# Techno-economic and environmental evaluation of on-site solar hydrogen systems for decarbonizing port in Corsica

Mohamed Hajjaji, Maude Chin Choi, Tchougoune Moustapha Mai, Christian Cristofari, Dhafer Mezghani, Abdelkader Mami

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Mohamed Hajjaji, Maude Chin Choi, Tchougoune Moustapha Mai, Christian Cristofari, Dhafer Mezghani, et al.. Techno-economic and environmental evaluation of on-site solar hydrogen systems for decarbonizing port in Corsica. International Journal of Hydrogen Energy, 2025, 134, pp.229-240. 10.1016/j.ijhydene.2025.05.035. hal-05483331

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Distributed under a Creative Commons CC BY 4.0 - Attribution - International License
Techno-Economic and Environmental Evaluation of On-
Site Solar Hydrogen Systems for Decarbonizing Port in
Corsica

Mohamed HAJJAJI<fnref n="1" />,<fnref n="2" />*, Maude CHIN CHOI<fnref n="1" />, Tchougoune Moustapha MAI<fnref n="1" />, Christian CRISTOFARI<fnref n="1" />, Dhafer MEZGHANI<fnref n="2" /> and Abdelkader MAMI<fnref n="2" />

Abstract

As part of the energy transition and efforts to develop green ports, green hydrogen emerges as a promising and environmentally sound solution for achieving carbon neutrality. This study investigates the potential of green hydrogen to decarbonize the Port of Ajaccio through a power-to-power strategy. A detailed electricity consumption profile was constructed based on data from docked vessels and two adjacent buildings. A multi-objective optimization model was employed to determine the optimal configuration of a hybrid energy system.
The optimal system includes 12 MW of photovoltaic panels, a 5 MW electrolyzer, a 3 MW fuel cell, and 320 kg of hydrogen storage under water at 35 bar. This configuration enables a significant reduction in pollutant emissions: carbon dioxide (CO₂) by 80.02%, nitrogen oxides (NOx) by 84.27%, particulate matter (PM) by 84.27%, and sulfur dioxide (SO₂) by 84.26%. The resulting levelized cost of electricity (LCOE) is estimated at 298 €/MWh, making it a competitive alternative to conventional fossil-fuel-based generation. Furthermore, the study highlights the advantages of underwater hydrogen storage, demonstrating that greater storage depths lead to increased hydrogen density, reduced storage volume requirements, and minimized visual impact an essential aspect for enhancing public acceptance.

**Keywords:** Green ports, green hydrogen, carbon neutrality, power-to-power, underwater hydrogen storage

**1.Introduction**

On December 12, 2015, the United Nations Climate Change Conference (COP21) led to the Paris Agreement [1], committing signatories to reduce carbon dioxide (CO₂) emissions to achieve carbon neutrality by 2050. More recently, COP29 (November 11-22, 2024, Baku, Azerbaijan) assessed the progress of its implementation [2]. Despite significant efforts by the European Union, which halved its emissions, many countries are still struggling to meet their climate targets. This situation is particularly concerning in island territories, where emission levels can be up to three times higher than on the mainland [3]. Among the most lagging sectors, maritime transport remains a major issue, with a global fleet estimated at 109527 ships in 2024.

Ships play an essential role in global trade, transporting nearly 90% of goods. Although it is one of the most energy-efficient transport modes in terms of carbon emissions per ton-kilometer, it accounts for approximately 3% of global Greenhouse Gas (GHG) emissions, or about 1000 megatons of CO₂ per year [4][5]. These emissions are increasing, and the International Maritime Organization (IMO) forecasts a fivefold increase by 2050, making it a priority for climate change mitigation. A significant portion of maritime emissions occurs when ships are docked, with their auxiliary engines running to power onboard equipment. About 70% of maritime emissions occur near ports. Without appropriate measures, these emissions could reach 70 million tons of CO₂, 1.3 million tons of Nitrogen Oxides (NOx), and 160 000 tons of Sulfur Dioxide (SO₂) by 2050 [6]. Air pollution caused by these emissions affects human health, leading to dangerous diseases such as lung cancer, asthma, heart attacks, and other eye diseases. An epidemiological study established by [7] showed that particulate emissions are responsible for 60

<footnote n="1">¹ UMR 6134 SPE Laboratory, University of Corsica, 20250 Corte, France;</footnote>

<footnote n="2">² UR-LAPER Laboratory, Faculty of sciences of Tunis, University of Tunis El Manar, 1068 Tunis,Tunisia.*Correspondence: hajajji.mohamed@fst.utm.tn (M.H).</footnote>
000 cancer-related deaths each year. To tackle this challenge, several international regulations and initiatives have been implemented, such as the integration of maritime transport into the European Union Emissions Trading System (EU ETS) and the adoption of the Fuel EU Maritime regulation in 2022, alongside the EU's National Low Carbon Strategy and the "Fit for 55" plan [8]. This regulation, adopted in 2023, mandates ships over 5000 gross tons to reduce their GHG emissions intensity by 2% starting in 2025, with progressive reductions aiming for 80% by 2050 [9]. Furthermore, starting in 2030, ships docked for more than two hours must connect to the shore power grid unless an alternative zero-emission technology is adopted. Meanwhile, the IMO has established the International Convention for the Prevention of Pollution from Ships, 1973, as modified by the 1978 Protocol (MARPOL), which sets strict limits on sulfur emissions from ships. In emission control areas (ECAs), sulfur content is capped at 0.1%, while outside these zones, it is progressively reduced to 0.5% since 2020. The World Health Organization (WHO) recommends an annual limit of 5 µg/m³ for fine particles (PM), while the EU allows up to 25 µg/m³ [10][11]. For SO₂, the 24-hour limit is 20 µg/m³, while for NO₂, WHO recommends 10 µg/m³, compared to 40 µg/m³ in Europe [12][13].

