A 'lot less 'could' and 'might' in the article.....and it was right there in the click of a link, IF only.
Quote:Solar is going to play a much bigger role than most models predict
So far, official predictions have fallen woefully short of the rise of solar photovoltaic (PV) energy:
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pv predictions
(Nature Energy)
That red line is installed PV capacity. The black lines are forecasts from the International Energy Agency (IEA), blue from the German Advisory Council on Global Change, and green from Greenpeace. Only Greenpeace’s projections have come close, and only recently.
The graph is from a new commentary in the journal Nature Energy, by researchers from Germany’s Mercator Research Institute. In it, they review the reasons why models have traditionally underestimated PV and then try running a popular model updated with better information. The results are instructive, to say the least — if they are right, PV could potentially provide fully half of global electricity by 2050.
In most models that show the world reducing emissions enough to hit the 2°C climate target, “solar energy emerges only as a minor mitigation option” — around 5 to 17 percent of global electricity supply in one representative study used by the Intergovernmental Panel on Climate Change (IPCC). Models tend to be much more bullish on energy from biomass, despite its much lower total potential.
Why are models still so tepid on PV, despite its record? What are they missing? The researchers hone in on three phenomena that most models fail to properly account for:
1. Policy support: For the most part, models can’t or don’t take into account the kinds of tech-specific, country- or state-level policies that have been crucial to PV’s growth — especially feed-in tariffs (which guarantee homeowners a fixed 20-year return on PV investments) implemented early on in Germany, Spain, Italy, and China. The US used the investment tax credits and net metering. Other countries have other tools, but almost every country has some kind of support for PV. That support has dramatically accelerated its growth and innovation.
2. Rapid learning: The costs for solar PV modules “have decreased by 22.5% with each doubling of installed capacity,” which is a considerably more rapid learning rate than your average tech. (It’s a “steep learning curve,” in the jargon.) Faster capacity growth than expected + faster technological learning than expected = lower prices than expected.
3. Cost increases of competing clean energy sources: Models tend to be wildly optimistic on nuclear power and carbon capture and sequestration (CCS), despite the fact that, unlike PV, those technologies fall short of model projections again and again. The more decarbonization work that models assign to them, the less is left over for PV. Put more bluntly: Models stubbornly keep favoring nuclear and CCS over PV; the real world stubbornly keeps favoring PV over nuclear and CCS.
There is every reason to think all three of these phenomena will continue to be true in coming years. (The report contains a short but fascinating discussion of all the many technological developments on PV’s horizon — still tons of room to improve.)
The researchers see two key challenges ahead, if PV is to continue its rapid expansion. The first is the cost of financing, especially in the developing world. The second is integrating high levels of wind and solar into the grid. (Because wind and solar are variable, they require sophisticated balancing from other sources and grid technologies; I wrote about that challenge in some detail here.)
Say PV can address those challenges and maintain its current rate of learning, improvement, and expansion. What would a more realistic model projection look like?
To find out, the researchers plugged better cost information and more aggressive cost-curve assumptions into REMIND, a “global inter-temporally optimizing energy–economy model that has been extensively used for analyses of climate policies.”
Long story short, here are the results:
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