Netherlands

Retrofitting regional turboprop aircraft with hydrogen (H2)-electric powertrains using fuel cell systems (FCSs) has gained interest in the last decade. This type of powertrain eliminates CO2 NOx and fine particle emissions during flight as FCSs only emit water. In this context the “Hydrogen Aircraft Powertrain and Storage Systems” (HAPSS) project targets the development of a H2-electric propulsion system for retrofitting Dash 8- 300 series aircraft. The purpose of the study described in this paper is to analyze the performance of the retrofitted H2-electric aircraft during critical operating conditions. Takeoff as well as climb cruise and go-around performances are addressed. The NLR in-house tool MASS (Mission Aircraft and Systems Simulation) was used for the performance analyses. The results show that the retrofitted H2-electric aircraft has a slightly increased takeoff distance compared to the Dash 8-300 and it requires a maximum rated shaft power of 1.9 MW per propeller. A total rated FCS output power of 3.1 MW is sufficient to satisfy the takeoff requirements at the cost of lower cruise altitude and reduced cruise speed as compared to the Dash 8-300. Furthermore a higher-rated FCS is required to achieve the climb performance required for the typical climb profile of the Dash 8-300.

This paper evaluates the potential impacts of introducing low-carbon intensity hydrogen technologies in two oil refineries with different complexity levels emphasizing the role of hydrogen production in reducing CO2 emissions. The novelty of this work lies in three key aspects: Comprehensive system analysis of refinery complexity using real site data integration of low-carbon Hydrogen technologies long-term and short-term strategies. Two Colombian refineries serve as case studies with technological solutions adapted to their complexity levels. The methodology involves evaluating different options for hydrogen production accounting for improvement in technological efficiency over time.<br/>The refinery systems were evaluated in a cost-optimization model built in Linny-r. Three different scenarios were considered Business-As-Usual (BAU) high and low-ambitions decarbonization scenarios focusing on the time horizons of 2030 and 2050.<br/>When comparing the two case studies the preferred decarbonization strategy for both facilities involves the substitution of SMR technology with water electrolyzers powered by renewable electricity. Post-2030 biomass-based hydrogen technology is still a costly alternative; however to achieve CO2 neutrality negative emissions storage of biogenic CO2 emerges as an achievable alternative.<br/>Our results indicate the achievability of CO2 reduction objectives in both refineries. Our results show that achieving long-term CO2 neutrality requires both refineries to increase renewable electricity production by 5 to 6 times for powering water electrolyzers steam production by 2 to 2.5 times for CO2 capture and supply of dry biomass by 2.6 to 4.5 kt/d.<br/>The two most significant factors influencing the refining net margin in the decarbonization scenarios are primarily the CO2 and the renewable electricity prices. The short-term horizon emerges as the pivotal period particularly within the high-ambition decarbonization scenarios. In this context the medium complexity refinery demonstrates economic viability until a CO2 price of 140 €/t CO2 while the high complexity refinery endures up to 205 €/t CO2.<br/>The high complexity refinery is better prepared to face the challenges of decarbonization and the impacts generated on the refining margin. Compared to the BAU scenario the high complexity refinery shows a negative impact on the net margin that corresponds to a 40% and 5% reduction in the short and long term respectively. Meanwhile for the medium complexity refinery the impact on net margin amounts to a 52% reduction in the short term and a 27% improvement in the long term.<br/>Furthermore our research highlights the significant potential for reducing CO2 emissions by fully eliminating the use of refinery gas as fuel providing alternative applications for it beyond combustion.

Alkaline water electrolysis (AWE) is the most mature electrochemical technology for hydrogen production from renewable electricity. Thus its mathematical modeling is an important tool to provide new perspectives for the design and optimization of energy storage and decarbonization systems. However current models rely on numerous empirical parameters and neglect variations of temperature and concentration alongside the electrolysis cell which can impact the application and reliability of the simulation results. Thus this study proposes a simple four-parameter semi-empirical model for AWE system analysis which relies on minimal fitting data while providing reliable extrapolation results. In addition the effect of model dimensionality (i.e. 0D 1/2D and 1D) are carefully assessed in the optimization of an AWE system. The results indicate that the proposed model can accurately reproduce literature data from four previous works (R 2 ≥ 0.98) as well as new experimental data. In the system optimization the trade-offs existing in the lye cooling sizing highlight that maintaining a low temperature difference in AWE stacks (76-80°C) leads to higher efficiencies and lower hydrogen costs.