To meet these requirements, several solutions are proposed, including the use of cleaner fuels such as liquefied natural gas (LNG) [14], marine diesel, biofuels, or blends of conventional fuels and biodiesel [15][16]. However, although these fuels help reduce emissions, they remain polluting and depletable fossil resources [17], posing a problem in terms of energy sovereignty. Additionally, their market is largely dominated by a few countries, making their supply and pricing highly dependent on geopolitical and economic fluctuations. A promising solution that is gaining increasing interest within the scientific community is the electrification of ships at berth. Many studies are exploring its benefits, particularly in terms of reducing pollutant emissions in ports. Shore power, also known as cold ironing, is a technology that allows ships to be powered by electricity when docked in a port. In the literature, it is referred to by various names, including Onshore Power Supply(OPS), Shore-Side Power Supply, Shore-to-Ship Electrification, Shore-to-Ship Connection, Shore-to-Ship Power, Alternative Maritime Power, or High Voltage Shore Connection. Its primary goal is to replace the use of ships' auxiliary engines, which are particularly polluting, by providing electrical power during port stays. This solution ensures the operation of essential onboard equipment such as lighting, heating, ventilation, and air conditioning, while reducing dependence on fossil fuels and limiting pollutant emissions. The efficiency of this technology has been the subject of many studies worldwide. An investigation conducted at the Port of Long Beach in California revealed a concerning increase in CO₂ emissions, rising from 236 965 tons in 2019 to 240 536 tons in 2020, and reaching a peak of 496 012 tons in 2022, doubling in just three years. In response to this alarming trend, the introduction of shore power technology, which allows ships to connect to the onshore power grid, resulted in a 30% reduction in emissions, demonstrating its positive impact [18]. At the European scale, the benefits of this solution appear even more significant. An analysis conducted on 714 ports within the European Economic Area and the UK estimated that a widespread adoption of shore power could lead to an annual reduction of 3 to 5 million tons of CO₂. Simultaneously, air pollution would decrease significantly, with estimated reductions of 86 431 tons of NOx, 4 130 tons of SOx, 1 596 tons of PM10, 94 tons of CH₄, 4 818 tons of non-methane volatile organic compounds (NMVOCs) and 235 tons of N₂O. These results highlight the key role of shore power in improving air quality in port areas [19]. Other regions of the world confirm this trend. In British Columbia, studies on shore power showed a reduction in CO₂ emissions from 48% to 70%, and NOx emissions from 57% to 70%. Emissions of other pollutants were also significantly reduced, with reductions ranging from 3% to 60%, depending on the studied parameters. These performances are directly related to the frequency of calls and the duration of ships' connection to the power grid [20]. Similarly, in the Great Lakes and Saint Lawrence River corridor in Canada, port electrification could avoid 227 061 tons of CO₂ annually, along with 502 tons of NOx, 136 tons of SOx and 47 tons of PM2.5 [21]. A progressive approach adopted in Kaohsiung, Taiwan, illustrates the benefits of gradual integration of shore power to maximize environmental, fiscal, and socio-economic benefits. An adoption rate of 20% would reduce NOx by 104 tons and CO₂ by 8 464 tons annually. With a 40% integration rate, these figures would rise to 285 tons of NOx and 16 928 tons of CO₂, while a 60% adoption rate could avoid up to 428 tons of NOx and 25 391 tons of CO₂. These studies confirm that port electrification is a strategic lever to enhance the sustainability of the maritime sector and accelerate the global energy transition [22].

Despite all the advantages mentioned above, the economic viability of shore power largely depends on the energy source used to power the ships. In most cases, port facilities are directly connected to the terrestrial electrical grid. However, the effectiveness of this solution in reducing emissions heavily relies on the composition of the local energy mix. The more decarbonized the energy mix is, the more favorable the environmental impact, making shore power an especially valuable tool for the ecological transition of the maritime sector. The influence of the energy mix on the environmental benefits of this technology has been well documented. In Taranto, Italy, a study highlighted the importance of the electricity grid's emission factor on reducing atmospheric pollutants. By connecting ships to shore electricity, NOx emissions dropped by 94%, CO₂ by 42% and PM by 90%. These results underline the potential of electrification to improve air quality in port areas and reduce the health impacts associated with ship emissions [23]. A similar observation was made at the Port of Copenhagen, where the
integration of the Nordic energy mix was studied in detail. With emission factors of 426 g/kWh for CO2, 0.32 g/kWh for NOx, 0.07 g/kWh for SO2, and 0.03 g/kWh for particulate matter, the gains in terms of air pollution were substantial. SO2 emissions were reduced by 65%, NOx by 98%, while PM decreased by 90%, and CO2 by 34%. These data confirm that port electrification can only fully realize its potential when supported by low-carbon electricity [24]. This observation is confirmed on a larger scale, as demonstrated by a comparative analysis conducted across several international port hubs, including Los Angeles, Virginia, Juneau, and Seattle in the United States, Gothenburg in Sweden, Hamburg in Germany, Antwerp in Belgium, Sydney in Australia, and Shanghai in China [25]. The results revealed a recurring pattern: the environmental benefits of OPS are more pronounced when the share of renewable energy in the electricity mix is higher. This trend further emphasizes that an ambitious energy transition in the maritime sector must go hand in hand with the development of greener electricity production. India, for example, still derives 76% of its electricity from coal, which limits, in the short term, the impact of port electrification on global CO2 emissions. However, this energy transition presents an undeniable advantage: it allows pollution to be shifted away from densely populated urban areas to regions where power plants are located, thus reducing the harmful effects of pollutant emissions on public health. Additionally, this strategy paves the way for gradual improvements through the rise of renewable energy. With a population of nearly 1.5 billion people and a rapidly growing port industry [26], India is a key player in reducing maritime transport emissions. A gradual electrification, coupled with increased development of clean energy sources, could sustainably transform the country's energy landscape and maximize the ecological benefits of this technology [27].

The deployment of renewable energy as the primary power source for docked ships is increasingly viewed as a promising pathway to drastically curb pollutant emissions, potentially bringing them to negligible levels. This strategy is gaining traction among ports seeking to transition toward more sustainable and eco-friendly infrastructures. Nonetheless, the actual implementation of renewables in port areas remains limited, and the academic literature on the subject is relatively sparse. One notable study conducted at the Port of Mytilene demonstrated the significant environmental benefits of harnessing local solar and wind resources. A system combining 1.5 MW of wind power with 5 MW of photovoltaic panels was found to reduce CO2 emissions by 19.2 metric tons [28]. Similarly, a survey at the Port of Cartagena in Spain assessed the potential of integrating both onshore and offshore wind energy with solar power. The proposed system could achieve annual reductions of 28.4 tons of NOx, 30.7 tons of SO2, 1806.1 tons of CO2, and 4.4 tons of PM from cruise ships [29]. In the Port of Houston, a multi-energy configuration combining photovoltaic panels, wind turbines, and the electrical grid was studied. Results indicated that optimizing berth allocation enhances operational flexibility and facilitates port energy management [30]. However, the intermittent nature of renewable sources poses a major challenge to ensuring a stable and reliable energy supply. Energy storage systems (ESS) are essential to mitigate this issue by enabling the capture and redistribution of excess power. While batteries are the most common form of ESS, they present challenges related to limited lifespans and reliance on critical raw materials like lithium and graphite— resources often controlled by a few countries, raising concerns about energy security and market stability [31].

