxygen (mol/cm³).

The ohmic drop voltage across the cell is the result of the electronic resistances of the bipolar plates and can be given by the expression [37]:

Vohm = I_FC (R_M + RC)

(20)

R_M = ξ₅ + ξ₆ T+ ξ₇ I_FC

(21)

where

R_M is the resistance of the membrane;

R_C is the contact resistance to the conduction of electrons.

The concentration voltage is [36]:

Vcon = [(J/Jmax) − 1)

(22)

J is the current density of the cell (A/cm²)

Jmax is the maximum current density of the battery (A/cm²)

The output electric power of the fuel cell (P_FC) can be expressed as follows:

P_FC(t) = η_FCLHVH2dm_H2(t)

(23)

dm_H2(t): Hydrogen consumption rate by the fuel cell (kg/h);

LHVH2: Lower Heating Value of hydrogen = 33.3 kWh/kg;

η_FC: Fuel cell efficiency (40% to 60%).

5. Simulation Results

5.1. Simulation Framework

The system performance analysis employs a multi-scale simulation approach combining hourly energy balance calculations with detailed component models (PV, converter, electrolyzer, storage tank) for critical subsystems. HOMER provides the primary simulation platform for techno-economic optimization, incorporating detailed renewable resource data, component specifications, and economic parameters. Meteorological input data derives from hourly solar irradiance and wind speed data for the selected site location of Tunis (36°49′08″ N, 10°09′56″ E). Solar resource averaging 5.6 kWh/m²/day global horizontal irradiance and wind resources with mean speeds of 6.3 m/s at 80 m height characterize the site as favorable for hybrid renewable development. MATLAB/Simulink supplements HOMER analysis with detailed dynamic simulations of the solar system.

5.2. Control Strategy and Energy Management

The energy management system (EMS), which was illustrated in our previous study [34], implements a hierarchical control architecture with multiple operational modes optimized for different objectives [34]. The primary control layer ensures safe operation within component limitations, while supervisory control optimizes energy flows based on forecasts, market signals, and operational constraints. The electrolyzer operating strategy prioritizes continuous operation above minimum load (15% rated capacity) to minimize thermal cycling and associated degradation [34]. When renewable generation exceeds this threshold, the electrolyzer follows available power up to rated capacity. Excess generation beyond electrolyzer capacity is directed to battery storage (200 kWh) for short-term buffering or exported to the grid where interconnection exists. During periods of low renewable generation, the control system evaluates multiple options:

(a)

maintain minimum electrolyzer operation using grid power if economically favorable;

(b)

suspend electrolysis and utilize stored hydrogen for critical loads;

(c)

activate the stationary fuel cell to support EV charging demand.

5.3. Renewable Energy Generation Profiles

We implemented all previous models using MATLAB/Simulink software, with several climatic conditions (solar irradiation and ambient temperature). The parameters used for the simulation of the different components of the hydrogen production and storage system are illustrated in

Table 4. Component parameters of the solar H2 plant.

Component	Parameter	Value	Unit
Solar PV Array
	Installed Capacity	1200	kWp
	Module Type	Monocrystalline Si	-
	Module Efficiency	20	%
	Number of Modules	3042	units
	Annual Generation	1924	MWh
Wind Turbines
	Installed Capacity	800	kW
	Number of Turbines	2	units
	Hub Height	80	m
	Rated Speed	10	m/s
	Annual Generation	1752	MWh
PEM Electrolyzer
	Capacity	1000	kW
	Operating Pressure	30	bar
	Operating Temperature	60–80	°C
	Efficiency (HHV)	62	%
	Water Consumption	9	L/kg H2
Fuell cell
	Capacity	250	kW
	Operating Pressure	30	bar
	Efficiency (HHV)	60	%

. Data and geographic position of these curves correspond to Tunis city with GPS localization.

Three scenarios are adopted (Only PV, Only Wind, and Hybrid)

-

Scenario 1: Photovoltaic station of 1.2 MW: only PV source

Site: Tunis Latitude: 36°49′08″ N, Longitude: 10°09′56″ E

According to Figure 5, Figure 6, Figure 7, Figure 8, Figure 9 and Figure 10, the average values for solar radiation, wind speed, energy produced, and hydrogen production are calculated over monthly periods (January to December) by taking the arithmetic mean of 30 days in each month. This also allows for the calculation of annual production and gains for the entire year in question. This is necessary for calculating costs, cost price, and energy satisfaction rates.

The simulation results illustrated in Figure 5, Figure 6, Figure 7, Figure 8, Figure 9 and Figure 10 demonstrate strong complementarity between solar and wind resources at the selected site. Annual solar generation totals 1924 MWh from the 1.2 MWp array, with monthly variation ranging from 98 MWh in December to 241 MWh in July. The capacity factor of 18.3% reflects the impact of two-axis tracking in Southern Spain’s favorable solar conditions. Wind generation contributes 1752 MWh annually from the 800 kW installation, achieving a 25% capacity factor with peak production during winter months (December–February) when solar generation is minimal. The combined renewable generation profile shows remarkable consistency, with the standard deviation of daily energy production reduced by 38% compared to the solar-only configuration. This improved consistency directly translates to enhanced electrolyzer utilization, with operational hours increasing from 3124 (solar only) to 6234 (hybrid) annually.

