# Refurbishment of Natural Gas Pipelines towards 100% Hydrogen—A Thermodynamic-Based Analysis

^{1}

^{2}

^{*}

## Abstract

**:**

_{2}is considered one of the most energy- and resource-efficient energy transportation methods. The question remains whether the transportation of 100% H

_{2}with reasonable adaptions of the infrastructure and comparable energy amounts to natural gas is possible. The well-known critical components for refurbishment, such as increased compressor power, reduced linepack as well as pipeline transport efficiencies, and their influencing factors were considered based on thermodynamic calculations with a step-by-step overview. A H

_{2}content of 20–30% results in comparable operation parameters to pure natural gas. In addition to transport in pipelines, decentralized H

_{2}production will also play an important role in addressing future demands.

## 1. Introduction

_{2}demand is supplied with green hydrogen (from renewables) or from fossil fuel plants equipped with carbon capture and utilization infrastructure (CCUS) [7].

_{2}(1-10%), CO

_{2}(0.1–2%), and other hydrocarbons, such as ethane (1.5–7%), propane (0.1–1.5%), butane (0.003–0.15%), and pentane (0.01–0.07%) [20]. Hydrogen has approx. one-third of the volumetric energy content compared to methane (Table 1). However, in order to keep the velocity intact over long distances, either more powerful compressors or a larger number of compressors are necessary.

_{2}and NG lead to different flow behaviors that have to be considered in order to establish the transportation of 100% H

_{2}in refurbished NG pipelines. This research paper considers the contributing factors and gives an overview of the technical challenges and the thermodynamic calculations, starting from pure NG and raising the share of H

_{2}up to 100%. As a result, technical potentials, and challenges are derived.

_{2}has raised increased attention, which has also resulted in a large number of publications. One of the major focus points is still the influence of hydrogen on the pipeline materials, such as embrittlement [24,25,26,27,28,29,30,31,32]. Several authors [24,27,28,32] provide a detailed overview of hydrogen embrittlement and its influence variables. Bouledroua et al. [29] showed that hydrogen embrittlement of steel pipelines in contact with the hydrogen environment, together with the transient gas flow, significantly increased transient pressure values, and also increased the probability of failure of a cracked pipeline. Li et al. [30] provided a detailed overview of hydrogen embrittlement-related problems with specific emphasis on hydrogen behaviors, hydrogen embrittlement and related characterizations, and mitigation strategies. Martin et al. [31] provided proof that X70 pipeline steel fracture toughness and fatigue behavior are within acceptable bounds for hydrogen service. Andrews et al. [25] investigated the influence parameters of fatigue crack growth acceleration and showed that the interaction of cyclic loads and hydrogen makes pipeline steel highly susceptible to cracking.

_{2}, its technical feasibility, effects, and mixing behavior have also been greatly investigated [33,34,35,36,37,38]. Melaina et al. [38] provided a detailed overview of the key issues of blending H

_{2}into NG-pipeline networks. Liu et al. [33] revealed the standing and flowing stratification of H

_{2}-CH

_{4}blended gas and verified their findings through experiments. Eams et al. [34] proved that bottom-side injection promotes mixing within the flow interior and reduces wall concentration at the lower surface compared to top-side injection. This helps reduce embrittlement effects based on local hydrogen concentrations. Ekhtiari et al. [35] revealed that H

_{2}concentrations of up to 15.8% occur by using multiple injection points and highlighted the importance of modeling both the gas as well as electricity systems when investigating any potential power-to-hydrogen installations. In a preliminary study, Pellegrini et al. [36] assess the green hydrogen blending potential in the natural gas network as a tool for policy makers, grid and network managers, and energy planners. Vaccariello et al. [37] investigated the blending of hydrogen into distribution gas networks, focusing on the steady-state fluid dynamic response of the grids and gas quality compliance issues at increasing hydrogen admixture levels. The results show that lower probabilities of violating fluid dynamics and quality restrictions are obtained when hydrogen injection occurs close to or in correspondence with the system city gate.

_{2}content, which led to increased compressor power, were calculated using MATLAB simulations. The lower energy buffer (linepack) with rising H

_{2}content was also evaluated. Furthermore, thermodynamic calculations of the isentropic and isothermal compression for radial and piston compressors, respectively, were carried out. In order to methodically identify the influence of the H

_{2}concentration, two scenarios were compared, namely, constant energy flow, and constant pressure drop. Finally, to compare the distribution options of pure hydrogen, the thermodynamic transport efficiencies of different transport technologies are compared.