Hydrogen has recently emerged as a compelling alternative for both energy storage and electricity generation, especially when produced via renewable-powered electrolysis. Its high energy density and long-term storage capability make it a robust solution to counteract renewable variability and improve energy autonomy. Consequently, many ports worldwide are exploring hydrogen integration to decarbonize operations and support the transition to zero-emission logistics [32][33][34][35][36][37]. Examples include the ports of Qingdao and Shanghai in China, as well as Rotterdam and Hamburg in Europe, where infrastructure for hydrogen production, storage, and distribution is under development [38][39]. These efforts primarily aim to supply hydrogen for port vehicles and ships operating within the harbor. Despite these advances, most existing studies concentrate on Power-to-Gas systems using hydrogen as fuel rather than Power-to-Power applications where hydrogen is used for electricity generation. This gap in research overlooks hydrogen's potential to electrify port infrastructure and support grid stability. Some recent investigations have begun to explore this pathway. For instance, the Port of Milos implemented a hybrid system combining renewables and hydrogen storage to generate power autonomously for 24 hours [40]. Likewise, a study in the Port of Harcourt, Nigeria, showed that integrating hydrogen fuel cells with battery systems significantly improved performance, offering a more sustainable alternative to conventional battery-only setups [41].

Overall, the literature underscores the growing relevance of hydrogen in shaping the future of clean port operations. However, its role in electricity production remains underexplored, especially in practical, spatial, and socio-technical contexts. One key issue is the physical implementation of hydrogen infrastructure, as ports are spatially constrained environments. Safety concerns and social acceptance also arise, particularly due to their proximity to urban zones. Notably, no studies to date have addressed the integration of green hydrogen in Corsican ports, despite
the island's six harbors and its significant potential for renewable energy deployment. In such contexts, hydrogen could be a pivotal component of the island's broader energy transition strategy.

To fill these gaps, this article offers several innovative contributions :

* Evaluation of the feasibility of integrating hydrogen as a source of electricity in the port of Ajaccio, relying on local resources to maximize energy autonomy.

* Unlike previous studies that primarily focus on supplying ships at berth, this research also examines the electricity supply of two large buildings adjacent to the port, thus enhancing the overall impact of this energy transition.

* Optimization of the energy system's sizing through a genetic algorithm, allowing a tri-objective optimization. The study analyzes the influence of component sizing on installation costs and emissions, providing decision-makers with a clear and transparent view of the economic and environmental implications of their investments.

* Development of a secure hydrogen storage strategy, exploring the advantages of underwater storage. The impact of water temperature on storage capacity and safety is also studied.

* A specific approach is introduced to evaluate the percentage of emissions of the proposed system and compare it with those of the current electrical grid, thus comprehensively examining the ecological benefits of hydrogen.

After presenting the general framework of this study, the remainder of the article is structured as follows: Section 2 introduces the port of Ajaccio and the energy consumption profiles used, while integrating the essential meteorological data for modeling the system. Section 3 describes the architecture of the solar system coupled with a hydrogen chain and defines the objective functions used in the optimization algorithm. Section 4 details the energy system sizing by applying the NSGA-II algorithm with a multi-objective approach aimed at optimizing its performance. Section 5 presents and analyzes the optimization results exploring different specific configurations. A sensitivity analysis is also conducted to assess the robustness of the optimal choices, examine the interactions between the system's components, their ability to meet energy demand, and their impact on emissions. A comparison with a scenario fully powered by the electrical grid is carried out and the advantages of underwater hydrogen storage are also explored. Finally, Section 6 summarizes the main results discusses potential improvements and identifies the limitations of the study.

## 2. Methodology

### 2.1. Case Study

The Port of Commerce in Ajaccio, strategically positioned at the heart of the Gulf of Ajaccio and in close proximity to the city center, serves as a critical hub for regional maritime trade. Handling over one million passengers annually and approximately 2500 ship rotations, it stands as the second-largest cruise port in France, accommodating more than 460000 cruise passengers and 205 ports calls each year. Beyond its economic significance, the port plays a fundamental role in regional commercial activity. However, the emissions generated by docked cruise ships pose significant environmental and public health concerns, particularly for local residents. Corsica is classified as a non-interconnected zone within the French energy network, relying on a limited 50 MW connection to Italy [42]. As of 2023, the island remains highly dependent on fossil fuels, resulting in substantial greenhouse gas emissions that exacerbate climate change. Additionally, the port's energy demands are currently met through the existing electrical grid, further reinforcing its reliance on carbon-intensive energy sources. This study proposes a comprehensive decarbonization strategy for the port and its surrounding infrastructure, including key facilities such as the maritime station and adjacent buildings. The proposed approach will be further elaborated in subsequent sections.

### 2.2. Data Collection

Ajaccio, one of the largest cities in Corsica, bases a significant part of its economy on tourism. One of its main assets is its high level of sunshine, with an average of 2973 hours of sunlight and 124 sunny days per year. The
city also benefits from a solar irradiation of 5.30 kWh/m² and a pleasant average temperature of 16°C, as shown in Fig. 1. The integration of green and sustainable energy could enhance Ajaccio’s attractiveness, especially as tourists are increasingly favoring eco-friendly tourism.

