A presentation in Ottawa earlier this month by pioneering U.S. energy economist Daniel Yergin was all the proof you’ll ever need that you won’t get the right answers about energy and carbon by asking the wrong questions. Yergin is hard to criticize. He’s a Pulitzer-winning author and vice-chair of IHS, one of the handful of research, modelling, and analysis firms the fossil industry counts on to monitor today’s energy markets and anticipate tomorrow’s.
In his talk, hosted by Canada 2020 and moderated by Natural Resource Minister and GreenPAC endorsee Jim Carr, Yergin name-checked many of the trends and transformations that are sweeping the energy sector, helping to drive a fossil industry crisis that has wiped out 350,000 jobs so far, and more than US$1 trillion in investment by 2020. Yet he still expects oil demand to increase by five to six million barrels per day over the next five years, then continue growing through 2030 before it begins levelling off, with renewable energy only starting to make a dramatic difference by 2040 or 2050.
“The question is the speed,” Yergin said. “Oil was discovered in 1859,” but “it wasn’t until basically the 1960s that oil took over as a number one energy source.” While the future will see “much more diverse sources of energy coming out of the wall and otherwise,” IHS still expects that transformation to unfold “over decades”. If that’s the extent of the energy modelling insight available to federal and provincial/territorial governments over the next few months, you can expect much the same trajectory to underlie their forthcoming pan-Canadian climate plan.
How Energy Modelling Gets It Wrong
The basic problem with energy models is surprisingly simple. Whether they come from private firms like IHS or public bodies
like the National Energy Board or the U.S. Energy Information Administration, they’re reasonably good at taking past trends and projecting them into the future. They’re often far less effective at weighing and combining the multiple, simultaneous,
disruptive changes in technology, the economy, and the environment that are the hallmark of our times. And modelling doesn’t usually lend itself very well to picking a desired future—like the 1.5°C long-term global warming target that diplomats adopted at last year’s United Nations climate summit in Paris—and charting a course to make it a reality. The most basic energy model would take past trends for population and economic growth,project them two or three decades into the future, assume that energy demand will grow in lockstep with the economy (even though energy and GDP have been decoupling since the 1970s), then factor in the competing prices of mostly conventional energy sources.
An edgier model would look at a wider range of emerging trends—in his talk, Yergin mentioned driverless cars, as well as energy efficiency improvements that he admitted have achieved far more than most economists thought possible. (And we’re just getting started.) But even then, most alternative scenarios start out with conventional assumptions—economies will grow, energy demand will follow, and fundamental change takes a century, not a couple of decades—then graft on a few trends that could “bend the curve,” as the modellers like to say.
That’s how you reconcile the twin realities of a global climate crisis and a massive clean energy revolution, with models that show a growing market for fossil fuels. Clean energy prices are plummeting. Grid-scale battery storage is surging. Electric vehicles are set to outperform internal combustion cars as soon as 2022. And the world’s governments are finally getting serious about deep(er) greenhouse gas emissions, with developing economies like China and India taking leadership positions. But somehow, such luminaries as the NEB, the EIA, and Exxon seem to keep missing the memo. Governments plan accordingly. And then we wonder why the world can’t seem to get its carbon emissions under control.
How Fast Can We Change?
There’s a better way to build an energy model. You start with an established source like the NEB's Energy Future 2016 long-term outlook as an initial reference—modelling geeks call that a “seed scenario”—but use it to open a conversation, rather than closing it off. By digging into the baseline assumptions in the model—how quickly households will form, whether retail space will shrink due to e-commerce, whether smaller homes would use less energy and require smaller, less resource-intensive consumer goods, whether an emphasis on local food raises or lowers your carbon footprint (I’ve heard both)—the right kind of energy model allows economists, politicians, and citizens to imagine alternate futures. By listening to “unusual suspects” outside the energy field, modellers can get a rich menu of options to explore. The rising tide of innovation is not only reshaping the ways in which we produce and use fuels and electricity. It’s transforming what energy modellers euphemistically call “business-as- usual”, the unsustainable baseline on which their projections are built.
Even in Canada, with all the oil and gas we produce for export, the entire energy sector makes up less than 10% of our economic activity. Information technology and other innovations are sweeping through the other 90% of the economy, as well, with profound implications for what can and will happen inside the 10% piece of the pie on which most energy modelling focuses. How fast can the system change? As any utility or oil company shareholder can attest, faster than the time it takes to plan and build a megaproject. “Energy technology is starting to get smaller,” writes vox.com climate specialist David Roberts. “Where once there were a few gigawatt-level power technologies available, now there are many options, ranging in scale from gigawatts all the way down to kilowatts.” That alone opens up the prospect of a new, transformed energy system. “Small technologies iterate and improve faster,” Roberts notes. “To the extent that the clean energy transition is a software challenge, we can expect it to move more rapidly than previous energy transitions, simply because software moves much faster than hardware.”
A cleantech future isn’t guaranteed, any more than multi-million- barrel growth in fossil fuel demand is a foregone conclusion. But before we can plan for a post-carbon future, we have to be able to imagine it. It’ll be a lot easier for federal and provincial/territorial governments to hit the right level of ambition with their forthcoming climate plan if their modelling shows them a wider range of options.