In recent years the intensification of human activities has led to an increase in waste production and energy demand. The treatment of pollutants contained in wastewater coupled to energy recovery is an attractive solution to simultaneously reduce environmental pollution and provide alternative energy sources. Hydrogen represents a clean energy carrier for the transition to a decarbonized society. Hydrogen can be generated by photosynthetic water splitting where oxygen and hydrogen are produced and the process is driven by the light energy absorbed by the photocatalyst. Alternatively hydrogen may be generated from hydrogenated pollutants in water through photocatalysis and the overall reaction is thermodynamically more favourable than water splitting for hydrogen. This review is focused on recent developments in research surrounding photocatalytic and photoelectrochemical hydrogen production from pollutants that may be found in wastewater. The fundamentals of photocatalysis and photoelectrochemical cells are discussed along with materials and efficiency determination. Then the review focuses on hydrogen production linked to the oxidation of compounds found in wastewater. Some research has investigated hydrogen production from wastewater mixtures such as olive mill wastewater juice production wastewater and waste activated sludge. This is an exciting area for research in photocatalysis and semiconductor photoelectrochemistry with real potential for scale up in niche applications.

Hydrogen has the potential to make countries energetically self-sufficient and independent in the long term. Nevertheless its extreme combustion properties and its capability of permeating and embrittling most metallic materials produce significant safety concerns. The Hydrogen Incidents and Accidents Database 2.0 (HIAD 2.0) is a public repository that collects data on hydrogen-related undesired events mainly occurred in chemical and process industry. This study conducts an analysis of the HIAD 2.0 database mining information systematically through a computer science approach known as Business Analytics. Moreover several hydrogen-induced ma terial failures are investigated to understand their root causes. As a result a deficiency in planning effective inspection and maintenance activities is highlighted as the common cause of the most severe accidents. The lessons learned from HIAD 2.0 could help to promote a safety culture to improve the abnormal and normal events management and to stimulate a widespread rollout of hydrogen technologies.

Hydrogen is gaining traction as a key energy carrier due to its clean combustion high energy content and versatility. As the world shifts towards sustainable energy hydrogen demand is rapidly increasing. This paper introduces a novel hybrid time series modeling approach designed and developed to accurately predict hydrogen demand by mixing linear and nonlinear models and accounting for the impact of non-recurring events and dynamic energy market changes over time. The model incorporates key economic variables like hydrogen price oil price natural gas price and gross domestic product (GDP) per capita. To address these challenges we propose a four-part framework comprising the Hodrick–Prescott (HP) filter the autoregressive fractionally integrated moving average (ARFIMA) model the enhanced empirical wavelet transform (EEWT) and high-order fuzzy cognitive maps (HFCM). The HP filter extracts recurring structural patterns around specific data points and resolves challenges in hybridizing linear and nonlinear models. The ARFIMA model equipped with statistical memory captures linear trends in the data. Meanwhile the EEWT handles non-stationary time series by adaptively decomposing data. HFCM integrates the outputs from these components with ridge regression fine-tuning the HFCM to handle complex time series dynamics. Validation using stochastic non-Gaussian synthetic data demonstrates that this model significantly enhances prediction performance. The methodology offers notable improvements in prediction accuracy and stability compared to existing models with implications for optimizing hydrogen production and storage systems. The proposed approach is also a valuable tool for policy formulation in renewable energy and smart energy transitions offering a robust solution for forecasting hydrogen demand

