Integrating solid direct air capture systems with green hydrogen production: Economic synergy of sector coupling (2406.00665v3)

Abstract: In the global pursuit of sustainable energy solutions, mitigating carbon dioxide (CO2) emissions stands as a pivotal challenge. With escalating atmospheric CO2 levels, the imperative of direct air capture (DAC) systems becomes evident. Simultaneously, green hydrogen (GH) emerges as a pivotal medium for renewable energy. Nevertheless, the substantial expenses associated with these technologies impede widespread adoption, primarily due to significant installation costs and underutilized operational advantages when deployed independently. Integration through sector coupling enhances system efficiency and sustainability, while shared power sources and energy storage devices offer additional economic benefits. In this study, we assess the economic viability of polymer electrolyte membrane electrolyzers versus alkaline electrolyzers within the context of sector coupling. Our findings indicate that combining GH production with solid DAC systems yields significant economic advantages, with approximately a 10% improvement for PEM electrolyzers and a 20% enhancement for alkaline electrolyzers. These results highlight a substantial opportunity to improve the efficiency and economic viability of renewable energy and green hydrogen initiatives, thereby facilitating the broader adoption of cleaner technologies.

• The paper shows that coupling DAC and green hydrogen production significantly reduces total annualized costs, with PEM-based systems improving by around 10% and Alkaline systems by about 20%.
• The paper uses a two-stage stochastic programming model to optimize system sizing and operations, effectively balancing energy flows under uncertain renewable supply.
• The paper reveals that sharing expensive infrastructure like batteries and heat pumps in a sector-coupled system mitigates cost penalties and enhances overall economic resilience.

Integrating solid direct air capture (DAC) systems with green hydrogen (GH) production, as explored in this paper (2406.00665), presents a compelling strategy to address both climate change and the challenges of renewable energy integration. The core idea is that coupling these two energy-intensive processes, powered by variable renewable sources like wind and solar, can lead to economic synergies that make both technologies more viable than when deployed independently.

The primary motivation is the high cost and operational inflexibility of standalone DAC and GH systems. Solid DAC systems, particularly using temperature-vacuum swing adsorption (TVSA), require significant capital investment and need high utilization rates to be economically feasible. Green hydrogen production via electrolysis, especially using renewable energy, faces challenges from the intermittent nature of renewables, potentially leading to oversized facilities and energy curtailment. Sector coupling aims to mitigate these issues by allowing shared renewable energy resources, energy storage (batteries, hydrogen tanks, thermal storage), and potentially coordinated operation to balance the variable supply with the demands of both processes.

The paper focuses on the techno-economic viability of this integration, comparing systems based on Polymer Electrolyte Membrane (PEM) and Alkaline electrolyzers, which have different operational characteristics (specifically, minimum operating loads). Solid DAC plants primarily require electrical and thermal energy (for the desorption phase, often supplied by a heat pump), while electrolyzers primarily need electrical energy.

System Architecture and Components

A sector-coupled system typically involves:

1. Renewable Energy Sources: Wind turbines and PV panels as primary power generators.
2. Electrolyzers: PEM or Alkaline, converting water to hydrogen.
3. Solid DAC Plant: Capturing CO₂ from the air using solid adsorbents and releasing it via thermal energy and vacuum.
4. Energy Storage:
   • Batteries (Electrical storage)
   • Hydrogen Tanks (Hydrogen storage)
   • Thermal Energy Storage (TES) (Heat storage for DAC desorption)
5. Energy Conversion:
   • Fuel Cells (Convert H₂ back to electricity, primarily for meeting minimum operational loads or grid support)
   • Heat Pumps (Convert electricity to thermal energy for DAC)
   • Converters (DC/DC, AC/DC, AC/AC) to manage different current requirements (electrolyzers, batteries are DC; DAC, heat pumps are AC). The paper finds a hybrid DC-AC configuration to be most efficient.
6. Control System: An optimization framework (like the Two-stage Stochastic Programming used) is necessary to determine optimal facility sizing (capacity) and hourly operational schedules (energy flows, component states) under uncertain renewable energy availability and potentially variable demand.

Implementation Approach (Modeling and Optimization)

The paper employs a Two-stage Stochastic Programming (2SSP) model to find the optimal system design and operation.

• First Stage: Decisions on the capacity of all components (wind turbines, PV panels, batteries, electrolyzers, DAC plant, tanks, heat pumps, TES, fuel cells) are made before knowing the exact future weather and demand.
• Second Stage: Operational decisions (charging/discharging storage, power to electrolyzers/DAC/heat pumps, curtailment, fuel cell dispatch) are made after the uncertainty (represented by weather scenarios) is realized, aiming to minimize operating costs while meeting hydrogen demand (timely satisfaction) and CO₂ removal targets (annual average).

The objective function is to minimize the Total Annualized Cost (TAC), which includes annualized investment costs and operational/maintenance costs.

$min \sum_i [IC_i \times X_i \times (CRF_i + OM_i)]$

Where $IC_i$ is investment cost, $X_i$ is capacity, $CRF_i$ is capital recovery factor, and $OM_i$ is O&M cost for facility $i$.