-

Scenario 2: Wind station

Site: Bizerte (North of Tunisia). Latitude: 37°16′27.91″ N, Longitude: 9°52′26.08″ E.

5.4. Electrolyzer Performance and Hydrogen Production

Table 5. Solar plant outputs with three configurations (PV-only, Wind-only, and hybrid).

Month	Solar Generation (MWh)	Wind Generation (MWh)	Total Renewable (MWh)	Electrolyzer Input (MWh)	H2 Production (ton)	Grid Export (MWh)
Jan	98.4	187.3	285.7	248.2	4.2	15.8
Feb	112.7	172.4	285.1	251.3	4.3	12.4
Mar	156.8	165.2	322.0	278.9	4.8	21.3
Apr	189.2	143.6	332.8	290.4	5.0	24.7
May	213.4	128.9	342.3	298.7	5.1	28.9
Jun	227.6	112.3	339.9	295.8	5.0	31.2
Jul	241.2	104.7	345.9	301.2	5.1	33.6
Aug	224.8	108.9	333.7	289.6	4.9	30.8
Sep	178.9	124.5	303.4	263.2	4.5	25.7
Oct	143.2	156.8	300.0	259.8	4.4	22.9
Nov	104.6	178.9	283.5	245.7	4.2	18.6
Dec	98.2	192.5	290.7	252.3	4.3	16.4
Total	1989.0	1776.0	3765.0	3275.1	55.8	282.3

illustrates the monthly indicators of the three configurations (PV-only, Wind-only, hybrid). The PEM electrolyzer demonstrates excellent load-following capabilities when operated with the hybrid renewable input (PV = 1.2 MW, Wind = 0.8 MW). The system achieves an annual average efficiency of 65% with 8% of surplus exported to the electricity grid. Annual hydrogen production totals 55,873 kg, representing a specific energy consumption of 3275 MWh/year. The monthly production profile shows relative stability, ranging from 4200 kg in November to 5100 kg in July, demonstrating the effectiveness of resource complementarity. The electrolyzer capacity factor of 65% significantly exceeds typical values for single-source systems (50–60%), validating the hybrid approach’s economic advantages [34].

Table 6. Hydrogen plant indicators.

Parameter	Daily Average	Annual Total	Unit
H2 Production	153.1	55,873	kg
Electrolyzer Operating Hours	17.1	6241	h
Electrolyzer Capacity Factor	65	65	%
Storage Pressure Range	350	-	bar
Compression Energy	0.54	198	MWh
H2 to FCEV Refueling	117.6	42,924	kg
H2 to fuel cell	24.4	8966	kg
Storage Efficiency	89	89	%
H2 Purity	99.99	99.99	%
Water Consumption	1.28	468	m3

presents the main operational and energy indicators of the hydrogen production, storage, and utilization system on a daily and annual basis. Average daily hydrogen production reaches 153 kg, resulting in a monthly production of 5 tonnes of H2 as illustrated in Figure 11, and an annual production of 55,873 kg, reflecting a suitable sizing of the electrolyzer for a mid-scale hydrogen mobility application. The annual operating hours of the electrolyzer (6241 h/year) correspond to a load factor of 65%, indicating a good match between the availability of renewable energy sources and the capacity of the electrolysis system. The energy consumed for compression, estimated at 0.54 MWh per day (or 198 MWh/year), represents a significant portion of the system’s overall energy consumption, highlighting the importance of optimizing storage and compression strategies. The distribution of the hydrogen produced shows that the majority is used to refuel the fuel cell electric vehicles (42,924 kg/year, or approximately 77%), while a smaller fraction powers a fuel cell (8906 kg/year) for auxiliary electricity generation, thus improving the system’s flexibility and energy resilience. The high storage efficiency (89%) and the purity of the hydrogen produced (99.99%) confirm the quality of the process and its compliance with the stringent requirements of hydrogen mobility. Finally, water consumption, estimated at 1.28 m³ per day (or 468 m³/year), remains moderate relative to the volumes of hydrogen produced, which reinforces the overall sustainability of the system, particularly when combined with recycling solutions or non-potable water supply.

The radar chart in Figure 12 presents a comparative assessment of PEM electrolysis and alkaline electrolysis across four key dimensioning criteria: design, technology, applications, and operating conditions (see also Table 5). The results highlight the relative strengths and limitations of each technology and justify the choice of PEM electrolysis for advanced hydrogen systems. From a design perspective, PEM electrolysis exhibits a moderate score compared to alkaline technology, reflecting its more compact architecture but also its higher material and manufacturing complexity. Nevertheless, the reduced footprint and modularity of PEM systems make them particularly attractive for decentralized and space-constrained installations. In terms of technology maturity, alkaline electrolysis scores higher due to its long industrial history and proven reliability. However, PEM electrolysis still demonstrates strong technological performance, benefiting from rapid advancements in membrane materials, catalysts, and power electronics, especially in applications coupled with renewable energy sources.