## 2. Materials and Methods

#### 2.1. Pressure Loss Calculation

#### 2.2. Mixture Properties

- Density:

- Lower heating value:

- Specific heat capacity isobaric:

- Specific heat capacity isochoric:

#### 2.3. Scenario Building

- Scenario 1: constant energy flow $\dot{E}$ at different hydrogen contents, with 100% NG as the reference case: ${\dot{E}}_{\mathrm{NG}}={\dot{E}}_{\mathrm{H}2}=\mathrm{const}.$
- Scenario 2: constant pressure drop over 100 km at different hydrogen contents, with 100% NG as the reference case; $\Delta {p}_{\mathrm{NG}}$ $=\Delta {p}_{\mathrm{H}2}=\mathrm{const}.$

_{2}mixtures in scenario 2, no additional compressor stations are required compared to the 100% NG reference case. However, with increased H

_{2}content, a decrease in transportable energy is expected in this scenario.

#### 2.3.1. Scenario 1-Constant Energy Flow $\dot{E}$

#### 2.3.2. Scenario 2: Constant Pressure Drop Δp

_{2}/CH

_{4}ratios. With the reference pressure drop, the flow velocity can be calculated by transforming the Darcy–Weisbach equation (Equation (1)). Since the friction factor $\lambda $ is also a function of the flow velocity, the calculation is performed iteratively by guessing an initial flow velocity. The iterative process is similar to that presented in Scenario 1, with the flow velocity being iterated instead of the outlet pressure.

#### 2.4. Compressor Power and Energy Buffer

#### 2.5. Boundary Conditions of the Reference Case

## 3. Results and Discussion

_{2}at 8 m/s and 70 bar operating pressure are assumed in the depictions below.

#### 3.1. Validation of the Analytical Approach with CFD Simulation Models

_{4}, 50% CH

_{4}50% H

_{2}, and 100% H

_{2}. From Equation (15), the required mass flows of the mixtures, to satisfy the constant energy flow condition, can be calculated. These mass flows are prescribed at the outlet boundary condition of the respective case. The relevant model settings and boundary conditions of the 2D CFD validation cases are summarized in Table 3 and Table 4, respectively. The cell size was gradually reduced to ensure mesh independence from the results.

_{4}and 100% H

_{2,}respectively, the difference between Fluent and MATLAB is below 100 Pa, showing excellent agreement. By linearly extrapolating this difference over 500 m to 100 km, the error is below 20 kPa. The relative error in both cases is below 1%. A slightly higher discrepancy between the pressure drops of the models was obtained for Case 2, where a 50% CH

_{4}50% H

_{2}mixture was calculated. The difference for the 500-m segment is 508 Pa with a relative error of approx. 4.6%. After extrapolation to 100 km, where the pressure drop is between 30 and 40 bar depending on the mixture composition, this results in a discrepancy between the models of 1–1.5 bar. Although the discrepancy is bigger compared to the other two cases, the impact on the results presented in this work is still negligible. Therefore, it can be concluded that the MATLAB pressure drop model and its accuracy are sufficient for the calculations presented in this work.

#### 3.2. Energy Transported Ė

_{2}blend in refurbished pipelines is a particularly relevant parameter. In order to establish comparability between NG and H

_{2}energy transport, as an input constraint, the driving pressure gradient Δp

_{H2}= Δp

_{NG}= 18.2 bar is the same for both (reference case condition).

_{2}volume fraction in NG. The course of the chart shows that the transportable energy has a minimum at approximately 90% H

_{2}volume fraction. Ė of a pure H

_{2}pipeline is 83% compared to the maximum transport capacity of NG.

_{2}. The function of the flow velocity (Figure 4c, Δp = const.) in terms of the H

_{2}volume fraction is non-linear. Higher H

_{2}content leads to disproportionately higher velocities. Up to approx. 90% of the H

_{2}volume fraction, the increasing velocity cannot compensate for the decreasing values of $LHV$ and ρ (the first total derivative of Equation (14) with respect to the H

_{2}volume fraction is negative). At volume fractions above 90%, the high positive velocity gradient leads to an increase in Ė.

_{H2}= Δp

_{NG}and therefore the same constraints for calculation of Ė above (Figure 4a). As it can be seen, the flow velocity and correspondingly the volume flow (Figure 4c) increase, which thus compensates for the decreasing volumetric heating value of H

_{2}. The calculated flow velocity is maximum at 100% hydrogen fraction (25 m/s), and the value is approximately three times higher than the flow velocity of pure NG. In order to keep the energy transport at a constant level, the flow velocity has to rise even more (Scenario 1: Ė

_{H2}= Ė

_{NG}= const. in Figure 4c). In order to transport an equal amount of energy Ė with pure hydrogen compared to 100% NG, the flow velocity has to reach a ratio of 36 m/s and, thus, almost quadruple. The increase in flow velocity implies two problems that need to be investigated for practical application but are beyond the scope of this work: erosive effects on the pipe material, as well as oscillation and corresponding noise emissions. Both contribute to fatigue and a reduced lifespan.