Constraints include:

• Energy balance equations for electrical, thermal, and hydrogen systems at each time step.
• Operational constraints for each component (e.g., minimum/maximum loads, storage limits, charging/discharging rates, efficiencies).
• Sequential constraints for the solid DAC process phases (adsorption, shutdown, desorption, shutdown).
• Meeting hydrogen demand and CO₂ removal targets across defined time horizons.

Practical implementation requires:

• Data: High-resolution historical weather data (solar irradiance, wind speed) for multiple years to generate representative scenarios. Hydrogen demand profiles and CO₂ removal targets.
• Component Models: Mathematical models describing the energy input/output and operational constraints of each technology component. The paper provides examples of these models (e.g., equations A1-A28 in the supplementary material).
• Optimization Solver: A robust solver capable of handling large-scale mixed-integer linear programming (MILP) or linear programming (LP) problems, depending on how discrete variables are handled (the paper treats DAC units as continuous for simplicity). Solvers like IBM CPLEX (used in the paper), Gurobi, or open-source options like CBC or GLPK accessed via modeling languages like Pyomo or GurobiPy are needed.
• Computational Resources: Solving large 2SSP models can be computationally demanding, requiring significant processing power and memory, especially with many scenarios and high temporal resolution.

Key Practical Findings and Implications

1. Economic Synergy: The sector coupling strategy significantly reduces the overall TAC compared to operating standalone systems. The paper shows ~10% improvement for PEM-based coupling and ~20% for Alkaline-based coupling. This highlights that the joint optimization and shared infrastructure benefits are substantial.
2. Alkaline Advantage in Coupling: Surprisingly, while standalone Alkaline GH systems were ~15% less cost-effective than PEM due to higher minimum load and associated battery costs, the Alkaline system shows greater synergy (~20% vs ~10%) in the sector-coupled configuration.
   • Implication: This suggests that the capital cost advantage of Alkaline electrolyzers becomes more impactful when integrated with DAC. The high battery requirement for DAC facilities means that the coupled system already needs significant battery capacity. Sharing this battery capacity mitigates the standalone Alkaline system's specific weakness (high battery costs due to high minimum load), allowing its lower capital cost to drive greater overall economic benefit in the coupled system. This is a crucial factor for site-specific technology selection.
3. Impact of Demand/Target Ratio: The economic benefits (Improvement and Synergy) are sensitive to the ratio of annual hydrogen demand to the annual CO₂ removal target. Optimizing this ratio is key for maximizing synergy in a deployed system.
4. Cost Sensitivities:
   • Increased Battery Costs: Counter-intuitively, higher battery costs can increase synergy. This is because standalone systems are heavily penalized by high battery costs (especially DAC and Alkaline GH), whereas the coupled system benefits from sharing these expensive assets, making the relative advantage of coupling larger.
   • Decreased DAC/Electrolyzer Costs: Lower costs for DAC facilities and electrolyzers enhance the benefits of sector coupling. Cheaper units allow for larger installed capacities optimized for dynamic operation with variable renewables, increasing the opportunity for synergistic energy management.
   • Power Source Costs: The impact depends on the CO₂ removal target. Power sources enable dynamic operation but also benefit from reduced oversizing via coupling.
   • Overall Implication: The paper finds the synergy benefits to be relatively constant (+/- a few percentage points) even with significant (±20%) cost variations in key components. This suggests the structural advantage of coupling is robust to future technology cost uncertainties.
5. Heat Pump Flexibility: Increasing the operational flexibility of the heat pump serving the DAC unit (by reducing its minimum operating load) significantly improves the economic viability of the sector-coupled system, particularly at lower CO₂ removal targets.
   • Implication: Investing in more flexible heat pump technology can be a critical design choice to enhance the benefits of coupling, allowing the DAC plant to better adapt its thermal energy demand to the variable supply from renewables and TES.

Implementation Considerations and Deployment

• Site Selection: The analysis was performed for three specific locations with high renewable potential. Real-world deployment requires detailed, site-specific analysis using local weather data and considering grid connection capabilities and local energy market structures.
• Co-location: The synergy benefits strongly suggest co-locating GH and solid DAC facilities to minimize energy transmission losses and facilitate shared infrastructure.
• Control System Design: A sophisticated real-time energy management system is needed to implement the optimal operational strategy derived from the optimization model. This system must react dynamically to changing renewable generation, energy storage levels, and potentially variable hydrogen demand or CO₂ capture requirements.
• Scalability: The paper models modular DAC units and treats them as continuous variables for optimization. Scaling up to commercial capacity requires managing potentially thousands of these modules and their individual or group operational states.
• Integration Complexity: Implementing the electrical (DC and AC buses, converters), thermal (heat pump, TES), and hydrogen (electrolyzer, tank, fuel cell) systems with complex control logic is a significant engineering challenge.
• Regulatory Environment: Policies and incentives for green hydrogen production and CO₂ capture/storage (CCS) will heavily influence the economic viability of such projects.

In summary, the research provides a quantitative basis for the economic benefits of integrating solid DAC and green hydrogen production using renewable energy, offering valuable insights for designing and implementing such complex energy systems. The finding regarding the surprising advantage of Alkaline electrolyzers in a coupled system, and the robustness of synergy benefits to cost variations, are particularly impactful for practical decision-making. The methodology highlights the importance of using optimization under uncertainty to correctly size and operate these variable, interconnected systems.