5.5. Storage System Performance

The hydrogen storage system successfully manages production-demand imbalances while maintaining safe operating pressures. The 153 kg storage capacity (approximately 4750 Nm³ at 350 bar) provides 3 days of average production buffer, enabling continued operation during extended periods of low renewable generation or high demand. The compression system consumes 198 MWh annually, representing 5% of total renewable generation. Storage efficiency, accounting for compression energy and minor hydrogen losses through seals and purging, reaches 88% (see efficiency value of Figure 13). The energy penalty is partially offset by pressure recovery during dispensing, with expansion energy recovery reducing net compression requirements by approximately 12%.This relatively high efficiency reflects the advanced composite tank design with minimal permeation and optimized pressure management strategies. Figure 13 also shows that the Capacity value is evaluated to 72%.

5.6. Fuel Cell Performance and Grid Support

According to Figure 14, the 250 kW stationary PEM fuel cell operates 2847 h annually, primarily during evening peak demand periods and low renewable generation events. The fuel cell consumes 8966 kg of hydrogen annually, generating 438 MWh of electricity at an average efficiency of 55%. The efficiency varies with load around 58%. During simulated grid outage events, the fuel cell maintained critical charging infrastructure for up to 72 h using stored hydrogen reserves. Heat recovery from the fuel cell provides 402 MWh of thermal energy annually at 60–70 °C, suitable for electrolyzer preheating and facility space heating. This cogeneration capability improves overall system efficiency by 8%, demonstrating the benefits of integrated system design.

5.7. Hydrogen End-Use Analysis

Table 7. Hydrogen utilization and end-use analysis.

Application	Daily Average (kg of H2)	Monthly Range (kg of H2)	Annual Total (kg of H2)	Energy Equivalent (MWh)	Revenue (€)
FCEV Refueling
Passenger Vehicles	78.4	2156–2487	28,616	952.3	200,312
Buses	26.1	719–829	9527	317.0	66,689
Trucks	12.8	352–406	4673	155.5	32,711
Forklifts	0.5	14–16	183	6.1	1281
Stationary Applications
Fuel Cell to Grid	24.4	672–963	892	296.8
Backup Power	3.2	88–112	1168	38.9	8176
Indus Use	7.4	204–259	2701	89.9	18,907
Total	152.8	4205–4672	55,788	1856.5	328,000

’s value analysis reveals that the proposed integrated hydrogen system is predominantly a green mobility solution, with over 77% of its 55,788 kg/year output allocated to FCEV refueling, and passenger vehicles alone driving 61% of the total €328,000 annual revenue. While the H2 demand is heavily concentrated in the transport sector, the inclusion of fuel cell-to-grid (the largest stationary use) is crucial for operational resilience, allowing the system to consume excess intermittent solar/wind power and stabilize the electrical grid. The system operates at a small-to-medium scale, 152.8 kg/day, with an implied selling price of 5.88 €/kg. The commercial success will therefore be highly dependent on achieving the necessary economies of scale to keep the Levelized Cost of Hydrogen below this target price.

Figure 15 illustrates the distribution of revenues by final application of hydrogen. There is a strong dominance of the private vehicle sector, which generates by far the highest revenue, indicating that individual mobility is currently the main economic driver of the hydrogen market. Hydrogen buses occupy second position, with significant revenues, reflecting the growing interest in low-carbon public transport policies. Trucks have intermediate potential, consistent with their progressive adoption in heavy transport. In contrast, industrial applications, backup power and forklifts generate significantly lower revenues, suggesting either a still emerging market or more targeted adoption. Overall, the figure highlights that mobility remains the main economic lever for the deployment of hydrogen in the short and medium term.

6. Economic Analysis

The goal of the economic analysis is to estimate:

-

CAPEX and OPEX breakdown;

-

Levelized Cost of Hydrogen (LCOH);

-

Levelized Cost of Electricity (LCOE) for EV charging from H_2;

-

Profitability indicators: NPV, IRR, payback;

-

Sensitivities to key techno-economic parameters.

The economic evaluation employs Levelized Cost analysis complemented by detailed cash flow modeling over a 20-year project lifetime. Capital costs (CAPEX) include all equipment, installation, and commissioning expenses based on recent market data and vendor quotations. Operating costs (OPEX) encompass maintenance, replacement parts, water, and grid electricity when required. The levelized cost of hydrogen (LCOH) is calculated as follows:

$$LCOH= {\displaystyle \frac{\sum \frac{CAPEXt+OPEXt}{{\left(1+\mathrm{r}\right)}^2}}{\sum \frac{H2 Prod, t}{{\left(1+\mathrm{r}\right)}^2}}}$$

(24)

where:

r: represents the discount rate (6% base case: standard value);

n: is the project lifetime;

(H₂,prod,t): is the annual hydrogen production;

CAPEXt: Capital Expenditure for the year (t);

OPEXt: Operating Expenditure for the year (t).

