Contributed by Ron Beck, Senior Director, Solutions Marketing, Aspen Technology Inc, Bedford MA
The level of investment in hydrogen projects shows that the world’s financial community is voting for the hydrogen economy as an important component of the world’s energy transition. Hydrogen is attracting not only investment capital but also focus from some of the world’s largest current energy players, and additionally, government funding attention. The race is on to innovate and scale some of the key technology elements that are needed to make the hydrogen economy a high-impact energy transition area. Digital solutions are strategic in getting out of the gates quickly and persisting and winning in this race.
Technology breakthroughs, and the associated economic breakthroughs, are still needed to make hydrogen a viable and reliable building block in the energy picture over the next several decades. Digitalization is most certainly a crucial component in achieving these technological and economic breakthroughs. The concept of “born digital” is nowhere more relevant than with the massive projects on the drawing board for low carbon hydrogen production, safe hydrogen transportation and storage, and efficient, reliable, and safe hydrogen use.
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The opportunities and challenges of hydrogen adoption
Green hydrogen is especially attractive from a zero-carbon viewpoint (though still challenging from an economic and technology risk perspective), since it can be produced from water and renewable power, with no carbon emissions. As a transition fuel, hydrogen can be mixed with natural gas in the pipeline transport and distribution network and end-use systems, to reduce the carbon intensity of natural gas. The further production of green ammonia as an optional outcome of the green hydrogen strategy can have an important and sizeable decarbonization impact on fertilizer production, and indirectly on food production (the CO2 cost of fertilizer manufacture is often skipped from the lifecycle analysis of food production today.).
The adoption challenge is the capital and operating cost of hydrogen electrolyzers (where hydrogen is produced from water using electricity), and also the capital cost penalties of adding significant battery storage into the green hydrogen system. Operating cost challenges are driven by the stochastic and variable nature of solar and wind production which lead to low “load factors,” i.e. low average utilization of the electrolyzer and ammonia conversion process units. Figure 1, recently published by the US Department of Energy (DoE), shows the targeted improvement in green hydrogen economics that the US DoE’s hydrogen program hopes that its industry project grants will help achieve.
Here are seven concepts for applying digital solutions for scaling and accelerating the hydrogen economy:
1. Born digital hydrogen production
Producing both green and blue (low carbon) hydrogen involves new technology innovations. Each new technology incorporated into a system introduces uncertainty. Digitalization from the project concept and carried through into operations will result in a more intelligent and data-capable asset. This makes the design of subsequent generations of these assets faster, makes today’s new asset automation-ready, enables operation with fewer specially trained operators, and provides data streams for evaluating and eliminating design uncertainties. Traditional ways of developing energy assets involve individually engineered facilities (usually by one engineering organization), project execution (usually by a separate construction organization), and operations (by a third organization) that are inefficient, slow, and difficult to scale.
This indicates the need for a ‘born digital’ approach, beginning with a digital twin at the very front end of the feasibility study phase, and then elaborated and carried forward into project execution, and finally turned over to operations for a fully digital, sustainable, operable and safe hydrogen asset (see Figure 2).
2. Systems-level modeling for investment certainty
Systems-level, probability-based models are helping project sponsors sort through the dizzying array of options for designing the desired hydrogen systems. Because of the number of new technologies involved, the technology selection choices, the tradeoffs between different renewable sources (wind, solar, hydro, geothermal), and the CAPEX – OPEX tradeoff between adding battery storage and operating at variable capacity factors, it becomes almost impossible to manually rank the alternatives. It becomes even harder to consider all the systems-level choices. However, several hydrogen developers are doing this successfully.
A major southern hemisphere energy player has used this approach to evaluate the feasibility of alternative renewable power options and storage options. Several electrolyzer technology suppliers had approached them with proprietary approaches. Several consultancies had proposed different renewables and power storage scenarios. This approach helped them quantitatively, and in a fact-based manner, choose among the feasible options. A major Asian hydrogen developer is using this same approach to evaluate the scale-up risks and rank various electrolyzer technologies based on demonstration-scale implementations that they are putting in place.
