Techno-Economic Assessment of Hybrid Renewable Energy Systems for Direct Air Capture in Saudi Arabia

Abstract

In alignment with Saudi Arabia’s Vision 2030, the Kingdom aims to achieve one of its main environmental targets: reaching net zero emissions by 2060. This ambitious goal can be realized through Carbon Dioxide Removal (CDR) technologies, particularly Direct Air Capture (DAC), which is among the most promising solutions. DAC offers high potential for extracting Carbon Dioxide (CO₂) directly from the atmosphere and is considered sustainable, especially when powered by renewable energy rather than fossil fuels. However, the technology remains highly cost-intensive. This paper presents a techno-economic assessment of renewable energy configurations to determine the most cost-effective solutions for DAC deployment. The evaluation focuses on Net Present Cost (NPC) and Levelized Cost of Energy (LCOE) across several regions in Saudi Arabia, using the Hybrid Optimization of Multiple Energy Resources (HOMER) Pro software (version 3.18.4).

1. Introduction

The HOMER Pro software is a widely adopted computational platform developed for designing and optimizing renewable energy systems. It simulates and analyzes various combinations of power sources and storage (such as solar photovoltaics, wind turbines, and battery banks) to identify cost-effective and technically feasible solutions [1].

As of 2025, HOMER stands as a flagship modeling software for hybrid renewable systems, reflecting the sector’s increasing demand for decentralized, cost-effective, and technically robust energy solutions [2].

Kavadias and Triantafyllou conducted a systematic comparison of HOMER Pro with other leading tools such as iHOGA and ESA Microgrid Simulator. Their findings emphasized that HOMER often prioritizes cost optimization by selecting smaller battery capacities with higher excess energy, in contrast to iHOGA, which tends toward greater storage capacity [3]. While HOMER is highly functional within the constraints of user-defined parameters, the study suggested that integrating broader optimization techniques could enhance solution quality.

In the global effort to combat climate change, optimizing hybrid renewable systems has become essential. The Paris Agreement and national climate targets including Saudi Arabia’s Net Zero 2060 commitment under the Saudi Green Initiative underline the urgency of transitioning to low-carbon energy systems. Within this context, HOMER Pro serves as a vital tool for simulating, optimizing, and evaluating complex energy configurations. Its use supports the development of low-emission, resilient energy infrastructure aligned with national and global sustainability goals. Recent case studies in Saudi Arabia demonstrate HOMER Pro’s utility in optimizing hybrid systems—such as solar–wind–battery configurations for remote areas and hydrogen-based energy models—reinforcing its role in supporting the Kingdom’s energy transition and decarbonization goals under the Saudi Green Initiative [4,5,6,7].

HOMER Pro, the professional edition, enables users to model diverse system designs involving photovoltaic (PV) panels, wind turbines, energy storage, and AC/DC converters. Users can define component sizing and energy dispatch strategies, particularly load following and cycle charging [5]. The software assesses technical feasibility and lifecycle cost, encompassing capital, operations, and maintenance over a system’s projected Lifetime. Moreover, HOMER Pro allows scenario-based modeling for grid-connected, off-grid, and islanded microgrid systems [7,8]. This capability is crucial for evaluating system feasibility and environmental implications under different operational conditions. The following section explores key case studies and HOMER simulations that offer insights into decision-making for renewable configurations in various geographic and functional contexts.

For instance, Pürlü et al. (2022) conducted a rural electrification study in Turkey, designing both grid-tied and off-grid systems using HOMER [9]. Their findings revealed that while on-grid systems were more economical, off-grid systems had greater environmental benefits. Limiting grid usage and sell-back capacity enabled viable systems with lower emissions [9].

Mariño et al. (2023) analyzed solar- and wind-integrated microgrids in Ecuador’s El Aromo and Villonaco regions using HOMER Pro [10]. Their comparative study helped determine the most viable system for each location based on economic and energy performance [10].

In this study, HOMER Pro is applied to assess solar and wind integration with battery storage to support DAC systems. The simulation incorporates site-specific variables such as meteorological data, load profiles, and system specifications to determine cost-minimized and efficient energy configurations [11,12].

Two primary scenarios are evaluated: an off-grid renewable system for powering DAC and a comparative regional analysis of configurations that minimize LCOE while maintaining zero carbon emissions. A sensitivity analysis within HOMER assesses how changes in resource availability and component costs affect overall system performance.

