United States

With the clear adverse impacts of fossil fuel-based energy systems on the climate and environment ever-growing interest and rapid developments are taking place toward full or nearly full dependence on renewable energies in the next few decades. Estonia is a European country with large demands for electricity and thermal energy for district heating. Considering it as the case study this work explores the feasibility and full potential of optimally sized photovoltaic (PV) wind and PV/wind systems equipped with electric and thermal storage to fulfill those demands. Given the large excess energy from 100% renewable energy systems for an entire country this excess is utilized to first meet the district heating demand and then to produce hydrogen fuel. Using simplified models for PV and wind systems and considering polymer electrolyte membrane (PEM) electrolysis a genetic optimizer is employed for scanning Estonia for optimal installation sites of the three systems that maximize the fulfillment of the demand and the supply–demand matching while minimizing the cost of energy. The results demonstrate the feasibility of all systems fully covering the two demands while making a profit compared to selling the excess produced electricity directly. However the PV-driven system showed enormous required system capacity and amounts of excess energy with the limited solar resources in Estonia. The wind system showed relatively closer characteristics to the hybrid system but required a higher storage capacity by 75.77%. The hybrid PV/wind-driven system required a total capacity of 194 GW most of which belong to the wind system. It was also superior concerning the amount (15.05 × 109 tons) and cost (1.42 USD/kg) of the produced green hydrogen. With such full mapping of the installation capacities and techno-economic parameters of the three systems across the country this study can assist policymakers when planning different country-scale cogeneration systems.

A proton exchange membrane (PEM) electrolyzer is fed with water and powered by electric power to electrochemically produce hydrogen at low operating temperatures and emits oxygen as a by-product. Due to the complex nature of the performance of PEM electrolyzers the application of an artificial neural network (ANN) is capable of predicting its dynamic characteristics. A handful of studies have examined and explored ANN in the prediction of the transient characteristics of PEM electrolyzers. This research explores the estimation of the transient behavior of a PEM electrolyzer stack under various operational conditions. Input variables in this study include stack current oxygen pressure hydrogen pressure and stack temperature. ANN models using three differing learning algorithms and time delay structures estimated the hydrogen mass flow rate which had transient behavior from 0 to 1 kg/h and forecasted better with a higher count (>5) of hidden layer neurons. A coefficient of determination of 0.84 and a mean squared error of less than 0.005 were recorded. The best-fitting model to predict the dynamic behavior of the hydrogen mass flow rate was an ANN model using the Levenberg–Marquardt algorithm with 40 neurons that had a coefficient of determination of 0.90 and a mean squared error of 0.00337. In conclusion optimally fit models of hydrogen flow from PEM electrolyzers utilizing artificial neural networks were developed. Such models are useful in establishing an agile flow control system for the electrolyzer system to help decrease power consumption and increase efficiency in hydrogen generation.

A growing hydrogen economy requires new hydrogen distribution infrastructure to link geographically distributed hubs of supply and demand. The Hydrogen Optimization with Deployment of Infrastructure (HOwDI) Model helps meet this requirement. The model is a spatially resolved optimization framework that determines location-specific hydrogen production and distribution infrastructure to cost-optimally meet a specified location-based demand. While these results are useful in understanding hydrogen infrastructure development there is uncertainty in some costs that the model uses for inputs. Thus the project team took the modeling effort a step further and developed a Monte Carlo methodology to help manage uncertainties. Seven scenarios were run using existing infrastructure and new demand in Texas exploring different policy and tax approaches. The inclusion of tax credits increased the percentage of runs that could deliver hydrogen at <$4/kg from 31% to 77% and decreased the average dispensed cost from $4.35/kg to $3.55/kg. However even with tax credits there are still some runs where unabated SMR is deployed to meet new demand as the low-carbon production options are not competitive. Every scenario except for the zero-carbon scenario (without tax credits) resulted in at least 20% of the runs meeting the $4/kg dispensed fuel cost target. This indicates that multiple pathways exist to deliver $4/kg hydrogen.

