Ireland

Hydrogen was doped in austenitic stainless steel (ASS) 316L tensile samples produced by the laser-powder bed fusion (L-PBF) technique. For this aim an electrochemical method was conducted under a high current density of 100 mA/cm2 for three days to examine its sustainability under extreme hydrogen environments at ambient temperatures. The chemical composition of the starting powders contained a high amount of Ni approximately 12.9 wt.% as a strong austenite stabilizer. The tensile tests disclosed that hydrogen charging caused a minor reduction in the elongation to failure (approximately 3.5% on average) and ultimate tensile strength (UTS; approximately 2.1% on average) of the samples using a low strain rate of 1.2 × 10⁻⁴ s⁻¹. It was also found that an increase in the strain rate from 1.2 × 10⁻⁴ s⁻¹ o 4.8 ×10⁻⁴ s⁻¹ led to a reduction of approximately 3.6% on average for the elongation to failure and 1.7% on average for UTS in the pre-charged samples. No trace of martensite was detected in the X-ray diffraction (XRD) analysis of the fractured samples thanks to the high Ni content which caused a minor reduction in UTS × uniform elongation (UE) (GPa%) after the H charging. Considerable surface tearing was observed for the pre-charged sample after the tensile deformation. Additionally some cracks were observed to be independent of the melt pool boundaries indicating that such boundaries cannot necessarily act as a suitable area for the crack propagation.

Future low-carbon systems with very high shares of variable renewable generation require complex models to optimise investments and operations which must capture high degrees of sector coupling contain high levels of operational and temporal detail and when considering seasonal storage be able to optimise both investments and operations over long durations. Standard energy system models often do not adequately address all these issues which are of great importance when considering investments in emerging energy carriers such as Hydrogen. An advanced energy system model of the Irish power system is built in SpineOpt which considers a number of future scenarios and explores different pathways to the wide-scale adoption of Hydrogen as a low-carbon energy carrier. The model contains a high degree of both temporal and operational detail sector coupling via Hydrogen is captured and the optimisation of both investments in and operation of large-scale underground Hydrogen storage is demonstrated. The results highlight the importance of model detail and demonstrate how over-investment in renewables occur when the flexibility needs of the system are not adequately captured. The case study shows that in 2030 investments in Hydrogen technologies are limited to scenarios with high fuel and carbon costs high levels of Hydrogen demand (in this case driven by heating demand facilitated by large Hydrogen networks) or when a breakthrough in electrolyser capital costs and efficiencies occurs. However high levels of investments in Hydrogen technologies occur by 2040 across all considered scenarios. As with the 2030 results the highest level of investments occur when demand for Hydrogen is high albeit at a significantly higher level than 2030 with increases in investments of large-scale electrolysers of 538%. Hydrogen fuelled compressed air energy storage emerges as a strong investment candidate across all scenarios facilitating cost effective power-to-Hydrogen-to-power conversions.

As the offshore energy landscape transitions to renewable energy useful decommissioned or abandoned oil and gas infrastructure can be repurposed in the context of the circular economy. Oil and gas platforms for example offer opportunity for hydrogen (H2) production by desalination and electrolysis of sea water using offshore wind power. However as H2 storage and transport may prove challenging this study proposes to react this H2 with the carbon dioxide (CO2) stored in depleted reservoirs. Thus producing a more transportable energy carriers like methane or methanol in the reservoir. This paper presents a novel thermodynamic analysis of the Goldeneye reservoir in the North Sea in Aspen Plus. For Goldeneye which can store 30 Mt of CO2 at full capacity if connected to a 4.45 GW wind farm it has the potential to produce 2.10 Mt of methane annually and abate 4.51 Mt of CO2 from wind energy in the grid.

