(36c) Biomass, Solar and Wind-Based Hydrogen and Carbon Dioxide Supply Chain Optimization Considering Enhanced Oil Recovery: A Colombian Case Study

Several research initiatives worldwide are focusing on the incorporation of green and blue hydrogen as a non-conventional energy source to diversify the global energy matrix and to reduce net carbon emissions. According to [1], despite the interesting environmental benefits that come with the use of hydrogen as an energy vector, its implementations must achieve economies of scale to reduce costs. This is accomplished with an adequate study of the hydrogen supply chain that promotes its use and applications in different sectors.

Similarly, it has been identified that the hydrogen implementation in the energy matrix entails great challenges such as: analysis of production technologies focused on reducing costs [2] [3], studies on infrastructure and logistics to evaluate ways to distribution and storage [4], determination of management and safety plans [5], studies on the lack of regulations that encourage their demand [5], diagnosis on the environmental implications in the use of technologies for H₂ production [6], among other challenges.

In Colombia there are different initiatives with the aim of diversifying the energy matrix and reducing net carbon emissions. To achieve this objective, there has been investigations focused on: a roadmap for hydrogen [7], the location of areas that have the best characteristics to develop wind and solar photovoltaic farms from geographic information systems [8], and the potential of biomass conversion to biogas in Colombia [9]. In this regard, for countries like Colombia it is necessary to evaluate the use of different resources to produce bioenergy that diversifies the energy matrix.

To reduce to zero the net carbon emissions, it is necessary to consider the incorporation of Carbon Capture, Use and Storage (CCUS). In this sense, CO₂-EOR is frequently recognized as the main use of CO₂ to leverage the deployment of CO₂ capture chains even in the absence of tax benefits or carbon credits. Additionally, some industries emit high purity CO₂ (e.g., natural gas processing, bioethanol production and hydrogen production), becoming an important source of low-cost CO₂ for CCUS supply chains. The potential to develop CO₂-EOR operations as a strategy to reduce CO₂ emissions has been little studied in Colombia. In recent works, it was found a significant potential for CO₂-EOR projects and established a methodology for matching CO₂ sources and sinks through a dedicated pipeline network [10] [11]. However, a mathematical programming approach has not yet been explored.

Some works have introduced CO₂ capture into their hydrogen supply chain network design (HSCND) models, they found that combining carbon capture and storage (CCS) with hydrogen production plants is the alternative most cost-effective to maintain a low level of carbon emissions and avoid carbon tax penalties [12]. Until now, the HSCND models have not included CO₂ utilization for CO₂-EOR.

Methods

In this work, we proposed a sustainable supply chain optimization model that maximizes the net present value (NPV) of the supply chain and considers: (1) hydrogen production from renewable resources (solar, wind and biomass), multimodal transportation and storage; (2) carbon dioxide capture, multimodal transportation, utilization for EOR and geological storage; and (3) carbon taxes and credits to evaluate the impact on the hydrogen sale price. The mathematical formulation for the supply chain is based on the work of Almansoori and Shah [12] and Moreno-Benito et al. [13], and the representation of the CO₂-EOR operation is based on the work of Calderón and Pekney [14].

The optimization problem was formulated as Mixed Integer Linear Programming (MILP) and was solved in GAMS 33.2.0 using CPLEX v12.10. On one hand, the model inputs can be summarized as: (1) economic data (including carbon taxes and credits), (2) resources availability, (3) hydrogen demand and potential of CO₂ storage and oil recovery for EOR operation, (4) production technologies specification (capex, opex, capacity and yields), (5) transportation modes (capex, opex, capacity), and (6) distances between nodes. On the other hand, the model outputs can be summarized as: (a) resources (biomass, solar and wind power) utilization rates, (b) production and capture rates, (c) flow rates between nodes, (d) CO₂ storage and oil recovery rates for the CO₂-EOR operations, (e) production plants (selection of number, location, technology, capacity), and (f) transport mode (selection of number, capacity, length, diameter).