The CAPEX: (Capital Expenditure) refers to the initial investment costs required to design and build a project or asset. In a hydrogen energy project, CAPEX includes the following:

• Renewable generation systems (PV panels, wind turbines).
• Electrolyzer system (stack, power electronics, balance of plant).
• Hydrogen storage (tanks, compression systems).
• Refueling station infrastructure (dispensers, safety systems).
• Grid connection and electrical infrastructure.
• Control, monitoring, and safety systems.

CAPEX = ∑ (Equipment Cost + Installation cost + Engineering cost + Infrastructure cost)

(25)

The OPEX (Operating Expenditure) refers to the ongoing, recurring costs required to operate and maintain a system or project throughout its lifetime. Unlike CAPEX, OPEX is incurred continuously (annually or monthly) after commissioning. In a hydrogen energy project, typical OPEX includes the following:

• Electricity cost for electrolyzer operation.
• Water consumption and treatment.
• Routine maintenance of electrolyzers, compressors, and storage systems.
• Replacement of components.
• Personnel and monitoring systems.
• Insurance, safety inspections, and regulatory compliance.

We can write:

OPEX = electricity cost + maintenance cost + consumables cost +insurance cost

(26)

OPEX has a direct impact on hydrogen production cost (LCOH) and often represents a significant share of total lifetime cost, especially when electricity prices are high.

6.1. Capital Investment Breakdown Evaluation

The total capital investment for the system, which is illustrated by

Table 8. CAPEX costs of the H2 solar plant.

Subsystem	Size Specific	Cost	CAPEX (M€)
PV(modules + BoS + tracking)	1.2 MWp	850 €/kWp	1.02
Wind (800 kW)	0.8 MW	1200 €/kW	0.96
PEM Electrolyzer	1 MW	1150 €/kW	1.15
H2 Tanks (350–700 bar)	200 kg	1050 €/kg H2	0.21
PEMFC	0.25 MW	1000 €/kW	0.25

and Figure 16, was estimated to be €3,590,000 distributed across five subsystems. The PV array, including modules, balance of system, and tracking, represents €1,020,000 (28.4% of total CAPEX), while the wind turbine (800 kW) accounts for €960,000 (26.7%). The PEM electrolyzer system constitutes the largest investment at €1,150,000 (32.0%), reflecting a specific cost of 1150 €/kW. Hydrogen storage in high-pressure tanks (350–700 bar, 200 kg H₂ capacity) requires €210,000 (5.8%), based on a specific cost of 1050 €/kg H₂. The stationary fuel cell system (PEMFC, 0.25 MW) adds €250,000 (7.0%), at a specific cost of 1000 €/kW. The specific system investment cost amounts to 3590 €/kW (based on electrolyzer capacity of 1 MW), which aligns with current market benchmarks for integrated renewable hydrogen systems. Projected cost reductions of 30–40% by 2030 through technology learning and scale effects would improve project economics.

6.2. Operating Costs and Revenue Evaluation

Figure 17 provides a breakdown of the projected Year 1 Operational Expenditure (OPEX), totaling €69,810. The chart highlights that maintenance of the energy generation assets is the primary cost driver.

The largest share of the budget goes to maintaining the renewable energy infrastructure. PV O&M and Wind O&M each contribute €14,400, together representing 41.2% of total operational costs. Direct hydrogen production costs are the next significant tier. Electrolyzer maintenance (€10,000, 14.3%) combined with essential Water and chemicals feedstocks (€8460, 12%) account for over a quarter of the annual spend. The remaining third covers necessary supporting infrastructure, including Monitoring and telecom (12%), Grid connection fees (7.7%), administrative overhead (7.2%), and smaller fuel cell maintenance costs (5.4%). Overall, the data indicate that over 60% of the first year’s operational budget is dedicated directly to equipment maintenance.

6.3. Levelized Cost of Hydrogen (LCOH)

The Levelized Cost of Hydrogen production reaches €5.82/kg over the 20-year project lifetime, assuming a 6% discount rate. This cost includes all capital and operating expenses but excludes potential revenue from grid services and EV charging, which could reduce net costs to approximately €4.95/kg when fully valued. Comparative analysis with alternative production methods shows competitiveness with grid-connected electrolysis (€5.50–7.00/kg) and approaching parity with blue hydrogen (€4.50–5.50/kg including carbon capture). Continued renewable cost reductions and electrolyzer improvements project LCOH below €3.50/kg by 2030, achieving cost parity with gray hydrogen without carbon pricing. The economic evaluation employs levelized cost analysis complemented by detailed cash flow modeling over a 20-year project lifetime.

