The Critical Role of Digital Technologies to de-risk and scale the Power-to-X Applications

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As the industry accelerates its energy transition to reduce carbon emissions, the hard-to-abate fields, such as chemicals, refining, cement, and steel are among the most carbon-unconscious. Consequently, they account for about “20% of global carbon emissions, with cement and steel manufacturing alone accounting for 14%,” per the IFC.  Additionally, there are the so-called “hard to electrify” industries like marine shipping, heavy-duty trucking, long duration energy storage, and aviation, which naturally can be placed in the same box as the hard-to-abate fields. Green hydrogen, also known as renewable hydrogen, is a key decarbonization lever—particularly when substituting the current 800 mtpa of grey hydrogen (or unrenewable hydrogen) that is currently consumed by this sector. Power-to-X applications can be leveraged towards this renewable electricity.

Power-to-X refers to the suite of process technologies that convert electricity (electrons), those ideally generated from renewable sources, into an industrial feedstock, such as hydrogen through electrolysis. Further synthesis downstream could produce ammonia or synthetic fuels (molecules). These applications play a crucial role in energy transition as a means to decarbonize the hard-to-abate and the hard to electrify fields.

The Power-to-X investments are currently at a stage where FIDs are pending due to the inherent risk and cost of implementation. Power-to-X requires a high premium compared to the conventional means used to produce hydrogen from fossil fuels. Digital technologies have a critical role to play in both eradicating risk from hydrogen and promoting its use as a clean feedstock alternative as well as in scaling hydrogen implementation. At Schneider Electric, we leverage our digital portfolio, reinforced by AI, combined with deep domain knowledge in power and continuous productive process, to enable the Power-to-X ecosystem to:

1. Minimize levelized cost of hydrogen (LCOH).
2. Manage power fluctuation and enable end-to-end optimization.
3. Maximize safety.

Let’s take a closer look at these key aspects of successful green hydrogen implementation.

1. Minimizing levelized cost of hydrogen (LCOH)

Digital technologies, empowered by AI and used coherently and consistently across the asset lifecycle, can positively impact LCOH in several ways, such as reduced CapEx by using co-simulation during the design and build phase. With the power of digital twin technology, it is possible to optimize plant design while accelerating the engineering and construction phases for cost, efficiency, and safety. Co-simulation allows for the rightsizing of power generation, sourcing, and distribution systems—for instance, optimizing CapEx in relation to procurement. Finally, data-centric collaboration speeds up all activities during the EPC phase. Using digital twins during the design and build phases accelerates start-up and commissioning, facilitating a faster time to market, by empowering plant managers to train operators ahead of time and test the automation system before arriving at the site.. Combined, these contributions can substantially reduce the CapEx portion of LCOH.

2. Managing power fluctuation and end-to-end optimization of the Power-to-X Value Chain

It is important to know that power fluctuation for renewable energy is happening in the millisecond frequency, whereas on the hydrogen (molecule) side, the fluctuation on the demand is happening in the minutes-hour range. Without a doubt, it is a complex equation to determine the optimal setpoint using the cheapest and cleanest available power while also taking into consideration the ability of hydrogen to meet higher demands. Digital technologies can solve this equation to better manage power fluctuation and make green hydrogen possible.

Specifically, there is a tremendous benefit in using digital twins to optimization the Energy Management System (EMS). In a green hydrogen plant, digital twin capability—coupled with grid and energy management systems—can stabilize and optimize power sourcing from hybrid and distributed sources, ensuring reliable production. Plant owners can also optimize costs by using AI to make optimal power sourcing decisions, particularly when married with storage. An end-to-end digital platform also enables hydrogen operations to take advance of tax incentives by proving that the hydrogen molecules have been produced with green electrons.

In an operative sense, a rightsized plant is more cost-effective to maintain. AI-enabled digital capabilities, such as Predictive Asset Operations, allow operators to find the “sweet spot” between predictive maintenance, asset reliability & performance, and production operations. This is one example of how digitalization is a major influence on optimizing OpEx efficiency.

Another example is Schneider’s recent work with a major European electrolyser membrane manufacturer on using AI to enable optimal operations to maximize membrane lifetime. This is important because an electrolyser’s membrane requires a minimum load and needs to avoid gas crossover and reverse currents. At the same time, the membrane represents most of the impedance the electrolyser will create, and, therefore, is responsible for the efficiency of the stack.

3. Maximizing the safety of green hydrogen production

The final major consideration on accelerating the production of green hydrogen is safety. Indeed, safety is paramount, especially considering that hydrogen is a highly explosive gas. Hydrogen safety is especially important for synthesis, storage, and transportation in refining petrochemicals in plants. Schneider is already working with green hydrogen plants up to a 100MW scale. The role of safety will become even more important as hydrogen sites increase scaling.

Safeguarding safety processes in the design, implementation, and operation phases is a complex task. There is proven experience with operations and maintenance in smaller plants, but there is a disparity in large-scale production. A lack of reliable historical data and validated models of failure frequencies and consequences mean that electrolyser system suppliers, asset owners, and authorities have only limited data and knowledge on specific fire and explosion hazard scenarios. This is where digital technologies and AI can be of use. There are four key areas where digital and AI can elevate the safety of green hydrogen production:

• Layers of protection at the control level using safety instrumented systems, like Modicon Safety PLC and EcoStruxure™ Triconex, which have historical track records in process automation implementations. Additional layers of process protection, like EcoStruxure™ Foxboro DCS (which runs the process within operational constraints and safely shuts down the system if the process control goes out of safe operating conditions and into other conditions which could result in damage or catastrophic event).
• Maintenance optimized by predictive analytics, which can use machine learning models to detect potential failure of sophisticated machines—such as electrolysers—as well as by augmented reality or virtual reality technologies that can enable remote assistance when needed.
• Simulation, which is an innovative area that allows for what-if scenarios that facilitate safe operations and optimal design, permitting the verification of the hazards hypothesis, specifically during the design and test of the functional safety system.
• Operator training systems to ensure education on safe practices and correct responses in case of system failure.

A case study in green hydrogen production

Schneider Electric already is bringing together all these facets of digital technologies and AI. For example, we are working with a major power-to-ammonia plant where the customer seeks to minimize their reliance on grid power as much as possible. Instead, they are maximizing the use of an integrated wind farm to power the electrolysers. We also are building a unique digital twin for the power system (electrons) that is fully integrated within the process systems (molecules). This model is used during the feasibility study to perform what-if scenarios to enable an optimized plant design, including the battery storage system sizing as well as the optimal size and charge-discharge curves for an intermediate green hydrogen buffer.

The ambition for green hydrogen to decarbonize the hard-to-electrify fields

We are excited that there is growing attention and emphasis on digital and its role in enabling the scaling up and de-risking of hydrogen complex value chain implementation. “As the most abundant element on Earth, hydrogen has the potential to transform many of the sectors that power our world, from transportation and utilities to biofuels, fertilizers and environmentally benign chemicals.” The primary focus in the beginning of seizing the hydrogen opportunity has been more on incentives about physical process. In fact, green hydrogen costs are expected to drop sharply by 2030, thanks to technological advancements. Today, we see digital technologies as the primary differentiator for bringing the hydrogen economy to life.

Learn more https://www.se.com/ww/en/work/solutions/for-business/energies-and-chemicals/green-hydrogen.jsp