_{H2}= Ė

_{NG}= const.) can also be used to derive the pressure drop over the transport distance as a function of the H

_{2}fraction (Figure 5).

_{2}has to be compressed after approx. 100 km. Currently used radial compressors tolerate an H

_{2}share of up to 40% [49]. In order to be able to transport the same amount of energy, compression must take place after approximately 150 km at a 40% H

_{2}share. Current guidelines of the ÖVGW in Austria and the DVGW in Germany allow a H

_{2}share of 10% [50]. In this case, the pressure level would drop from the current 35 bar to approximately 32 bar upon arrival at the compressor station. This calculated pressure difference can be classified as unproblematic.

#### 3.3. Compressor Power

_{2}fraction leads to an increase in compressor power (Figure 6). Analyzing the thermodynamic equivalent process, both compressor working principles (piston and radial compressor) are nearly equal in energy consumption. In order to apply an equal pressure drop (Figure 6, Δp = const.), the compressor power consumption increases up to 240%. To ensure constant energy flow (Figure 6, Ė = const.), the compressor capacity increases to 720–780% at 100% H

_{2}.

_{2}with high efficiency. At the same time, however, they reach limits in terms of volume flow. By raising the number of cylinders, increasing the drive power and arranging several compressors in parallel, piston compressors can be operated economically up to a volume flow of approx. 750,000 m

^{3}/h [51]. For higher volume flows, radial compressors are used. The higher flow rate of H

_{2}results in a higher impeller speed c. Specifically, the speed increases with the ratio of the flow velocities under the square root (Equation (24)). For both scenarios, this means an increase in c by a factor of 1.7–2.

_{2}is available on the market. One reason for this is that there are no suitable test environments for extensive investigation of oscillation behavior and lifespan. In general, it is expected that in the near future a radial compressor will be developed that meets the requirements of 100% H

_{2}[52].

#### 3.4. Energy Buffer

_{2}fraction.

_{2}volume fraction. The reason for this is the lower volumetric heating value of hydrogen, which is approximately three times lower (see Table 1). Correspondingly, at 70 bar the stored energy with 100% H

_{2}is approximately 70% less compared to that with pure NG. Increasing the pressure to 100 bar would increase the buffered energy to approximately 35%. Storage options with higher pressure levels off-grid thus become more important.

#### 3.5. Pipeline Transport Efficiency ${\eta}_{T}$

_{H2}= Ė

_{NG}= const.). Analogous to the transport of NG, it is also assumed that recompression to the operating pressure takes place after a pressure loss of 50%. The results are depicted in Figure 8. The required recompressions are marked with asterisks.

_{2}.

#### 3.6. Influences on Transport Efficiency ${\eta}_{T}$

_{H2}= Ė

_{NG}= const.) and the reference case parameters are assumed as framework and boundary conditions. The analyzed parameters were varied in order to quantify their influence on the transport efficiency.

#### 3.6.1. Wall Roughness k

_{2}volume share. This can be clearly derived from the increasing difference between the curves for 100% H

_{2}compared to 0% H

_{2}(marked violet in Figure 9). After 3000 km of transport distance, the difference in transport efficiency at 0% H

_{2}share is 1–2 percentage points, while at 100% H

_{2}it is approximately 7 percentage points. For the transport of 100% H

_{2}, this means that a reduction of the wall roughness from 0.1 to 0.01 mm enables approximately 800 km longer transport with the same energy input (3000 km instead of 2200 km). This signifies that measures to reduce wall roughness prior to conversion to 100% H

_{2}will contribute significantly to reducing the required compressor power and thus enhance economic and energetic efficiency.

#### 3.6.2. Operating Pressure MOP

_{2}share. Higher operating pressure leads to an increase in compressor power due to a less favorable compression ratio and, in absolute numbers, higher compression work. This can also directly be derived from Equation (20). The compressor inlet pressure ${p}_{1}$ (= pipeline pressure after the pressure drop) linearly increases the compressor power $P$. However, fewer compressor stations are required, as a larger distance can be covered with a relatively constant pressure loss of 50%. Therefore, although the compressor power per station increases, the decrease in the nr. of stations leads to an overall increase in the transport efficiency over long distances.