<figure><img src="image_2.png" /><figcaption>Fig. 1 Solar radiation, Air and water Temperatures in Ajaccio, data from meteorological service measurement point in Ajaccio [43]</figcaption></figure>

The ferries operating between Ajaccio and the mainland run almost continuously throughout the year. To accurately assess the energy consumption of the vessels at berth, the ferry with the highest energy demand was selected. This choice enables the identification of the most relevant levers for reducing pollutant emissions. The analysis is based on data provided by the Port of Ajaccio, including the duration of port calls and the technical characteristics of the vessel under study. The ferry is equipped with auxiliary engines with a power of 8 700 kW, an efficiency of 0.35 and a load factor of 0.65. Using these parameters, the evolution of the vessel's energy demand over the course of a full year was modeled. The port call data used in this study are from the year 2019. Furthermore, the evaluation of the energy consumption of associated port infrastructure focused on the maritime station and the conference hall. The annual energy consumption of the latter reaches 971 MWh, with peaks during the summer, primarily due to the intensive use of air conditioning systems Fig. 2(a). The maritime station, on the other hand, has an annual consumption of 757 MWh, showing a similar pattern with an increase during the summer due to the influx of tourists Fig. 2(b). In contrast, the energy consumption of vessels at berth is higher in winter, when the port calls are longer, and decreases in the summer. The total annual energy consumption of the vessels amounts to 9.5 GWh, as illustrated in Fig. 2(c).

<figure><img src="image_3.png" /></figure>
<figure><img src="image_4.png" /><figcaption>Fig.2. Load demand of conference room (a) Load demand of maritime station (b) and Load demand of Boats (c)</figcaption></figure>

**2.3. Proposed model :**

The use of hydrogen in ports plays a pivotal role in ensuring the energy supply to ships throughout the year. To better understand the operation of this innovative system, the schematic diagram is presented in Fig. 3. Photovoltaic panels serve as the primary energy source directly powering various port components. In the event of excess energy, an alkaline electrolyzer utilizes this surplus to produce hydrogen. The hydrogen produced is then transferred via dedicated pipes to underwater storage tanks, where it is stored for future use. When the storage tanks are sufficiently filled, the surplus hydrogen is injected into the electrical grid. During periods of low sunlight, the chemical reaction in the fuel cell membranes generates electricity ensuring a continuous power supply to port loads. Finally, should additional energy be required, the network may intervene when hydrogen reserves begin to deplete, thus ensuring a continuous supply to ships and port facilities.
<figure><img src="image_5.png" /><figcaption>Fig.3 Schematic design of the components of the system</figcaption></figure>

## 2.4. Functional description

### 2.4.1 PV Module

The primary energy source for powering the port is solar panels. The energy from the solar panels is used to directly supply consumers within the port. The photovoltaic output power $P_{pv}$ is calculated from Equation (1) by considering local climatic conditions [44].

$$P_{pv} = N_{pv} \times P_{pv0} \times F_{pv} \times (G_t / G_{tst}) \times (1 + \beta \times (T_m - T_{st})) \quad (1)$$

Here, $P_{pv0}$ represents the maximum power of the panel under standard conditions (1 kW/m² and 25°C), $F_{pv}$ is the overall performance factor of the system (typically between 0.75 and 0.9 to account for losses due to shading, conversion, etc.), $G_t$ is the current solar irradiation, and $G_{tst}$ the reference irradiation (1000 W/m²). The temperature coefficient $\beta$ reflects the impact of thermal variations on efficiency while $T_m$ is the actual temperature of the module influenced by the environment.

### 2.4.2 Electrolyser:

The electrolyzer is a key component of the system that enables hydrogen production from excess solar energy. This process relies on the dissociation of water molecules into hydrogen and oxygen using electricity supplied by renewable sources [45]. In our study, we used alkaline electrolyzers a widely commercialized technology for hydrogen production. Each electrolyzer has a nominal power of 1 MW, allowing for a production rate of approximately 200 Nm³/h of hydrogen, which corresponds to about 18 kg/h under standard temperature and pressure conditions.

The electrochemical reactions at the electrodes of the electrolyzer are calculated from Equation (2) and Equation (3):

$$ \text{Cathode: } 2H_2O + 2e^- \rightarrow H_2 + 2OH^- \quad (2) $$

$$ \text{Anode: } 4OH^- \rightarrow O_2 + 2H_2O + 4e^- \quad (3) $$
The amount of hydrogen produced is calculated from Equation (4) and Equation(5)

$$ 
\begin{aligned}
P_{el} &= P_e \times \eta \\
mH_2 &= (M_{h2} \times P_{el} \times \eta) / \Delta H_m
\end{aligned} 
\qquad (4) \qquad (5) $$

Where, mH₂ is the mass of hydrogen produced (kg/h), M<sub>h2</sub>=2.016 g/mol is the molar mass of hydrogen, Pe<sub>l</sub> is the power supplied to the electrolyzer (W), η is the efficiency of the electrolyzer and ΔH<sub>m</sub>≈286 kJ/mol is the enthalpy of water dissociation.

### 2.4.3 Fuel Cell:

The fuel cell's role is to convert hydrogen into electricity by exploiting the electrochemical reactions between hydrogen and oxygen. We have chosen to use Proton Exchange Membrane fuel cells, which are currently at the forefront of development efforts in the field of clean energy production due to the availability of their components and their efficiency[46]. For our study, we selected a 1 MW fuel cell with an efficiency of 45% and a hydrogen consumption of 60 kg/h at maximum power. This relationship allows us to quantify the hydrogen used in relation to energy production. The electrochemical reactions in the fuel cell are calculated from Equation (6) and Equation (7) [47]:

$$ 
\begin{aligned}
\text{Anode: } 2H_2 &\rightarrow 4H + +4e^- \\
\text{Cathode: } &O_2 + 4e^- + 4H^+ \rightarrow 2H_2O
\end{aligned} 
\qquad (6) \qquad (7) $$

The output voltage of the fuel cell, a key element to ensure optimal energy conversion, is given by the Equation (8) [48][49]:

$$ V_{fuel} = N_{cell} \times V_{cell} = V_0 - V_{act} - V_{ohm} - V_{con} \qquad (8) $$

Where: N<sub>cell</sub> is the number of cells in the fuel cell stack, V<sub>0</sub> is the open-circuit voltage, V<sub>act</sub> represents the activation losses, V<sub>ohm</sub> corresponds to the ohmic losses and V<sub>con</sub> refers to the concentration losses.