The majority penetration of Variable Renewable Energy (VRE) will challenge the stability of electrical transmission grids due to unpredictable peaks and troughs of VRE generation. With renewable generation located further from high demand urban cores there will be a need to develop new transmission pathways to deliver the power. This paper compares the transport and storage of VRE through a hydrogen pipeline to the transport of VRE through a High Voltage Direct Current (HVDC) transmission line. The analysis found a hydrogen pipeline can offer a cost-competitive method for VRE transmission compared to a HVDC transmission line on a life-cycle cost basis normalized by energy flows for distances at 1000 miles with 2030 technology. This finding has implications for policy makers project developers and system operators for the future development of transmission infrastructure projects given the additionality which hydrogen pipelines can provide in terms of energy storage.

Hydrogen (H2) is widely viewed as critical to the decarbonization of industry and transportation. Water electrolysis powered by renewable electricity commonly referred to as green H2 can be used to generate H2 with low carbon dioxide emissions. Herein we analyze the critical mineral and energy demands associated with green H2 production under three different hypothetical future demand scenarios ranging from 100–1000 Mtpa H2. For each scenario we calculate the critical mineral demands required to build water electrolyzers (i.e. electrodes and electrolyte) and to build dedicated or additional renewable electricity sources (i.e. wind and solar) to power the electrolyzers. Our analysis shows that scaling electrolyzer and renewable energy technologies that use platinum group metals and rare earth elements will likely face supply constraints. Specifically larger quantities of lanthanum yttrium or iridium will be needed to increase electrolyzer capacity and even more neodymium silicon zinc molybdenum aluminum and copper will be needed to build dedicated renewable electricity sources. We find that scaling green H2 production to meet projected netzero targets will require ~24000 TWh of dedicated renewable energy generation which is roughly the total amount of solar and wind projected to be on the grid in 2050 according to some energy transition models. In summary critical mineral constraints may hinder the scaling of green H2 to meet global net-zero emissions targets motivating the need for the research and development of alternative lowemission methods of generating H2

Because of hydrogen's low energy density hydrogen storage is a critical component of the hydrogen economy particularly when large-scale and flexible hydrogen utilization is required. There is a sense of urgency to develop hydrogen geological storage projects to support large-scale yet flexible hydrogen utilization. This study aims to answer questions not yet resolved in the research literature discussing the valuation of hydrogen geological storage options for commercial development. This study establishes a net present value (NPV) evaluation framework for geological hydrogen storage that integrates the updated techno-economic analysis and market-based operations. The capital asset pricing model (CAPM) and the related finance theories are applied to determine the risk-adjusted discount rate in building the NPV evaluation framework. The NPV framework has been applied to two geological hydrogen storage projects a single-turn storage serving downstream transportation seasonal demand versus a multiturn storage as part of an integrated renewables-based hydrogen energy system providing peak electric load. From the NPV framework both projects have positive NPVs $46 560 632 and $12 457 546 respectively and International Rate of Return (IRR) values which are higher than the costs of capital. The NPV framework is also applied to the sensitivity analysis and shows that the hydrogen price spread between withdrawal and injection prices site development and well costs are the top three factors that impact both NPV and IRR the most for both projects. The established NPV framework can be used for project risk management by discovering the key cost drivers for the storage assets.

When driven by sunlight molten catalytic methane cracking can produce clean hydrogen fuel from natural gas without greenhouse emissions. To design solar methane crackers a canonical plug flow reactor model was developed that spanned industrially relevant temperatures and pressures (1150–1350 Kelvin and 2–200 atmospheres). This model was then validated against published methane cracking data and used to screen power tower and beam-down reactor designs based on “Solar Two” a renewables technology demonstrator from the 1990s. Overall catalytic molten methane cracking is likely feasible in commercial beam-down solar reactors but not power towers. The best beam-down reactor design was 9% efficient in the capture of sunlight as fungible hydrogen fuel which approaches photovoltaic efficiencies. Conversely the best discovered tower methane cracker was only 1.7% efficient. Thus a beam-down reactor is likely tractable for solar methane cracking whereas power tower configurations appear infeasible. However the best simulated commercial reactors were heat transfer limited not reaction limited. Efficiencies could be higher if heat bottlenecks are removed from solar methane cracker designs. This work sets benchmark conditions and performance for future solar reactor improvement via design innovation and multiphysics simulation.