Table 9. Seasonal performance of a hybrid solar–wind hydrogen production system.

Season	Solar CF (%)	Wind CF (%)	Combined CF (%)	H2 Production (kg)	Electrolyzer CF (%)	LCOH (€/kg)
Winter	12.8	31.2	20.8	12,824	68.4	6.12
Spring	19.4	24.8	21.8	14,807	72.8	5.67
Summer	22.3	18.9	20.8	15,127	74.3	5.58
Autumn	16.9	26.3	21.2	13,115	69.1	5.94

presents the seasonal performance of a hybrid solar–wind hydrogen production system, highlighting the interplay between renewable capacity factors, electrolyzer utilization, hydrogen output, and production cost. Winter shows low solar availability (12.8%) but strong wind performance (31.2%), resulting in a moderate combined capacity factor (20.8%). Despite reduced hydrogen production, the electrolyzer maintains a relatively high utilization (68.4%), though the LCOH is highest (6.12 €/kg) due to lower overall energy efficiency and seasonal constraints. In spring and summer, higher solar capacity factors significantly improve system performance. Summer achieves the highest hydrogen production (15,127 kg) and electrolyzer capacity factor (74.3%), leading to thelowest LCOH (5.58 €/kg). Spring shows comparable behavior, benefiting from balanced solar and wind contributions. Autumn benefits from renewed wind dominance (26.3%), but lower solar input slightly limits hydrogen output, increasing LCOH to 5.94 €/kg as illustrated in Figure 18. Overall, the table demonstrates that higher combined renewable capacity factors increase electrolyzer utilization, enhance hydrogen production, and reduce LCOH, confirming the advantage of seasonal complementarity between solar and wind resourcesin stabilizing hydrogen supply and cost.

6.4. Financial Metrics

The graph of Figure 19 clearly summarizes the economic superiority of the Hybrid PV and Wind configuration over single-source systems. The key metric, LCOH (Levelized Cost of Hydrogen), is the lowest for hybrid, standing at around €5.8/kg (a significant reduction compared to €7.8/kg for PV alone).

This performance is directly linked to the improvement in the load factor of the electrolyzer due to the complementarity of the sources, allowing better amortization of the invested capital. Consequently, the hybrid configuration displays the highest Internal Rate of Return (IRR), exceeding 8.5%, making it the most profitable option. It also has the shortest Payback Period of around 11.3 years, reducing exposure to risks and increasing attractiveness for investors.

In conclusion, hybridization is the optimal strategy to ensure the competitiveness and long-term financial viability of the green mobility infrastructure project.

7. Environmental Impact Assessment

7.1. CO₂ Reduction

The environmental impact assessment of the integrated solar–wind hydrogen refueling and charging station focuses on life-cycle greenhouse gas (GHG) reductions, local air quality benefits, resource use (water and land), and pollutant avoidance compared with conventional fossil-based alternatives. According to

Table 10. Environmental impact assessment.

Metrics	Value	Unit	Baseline	Reduction (%)
Annual CO2 Avoided (vs. Grid)	1656	t CO2/year	0.45 kg/kWh	100
Annual CO2 Avoided (vs. Grey H2)	518	t CO2/year	9.3 kg CO2/kg H2	100
Lifetime CO2 Reduction	2834	t CO2	20-year operation	-
Carbon Payback Period	2.3	years	Manufacturing emission	-
Water Consumption	468	m3/year	-	-
Land Use	4.2	hectares	-	-
NOx Emissions Avoided	2.84	t/year	Diesel generators	100
PM2.5 Emissions Avoided	0.156	t/year	Diesel generators	100
SO2 Emissions Avoided	1.23	t/year	Coal power	100

, the life-cycle carbon footprint analysis reveals substantial environmental benefits compared to conventional alternatives. Annual CO₂ emission reductions total 1656 tonnes compared to grid-powered hydrogen production (assuming 450 g CO₂/kWh grid intensity). When displacing gray hydrogen from steam methane reforming, emission reductions reach 518 tons of CO₂ annually. The complete life-cycle assessment, including manufacturing and end-of-life impacts, shows carbon payback within 2.3 years.

The “payback” period represents the time it takes for the station’s annual CO₂ savings (1656 tonnes vs. grid or 518 tonnes vs. gray hydrogen) to offset the initial carbon “debt” created during its production and future disposal.

The renewable infrastructure’s 20-year lifetime ensures significant net carbon reduction, totaling approximately 32,120 tonnes CO₂ equivalent over the project duration. Water consumption of 468 m³ annually for electrolysis represents minimal environmental impact, particularly when using treated wastewater or seawater with appropriate preprocessing.

7.2. Key Findings on Environmental Impact and LCA

Here is a short idea about an evaluation of the full life-cycle assessment (LCA).