By leveraging HOMER’s capabilities, this study calculates techno-economic metrics NPC, LCOE, and system efficiency under varied conditions. The goal is to assess hybrid renewable energy systems feasibility in meeting DAC’s substantial energy needs while maintaining economic and environmental sustainability. Initially built for off-grid systems, HOMER Pro now supports complex energy modeling, including microgrids and emerging technologies such as green hydrogen. Its evolving capabilities broaden its relevance to modern energy challenges [13,14]. Globally, HOMER Pro has been applied to optimize hybrid systems in diverse contexts from rural electrification in Africa to microgrids in Alaska and grid-integrated renewables in Europe and Southeast Asia [15,16]. In Saudi Arabia, it has been used to assess hybrid solar–wind–battery systems for remote areas and hydrogen-based systems aligned with the Saudi Green Initiative [17]. These applications highlight HOMER’s value in supporting the transition to low-carbon and resilient infrastructures.

2. Review of HOMER Pro Applications and Renewable-Powered DAC System

2.1. Overview of HOMER Pro Software

HOMER, which stands for Hybrid Optimization Model for Electric Renewables, is a software platform developed by the U.S. Department of Energy’s National Renewable Energy Laboratory (NREL) to aid in the design and optimization of hybrid renewable energy systems. It was first released as a commercial product in 2014 [1]. The software enables the modeling and simulation of a wide range of power system configurations by integrating components such as solar PV panels, wind turbines, diesel generators, DC–AC converters, battery storage systems, and utility loads.

HOMER performs three core functions using user-defined data parameters [11]:

• Simulation evaluates the feasibility of various configurations such as PV modules, wind turbines, DC–AC converters, and batteries to meet electric demand.
• Optimization identifies the most cost-effective combination of system components to satisfy the given load and operational requirements [18].
• Sensitivity analysis explores how fluctuations in inputs (e.g., fuel prices, resource availability) affect system performance, helping determine the most resilient and economical solutions [12].

2.2. Implementation of Energy System Modeling Using HOMER

HOMER Pro software is extensively used for techno-economic modeling of Hybrid Renewable Energy Systems (HRES). It enables simulations of different generation and storage combinations to identify designs that minimize cost and maximize reliability [19]. In Saudi Arabia, the software has been utilized in several studies that align with Vision 2030. For instance, Alghamdi et al. evaluated renewable energy deployment in Yanbu and found that an 850 MW grid-connected solar PV system (without storage) had the lowest NPC [20]. Other studies modeled hybrid PV–wind–battery systems for campuses and industrial zones, optimizing for NPC, LCOE, and CO₂ emissions [21].

These studies confirm HOMER Pro’s strength in evaluating renewable supply systems across diverse Saudi regions. However, the modeled loads in these studies were conventional (residential, institutional, or industrial demand) with no inclusion of emerging high-energy processes such as carbon removal technologies. As such, HOMER’s potential for modeling next-generation climate mitigation systems, including DAC, remains underexplored in this context [22].

2.3. Solid Sorbent Direct Air Capture: Technology and Economics

DAC is a CDR technique that extracts CO₂ directly from ambient air. Solid sorbent-based DAC systems use porous materials that capture CO₂ through cyclic adsorption-desorption processes, typically at 80–120 °C [21,22]. This makes DAC compatible with low-grade thermal sources like solar thermal or industrial waste heat [23]. Despite its feasibility, DAC is highly energy-intensive due to the low concentration of atmospheric CO₂ (~400 ppm). Most of the energy demand (5–8 GJ/ton of CO₂) is in the form of low-temperature heat, with some electricity required for fans and vacuums [24,25].

Commercial systems such as Climeworks report usage of 6.5 GJ of heat and 1.1–1.8 GJ of electricity per ton of CO₂ removed [26,27]. Currently, DAC costs range from USD 500 to USD 1000/ton of CO₂, which limits widespread deployment

The U.S. Department of Energy has set a target of USD 100–USD 200/ton within the next decade [28]. Achieving this requires advances in sorbent materials, process efficiency, and critically, the integration of low-cost renewable energy [29,30]

2.4. Technical and Economic Challenges Facing DAC Technology

To deliver net-negative emissions, DAC systems must be powered by carbon-free sources. Integrating DAC with solar or wind energy eliminates dependency on fossil-based grids and improves sustainability. Additionally, DAC systems are flexible in operation; they can run when excess renewable energy is available and pause when supply is low, making them ideal controllable loads for variable renewable grids.

Recent studies have proposed operating DAC as a controllable load powered by curtailed renewable energy. For example, Liu et al. modeled DAC units in China that absorb excess solar generation to improve grid efficiency and reduce carbon intensity. Other studies in the U.S. explored DAC-wind hybrid configurations to absorb overproduction and reduce curtailment. These approaches demonstrated the feasibility of reducing DAC costs and emissions by co-optimizing energy supply and process operation.