### 2.4.4 Hydrogen Tank

After hydrogen production, it is stored in tanks specifically designed to withstand the marine environment, including seawater. These tanks, suited for underwater conditions, are central to recent research on underwater hydrogen storage, which has gained significance in recent years, particularly for large-scale solutions at considerable ocean depths. Among the technologies being explored, the use of rigid tanks to store hydrogen, replacing water in the tank, seems particularly promising. This option is even more relevant considering hydrogen's low solubility in water. Indeed, at a pressure of 35 bars, hydrogen's solubility in water does not exceed 0.0008% [50]. This minimizes the risk of hydrogen dissolving in the water, ensuring more efficient storage. To keep the tanks submerged, especially in coastal areas, a portion of the tank is filled with sand to ensure stability and prevent the compressed hydrogen from floating. The level of hydrogen in the tank depends on several factors, such as the mass of hydrogen stored, the pressure at depth, and the temperature of the water at that depth. For example, between 5 meters and 50 meters depth, the density of hydrogen varies from 2.88 kg/m³ to 2.93 kg/m³ under a constant pressure of 35 bars.

The energy stored in these tanks at a given time t is determined by Equation (9).

$$ Estorage(t) = Estorage(t-1) + (Pelec \times \Delta t) - (Pfuel \times \Delta t \times \etastockage) \qquad (9) $$

Where, P<sub>fuel</sub> is the power supplied by the fuel cell, Δt is the time interval, η<sub>stockage</sub> is the storage efficiency

Table 1 presents a comparison between underwater and land-based hydrogen storage, highlighting the differences related to location, safety, and social acceptance. It also considers the specific challenges associated with integrating a storage tank within a port environment.

<table><caption>Table1. Comparison of Underwater and Land-Based Hydrogen Storage</caption><thead><tr><td>Criteria</td><td>Underwater Storage</td><td>Land-based Storage</td></tr></thead><tbody><tr><td>Space</td><td>Solves space issues, especially in port areas where space is limited.</td><td>Requires large land areas, which can be difficult to find in urban zones.</td></tr></tbody></table>
<table><thead><tr><th>Criteria</th><th>Underwater Storage</th><th>Land-based Storage</th></tr></thead><tbody><tr><td>Safety</td><td>Fewer risks of explosions or incidents in urban areas, due to submersion.</td><td>More direct risks for inhabitants in case of accidents, as leaks or explosions can have an immediate impact.</td></tr><tr><td>Proximity to residents</td><td>Can be located far from residential areas, reducing the impact on the local population.</td><td>Residential areas nearby increase safety concerns.</td></tr><tr><td>Social Acceptance</td><td>Often more accepted due to distance from residential areas and reduced perceived risk.</td><td>Acceptance may be lower in residential areas due to perceived risks and visual impact.</td></tr><tr><td>Cost</td><td>Although the infrastructure is expensive to install, it can be more cost-effective in the long term if suitable sites are found.</td><td>Cheaper in the short term, but requires more infrastructure to meet safety risks, and land acquisition costs can increase.</td></tr><tr><td>Technology and Feasibility</td><td>Requires advanced technologies to ensure safety and stability at great depths, but feasibility is facilitated in coastal areas.</td><td>Well-established technology, but limited by land availability and impact on residential areas.</td></tr></tbody></table>

## 2.4. Economic Evaluation

The economic evaluation of an energy system must account for the lifetime of its components to ensure accurate estimates of initial investments and ongoing expenses. The lifespan of elements such as electrolyzers, photovoltaic panels, and hydrogen storage tanks directly impacts the allocation of investment (CAPEX), as shown in Equation (10), and operational (OPEX) costs, as given by Equation (11). The Net Present Cost (NPC) and Levelized Cost of Energy (LCOE) indices are critical in this analysis. The NPC calculates the total discounted cost of the project, incorporating both initial investments and recurring costs, as presented in Equation (12) [51][52]. The LCOE, on the other hand, estimates the average cost of energy production, facilitating the comparison of different technologies based on their energy generation costs, as outlined in Equation (13) [53][54].

$$CAPEX = \sum_{i=1}^{n} CAPEX_{pv} + CAPEX_{elec} + CAPEX_{fuel} + CAPEX_{res} \quad (10)$$

$$OPEX = \sum_{i=1}^{n} (OPEX_{pv} + OPEX_{elec} + OPEX_{fuel} + OPEX_{res} + Cost_{grid}) \quad (11)$$

$$LCOE = \frac{CAPEX + OPEX}{\sum_{t=1}^{T} \frac{Et}{(1+r)^t}} \quad (12)$$

$$NPC = \sum_{i=1}^{n} \frac{CAPEX + OPEX}{(1 + r)^i} \quad (13)$$

Where *Et* is the energy produced in year *t* and *T* is the project lifetime which is set to 20 years.

Table 2 presents the costs of all the components of the system used in this study, according to the investigated literature market data.

<table><caption>Table 2. Economic parameters of the system</caption><thead><tr><th>Components</th><th>Capex €/KW</th><th>Opex €/KW</th><th>Lifetime</th></tr></thead><tbody><tr><td>Solar panels</td><td>1200 [55]</td><td>45</td><td>25</td></tr><tr><td>Electrolyseur</td><td>1500 [56]</td><td>60</td><td>20</td></tr><tr><td>Fuel cell</td><td>3500 [57]</td><td>130</td><td>7</td></tr><tr><td>Hydrogen Storage</td><td>1500 €/Kg [58]</td><td>5 €/Kg</td><td>20</td></tr></tbody></table>

## 2.5. Environmentle Evaluation :
One of the main objectives of this study is to calculate the emissions of ships during their port calls. Big ships, which are highly energy-intensive, use different types of marine fuels Heavy Fuel Oil (HFO), Marine Gas Oil MGO and Marine Diesel Oil (MDO), whose emissions vary depending on their sulfur content. Since 2020, the IMO has reduced this sulfur content to 0.5% for certain fuel. Table 3 presents the emission coefficients associated with each type of marine fuel

<table><caption>Table3. The Emission coefficients of different types of marine fuel [59]</caption><thead><tr><th>Emission factors:</th><th>CO<sub>2</sub> (g/kWh)</th><th>NO<sub>x</sub> (g/kWh)</th><th>PM (g/kWh)</th><th>SO<sub>2</sub> (g/kWh)</th><th>Teneur en soufre (%)</th></tr></thead><tbody><tr><td>HFO</td><td>722</td><td>14.9</td><td>1.5</td><td>11.1</td><td>3.5%</td></tr><tr><td>MGO/ MDO</td><td>692</td><td>13.9</td><td>0.38</td><td>2.12</td><td>5%</td></tr><tr><td>MGO/MDO</td><td>645</td><td>13.2</td><td>0.207</td><td>0.2</td><td>1%</td></tr></tbody></table>

Only emissions from auxiliary engines are considered in this study, although boilers also contribute to dockside emissions since they are essential for maintaining fuel temperature and preventing costly failures [60][61]. Port buildings use the electrical grid (Egrid) for electrification. To calculate emissions accurately, this study also examines the reduction of emissions associated with the grid. Corsica's energy mix is predominantly reliant on fossil fuels, accounting for 34% of emissions, and electricity imports from Italy, which contribute 27%. Other emissions from these plants include 12.5 g/kWh of NOx, 0.3 g/kWh of PM and 2 g/kWh of SO2 of electricity generated.