-

Carbon Footprint and Payback: The full life-cycle analysis, including manufacturing and end-of-life impacts (embodied emissions of PV panels, wind turbines, electrolyzers, and storage systems), shows a Carbon Payback Period of 2.3 years. This rapid recovery period confirms that the emissions generated during the manufacture of the renewable infrastructure are quickly offset by the clean hydrogen production.

-

Lifetime Emission Reduction: Over the 20-year project duration, the system is projected to achieve a significant net carbon reduction totaling approximately 32,120 tonnes CO₂ equivalent (1656 tonnes/year × 20 years = 33,120 tonnes).

-

Comparison to Conventional Methods (CO₂ Avoidance): Versus Grid-Powered Hydrogen: The system avoids 1656 tonnes of CO₂ annually compared to producing hydrogen using grid electricity (assuming a grid intensity emissions of 450 g CO₂/kWh: https://www.iea.org/reports/electricity-2025/emissions accessed on 1 January 2026).

-

Comparison to Conventional Methods Versus Gray Hydrogen: When displacing conventional hydrogen from Steam Methane Reforming (SMR, or “gray hydrogen”), the annual emission reduction is 518 tonnes CO₂.

-

Pollutant Avoidance: In addition to CO₂ reductions, the system eliminates local pollutant emissions typically associated with fossil fuels, including NOx, PM2.5, and SO₂.

8. Discussion and Comparison

8.1. Advantages of the Proposed Integrated System

The advantages of the proposed hybrid PV-Wind system over standalone (PV-only or Wind-only) systems are extensively highlighted through the comparison in the results synthesis, illustrated in

Table 11. Comparison of configuration scenarios.

Advantage	Hybrid PV + Wind System	Standalone Systems (PV-Only/Wind-Only)
Energy Generation	Highest annual generation (3765 MWh).	Lower generation (1989 MWh and 1776 MWh, respectively).
Resource Stability	Significantly reduces generation variability (28.4) due to resource complementarity.	Higher generation variability.
Hydrogen Production	Produces 55,873 kg of H2 annually (nearly double PV-only).	Lower production.
Electrolyzer Utilization	High capacity factor (71.2%). This leads to fewer start/stop cycles and improved equipment lifetime.	Lower utilization and more frequent cycling negatively affecting durability.
Economic Viability	Lowest LCOH (€5.82/kg) and highest Internal Rate of Return (IRR) (8.7%).	Lower financial viability; the hybrid LCOH is 25.6% better than the PV-only configuration.
Resilience	Ensures over 60 h of grid-independent operation.	Likely less resilient due to dependence on a single intermittent source.

.

Resource Stability (RS) refers to the consistency, duration, and predictability of the power supply provided by the renewable source (Wind or Solar).

RS = 1 − (σ_p/μ_p)

(27)

μp = Mean power (MW).

σp = Standard deviation of power (MW).

According to

Table 12. Technical, operational, and economic performance of three hydrogen production configurations.

Performance Metric	Category	PV-Only System	Wind-Only System	Hybrid PV + Wind
Annual Power Generation	Energy Generation	1989 MWh	1776 MWh	3765 MWh
System Capacity Factor	Energy Generation	18.3%	25.0%	21.5%
Generation Variability	Operational Stability	45.8	38.2	28.4
Annual H2 Production	Hydrogen Prod	27,340 kg	30,180 kg	55,873 kg
Electrolyzer Operating Hours	Electrolyzer Use	3124 h/yr	3854 h/yr	5980 h/yr
Electrolyzer Capacity Factor	Electrolyzer Use	35.7%	44.0%	71.2%
Start/Stop Cycles	Equipment Lifespan	487 cycles	312 cycles	186 cycles
Average System Efficiency	Conversion Efficiency	65.8%	66.9%	68.2%
LCOH (€/kg)	Economic Metric	€7.82	€6.94	€5.82
IRR (%)	Financial Metric	3.8%	5.9%	8.7%

, Annual energy = 3765 MWh and Hours per year = 5980 H, then μ_p = 3765/5980 = 0.62.

If we adopt a standard deviation σ_p = 0.45, then RS= 1 − (0.45/0.62) = 28% = 0.28.

8.2. Main Limitations

The main limitations of this study, based on the provided text, include the following:

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Exclusion of Revenue in Primary LCOH Calculation: The initially calculated Levelized Cost of Hydrogen (LCOH) of €5.82/kg excludes potential revenue streams from grid services and EV charging. While the study estimates a potential net cost reduction to €4.95/kg if these are fully valued, the primary reported LCOH does not reflect this.

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Reliance on Simulation: The study is based on detailed techno-economic simulation using HOMER Pro and MATLAB/Simulink. While comprehensive, simulation results may differ from real-world performance due to unforeseen component degradation, control system complexities, or site-specific weather variations not fully captured by the average meteorological data.