Although HOMER Pro is commonly used for modeling microgrids and green hydrogen production in Saudi Arabia [31], applications that explicitly model DAC-powered renewable systems are nearly absent in the current literature. A review of research from 2021 to 2025 revealed no Saudi-based studies combining DAC with HOMER-based optimization, highlighting a significant research gap.

2.5. The Role of HOMER Pro in Reducing the Cost of Direct Air Capture

Reducing the cost of Direct Air Capture while maintaining effectiveness could be challenging, as the United States has set a key target highlight that removing CO₂ at USD 100 per ton is considered the economic benchmark for DAC viability [32]. A study conducted by Eisenberger and Realff (2024) reported that no major “showstoppers” with issues like heat management, sorbent material, and mechanical reliability remain; they considered manageable issues that must be addressed to control the cost of DAC [33]. It presents a transformative opportunity to improve the sustainability and cost-efficiency of CDR technologies by integrating renewable energy sources, such as wind and solar.

A recent study highlights the feasibility of coupling DAC with renewable energy for off-grid systems, which eliminates dependency on traditional electricity grids and further enhances sustainability [34]. Rinaldi and Moghaddam poor (2021) used HOMER Pro to optimize hybrid renewable energy systems, seeking to reduce costs and improve efficiency. By selecting the optimal renewable power source to meet a DAC plant’s electricity demand based on its electricity demand and installation site, system productivity and efficiency can be enhanced [4].

Moreover, both NPC and LCOE can be significantly reduced by performing a techno-economic study for DAC implementation. This highlights a critical gap. Given Saudi Arabia’s renewable energy capacity and growing interest in CDR technologies, integrating HOMER Pro with DAC modeling presents an untapped research opportunity.

3. Methodology

3.1. Solar and Wind Resources in Saudi Arabia

Owing to its diverse climatic conditions and strategic geographical location, the Kingdom of Saudi Arabia presents a highly favorable environment for the deployment of alternative energy sources, particularly solar and wind energy. The country has historically relied on fossil fuels like oil and natural gas for its electricity generation. Fossil fuels are finite and have historically shown price volatility and high carbon emissions, posing long-term challenges to the nation’s energy security. Critical Infrastructure Protection (CIP) is a concept distinct from “energy security,” which should consider sustainable energy sources (such as solar and wind) as vital energy supplies in Saudi Arabia.

According to the Saudi Arabia Renewable Energy Tracker, developed by KAPSARC, the Kingdom has officially launched 10 sustainable energy projects to date, as shown in

Table 1. Installed solar and wind energy projects in Saudi Arabia [35].

Project Name	Type	State	Expected Commissioning Year	Capacity (GW)
Shuaibah 2	Solar	Installed	2024	2.06
Ar Rass 1	Solar	Installed	2024	0.7
Shuibah 1	Solar	Installed	2024	0.6
Saad 1	Solar	Installed	2024	0.3
Layla	Solar	Installed	2024	0.091
Sudair	Solar	Installed	2023	1.5
Rabigh 1	Solar	Installed	2023	0.3
Jeddah	Solar	Installed	2023	0.3
Dumat Al-jandal	Wind	Installed	2022	0.4
Sakaka	Solar	Installed	2020	0.3

. This number is projected to increase to 38 projects by the year 2028. As illustrated in Figure 1, approximately 15.5% of these projects are wind energy initiatives, while the remaining 84.5% are focused on solar power development.

Renewable energy projects in the kingdom are primarily concentrated in the central and western regions. According to the latest census conducted in April 2025, most of the installed projects are solar energy projects, with only one installed wind energy project (Dumat Al Jandal), which has a capacity of 400 MW and includes 99 wind turbines. This represents an advancement in KSA’s sustainable energy sector. As reported by ACWA Power, the country has managed to increase its renewable power market size from 700 MW between 2012 and 2022 to reach 2.1 GW by early 2024 [35].

3.1.1. Solar Energy

The Kingdom of Saudi Arabia is positioned sixth among the top ten nations regarding the potential for solar energy production. As per the Renewable Energy Atlas created by K.A. CARE, the northern area of the Kingdom (particularly the cities of Asir and Tabuk), demonstrated significant solar energy output owing to high average solar irradiance and comparatively low average temperature. Similarly, urban areas in the southern part of Saudi Arabia showed elevated average solar irradiance levels [35]. Conversely, the western region along the Red Sea coastline showed the lowest average irradiance measurements, as shown in Figure 2 [36].

A 2020 analysis [38] identified the southern and western regions of Saudi Arabia as optimal for solar energy deployment, based on high Global Horizontal Irradiance (GHI) and other solar radiation metrics. GHI refers to the total solar radiation received on a horizontal surface, which includes both Direct Normal Irradiance (DNI), the direct beam of sunlight, and Diffuse Horizontal Irradiance (DHI), which is the portion of sunlight scattered by atmospheric particles and reaching the surface from all directions. These components are illustrated in Figure 3.