#### 3.6.3. Pipeline Diameter

_{2}-ready is to use liners to combine both H

_{2}-compatible materials and reduced wall roughness [53]. The diameter can also be changed during this process. A significant reduction in diameter can also be intentionally caused in order to adapt the transport volume to the production capacities. Therefore, the influence of the diameter on the transport efficiency is examined in Figure 11.

#### 3.6.4. Distance between Compressor Stations for Hydrogen Pipeline Transport

_{2}share of up to 20% can be implemented without any restrictions and the same amount of energy can be transported as with pure NG. This statement also corresponds to the above findings regarding transport efficiency and transportable energy amount. With slight adjustments to the operating conditions, an increase to 40% is also possible by using existing infrastructure and recompression distances. Furthermore, it can be seen that a reduction in friction from k = 0.1 to k = 0.01 mm leads to a significant decrease in number of recompressions from 60 to 43 for the 100% H

_{2}case. Additionally, it can be derived that the increase in diameter as well as pressure level results in a reduction in the number of required compressor stations.

#### 3.7. H_{2} transport Efficiencies of Different Distribution Technologies

_{2}-NG mixtures. In this sub-chapter, the efficiency of different transport technologies for the distribution of pure H

_{2}are compared. In [54] the transport efficiencies of different distribution options are initially compared and discussed. These considerations shall now be expanded with the findings from this work. The following means of on-land transportation will be considered: GH2 200 bar trailer (${m}_{\mathrm{H}2,\mathrm{load}}$ = 300 kg H

_{2}loading capacity), GH2 500 bar trailer (${m}_{\mathrm{H}2,\mathrm{load}}$ = 1100 kg H

_{2}), liquid hydrogen trailer (${m}_{\mathrm{H}2,\mathrm{load}}$= 3500 kg H

_{2}) and pipeline transport. For the pipeline transport efficiency, the curve according to Figure 8 at 100% H

_{2}is selected. The transport efficiency as a function of the distance $x$ for the transport by trailer can be calculated as follows:

_{0}represents the initial required compression work at different pressure levels or the liquefaction energy for the gaseous and liquid storage respectively. For the initial compression work, isothermal compression from 1 bar to the pressure level for transport (200, 500 bar) with a piston compressor (according to Equation (22)) is assumed. Energy demand for liquefaction of 1 kg H

_{2}is usually cited in literature at approx. 30% of its gravimetric energy density (LHV) and thus amounts to 36 MJ/kg [6].

_{2}transport, however, it must be assumed that the trailer has to travel the same distance back empty, as an alternative freight cannot be transported for technical reasons. This means that the fuel demand effectively doubles and is therefore 60 litres per 100 km of distance between hydrogen source and hydrogen consumer, resulting in approx. E

_{Transport}= 25.56 MJ/km. For the purposes of this analysis, the fuel consumption is assumed constant and independent of the loading state or routing. The results are plotted in Figure 13.

_{2}-emissions if powered by fossil fuels. Nevertheless, the diagram allows a basic assessment of the efficiencies that can be achieved:

- Pipeline transport is the most energy-efficient method of transporting H
_{2}on land in large quantities and over long distances. - GH2 efficiency increases significantly with the pressure level. The losses for the initial compression are marginal compared to the transport losses.
- LH2 liquefaction efforts are amortized after approx. 2200 km of trailer transport.

## 4. Conclusions and Outlook

_{2}. However, mixtures with higher hydrogen content require additional compressor stations at shorter distance intervals as well as increased compressor power per station. For pure hydrogen, the compressor power per station is greater by a factor of 2–3 compared to the reference case for the same compression ratio, while the required distance between compressor stations decreases by 33%. This leads to a significant decrease in transport efficiency of up to 37%, over long distances up to 6000 km. However, for lower hydrogen contents up to 30%, the decrease in transport efficiency is below 7%, while the compressor power is greater by a manageable factor of ~1.5.

_{2}decreases by 70% relative to the reference case. Even if the pressure is increased up to 100 bar, the storage capacity with 100% H

_{2}is below 40% relative to the reference case. This leads to the need for off-grid storage options in order to be able to compensate for failures or fluctuations.

_{2}pipeline will continue at HyCentA. Currently, H

_{2}quality is being intensively analyzed. When transporting H

_{2}in the repurposed NG grid, achievable H

_{2}quality plays a crucial role. Depending on the consumer, high demands can be placed on purity. This is contrasted with the history and use of NG pipelines. Experience shows that various groups of substances, e.g., from odorization to adsorption processes on the pipeline wall and deposition at low points, can still be detected many years after entry into this pipeline has ended. When transporting H

_{2}, these contaminants will desorb from the pipe walls and enter the gas. These contamination levels and achievable H

_{2}quality are currently being analyzed at the HyCentA. Furthermore, the H

_{2}-compatibilities of individual components of the NG infrastructure, such as valves and seals, are characterized. In the course of this project, in Austria, the first NG pipeline will also be repurposed for the transport of H

_{2}.