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Future Cost Projections: The viability assessment relies on projected cost reductions (LCOH below €3.50/kg by 2030) to achieve parity with gray hydrogen, which assumes continued technological advancements in renewables and electrolyzers. If these cost reductions do not materialize as rapidly as projected, the long-term economic competitiveness may be affected.

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Grid Interconnection Constraints: While the system can provide grid services, the paper notes that “grid capacity constraints in many regions limit export potential, necessitating careful siting and potentially costly grid upgrades,” which could pose a significant practical limitation for replication.

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Fixed Discount Rate: The LCOH calculation is based on a fixed 6% discount rate over the 20-year project lifetime. Changes in actual financing costs or market interest rates could significantly alter the financial viability metrics (IRR and LCOH).

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Focus on Specific Location Data: The meteorological data (solar irradiance and wind speed) used for simulation are specific to Tunis (36°49′08″ N and 10°09′56″ E). The scalability and replication potential in other geographic regions would require site-specific optimization, as resource profiles greatly influence the hybrid system’s performance.

8.3. Scalability and Replication Potential

The modular system architecture facilitates scaling from demonstration to commercial deployment. The design principles and control strategies remain valid across scales from 100 kW to 10 MW electrolyzer capacity, with economies of scale improving economics for larger installations. Preliminary analysis suggests 1 MW systems could achieve LCOH of €5.50/kg with current technology costs. Geographic replication potential extends to regions with complementary renewable resources, particularly coastal areas with combined solar and wind availability. Adaptation to local conditions requires site-specific optimization of component sizing and control strategies, but the fundamental architecture remains applicable. Tropical regions with consistent resources might achieve even higher capacity factors, while northern latitudes benefit from stronger wind resources offsetting reduced solar availability. Integration with existing energy infrastructure presents both opportunities and challenges. Furthermore, grid-connected configurations can provide valuable balancing services while also benefiting from backup power during prolonged periods of low production. However, grid capacity constraints in many regions limit export potential, necessitating careful site selection and grid upgrades tailored to the hydrogen production value chain and its transport and distribution infrastructure [38].

8.4. Results Synthesis

Table 12 compares the technical, operational, and economic performance of three hydrogen production configurations: PV-only, wind-only, and hybrid PV–wind systems. From an energy perspective, the hybrid system delivers the highest annual power generation (3765 MWh), benefiting from resource complementarity, while the wind-only system shows the highest individual capacity factor (25%). Importantly, the hybrid configuration significantly reduces generation variability (28.4)compared to PV-only and wind-only systems, enhancing operational stability. In terms of hydrogen production, the hybrid system clearly outperforms standalone solutions, producing 55,873 kg of H₂ annually, nearly double that of the PV-only system. This improved power availability results in a much higher electrolyzer capacity factor (71%), fewer start/stop cycles, and improved equipment lifetime. By contrast, standalone systems experience more frequent cycling and lower utilization, which negatively affects durability and performance. Economically, the hybrid system demonstrates thelowest LCOH (5.82 €/kg)and thehighest IRR (8.7%), confirming its superior financial viability. The higher average system efficiency further reinforces these benefits. International standard values indicate that an IRR between 6% and 9% is acceptable and considered a “low risk” system or project.

The moderate IRR values of single-source systems (PV-Only or Wind-Only) is that the hybrid configuration improves the load factor of the electrolyzer, allowing for better amortization of invested capital. Conversely, standalone systems experience more frequent cycling and lower utilization (lower capacity factor), which negatively affects durability and performance, leading to lower profitability metrics like IRR.

The project’s viability is highly sensitive to three major uncertainties:

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Electrolyzer Degradation: A shorter stack lifetime (e.g., 5 years) or increased catalyst price volatility would necessitate more frequent replacement CAPEX, potentially driving the Levelized Cost of Hydrogen (LCOH) above €6.50/kg.

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Hydrogen Price Volatility: A 10% reduction in the H₂ selling price would extend the Payback Period from 11 years to 14–16 years, severely impacting the IRR.

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CAPEX Risk: A 10% overrun in initial capital expenditure would push the LCOH towards €6.20/kg, reducing competitiveness against alternative production methods.

8.5. Energy Management System (EMS)

The hybrid solar-wind system’s Energy Management System (EMS) offers superior performance compared to single-source strategies by maximizing resource complementarity. This results in a higher electrolyzer capacity factor (71% vs. 35% for PV-only) and a sharp reduction in component stress (186 start/stop cycles vs. 487). Unlike conventional grid-dependent systems, the EMS enables significant environmental gains (1656 tonnes annual CO₂ reduction) and enhances resilience with over 60 h of grid-independent operation. Furthermore, the architecture’s integration of hydrogen reconversion (Power-to-Electricity via a stationary fuel cell) allows the EMS to flexibly support both FCEV refueling and EV charging infrastructure. Compared to other EMS, like those developed by Hammoudi [39] and Dhifli [40], our strategy gives more advantages and performances, especially for efficiency and capacity.