In 2021, the Kingdom significantly expanded its solar power generation capacity by approximately 439 megawatts, marking a major step forward in its renewable energy initiatives [37].

3.1.2. Wind Energy

Wind energy is projected to play a pivotal role in the diversification of Saudi Arabia’s renewable energy mix, driven by its accelerated development relative to other energy sources. The Kingdom encompasses multiple regions with high potential for wind power generation [37], particularly along coastal zones. As illustrated in Figure 4, the Saudi Wind Atlas provides detailed insights into the spatial distribution of average wind speeds and indicates substantial offshore wind potential.

In addition, elevated wind speeds are predominantly observed in the northeastern, central, and western mountainous areas of the country, showing an expansion in wind flow. For example, Saudi Arabia ranks 13th among the leading 15 nations in terms of onshore wind generation potential [35]. Moreover, wind measurements at 100 m above ground level, coupled with favorable capacity factors, reinforce the technical and economic viability of large-scale wind energy deployment across these regions [37].

3.2. Region Selection

Saudi Arabia offers significant potential for the implementation of renewable energy technologies, especially solar and wind, owing to its favorable natural attributes. The country benefits from an average of approximately 8.9 h of sunshine per day, and a mean GHI of around 5523 Wh/m²/day [40]. Additionally, its strong wind energy potential, driven by advantageous geographic and climatic factors, positions Saudi Arabia as a leading candidate for large-scale renewable energy initiatives. The selection of regions was based on the goal of maximizing renewable energy generation while aligning with the potential for CO₂ capture, as illustrated in Figure 5. The selection criteria included:

• Resource Potential: Strong sunlight availability and consistent wind patterns.
• Proximity to CO₂ Sources: Industrial centers with high emissions to enable efficient carbon capture.
• Economic Feasibility: Assistance from the government, access to infrastructure, and consistency with national sustainability objectives.

Figure 5. Comparative advantages of selected study locations.

Figure 5. Comparative advantages of selected study locations.

Based on these criteria, the regions of NEOM, Jubail, and Jeddah were identified as suitable candidates. NEOM, located in the northwest, offers excellent solar and wind resources, mild temperatures, and proximity to Red Sea industrial centers, making it well-positioned for carbon management initiatives. Jubail, situated in the Eastern Province, is one of the world’s most prominent industrial cities. It hosts extensive petrochemical facilities, generates significant CO₂ emissions, and has robust infrastructure to support large-scale carbon capture projects.

Finally, Jeddah also meets the selection criteria due to its strategic location, strong infrastructure, and access to both industrial zones and major ports. Collectively, these regions provide optimal conditions for integrating renewable energy systems with DAC technologies to advance energy and climate objectives.

3.3. Saudi Arabia Net Zero Emission by 2060

Saudi Arabia launched Vision 2030, an ambitious framework aimed at guiding the nation toward a more sustainable and diversified future. As part of this vision, the Kingdom has established clear sustainability targets, including a commitment to achieving net-zero greenhouse gas (GHG) emissions by 2060 [41]. In line with this objective, Saudi Arabia is actively advancing its renewable energy initiatives to meet its emission reduction goals. A recent initiative led by the Ministry of Energy, in collaboration with various sectors, involves a comprehensive geographic survey to identify optimal locations for renewable energy projects. This initiative includes the deployment of 1200 monitoring stations nationwide to assess solar and wind energy potential [42].

Achieving the 2060 net-zero target requires not only the expansion of renewable energy infrastructure but also significant efforts to reduce carbon emissions [43]. In this context, carbon capture technologies play a pivotal role. Among these, DAC is considered one of the most promising solutions, offering significant potential to help meet net-zero commitments [44]. For Saudi Arabia to achieve its climate goal, CDR strategies will be essential. Estimates indicate that approximately 371 million metric tons of CO₂ will need to be removed annually to offset the country’s projected emissions [45]. While CDR technologies such as DAC are energy-intensive and currently expensive, their implementation can be optimized. Given that Saudi Arabia is among the world’s leading oil exporters, a sector that significantly contributes to its emissions profile, powering DAC facilities with renewable energy can substantially reduce both operational costs and emissions. This approach ensures the carbon removal process remains emission-free [46].

Multiple carbon capture projects and research efforts are currently underway across the Kingdom. These initiatives are in various stages of development and assessment.

To ensure their maximum impact at the lowest possible cost, it is critical to evaluate such systems from multiple technical and economic perspectives. One of the most essential factors in this evaluation is the selection of appropriate project locations, particularly considering the geographical diversity of Saudi Arabia.

