The future of energy is modular

Plugging into reality with cheap, uniform shapes

Historically, energy and natural resources (ENR) projects have had to grapple directly with base reality in a way few other industries do. They don’t get their raw inputs delivered on a truck or train like a normal factory might¹. The folks doing this work are setting up and running the systems that transform uneven natural inputs into homogenized commodity products that are legible and tractable for the rest of the civilizational stack.

In these industries, the specific folds of reality matter², and they are expensive to figure out (though often more expensive to get wrong³). This creates significant upfront costs in survey, planning, and design for projects that interface with reality in this way. Reality has a surprising amount of detail⁴, and those details must be managed.

With that in mind, there are significant opportunities to modularize the clean energy stack to an extent that was never possible with traditional hydrocarbon-based energy.

This is driven by the more even geographic dispersion (and relative homogeneity) of the resources being targeted by these new technologies. There are only a few places in the world with hydrocarbon deposits rich enough to justify a remote installation to extract them⁵. There are many places where the wind blows or the sun shines, where the earth is warm 1km belowground or where a concrete pad can be poured to hold a container’s worth of equipment manufactured far away.

This relative homogeneity allows for repeated deployment at scale, with limited variation of the core stack. This repeatability allows manufacturers and developers to more quickly and effectively move down their respective technological learning curves. While project specifics will continue to matter, the number of relevant inputs are more predictable and fewer in number, with less riding on the outcome of any individual project.

We have already seen this with utility-scale solar⁶ and wind projects. This modularization will be increasingly relevant at higher levels of the stack like energy storage and transformation (e.g., hydrogen electrolysis).

The benefits of a modular approach include:

• Reduced planning and design costs for project developers

• Reduced construction time and complexity for engineers and installers

• Stabilized technical risks for project financiers

• Increased spreading of fixed capital costs for manufacturers

• Increased surface area for optimization across the stack

Those that orient themselves towards a modular, scalable approach will be able to get the repetitions to beat out others on cost and speed to market, creating a powerful flywheel. End customers don’t want to buy a technology, they want a solution that takes predictable inputs to create high quality outputs at a known cost. The winners of the clean energy transition will do this more cheaply and more effectively at scale using a modular approach.

This is the difference between (for example) a custom-designed, cavern-based CAES system and the dream of an acre of Form Energy batteries stamped down like a Factorio blueprint⁷. Both have the potential to serve as effective long-duration energy storage due to their low ‘reservoir’ costs, but only one is modular and manufacturable at scale⁸.

This modularization will need to happen at various levels of abstraction, with opportunities at the level of the specific parts that comprise subsystems to entire systems being fabricated in factories and dropped into place.

The ongoing refinement of battery storage systems gives one example of what this looks like in practice⁹, with a shift from walk-in enclosures towards cabinet designs that obviate the need for one-off design and testing costs as well as location-specific fire code considerations. These types of minor tweaks comprise the improvements that will drive costs down the learning curve and widespread deployment.

It will be by enabling modularity up and down the stack that we will be able to leverage the unique characteristics of clean energy technologies to unlock true energy abundance.

1. This is not to say that other industries don’t have details (reality is fractally complex), but for those manufacturing intermediate or end products, they are often contracting with primary producers for a given grade and quantity of an input. It is up to the primary producers (in e.g., oil & gas, mining, agriculture) to get that input into a useable form on a truck, train, or ship.

2. Working in gold mining first really brought this home for me, where a few grams of gold per tonne (or a different-than-expected sulfur content) could differentiate a big success and a grinding failure of a project.

3. Industrial Megaprojects has a seeming litany of ways projects can go wrong when teams get data wrong ahead of project design. The history of engineering more generally is littered with unnoticed or underestimated details leading to unexpected outcomes.

4. Requisite blog reference here, though the phrase has seeped into more common usage over the last ~7 years.

5. Incidentally, this is a big part of what drove the huge cost declines associated with the ‘fracking revolution’. Shifting from one-off megaprojects to high repetition drilling cycles allow huge productivity gains. It also helps that fracking wells are often being opened in relatively accessible places like western Pennsylvania to a depth of ~2,000 meters, not in ultra deep water through a salt deposit off the coast of Brazil (for a net depth of ~5,500-7,500 meters below sea level).

6. People have made the point that anything that can be shipped over on a container from China has gotten way cheaper in the last 20 years. They usually are making a point about China’s manufacturing prowess, but I’d argue the modularity inherent in manufacturing at scale was just as important.

7. Still subject to a currently-glacial permitting process, unfortunately.

8. If I’m wrong about our ability to cheaply create new CAES caverns at scale, please do correct me.

9. “Another cost issue that is based on the specific energy storage technology is the physical complexity of the system. The modularity of the technology allows smaller systems to be collected into standardized energy blocks that can be replicated with larger systems. For outdoor deployments, many storage technologies have a standard design arrangement combining these modular storage building blocks into either 20- or 40-foot enclosures or containers. In addition, cabinet designs are becoming increasingly prevalent. The evolution of enclosures, from walk-in spaces equipped with standard access doors and interior accessible equipment to cabinets where there is no interior occupiable space and all equipment is accessed from the exterior, has been driven by several factors. One factor is additional life safety requirements in the model fire codes for occupiable spaces, another is requirements for the UL9540 product safety standard. As fire and explosion testing is a required component of product listing, performing this destructive testing on representative samples is facilitated in a standardized modular cabinet design as opposed to in one-off enclosure designs. This leads to ease of validation of consistent fire safety system requirements for the cabinet, simpler overall plant design and costs, and reliable listing requirements in the fire codes (Paiss, 2021). Indoor deployments are also based on these standard rack systems allowing for lower cost requirements. ESSs that have a lower degree of modularity for a similar system rating (power or energy) can have a large degree of non-recurring engineering costs.

Finally, the experience of the EPC firm with energy storage technologies will also have an impact on the engineering design costs. A system with significant modular layout will allow the firm to utilize previous design efforts on future project work, lowering the cost for these subsequent deployments. The ability to use prior engineering efforts in subsequent deployments is an ongoing challenge for engineering firms to avoid nonrecurring expenses.“

- 2022 Grid Energy Storage Technology Cost and Performance Assessment (PNNML-33283, page 15)