Hydrogen economy is spreading across the maritime sector in response to increasingly stringent regulations for shipping emissions. The challenging on-board hydrogen logistics are often mitigated with hydrogen carriers such as methanol. Research on methanol reforming to hydrogen for fuel cell feed is conducted mostly in steady state overlooking dynamic reactor operation and its effects on the power production system. Forced reactor operations induce fluctuations of CO content in the reformate potentially harmful to the PEM fuel cell and drops in methanol conversion causing inefficient operation. In present research simulations with a physical 2D unsteady model of a packed bed methanol steam reforming reactor resulted in methanol conversion drop durations of up to a minute. Additionally temporary increases of CO content up to 112% were observed. Throughput ramp ups most notably impact the conversion while ramp downs negatively affect selectivity. The investigation on reactor geometry concludes that larger tube diameters increase transient time and CO spikes while they decrease with reactor length. Amplified unsteady effects are also observed with larger changes in input process variables. The results imply that heat transfer rate to the reactor are most often the detrimental factor for transient effects and durations in practice. Following this work inclusion of realistic heating methods is recommended instead of uniform tube temperatures used in present simulations. Heating system characteristics are necessary for realistic evaluation of the methanol reformer constraint on fuel cell feed demand in fully integrated systems.

Hydrogen valleys are envisaged (imagined) integrated industrial systems where hydrogen is produced stored and utilized. Here we show how hydrogen valleys as sociotechnical imaginaries are differentiated in terms of their specific configurations but homogenous in terms of reflecting the interests of large industrial fossil fuel suppliers and consumers. This path dependence is anticipated in sociotechnical transitions theory which emphasises the power of incumbents with vested interests to maintain basic templates or regimes of production and consumption. The simultaneously heterogeneous and homogenous nature of hydrogen valley imaginaries can be thought of as a form of glocalisation for which we draw on Roudometof's theory of glocalisation as involving the local refraction of diffusing global tendencies. To illustrate this we compare two hydrogen valleys one in the north of the Netherlands and one in southern Spain. In the north Netherlands the hydrogen valley imaginary comprises use of offshore windpower to electrolyse hydrogen for transport fuel and as feedstock to heavy industry in proximate regions including northern Germany and Belgium. This is consistent with existing gas distribution networks connecting industrial consumers. In the southern Spanish case the imaginary positions Spain as a major exporter of green hydrogen to the rest of Europe via onshore renewable electrolysis with export including via ocean tankers and chemical refining in existing infrastructure in Rotterdam. Overall the study explores empirically theoretically-informed themes concerning the interrelationship of mutually supportive local and global imaginaries – hence our term glocalised imaginaries.

Liquid hydrogen has the potential to significantly reduce in-flight carbon emissions in the aviation industry. Among the most promising aircraft configurations for future hydrogen-powered aviation are the blended wing body and the pure flying wing configurations. However their tapered and flattened airframe designs pose a challenge in accommodating liquid hydrogen storage tanks. This paper presents a design guide to tapered conformable pressure tanks for liquid hydrogen storage. The proposed tank configurations feature a multi-bubble layout and are subject to low internal differential pressure. The objective is to provide tank designers with simple geometric rules and practical guidelines to simplify the design process of tapered multi-bubble pressure tanks. Various tank configurations are discussed starting with a simple tapered two-bubble tank and advancing to more complex tapered configurations with a multi-segment and multi-bubble layout. A comprehensive design methodology is established providing tank designers with a step-by-step design procedure and highlighting the practical guidelines in each step of the design process.

The global energy transition necessitates the development of technologies enabling cost-effective and scalable conversion of renewable energies into storable and transportable forms. Green ammonia with its high hydrogen storage capacity emerges as a promising carbon-free hydrogen carrier. This article reviews recent progress in industrially relevant catalysts and technologies for ammonia cracking which is a pivotal step in utilizing ammonia as a hydrogen storage material. Catalysts based on Ru Ni Fe Co and Fe–Co are evaluated with Cobased catalysts showing exceptional potential for ammonia cracking. Different reactor technologies and their applications are briefly discussed. This review concludes with perspectives on overcoming existing challenges emphasizing the need for catalyst development effective reactor design and sustainable implementation in the context of the energy transition.