3.4. Selection and Justification of HOMER Pro for Renewable Energy System Optimization

A variety of software tools exist for modeling and simulating renewable energy systems, each providing distinct functionalities. For instance, PVSyst, SAM, and PV*SOL provide excellent precision and visualization for either wind or PV yet vary in their visual representation in hybrid system functions. Helioscope excels in visualization, making it ideal for presentations and shade analysis, but it offers limited support for hybrid systems. MATLAB R2025a, although considered challenging to use because of its coding-centric interface, provides exceptional accuracy, versatility, and sophisticated hybrid system modeling, rendering it extremely beneficial for tailored simulations and scholarly work [47].

For this study, which aims to analyze different scenarios for each chosen region and conduct a comprehensive techno-economic assessment, HOMER Pro was chosen. This selection is based on HOMER’s enhanced capability to handle intricate case studies, its adaptability in modeling various system setups, its ability to compare between systems, and its powerful tools for optimization and sensitivity assessment [48].

Furthermore, HOMER Pro is recognized for its intuitive design and efficient graphical representation of simulation results, making it both effective and user-friendly.

3.4.1. System Description

This study simulated off-grid renewable energy systems for DAC applications in the three selected regions. The load profile represents industrial-level demand, with a daily load of 1142.4 kWh/day and a peak demand of 87.26 kW. The system was designed for a 25-year lifetime using HOMER Pro. Key simulation inputs included Capital cost, Replacement costs, Operation and Maintenance (O&M) costs, project timeline, and the equipment specifications, as illustrated in Figure 6.

3.4.2. Site Selection

Certain coastal regions of Saudi Arabia exhibit relatively higher wind speeds compared to others, while Figure 7 demonstrates that solar irradiance is generally more pronounced in the northwestern and southwestern areas of the Kingdom. For the purposes of this study, three locations were selected for analysis: Jubail, Jeddah, and NEOM. The necessary wind and solar resource data for these sites were obtained directly from HOMER Pro, utilizing the NASA POWER (Prediction of Worldwide Energy Resources) database. This database generates synthetic hourly data and serves as a valuable tool for acquiring meteorological information in the subsequent phase of the research. The dataset offers a comprehensive overview of various climate-related parameters, including humidity, temperature, solar radiation, and wind speed, enabling researchers to access accurate and reliable weather data for the study region [49]. For this study, data on solar radiation, wind velocity, and air temperature averaged over the period from 1983 to 2005 were obtained from the NASA database. These data were used to assess the feasibility of deploying solar, wind, or hybrid energy systems at various locations to meet the energy demands of the designated unit. While the 1983–2005 NASA dataset provides a reliable long-term baseline and remains the default source within HOMER Pro for ensuring methodological consistency, it is important to recognize its limitations. In particular, these historical averages may not fully reflect recent climate variability, technological advancements, or the potential impacts of climate change on solar and wind resources. Consequently, the results of this study should be interpreted as indicative of long-term feasibility rather than precise present-day projections. Future research could benefit from incorporating updated high-resolution datasets, such as NASA POWER, to complement the robustness of HOMER-based simulations. Nevertheless, the dataset still provides valuable insights into regional solar and wind resource patterns. As shown in Figure 7, the average daily solar radiation in Jubail ranges from 3.57 to 8.00 kWh/m²/day, with an annual mean of 5.72 kWh/m²/day. In NEOM, values range from 3.56 to 8.05 kWh/m²/day, with a yearly average of 5.86 kWh/m²/day. Jeddah exhibited the highest overall solar irradiance, ranging from 4.15 to 7.17 kWh/m²/day, and an annual average of 5.94 kWh/m²/day. Jubail, located on the eastern coast along the Arabian Gulf, experiences higher wind speeds due to its open sea exposure and minimal terrain obstacles, which allow for steady and strong wind flow [50]. In contrast, Jeddah, situated on the Red Sea coast, experiences moderate wind speeds as a result of the nearby Hijaz Mountain range, which increases surface roughness and induces turbulence, thereby reducing wind velocity [51]. NEOM’s complex mountainous terrain further disrupts airflow, leading to lower wind speeds compared to coastal regions. These local topographic conditions explain the observed gradient in wind speeds across the study sites [49].

Wind speed measurements were taken at a height of 50 m above level ground, using monthly averages over a 30-year period (from January 1984 to December 2013). The data were obtained from the NASA Surface Meteorology and Solar Energy Database (accessed on 4 April 2025). Figure 8 illustrates the typical monthly wind speed patterns for the selected locations.

The annual average wind speed was approximately 5.68 m/s in Jubail, followed by 5.21 m/s in Jeddah and 5.02 m/s in NEOM. Overall, the average wind speeds across the three cities were relatively similar.

