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Load shifting of computing can lower emissions and soak up surplus renewables. Except when it doesn’t.

 March 12, 2024 

As computation has exploded — whether for AI, Bitcoin, or general use — data center energy use is projected to double over just the next two years. In response, load shifting has emerged as a simple yet powerful strategy to unlock myriad benefits.

This focus on load flexibility has garnered more attention of late, from a New York Times investigative piece last year digging into whether Bitcoin mining operations truly modulate their load to soak up more renewables, to a recent Bloomberg article about the growing electricity consumption of the world’s data centers and their attempts to reduce the associated emissions and use more renewable energy through various forms of load shifting.

Load shifting can potentially drive many benefits, for example:

  1. Load shifting away from times of extreme peak demand can alleviate strain on the grid, supporting greater reliability, reducing the risk of blackouts, and potentially lowering costs.
  2. Similarly, load shifting away from times of dirtier electricity, such as when a more-polluting fossil peaker plant is the responding generator, can lower overall grid emissions.
  3. Load shifting toward times of excess wind or solar generation that’s being curtailed (AKA thrown away), can both reduce emissions and also boost renewable energy’s grid integration. 

But whenever you see a story about load shifting, the key question is, which times is the organization’s electricity use shifting to and from? Or, in a question so critical we named our whole nonprofit after it: “Watt” time is the load being shifted to?

The promise (and pitfalls) of load shifting

As we just noted, load shifting is often touted for the beneficial things it can do. But load shifting is only good if it does do those things. And it only does those things if it shifts the load to the times that are best for a specific objective.

In fact, experts have long known — even since the late 2000s from research like this 2008 study — that many cases of load shifting that people thought helped the environment actually increased emissions, not decreased them. Then further research found it happening again and again. Why? Because whether load shifting helps or hurts any particular goal depends totally on what times you are shifting load to and from. 

This is because load shifting isn’t necessarily good or bad. It is simply a technique that can be leveraged toward various ends, to varying degrees of success (or not). Energy journalist David Roberts summed this up well in a 2019 article for Vox. His article was focused on battery energy storage, but the perspective applies equally to load shifting overall:

“It’s a mistake to deploy batteries, or energy storage in general, as though they will inevitably reduce emissions. They might or might not. Indeed, it’s probably a mistake to think of them as emissions-reducing technologies at all. Rather, it’s better to think of storage as akin to transmission lines. Wires can carry both clean and dirty energy; their impact on emissions depends on local circumstances. Their primary purpose is not to reduce emissions, though, but to make the grid run more smoothly. They’re a grid tech, not a decarbonization tech. The same applies to batteries.”

For load shifting to reduce emissions, the software intelligence driving the load shifting needs to be optimized (or co-optimized) for doing that: reducing emissions. And you need to use the right signals to do so.

Load shifting based on marginal emissions and system-level impacts

Make no mistake: load shifting — by time, by location, or both — can indeed help sop up excess renewables and reduce grid emissions. But what does it really mean to do those things?

For many years, people tended to assume that shifting load to times when wholesale electricity prices were lower must reduce emissions. But all three studies linked earlier in this article showed that the opposite is often true. 

Then, for many years people assumed that shifting load to times of low average emissions rates — rather than low marginal emissions rates — must reduce emissions. Then study after study after study proved that that’s wrong, too.

With load shifting, more than a decade and a half of peer-reviewed studies has clearly established that what affects emissions and excess renewables are the marginal generator(s). Which power plant(s) respond by turning on or off, or ramping up or down, in response to changes in demand from load shifting? That’s how you appropriately measure the real impact on the grid system and its emissions.

If you’re perhaps thinking about load shifting data center computing to minimize emissions, you might think that shifting to a time and location where the sun is shining and solar PV is cranking out clean energy would help. But if that grid’s overall demand is already using all the solar that’s being generated, then adding new demand via your load shifting could cause a polluting fossil-fueled peaker plant to respond. Oops!

Load shifting to soak up surplus renewables that would otherwise be curtailed thus requires looking at the marginal emissions rate and the marginal generators. When and where are wind and solar on the margin? When and where are they being curtailed, such that shifted load could help absorb more of that clean electricity for zero increase in overall grid system emissions? That’s what affects the environmental aspects of load shifting.

We’re excited to see software practitioners increasingly thinking about the best times and locations for their software to consume electricity — and developing approaches to turn theory into practice. Called Carbon Awareness by the Green Software Foundation, software developers can build these capabilities into their operations.

It’s undoubtedly an exciting time. Software and computing are often the “brains” behind load shifting other technologies’ electricity use to reduce its associated emissions, from smart thermostats to EV charging. More than ever, practitioners are also looking at how computing itself can tap into these same load shifting opportunities.

As ever, we’re strong proponents of load shifting as an emissions-reduction solution with gigatons of potential at scale. To get there, we just have to do it right.