3. Modeling for innovation and design optimization
Accurate electro-chemical models employing first-principles modeling are crucial in improving and optimizing designs for renewables tied to the electrolysis process and so-called “balance-of-plant” (the systems that surround the electrolysis system and make it work at an industrial scale). Several large projects that are in the design phase are using this modeling system to answer these questions and optimize designs. The areas that models can improve economics based on the selected technologies include optimizing the sizing of all the supporting systems to ensure capital expenditures meet targeted production levels but do not “over-size” individual components, as well as optimizing waste heat capture and re-use to ensure that the entire design is as energy efficient as possible. Technology breakthroughs are also possible in terms of optimizing the integration of renewables with the hydrogen production subsystems.
Several major hydrogen players are using modeling to create the crucial digital twins that, when connected to data streams, are providing the key feedback to understand areas for economic improvement of hydrogen production but also for optimizing the current generation of plants. One of these is Air Products (APCI), which has published its results of implementing performance monitoring models of a network of grey and blue hydrogen plants. Others are using such models on green hydrogen production systems.
4. Industrial DERMS for integrating and optimizing renewables and power storage with electrolysis
Distributed energy resource management (DERMS) is an advanced approach for managing distributed renewables generation and distributed battery storage across a distribution network. This approach can be extended for use in a dedicated way in green hydrogen projects which need to integrate renewable power. This is usually for dedicated renewable power farms but is sometimes deployed across a wide area in a virtual power plant style (VPP).
Industrial microgrids can also be expected to increase the efficiency of tying renewables to the hydrogen process, increasing power yields from renewable arrays by up to 10%. Iberdrola, Spain’s leading supplier of renewable power, is successfully using AspenTech OSI advanced distribution management (ADMS) and DERMS to create a platform for transitioning to predominantly renewable power in Spain, with a highly automated grid and network management approach.
5. Hybrid Model-based digital twin for faster scale-up of new technologies
Hybrid models bring together first principles modeling with machine-learning-based empirical modeling. This approach is particularly valuable with the new process technologies being introduced for hydrogen electrolysis and for tying together steam methane reformer (SMR) technology for blue hydrogen with carbon capture systems. Once these are implemented in pilot or demonstration scale facilities, data collection from those systems can yield machine learning insights, that can then be combined with first principles models in a hybrid model approach. These are expected to be extremely insightful in hydrogen applications.
6. Advanced process control to dampen the impact of variability of renewables and drive down lifecycle cost
Optimization systems assisted by predictive AI will maximize load factors and minimize the operating impacts of variability of the incoming renewable power.
A company in China that is employing advanced process control and digital twins in the water-to-hydrogen-to-ammonia train believes that this digitalization approach will reduce the cost of hydrogen production from $6 per KG to $2.50 per KG.
7. Monitoring and modeling for safety of hydrogen storage and transport
Hydrogen storage, transport, and end-use present unique reliability challenges and safety requirements. A key challenge to achieving safe and scalable systems is the accurate prediction of hydrogen behavior under cryogenic and liquefaction conditions. A second challenge is the effective deployment of the appropriate advanced monitoring devices to detect and characterize any release of hydrogen into the atmosphere from storage and transportation infrastructure.
Advanced process modeling systems can build models that ensure the reliability, safety, and economics of hydrogen pipelines and transport, define safe and efficient cryogenic solutions, and evaluate reuse of natural gas pipeline networks in mixed hydrogen natural gas and pure natural gas applications.
The adoption of digital approaches that are interoperable between different hydrogen economy segments is being driven by innovation from startups and existing mega players, as well as new hydrogen global hubs. In addition, access to learnings and data from the early implementations of hydrogen electrolysis will be key to the industry quickly discovering how to optimize the economics of low-carbon hydrogen, and how to most effectively utilize renewable energy sources within green hydrogen systems.
End-to-end digitalization concepts for hydrogen will be key to achieving this goal.