3.4.3. Load Profile and System Inputs

From a demand-side perspective, the load profile of the study area plays a pivotal role in the optimization process. It is a critical factor in designing an efficient energy system that consistently meets power requirements while avoiding unnecessary costs associated with overdesign [47]. The system was designed to operate continuously on a 24 h basis, accounting for seasonal variations between summer and winter. As noted in the study by Said et al. (2024), the summer peak months in Saudi Arabia in June, July, and August typically exhibit higher energy consumption compared to the winter months of December, January, and February [52], as illustrated in Figure 9. The project’s operational lifetime was assumed to be 25 years.

The primary input parameters for HOMER Pro encompass monthly wind speed, solar irradiance, load profile, technical specifications of the wind turbine, PV system, batteries, and system converters, as well as the economic constraints, as detailed in

Table 2. Module parameter values used in HOMER Pro.

Component	Parameter	Value	Unit
PV	Capacity	Determined by HOMER optimizer	kW
	Lifetime	25	Year
	Capital cost	758	USD/kW
	Replacement	606.4	USD/kW
	O&M	15.7	USD
	Derating Factor	85	%
Converter	Capacity	Determined by HOMER Optimizer	kW
	Lifetime	15	Year
	Efficiency	95	%
	Capital	300	USD
	Replacement	300	USD
Battery	Nominal capacity	Determined by HOMER Optimizer
	Initial state of Charge	100	%
	Lifetime	Determined by HOMER Optimizer
	String size	1
Wind turbine	Initial capacity	Determined by HOMER Optimizer	USD
	Replacement	929	USD
	O&M	23.2	USD/year
	Lifetime	25	Year
	Hub Height	100	m
	Temperature Effect	Yes	Kelvin
Economical parameter	Project lifetime	25	Year
	Deal Discount Rate	6	%

.

3.4.4. Economical Optimization

In HOMER Pro, two main economic metrics are utilized to assess various system configurations: the NPC and the LCOE. The NPC refers to the total cost of installing, operating, maintaining, and replacing system components over the lifetime of the project. NPC can be measured as shown in Equation (1) by summing the total annualized cost divided by the capacity recovery factor (CRF), which can be calculated using Equation (2). Meanwhile, the LCOE computes the average cost per kWh of electrical energy of the system, as presented in Equation (3).

This research included both resource evaluation and a techno-economic analysis of solar/wind hybrid systems that are off-grid for the chosen cities. The software HOMER was utilized to create a hybrid off-grid system, assess power generation, and determine the most economical configuration [53].

(i)

Net Present Cost

$$\mathrm{N}\mathrm{P}\mathrm{C}={\displaystyle \frac{{\mathrm{C}}_{\mathrm{A}\mathrm{n}\mathrm{n},\mathrm{t}\mathrm{o}\mathrm{t}}}{\mathrm{C}\mathrm{R}\mathrm{F}(\mathrm{i},\mathrm{N})}}$$

(1)

$$\mathrm{C}\mathrm{R}\mathrm{F}={\displaystyle \frac{{\mathrm{i}(1+\mathrm{i})}^{\mathrm{N}}}{{(1+\mathrm{i})}^{\mathrm{N}}-1}}$$

(2)

where C_{Ann, tot} is the total annualized cost (USD/year), i is the annual real interest rate, N is the project lifetime, and CRF (i, N) is the capacity recovery factor

(ii)

Levelized Cost of Energy

$$\mathrm{L}\mathrm{C}\mathrm{O}\mathrm{E} \left({\displaystyle \frac{\$}{\mathrm{k}\mathrm{W}\mathrm{h}}}\right)={\displaystyle \frac{{\mathrm{C}}_{\mathrm{A}\mathrm{n}\mathrm{n},\mathrm{t}\mathrm{o}\mathrm{t}}}{{\mathrm{R}}_{\mathrm{E}\mathrm{l}\mathrm{e}\mathrm{c}\mathrm{t}\mathrm{r}\mathrm{i}\mathrm{c}\mathrm{a}\mathrm{l},\mathrm{t}\mathrm{o}\mathrm{t}}}}$$

(3)

R_{electrical, tot} refers to the total electrical load supplied, including both primary and deferred loads (if present), measured in kWh/year.

3.5. Simulation Process Using HOMER Pro

To evaluate the techno-economic feasibility of renewable-powered DAC systems across the selected regions, this study adopted a structured simulation process using HOMER Pro. Figure 10 illustrates the overall methodology, which integrates region-specific resource inputs, technical specifications, and economic parameters to simulate and optimize system configurations under a constant load profile.