The high environmental impacts of transport mean that there is an increasing interest in utilising low-carbon alternative energy carriers and powertrains within the sector. While electricity has been mooted as the energy carrier of choice for passenger vehicles as the mass and range of the vehicle increases electrification becomes more difficult. This paper reviews the shipping aviation and haulage sectors and a range of low-carbon energy carriers (electricity biofuels hydrogen and electro fuels) that can be used to decarbonise them. Energy carriers were assessed based on their energy density specific energy cost lifecycle greenhouse gas emissions and land-use. In terms of haulage current battery electric vehicles may be technically feasible however the specific energy of current battery technology reduces the payload capacity and range when compared to diesel. To alleviate these issues biomethane represents a mature technology with potential co-benefits while hydrogen is close to competitiveness but requires significant infrastructure. Energy density issues preclude the use of batteries in shipping which requires energy dense liquids or compressed gaseous fuels that allow for retrofits/current hull designs with methanol being particularly appropriate here. Future shipping may be achieved with ammonia or hydrogen but hull design will need to be changed significantly. Regulations and aircraft design mean that commercial aviation is dependant on drop-in jet fuels for the foreseeable future with power-to-liquid fuels being deemed the most suitable option due to the scales required. Fuel costs and a lack of refuelling infrastructure were identified as key barriers facing the uptake of alternatives with policy and financial incentives required to encourage the uptake of low-carbon fuels.

The need to reduce the climate impact of the transport sector has led to an increasing interest in the utilisation of alternative fuels. Producing advanced fuels through the integration of anaerobic digestion and power-to-fuel technologies may offer a solution to reduce greenhouse gas emissions from difficult to decarbonise modes of transport such as heavy goods vehicles shipping and commercial aviation while also offering wider system benefits. This paper investigates the energy balance of power-to-fuel (power-to-methane power-to-methanol power-to-Fischer-Tropsch fuels) production integrated with a biogas facility co-digesting grass silage and dairy slurry. Through the integration of power-to-methane with anaerobic digestion an increase in system gross energy of 62.6% was found. Power-to-methanol integration with the biogas system increased the gross energy by 50% while power-to-Fischer-Tropsch fuels increased the gross energy yield by 32%. The parasitic energy demand for hydrogen production was highlighted as the most significant factor for integrated biogas and power-to-fuel facilities. Consuming electricity that would otherwise have been curtailed and optimising the anaerobic digestion process were identified as key to improving the energetic efficiency of all system configurations. However the broad cross-sectoral benefits of the overarching cascading circular economy system such as providing electrical grid stability and utilising waste resources must also be considered for a comprehensive perspective on the integration of anaerobic digestion and power-to-fuel.

Green hydrogen i.e. the hydrogen generated from renewable energy sources (RES) will significantly contribute to a successful energy transition. Besides to facilitate the integration and storage of RES this promising energy carrier is well capable to efficiently link various energy sectors. By introduction of green hydrogen as a new flexibility source to power systems it is necessary to investigate its possible impacts on the generation scheduling and power system security. In this paper a security-constrained multi-period optimal power flow (SC-MPOPF) model is developed aiming to determine the optimal hourly dispatch of generators as well as power to hydrogen (P2H) units in the presence of large-scale renewable energy sources (RES). The proposed model characterizes the P2H demand flexibility in the proposed SC-MPOPF model taking into account the electrolyzer behavior reactive power support of P2H demands and hydrogen storage capability. The developed SC-MPOPF model is applied to IEEE 39-bus system and the obtained numerical results demonstrate the role of P2H flexibility on cost as well as RES's power curtailment reduction.

The rise in intermittent renewable electricity production presents a global requirement for energy storage. Biological hydrogen methanation (BHM) facilitates wind and solar energy through the storage of otherwise curtailed or constrained electricity in the form of the gaseous energy vector biomethane. Biological methanation in the circular economy involves the reaction of hydrogen – produced during electrolysis – with carbon dioxide in biogas to produce methane (4H2 + CO2 = CH4 + 2H2) typically increasing the methane output of the biogas system by 70%. In this paper several BHM systems were researched and a compilation of such systems was synthesized facilitating comparison of key parameters such as methane evolution rate (MER) and retention time. Increased retention times were suggested to be related to less efficient systems with long travel paths for gases through reactors. A significant lack of information on gas-liquid transfer co-efficient was identified