## Author Contributions

## Funding

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

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**Figure 4.**(

**a**) Transported energy, (

**b**) lower heating value, (

**c**) flow velocity, and (

**d**) density as a function of H

_{2}volume fraction in NG.

**Figure 5.**(

**a**) Pressure drop in pipeline as a function of distance for the transport of the equal amount of energy (Scenario 1) and (

**b**) pressure drop after 100 km for Scenarios 1 and 2.

**Figure 6.**Compressor power of the thermodynamic equivalent processes of piston and radial compressor.

Characteristic | H_{2} | CH_{4} |
---|---|---|

Molar mass [kg/kmol] | 2.016 | 16.04 |

Gravimetric energy density [MJ/kg]/[kWh/kg] | 119.93/33.314 | 55.598/15.444 |

Upper volumetric heating value [MJ/Nm^{3}]/[kWh/Nm^{3}] | 12.744/3.540 | 39.830/11.064 |

Lower volumetric heating value [MJ/Nm^{3}]/[kWh/Nm^{3}] | 10.782/2.995 | 35.896/9.971 |

Density [kg/Nm³] | 0.0898 | 0.7175 |

Specific gravity [-] | 0.0696 | 0.5537 |

Density at 70 bar, 10 °C [kg/m^{3}] | 5.7459 | 55.353 |

Upper Wobbe index [MJ/Nm^{3} | 48.34 | 53.45 |

Lower Wobbe index [MJ/Nm^{3}] | 40.90 | 48.17 |

Specific heat capacity [kJ/(kg·K)] | 14.198 | 2.1810 |

Kinematic viscosity [cm^{2}/s] | 0.9342 | 0.1429 |

Specifications and Assumptions | |
---|---|

Line type | Gas transport line |

Natural gas composition | 100% CH_{4} |

Transported energy amount | 14,856,000 kWh/h |

Inner diameter | DN 1000 |

Maximum operating pressure | MOP 70 |

Material | L450MB |

Line length | 100 km |

Average gas temperature | 283 K |

Initial pressure | 70 bar |

Average gas flow velocity at 100% NG | 8 m/s |

Average wall roughness k | 0.1 mm |

Model Settings | |
---|---|

Energy equation | on |

Turbulence model | Realizable- k-ε |

Wall model | Enhanced wall treatment |

Real gas model | Redlich-Kwong |

Species transport | CH_{4} and H_{2} |

Case 1 | Case 2 | Case 3 | |
---|---|---|---|

Gas composition | 100% CH_{4} | 50% CH_{4} 50% H_{2} | 100% H_{2} |

Temperature [K] | 283 | ||

Inlet pressure [bar] | 70 | ||

Outlet massflow [kg/s] | 297.12 | 256.88 | 123.80 |

Wall flux [W/m^{2}] | 0 | ||

Wall roughness [mm] | 0.1 |

Δp Fluent [Pa] | Δp Matlab [Pa] | Relative Error [%] | |
---|---|---|---|

Case 1: 100% CH_{4} | 7849 | 7800 | 0.6243 |

Case 2: 50% CH_{4} 50% H_{2} | 11008 | 10500 | 4.6148 |

Case 3: 100% H_{2} | 13194 | 13100 | 0.7124 |

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**MDPI and ACS Style**

Klopčič, N.; Stöhr, T.; Grimmer, I.; Sartory, M.; Trattner, A.
Refurbishment of Natural Gas Pipelines towards 100% Hydrogen—A Thermodynamic-Based Analysis. *Energies* **2022**, *15*, 9370.
https://doi.org/10.3390/en15249370

**AMA Style**

Klopčič N, Stöhr T, Grimmer I, Sartory M, Trattner A.
Refurbishment of Natural Gas Pipelines towards 100% Hydrogen—A Thermodynamic-Based Analysis. *Energies*. 2022; 15(24):9370.
https://doi.org/10.3390/en15249370

**Chicago/Turabian Style**

Klopčič, Nejc, Thomas Stöhr, Ilena Grimmer, Markus Sartory, and Alexander Trattner.
2022. "Refurbishment of Natural Gas Pipelines towards 100% Hydrogen—A Thermodynamic-Based Analysis" *Energies* 15, no. 24: 9370.
https://doi.org/10.3390/en15249370