The calculation of the ports' emissions (Eemis) can be represented by Equation (14), where the energy consumption is multiplied by the respective emission factors (EF):

$$Eemis = (Eboat + Egrid) \times EF \qquad (14)$$

## 3. Optimisation problem formulation :

### 3.1. Objective Problem

In our study, we aim to satisfy two objective functions. The first is economic, seeking to minimize the total system cost, while the second is environmental, aiming to reduce greenhouse gas emissions. Thus, our problem is formulated as follows: Minimize (NPC, Eemis). This leads to a bi-objective optimization problem, which requires a specific solution method. For such problems, stochastic methods, particularly evolutionary algorithms, have proven to be more effective. We have chosen the NSGA-II genetic algorithm as the solver, as it has demonstrated efficiency and robustness in solving multi-objective problems [62][63]. The adopted optimization method is illustrated in the functional diagram of Fig 4. The goal of NSGA-II is to adjust the power of various system components by determining the optimal number of elements, such as electrolyzes ($N_{elec}$), photovoltaic panels ($N_{pv}$), fuel cells ($N_{fuel}$), and the storage tank volume ($T_{H2}$). These adjustments ensure that port energy demands are met while minimizing harmful gas emissions and system costs. To ensure solution diversity and continuous improvement of results, 10 successive runs of the algorithm were performed, each with a population size of 100. This approach allows for an efficient exploration of the solution space and enhances overall optimization performance.
<figure><img src="image_6.png" /><figcaption>Fig4. Processus d'optimisation</figcaption></figure>

## 3.2. Imput variables :

The objective is to size the system components ($P_{pv}$, $P_{el}$, $P_{fuel}$, $T_{H2}$) to meet the port's energy needs while minimizing costs and greenhouse gas emissions. Table4 presents the variables to be optimized and their ranges of variation, subject to constraints such as the maximum size of the photovoltaic park and the capacity of the available storage tanks.

<table><caption>Table 4. The variables to be optimized and their ranges of variation</caption><thead><tr><td>Variables</td><td>Maximum value Xmax</td></tr></thead><tbody><tr><td>P<sub>pv</sub></td><td>13 MW</td></tr><tr><td>P<sub>el</sub></td><td>6 MW</td></tr><tr><td>P<sub>fuel</sub></td><td>3 MW</td></tr><tr><td>T<sub>H2</sub></td><td>500 Kg</td></tr></tbody></table>

## 3.3. Constraints :

To ensure the feasibility and reliability of the system, a constraint is applied to the hydrogen storage tank ($T_{H2}$) : maintaining a level between 10% and 98% of its total capacity as shown in Equation (15). A low level increases the risk of air infiltration and requires nitrogen purging, while a full tank poses risks related to thermal expansion. These precautions ensure safe hydrogen management and reduce maintenance costs [64][65].

$$T_{H2} > 10\% \text{ and } T_{H2} < 98\% \qquad (15)$$

## 4. Results and Discussion

In this section, we present the optimization results obtained after simulation using MATLAB 2023, performed on a Dell computer with an Intel i7 processor. The objective is to provide decision-makers and readers with a clear understanding of the benefits of decarbonizing the Port of Ajaccio, as well as to illustrate the impact of emission reduction on the overall system cost. The Fig.5 illustrates the evolution of the two objective functions, NPC and the grid integration rate, on the Pareto front. An optimal zone has been identified, representing a balance between these two criteria based on the grid integration threshold deemed acceptable by decision-makers. Outside this zone, one of the objective functions predominates, highlighting a prioritization of trade-offs. This analysis is further supported by Fig.6, which demonstrates the evolution of design variables concerning optimization objectives. The results show that increasing the system size leads to higher costs, while a reduction contributes to lower pollutant gas emissions. Thus, the choice of a compromise between economic viability and environmental impact directly depends on the level of grid integration considered acceptable.
<figure><img src="image_7.png" /><figcaption>Fig. 5. Pareto front of the objective function</figcaption></figure>

<figure><img src="image_8.png" /><figcaption>Fig. 6. Design parameters evolution along the optimal front versus system Emissions and versus NPC</figcaption></figure>

## 4.1 Analysis of some particular configurations

Analyzing multiple solutions from the optimal front allows for a comparison of their characteristics and an evaluation of trade-offs between different objectives, such as costs and emissions. By considering at least three solutions (Optimum 1, Optimum 2, and Optimum 3), a broader perspective on performance is gained. This helps in selecting a configuration that best meets the project's needs while avoiding the prioritization of a single criterion at the expense of others. The Selected configurations extracted from the zone of good compromise of the optimal front are summarized in table below

<table><caption>Table 5. Characteristics of the selected configurations</caption><thead><tr><th>Optimum</th><th>P<sub>pv</sub><br>(MW)</th><th>P<sub>elec</sub><br>(MW)</th><th>P<sub>fuel</sub><br>(MW)</th><th>T<sub>H2</sub><br>(Kg)</th><th>NPC<br>(M€)</th><th>Ratiogrid<br>(%)</th><th>Emission<br>(Tonnes)</th><th>LCOE<br>€/MWh</th></tr></thead><tbody><tr><td>Optimum 1</td><td>11.5</td><td>5</td><td>2</td><td>320</td><td>51.3</td><td>19.2</td><td>1549</td><td>271.3</td></tr><tr><td>Optimum 2</td><td>12</td><td>5</td><td>2</td><td>320</td><td>55.5</td><td>18.26</td><td>1526</td><td>295.6</td></tr><tr><td>Optimum 3</td><td>12</td><td>5</td><td>3</td><td>320</td><td>59</td><td>15.7</td><td>1343</td><td>298.7</td></tr></tbody></table>