Low-carbon hydrogen could be an important component of a net-zero carbon economy helping to mitigate emissions in a number of hard-to-abate sectors. The United States recently introduced an escalating production tax credit (PTC) to incentivize production of hydrogen meeting increasingly stringent embodied emissions thresholds. Hydrogen produced via electrolysis can qualify for the full subsidy under current federal accounting standards if the input electricity is generated by carbon-free resources but may fail to do so if emitting resources are present in the generation mix. While use of behind-the-meter carbon-free electricity inputs can guarantee compliance with this standard the PTC could also be structured to allow producers using grid-supplied electricity to qualify subject to certain clean energy procurement requirements. Herein we use electricity system capacity expansion modeling to quantitatively assess the impact of grid-connected electrolysis on the evolution of the power sector in the western United States through 2030 under multiple possible implementations of the clean hydrogen PTC. We find that subsidized grid-connected hydrogen production has the potential to induce additional emissions at effective rates worse than those of conventional fossil-based hydrogen production pathways. Emissions can be minimized by requiring grid-based hydrogen producers to match 100% of their electricity consumption on an hourly basis with physically deliverable ‘additional’ clean generation which ensures effective emissions rates equivalent to electrolysis exclusively supplied by behind-the-meter carbon-free generation. While these requirements cannot eliminate indirect emissions caused by competition for limited clean resources which we find to be a persistent result of large hydrogen production subsidies they consistently outperform alternative approaches relying on relaxed time matching or marginal emissions accounting. Added hydrogen production costs from enforcing an hourly matching requirement rather than no requirements are less than $1 kg−1 and can be near zero if clean firm electricity resources are available for procurement.

The declining cost of renewable power has engendered growing interest in leveraging this power for the production of chemicals and synthetic fuels. Here renewable power is added to the gas-to-liquid (GTL) process through Fischer–Tropsch (FT) synthesis in order to increase process efficiency and reduce CO2 emissions. Accordingly two realistic configurations are considered which differ primarily in the syngas preparation step. In the first configuration solid oxide steam electrolysis cells (SOEC) in combination with an autothermal reformer (ATR) are used to produce synthesis gas with the right composition while in the second configuration an electrically-heated steam methane reformer (E-SMR) is utilized for syngas production. The results support the idea of adding power to the GTL process mainly by increased process efficiencies and reduced process emissions. Assuming renewable power is available the process emissions would be 200 and 400 gCO2 L1 syncrude for the first and second configurations respectively. Configuration 1 and 2 show 8 and 4 times less emission per liter syncrude produced respectively compared to a GTL plant without H2 addition with a process emission of 1570 gCO2 L1 syncrude. By studying the two designs based on FT production carbon efficiency and FT catalyst volume a better alternative is to add renewable power to the SOEC (configuration 1) rather than using it in an E-SMR (configuration 2). Given an electricity price of $100/MW h and natural gas price of 5 $ per GJ FT syncrude and H2 can be produced at a cost between $15/MW h and $16/MW h. These designs are considered to better utilize the available carbon resources and thus expedite the transition to a low-carbon economy

Historically it has been a challenge to simulate the experimentally observed cellular structures and marginal behavior of multidimensional hydrogen-oxygen detonations in the presence of losses even with detailed chemistry models. Very recently a quasi-two-dimensional inviscid approach was pursued where losses due to viscous boundary layers were modeled by the inclusion of an equivalent mass divergence in the lateral direction using Fay’s source term formulation with Mirels’ compressible boundary layer solutions. The same approach was used for this study along with the inclusion of thermally perfect detailed chemistry in order to capture the correct ignition sensitivity of the gas to dynamic changes in the thermodynamic state behind the detonation front. In addition the strength of transverse waves and their impact on the detonation front was investigated. Here the detailed San Diego mechanism was applied and it has been found that the detonation cell sizes can be accurately predicted without the need to prescribe specific parameters for the combustion model. For marginal cases where the detonation waves approach their failure limit quasi-stable mode behavior was observed where the number of transverse waves monotonically decreased to a single strong wave over a long enough distance. The strong transverse waves were also found to be slightly weaker than the detonation front indicating that they are not overdriven in agreement with recent studies.