The simulation process begins with the collection of key input data, including solar irradiance, wind speed, ambient temperature, system costs, and operational assumptions. Three primary configurations consisting of PV/Battery, Wind/Battery, and PV/Wind/Battery are individually modeled in HOMER Pro to assess system reliability, NPC, and LCOE. These metrics enable a comparative evaluation of system performance across different geographic locations, facilitating the identification of the most cost-effective and emissions-minimizing configuration.

The simulation also incorporates sensitivity analysis to account for variability in resource availability and economic factors, ensuring robust and regionally optimized system design [46].

4. Results and Discussion

4.1. Integration of Renewable Energy Systems and Techno-Economic Assessment Using HOMER Pro

The system was configured and implemented in HOMER Pro, which performed all calculations on the input data provided, as shown in Table 2 in the methodology. After conducting the simulations, two main scenarios were suggested by HOMER: Wind/Battery and PV/Wind/Battery systems, although numerous studies indicate that integrating these elements can lower expenses by efficiently utilizing resources and equipment. For instance, a cohesive system could share elements such as electrical parts, inverters, and control frameworks, reducing overall capital, replacement, and operational costs [51].

After HOMER simulates the results, it performs a comparative analysis to identify the most cost-effective approach from a techno-economic perspective as a base case. The most suitable scenario was identified as the Wind/Battery system in Jubail and Jeddah and Wind/PV/Battery in NEOM. This is considered logically reasonable based on the solar irradiance and wind speed data obtained.

Jubail exhibits the lowest average solar irradiance among the selected regions, measuring approximately 5.72 kWh/m²/day, while recording the highest average wind speed at 5.68 m/s. Jeddah ranked second, benefiting from high levels of both solar irradiance and wind speed. Based on a comprehensive evaluation of cost-effectiveness, the Wind/Battery system was determined to be the most reliable option for both Jeddah and Jubail. In contrast, for NEOM, the Wind/PV/Battery hybrid system was identified as the most viable solution, offering the lowest NPC and LCOE.

4.2. Economic Analysis

As

Table 3. Optimization results of LCOE and NPC for the off-grid system.

	Levelized Cost of Energy LCOE (USD/kWh)		Net Present Cost NPC (USD)
Cities	Wind/Battery	Wind/PV/Battery	Wind/Battery	Wind/PV/Battery
Jubail	0.128	0.129	842,375	849,525
Jeddah	0.146	0.150	958,303	982,977
Neom	0.154	0.149	1.01 M	974,908

illustrates, the optimization results for the LCOE and NPC of the stand-alone system are presented. Jubail had the lowest NPC of USD 842,375 and an LCOE of USD 0.128/kWh, followed by Jeddah with an NPC of USD 958,303 and an LCOE of US D 0.146/kWh using a Wind/Battery system. NEOM incorporates the highest values in Wind/Battery. However, the chosen system with the optimal values was the hybrid system with an NPC of USD 974,908 and an LCOE of USD 0.149/kWh.

Based on the load entered, the DAC system will be capable of capturing approximately 364.2 tons of CO₂ annually, with a stable capture rate of 41.39 kg of CO₂ per hour.

Among the selected locations, NEOM’s relatively underdeveloped infrastructure and greater variability in renewable energy resources, particularly solar irradiance and wind consistency, necessitate larger energy storage capacity and higher system redundancy, which significantly increases capital and operational costs. In contrast, Jeddah benefits from more established infrastructure and high solar potential, though elevated ambient temperatures and humidity levels may slightly reduce system efficiency. Jubail, on the other hand, demonstrates lower NPC due to its favorable and stable wind conditions, which enhance turbine performance and reduces reliance on expensive storage components. Consequently, the techno-economic viability improves progressively from NEOM to Jubail, as reflected in the declining NPC values.

Although NEOM achieved the lowest NPC among the evaluated regions, it recorded the highest LCOE. This apparent contrast is primarily due to the high capital and operational costs per unit of electricity generated, which result from its remote location and less developed infrastructure. While the total system cost is minimized in absolute terms, the relatively low energy output per unit cost leads to a higher LCOE compared to Jeddah and Jubail.

Based on the results from the HOMER Pro simulation, the most cost-effective system configurations were identified for each location, along with their corresponding NPC and LCOE, as illustrated in Figure 11.

4.3. Scenario-Based Assessment of CO₂ Avoidance in DAC Systems Using Renewable vs. Fossil Fuel Energy

Unlike conventional power plants that rely on the combustion of fossil fuels such as coal, oil, or natural gas, renewable energy systems generate electricity with negligible direct greenhouse gas emissions. This contributes significantly to CO₂ avoidance, primarily through the displacement of high-emission grid electricity characterized by elevated carbon intensity. In Saudi Arabia, grid emission factors typically range between 0.6 and 0.7 kg CO₂/kWh. This implies that the higher the grid emission factor is, the greater the environmental benefit achieved by replacing fossil fuel-based power with renewable energy sources is.