The comparative analysis of the three configurations highlights a balance between cost, energy autonomy, and environmental impact. Optimum 1 is the most economical solution, with an NPC of 51.3 M€ and an LCOE of 271.3€/MWh, but it relies more on the grid and generates higher emissions 1549 tonnes. Optimum 3, although more expensive NPC of 59M€, reduces grid dependency 15.7% and limits emissions 1343 tonnes, making it the most environmentally friendly option. Optimum 2 represents a compromise between cost, autonomy, and sustainability. The final choice depends on the priorities between profitability and environmental impact.
Our primary objective is to reduce toxic gas emissions. To achieve this, we will focus on analyzing Optimum 3. Fig 7 illustrates the seasonal behavior of the energy system through two separate graphs representing two distinct periods: Graph A for summer and Graph B for winter. In Graph A PV production (yellow area) reaches its peak due to high solar irradiance, often exceeding the local energy demand. This excess energy is partially exported to the grid (pink area) and partially directed to the electrolyzer (blue area), which converts it into hydrogen for storage. During this season, the fuel cell (plum-colored area) remains largely inactive, as the energy supply is sufficient, and grid imports (purple area) are minimal or nonexistent. In Graph B, the situation reverses. Energy demand increases, notably due to extended port operations that require additional electricity. However, PV production decreases significantly, resulting in an energy deficit. To meet this demand, the system relies on grid imports and activates the fuel cell which utilizes hydrogen stored during the summer. In this period, grid exports are nearly absent, and the electrolyzer remains inactive, reflecting the limited availability of surplus renewable energy. This seasonal comparison clearly demonstrates the complementary operation of system components throughout the year. Hydrogen storage plays a key role by absorbing excess energy in summer and releasing it in winter, thus contributing to the system's year-round energy balance and resilience.

<figure><img src="image_9.png" /></figure>

<figure><img src="image_10.png" /><figcaption>Fig. 7. The Energy system of Optimum 3</figcaption></figure>

Table 6 presents the difference in emissions at the port when using only the grid versus the addition of the PV/Hydrogen hybrid system. A significant reduction in emissions is observed with the hybrid system: CO₂ emissions decrease by 80.02%, NOₓ by 84.27%, PM by 84.27%, and SO₂ by 84.26%. This reduction demonstrates the effectiveness of the PV/Hydrogen system in limiting environmental impact compared to relying solely on the grid.

<table><caption>Table 6. Comparison of Pollutant Emissions: Grid System vs PV/Hydrogen Hybrid System at the Port</caption><thead><tr><td>Emision</td><td>CO₂ (kg)</td><td>NOₓ (kg)</td><td>PM (kg)</td><td>SO₂ (kg)</td></tr></thead></table>
<table><tr><td>Grid System</td><td>8010800</td><td>165320</td><td>16643</td><td>123160</td></tr><tr><td>PV/Hydrogen/grid System</td><td>1600480</td><td>26012</td><td>2618</td><td>19378</td></tr></table>

### 4.1.1 Financial analysis

A financial analysis of the project reveals the distribution of system costs and highlights the most capital-intensive components. As illustrated in Fig. 8, certain elements of the energy system stand out due to their particularly high CAPEX. PV represent the largest share, accounting for 44% of total CAPEX, which underscores their central role in renewable electricity generation. Fuel cells constitute the second most significant investment, representing 32% of CAPEX, reflecting their importance in supplying electricity during periods of energy shortfall. Although representing a slightly lower share, the electrolyzer still accounts for 23% of CAPEX, affirming its essential role in converting surplus electricity into hydrogen for medium- and long-term storage. Over the 20-year lifetime of the project, OPEX are predominantly associated with components involved in electricity generation particularly PV modules and fuel cells which together represent 74% of the total OPEX. This is primarily attributed to ongoing maintenance requirements and the technical complexity of their continuous operation. These findings highlight the critical importance of accurate system sizing to balance capital investments with operational costs. A well-optimized configuration not only improves financial efficiency but also enhances the long-term sustainability and resilience of the energy system.

<figure><img src="image_11.png" /><figcaption>**Fig 8** CAPEX and OPEX of the various components of the system</figcaption></figure>

The cost of energy system components is highly sensitive to global economic dynamics and future investment trends. It is therefore essential to evaluate how variations in component prices can impact the overall performance and cost-effectiveness of the system. Figure 9 illustrates the evolution of the system's LCOE as a function of fluctuations in key component prices and electricity costs.

A 20% increase in the price of photovoltaic (PV) panels results in a significant rise in LCOE, reaching 324 €/MWh, whereas a 20% decrease in PV prices leads to a reduction of the LCOE to 272 €/MWh. Similarly, a 40% increase in the cost of the electrolyzer raises the LCOE to 325 €/MWh, while a 40% decrease reduces it to 271 €/MWh. In the case of fuel cells, a 60% increase in price causes the LCOE to climb to 335 €/MWh, whereas a 40% decrease in their cost lowers the LCOE to 257 €/MWh.

Although the hydrogen storage tank has a relatively lower impact on the LCOE compared to other components, its influence remains non-negligible. Overall, these results clearly demonstrate that the costs of PV panels and fuel cells are the most influential factors in determining the system's LCOE, particularly in configurations that rely heavily on solar energy for hydrogen production and electricity supply.
<figure><img src="image_12.png" /><figcaption>Fig.9 Impact of Component Cost Variations on Total System Cost</figcaption></figure>

4.1.2 Hydrogen storage

Submarine hydrogen storage appears as a promising solution for energy needs in port areas. Its effectiveness relies on the impact of depth on pressure and temperature, which influence the hydrogen density according to the ideal gas law. At the water's surface (35 bars, 20 °C), the hydrogen density is 2.895 kg/m³, requiring a volume of 110.5 m³ to store 320 kg of hydrogen. As the depth increases to 10 meters, the pressure slightly rises to 36 bars, while the temperature drops to 19 °C. This change in physical conditions results in an increase in density to 2.988 kg/m³, reducing the required storage volume to 107.1 m³. At 30 meters, the pressure reaches 38 bars, and the temperature decreases to 17 °C. The density increases to 3.176 kg/m³, allowing the same amount of hydrogen to be stored in a reduced volume of 100.8 m³, representing a significant space-saving. Finally, at 60 meters depth, where the pressure reaches 41 bars and the temperature drops to 14 °C, the density rises to 3.462 kg/m³. The required volume for storing 320 kg of hydrogen is thus reduced to just 92.4 m³. This increase in density with depth, as illustrated in Table 7, highlights the advantage of deep underwater storage.