This paper presents the results of techno-economic modelling for hydrogen production from a photovoltaic battery electrolyser system (PBES) for injection into a natural gas transmission line. Mellitah in Libya connected to Gela in Italy by the Greenstream subsea gas transmission line is selected as the location for a case study. The PBES includes photovoltaic (PV) arrays battery electrolyser hydrogen compressor and large-scale hydrogen storage to maintain constant hydrogen volume fraction in the pipeline. Two PBES configurations with different large-scale storage methods are evaluated: PBESC with compressed hydrogen stored in buried pipes and PBESL with liquefied hydrogen stored in spherical tanks. Simulated hourly PV electricity generation is used to calculate the specific hourly capacity factor of a hypothetical PV array in Mellitah. This capacity factor is then used with different PV sizes for sizing the PBES. The levelised cost of delivered hydrogen (LCOHD) is used as the key techno-economic parameter to optimise the size of the PBES by equipment sizing. The costs of all equipment except the PV array and batteries are made to be a function of electrolyser size. The equipment sizes are deemed optimal if PBES meets hydrogen demand at the minimum LCOHD. The techno-economic performance of the PBES is evaluated for four scenarios of fixed and constant hydrogen volume fraction targets in the pipeline: 5% 10% 15% and 20%. The PBES can produce up to 106 kilotonnes of hydrogen per year to meet the 20% target at an LCOHD of 3.69 €/kg for compressed hydrogen storage (PBESC) and 2.81 €/kg for liquid hydrogen storage (PBESL). Storing liquid hydrogen at large-scale is significantly cheaper than gaseous hydrogen even with the inclusion of a significantly larger PV array that is required to supply additional electrcitiy for liquefaction.

Accommodating renewables on the electricity grid may hinder development opportunities for offshore wind farms (OWFs) as they begin to experience significant curtailment or constraint. However there is potential to combine investment in OWFs with Power-to-Gas (PtG) converting electricity to hydrogen via electrolysis for an alternative/complementary revenue. Using historic wind speed and simulated system marginal costs data this work models the electricity generated and potential revenues of a 504 MW OWF. Three configurations are analysed; (1) all electricity is sold to the grid (2) all electricity is converted to hydrogen and sold and (3) a hybrid system where power is converted to hydrogen when curtailment occurs and/or when the system marginal cost is low with the effect of curtailment analysed in each scenario. These represent the status quo a potential future configuration and an innovative business model respectively. The willingness of an investor to build PtG are determined by changes to the net present value (NPV) of a project. Results suggest that configuration (1) is most profitable and that curtailment mitigation alone is not sufficient to secure investment in PtG. By acting as an artificial floor in the electricity price a hybrid configuration (3) is promising and increases NPV for all hydrogen values greater than €4.2/kgH2. Hybrid system attractiveness increases with curtailment only if the hydrogen value is significantly above the levelised cost of €3.77/kgH2. In order for an investor to choose to pursue configuration (2) the offshore wind farm would have to anticipate 8.5% curtailment and be able to receive €4.5/kgH2 or 25% curtailment and receive €4/kgH2. The capital costs and discount rates are the most sensitive parameters and ambitious combinations of technology improvements could produce a levelised cost of €3/kgH2.

Development of probabilistic modelling tools to perform Bayesian inference and uncertainty quantification (UQ) is a challenging task for practical hydrogen-enriched and low-emission combustion systems due to the need to take into account simultaneously simulated fluid dynamics and detailed combustion chemistry. A large number of evaluations is required to calibrate models and estimate parameters using experimental data within the framework of Bayesian inference. This task is computationally prohibitive in high-fidelity and deterministic approaches such as large eddy simulation (LES) to design and optimize combustion systems. Therefore there is a need to develop methods that: (a) are suitable for Bayesian inference studies and (b) characterize a range of solutions based on the uncertainty of modelling parameters and input conditions. This paper aims to develop a computationally-efficient toolchain to address these issues for probabilistic modelling of NOx emission in hydrogen-enriched and lean-premixed combustion systems. A novel method is implemented into the toolchain using a chemical reactor network (CRN) model non-intrusive polynomial chaos expansion based on the point collocation method (NIPCE-PCM) and the Markov Chain Monte Carlo (MCMC) method. First a CRN model is generated for a combustion system burning hydrogen-enriched methane/air mixtures at high-pressure lean-premixed conditions to compute NOx emission. A set of metamodels is then developed using NIPCE-PCM as a computationally efficient alternative to the physics-based CRN model. These surrogate models and experimental data are then implemented in the MCMC method to perform a two-step Bayesian calibration to maximize the agreement between model predictions and measurements. The average standard deviations for the prediction of exit temperature and NOx emission are reduced by almost 90% using this method. The calibrated model then used with confidence for global sensitivity and reliability analysis studies which show that the volume of the main-flame zone is the most important parameter for NOx emission. The results show satisfactory performance for the developed toolchain to perform Bayesian inference and UQ studies enabling a robust and consistent process for designing and optimising low-emission combustion systems.