Assuming a DAC plant operational lifetime of 25 years, the longer the system remains active, the more fossil fuel-based generation it displaces, resulting in a cumulative increase in avoided CO₂ emissions. In the present study, an off-grid hybrid system or Wind/Battery configuration has been established as the base case for powering the DAC unit, with a daily load of approximately 1142.4 kWh. The total amount of CO₂ avoided over the system’s lifetime was calculated using Equation (4).

$${\mathrm{C}\mathrm{O}}_2 \mathrm{A}\mathrm{v}\mathrm{o}\mathrm{i}\mathrm{d}\mathrm{n}\mathrm{c}\mathrm{e}\left({\displaystyle \frac{\mathrm{t}\mathrm{o}\mathrm{n}\mathrm{s}}{\mathrm{y}\mathrm{e}\mathrm{a}\mathrm{r}}}\right)={\displaystyle \frac{\mathrm{T}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{l} \mathrm{a}\mathrm{n}\mathrm{n}\mathrm{u}\mathrm{a}\mathrm{l} \mathrm{E}\mathrm{n}\mathrm{e}\mathrm{r}\mathrm{g}\mathrm{y} \mathrm{P}\mathrm{r}\mathrm{o}\mathrm{d}\mathrm{u}\mathrm{c}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n} (\mathrm{k}\mathrm{W}\mathrm{h}/\mathrm{y}\mathrm{e}\mathrm{a}\mathrm{r}) \mathrm{X} \mathrm{G}\mathrm{r}\mathrm{i}\mathrm{d} \mathrm{E}\mathrm{m}\mathrm{i}\mathrm{s}\mathrm{s}\mathrm{i}\mathrm{o}\mathrm{n} \mathrm{F}\mathrm{a}\mathrm{c}\mathrm{t}\mathrm{o}\mathrm{r}\left(\right(\mathrm{k}\mathrm{g} \mathrm{C}{\mathrm{O}}_2)/\mathrm{k}\mathrm{W}\mathrm{h})}{1000}}$$

(4)

An economic evaluation was conducted by considering two scenarios. The first scenario is based on renewable energy, with an annual energy production of approximately 416,976 kWh/year and zero carbon emissions from electricity generation. The second scenario relies on fossil fuels, assuming the same energy load, with 23% of the electricity used to power the vacuum and fan, and the remaining 77% generated using natural gas for heating. For this scenario, the grid emission factor was assumed to be 0.65 kg CO₂/kWh for electricity and 0.184 kg CO₂/kWh for natural gas [54]. The total CO₂ emissions were estimated at 121.417 tons per year, with 62.34 tons from electricity and 59.077 tons from natural gas, as shown in

Table 4. Total CO₂ emission for both case scenarios.

	Scenarios	Energy Source	Total Annual Load Value (kWh/year)	Total Amount of CO2 Emissions (tons/year)
1st	Renewable energy	100% Renewable Energy	416,976	0.0
2nd	Fossil fuel	23% Electricity, 77% Natural Gas	416,976	121.41

. These results clearly highlight the environmental benefits of using renewable energy sources over fossil fuels in the implementation of the DAC unit.

5. Conclusions

This study investigated the integration of renewable energy sources into DAC systems in Saudi Arabia, using HOMER Pro to evaluate the techno-economic performance across three key regions. By simulating various hybrid energy configurations in Jubail, Jeddah, and NEOM, the analysis identified the Wind/Battery system as the most cost-effective solution for Jubail and Jeddah, while the Wind/PV/Battery configuration emerged as optimal for NEOM due to its unique geographic and resource conditions. Among all locations, Jubail achieved the lowest NPC of USD 842,375 and the most competitive LCOE at USD 0.128/kWh. The integration of renewable energy not only enhanced economic performance but also demonstrated substantial environmental benefits, with the potential to reduce CO₂ emissions by approximately 121.4 tons annually compared to fossil fuel-based DAC systems. These results highlight the importance of conducting region-specific resource assessments and designing systems that align with local environmental and economic conditions. This research provides a practical framework for implementing low-emission, economically viable DAC systems that support Saudi Arabia’s clean energy transition and long-term climate goals.

Future Work

In future work, we aim to incorporate detailed Capital Expenditure (CAPEX) and Operational Expenditure (OPEX) data into the HOMER Pro simulations. This will enable a more comprehensive techno-economic analysis by capturing the full financial scope of DAC deployment, including investment costs, maintenance, and operational dynamics. By refining these inputs, the model will better reflect real-world scenarios and enhance the accuracy of system optimization and feasibility assessments.