<table><caption>Table7. Hydrogen Density, Storage Volume Required for 320 kg H2, Temperature and Pressure as a Function of Depth Variation</caption><thead><tr><td>Depth (m)</td><td>Pression (bar)</td><td>Temperature (°C)</td><td>Density (kg/m³)</td><td>Volume (m³)</td></tr></thead><tbody><tr><td>0</td><td>35.0</td><td>20.0</td><td>2.895</td><td>110.5</td></tr><tr><td>5</td><td>35.5</td><td>19.5</td><td>2.941</td><td>108.8</td></tr><tr><td>10</td><td>36.0</td><td>19.0</td><td>2.988</td><td>107.1</td></tr><tr><td>15</td><td>36.5</td><td>18.5</td><td>3.035</td><td>105.4</td></tr><tr><td>20</td><td>37.0</td><td>18.0</td><td>3.082</td><td>103.8</td></tr><tr><td>25</td><td>37.5</td><td>17.5</td><td>3.129</td><td>102.3</td></tr><tr><td>30</td><td>38.0</td><td>17.0</td><td>3.176</td><td>100.8</td></tr><tr><td>35</td><td>38.5</td><td>16.5</td><td>3.223</td><td>99.3</td></tr><tr><td>40</td><td>39.0</td><td>16.0</td><td>3.271</td><td>97.8</td></tr><tr><td>45</td><td>39.5</td><td>15.5</td><td>3.318</td><td>96.4</td></tr></tbody></table>

It is important also to mention the variation in the amount of hydrogen in the reservoir. The validation of our system is observed from Fig.11, where the state of the reservoir throughout the year is noticeable. During the
winter period, hydrogen consumption is high, leading to a significant discharge of the reservoir. In contrast, in summer, the reservoir does not undergo deep discharge, allowing the hydrogen to be converted into electricity and injected into the grid. Furthermore, the curve shows that the state of the reservoir remains within the defined limits, between 10% and 98% of its total capacity.

<figure><img src="image_13.png" /><figcaption>Fig.11 The state of the hydrogen reservoir</figcaption></figure>

**Conclusion:**

This study investigates the integration of renewable energy with hydrogen storage systems to supply electricity to isolated island areas, with a particular focus on decarbonizing the Port of Ajaccio. Through a comprehensive analysis using the NSGA-II genetic algorithm, the feasibility of meeting the port's annual consumption of over 10 GWh was explored. The results highlight the potential for utilizing local renewable energy sources, such as photovoltaic panels, alongside hydrogen storage, to create a reliable, sustainable, and low-emission energy supply.

The study shows that using 12 MW of photovoltaic panels, a 5 MW electrolyzer, a 3 MW fuel cell, and a hydrogen storage capacity of 320 kg at 35 bar significantly reduces greenhouse gas emissions by over 80%. The estimated energy production cost is 298€/MWh, making it competitive with Corsica's diesel-based power plants, which operate at a cost of around 300€/MWh. This demonstrates the viability of hydrogen as a cost-effective solution in the transition to renewable energy, emphasizing the environmental benefits of replacing diesel with hydrogen.

- A hydrogen-based energy system would lead to a reduction in CO₂ emissions by 80.02%, NOₓ by 84.27%, PM by 84.27%, and SO₂ by 84.26%. These reductions are particularly important for local communities concerned with air pollution in port areas, where hydrogen storage and energy conversion could significantly improve air quality and reduce public health risks.

- A 20% increase in the cost of photovoltaic panels leads to a rise in LCOE to 324€/MWh, while a 40% increase in electrolyzer prices raises the LCOE to 325€/MWh. These findings highlight the critical importance of reducing costs in key components, especially photovoltaic panels and electrolyzers, to improve the economic competitiveness of hydrogen-based systems. This underscores the need for continued technological advancements and cost reductions in renewable energy technologies to enhance the long-term feasibility of hydrogen-based systems.

- Storing hydrogen underwater allows for a more discreet, efficient solution, with increased storage density at greater depths. As depth increases, hydrogen density improves due to higher pressure and lower temperatures, allowing for significant space savings. At 60 meters depth, the required storage volume for 320 kg of hydrogen is reduced to just 92.4 m³, compared to 110.5 m³ at the surface. This deeper storage potential offers a strategic advantage in port areas where space is limited.

However, there are certain limitations to this study that should be considered. The data used in the analysis was based on a single year's worth of consumption, and extending the analysis over multiple years could provide more
accurate results, particularly when considering seasonal and yearly variations in energy demand and renewable energy generation. Moreover, the study did not extensively explore the potential costs of underwater hydrogen storage, which, while promising due to its efficient use of space and environmental impact reduction, is still under-researched. Furthermore, the operational costs associated with underwater storage are not yet well understood, and the cost model used in this study is based on land-based storage systems, which may not fully reflect the economic realities of underwater storage systems.

Looking ahead, the study suggests expanding the system's potential by using the port as a hydrogen refueling station for heavy-duty transportation, such as buses, particularly during the summer months when hydrogen production exceeds demand. This would provide an additional avenue for hydrogen utilization, further reducing the reliance on fossil fuels and contributing to broader decarbonization efforts in the region.

**CRediT authorship contribution statement**

**Mohamed Hajjaji:** Writing – review & editing, Writing – original draft, Visualization, Validation, Methodology, Formal analysis, Data curation, Conceptualization. **Maude chhin choi:** Writing – original draft, Visualization, Validation, Software, Methodology, Formal analysis, Data curation, Conceptualization. **Tchogoun Mostapha Mai Methodology, Conceptualization.** **Christian Cristofari,** Supervision. **Dhafer Mezghani,** Supervision.
**Abedelkader Mami,** Supervision

**Declaration of competing interest:**

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

**Acknowledgment:**

This work has received research funding from the French government managed by the National Research Agency under the France 2030 program, with reference number ANR-22-EXES-0016

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