The case study examines a nationwide multi-period long-term planning horizon in Colombia from 2020 to 2050. The territory is divided into different nodes that considers: (i) hydrogen demand for the power generation, industrial and mobility sectors [7]; (ii) biomass potential sources from agricultural residues and urban waste [9]; (iii) wind and solar energy potential [8]; and (iv) potential of CO₂ storage and oil recovery for the CO₂-EOR operation in oil fields [10]. Nodes are connected to each other by different transportation modes (i.e., pipeline and truck). We consider electrolysis and biomass gasification with carbon capture and as the available technologies for hydrogen production.

Results and Implications

A sensitivity analysis was conducted by varying the sale price of hydrogen (between 1.0 and 5.0 USD/tonH₂) to evaluate its effect on the NPV of the project. As a result of this analysis, information was obtained on the equilibrium price of the project (i.e., the sale price of hydrogen that leads to a value of zero for the NPV). Additionally, the effect of including or not including EOR within the proposed supply chain was analyzed. It was found that CO₂-EOR is a strategy with an important potential for the use of CO₂ in Colombia due to its economic benefits and its capacity to promote the energy transition towards renewable energies. As future work, it is proposed to analyze the impact of public policies on the NPV and study the carbon footprint on the sale price of hydrogen.

References

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[2] O. J. Guerra, J. Eichman, J. Kurtz y B. M. Hodge, «Cost competitiveness of electrolytic hydrogen,» Joule, vol. 3, nº 10, pp. 2425-2443, 2019.

[3] J. Eichman, O. J. Guerra y M. Koleva, «Economic Analysis of Integrated Solar Power, Hydrogen Production, and Electricity Markets (No. NREL/PR-5400-78040),» National Renewable Energy Lab.(NREL), 2020. [En línea]. Available: https://www.nrel.gov/docs/fy21osti/78040.pdf.

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[5] J. Nakayama, N. Kasai, T. Shibutani y A. Miyake, «Security risk analysis of a hydrogen fueling station with an on-site hydrogen production system involving methylcyclohexane,» International Journal of Hydrogen Energy, vol. 44, nº 17, pp. 9110-9119, 2019.

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[7] Minenergía, «Hoja de ruta del hidrógeno en Colombia,» 2021. [En línea]. Available: https://www.minenergia.gov.co/documents/10192/24309272/Hoja+Ruta+Hidroge....

[8] S. García Orrego, «Análisis espacial multicriterio para la ubicación de parques eólicos y granjas solares en Colombia,» Universidad Nacional de Colombia, 2021.

[9] UNAL y UPME, «Estimación del potencial de conversión a biogás de la biomasa en Colombia y su aprovechamiento,» UPME, 2018. [En línea]. Available: https://bdigital.upme.gov.co/jspui/bitstream/001/1317/1/Informe%20final.pdf.

[10] E. Yáñez, A. Ramírez, V. Núñez-López, E. Castillo y A. Faaij, «Exploring the potential of carbon capture and storage-enhanced oil recovery as a mitigation strategy in the Colombian oil industry,» International Journal of Greenhouse Gas Control, vol. 94, p. 102938, 2020.

[11] E. E. Yáñez Angarita, V. Núñez-López, A. Ramírez Ramírez, E. Castillo Monroy y A. Faaij, «Rapid screening and probabilistic estimation of the potential for CO2-EOR and associated geological CO2 storage in Colombian petroleum basins,» Petroleum Geoscience, vol. 28, nº 1, pp. petgeo2020-110, 2022.

[12] A. Almansoori y N. Shah, «Design and operation of a future hydrogen supply chain: multi-period model,» International journal of hydrogen energy, vol. 34, nº 19, pp. 7883-7897, 2009.

[13] M. Moreno-Benito, P. Agnolucci y L. G. Papageorgiou, «Towards a sustainable hydrogen economy: Optimisation-based framework for hydrogen infrastructure development,» Computers & Chemical Engineering, vol. 102, pp. 110-127, 2017.

[14] A. J. Calderón y N. J. Pekney, «Optimization of enhanced oil recovery operations in unconventional reservoirs,» Applied Energy, vol. 258, p. 114072, 2020.