8.6. Comparison with Other Projects

A comparison with other research and projects of hydrogen production for mobility was conducted and illustrated in Table 13. The table compares several green hydrogen production projects and studies, focusing on system configuration, H₂ production, electrolyzer capacity factor, and LCOH. The proposed project, combining 1.2 MW solar PV with 0.8 MW wind, achieves a moderate production of 153 kg/day (55.8 t/yr) with a high capacity factor of 71% and a competitive LCOH of €5.82/kg. This highlights the advantage of hybrid systems, which effectively mitigate the intermittency of single renewable sources. By contrast, single-source wind projects show more variable performance. For example, South African wind-only installations achieve 145 kg/day but with a lower capacity factor (45%) and a higher LCOH ($6.34–$8.97/kg), reflecting the impact of intermittent generation on electrolyzer utilization. Large-scale dedicated wind plants, such as Bad Lauchstädt in Germany, reach much higher production (1350 kg/day) and a relatively low LCOH (€5.50/kg), demonstrating economies of scale, although such centralized projects may not suit localized applications. Smaller-scale or on-site systems, like the Korean case study (70 kg/day, 40% capacity factor), show higher LCOH (€8.06/kg), emphasizing the challenges of low utilization. Overall, the proposed hybrid project balances production efficiency and cost-effectiveness, outperforming European averages (€6.70/kg) and showing that combining solar and wind is a viable strategy for sustainable, decentralized green hydrogen production.

Table 13. Technical and economic performance of three hydrogen production configurations.

Project/Study Context	System Configuration	H2 Production Capacity	Electrolyzer Capacity Factor	LCOH (€/kg)
Proposed Project	Hybrid Solar PV (1.2 MW) + Wind (0.8 MW)	153 kg/day (55.8 t/yr)	71%	€5.82
Turkey Case Study (Gökçeada Island) [41]	Hybrid Wind + PV + Battery	125 kg/day	65%	€7.92
South Africa Study (7 Cities) [42]	Wind-Powered only	145 kg/day	45%	€5.6–€7.98
Korea Case Study (Small-scale) [43]	On-site Production (General)	70 kg/day	40%	€8.06
Bad Lauchstädt Central Germany [44]	Dedicated Wind Farm (50 MW)	1350 kg/day	66%	€5.50
European Average (On-site RES)	Electrolysis connected to RES	Varies	Varies by source	€6.70

Table 13. Technical and economic performance of three hydrogen production configurations.

Project/Study Context	System Configuration	H2 Production Capacity	Electrolyzer Capacity Factor	LCOH (€/kg)
Proposed Project	Hybrid Solar PV (1.2 MW) + Wind (0.8 MW)	153 kg/day (55.8 t/yr)	71%	€5.82
Turkey Case Study (Gökçeada Island) [41]	Hybrid Wind + PV + Battery	125 kg/day	65%	€7.92
South Africa Study (7 Cities) [42]	Wind-Powered only	145 kg/day	45%	€5.6–€7.98
Korea Case Study (Small-scale) [43]	On-site Production (General)	70 kg/day	40%	€8.06
Bad Lauchstädt Central Germany [44]	Dedicated Wind Farm (50 MW)	1350 kg/day	66%	€5.50
European Average (On-site RES)	Electrolysis connected to RES	Varies	Varies by source	€6.70

9. Conclusions

This comprehensive study demonstrates the technical feasibility and economic viability of integrated solar-wind hydrogen production systems for sustainable mobility infrastructure. The hybrid renewable configuration achieves superior performance compared to single-source alternatives, with key findings. The hybrid system combining 1.2 MWp solar PV and 800 kW wind generation feeding a 1 MW PEM electrolyzer achieves 71% capacity factor, producing 51.8 tonnes of green hydrogen annually. This performance substantially exceeds typical single-source configurations, validating the complementarity benefits of hybrid renewable systems.

Economic analysis reveals a Levelized Cost of Hydrogen of €5.82/kg under current technology costs, with 25.6% of improvement over the PV-only configuration and is highly competitive against global market benchmarks. Consequently, the project exhibits a strong financial profile, boasting an Internal Rate of Return (IRR) of 8.7% and a quick carbon period of 2.3 years. The integrated architecture successfully supports both FCEV refueling and EV charging through flexible hydrogen storage and reconversion, demonstrating the feasibility of unified sustainable mobility infrastructure. The system maintains over 60 h of grid-independent operation, enhancing resilience and reducing infrastructure vulnerability. Environmental assessment confirms substantial benefits, with annual CO₂ emission reductions of 1656 tonnes and efficient resource utilization. The modular, scalable design enables deployment across diverse geographic regions and scales, from distributed community systems to industrial-scale facilities.

Future research priorities should focus on advanced control optimization incorporating machine learning techniques, integration of emerging electrolyzer technologies, and demonstration of multi-sector coupling, including industrial applications. Long-term performance validation through operational pilot projects will provide critical data for technology refinement and commercial deployment.