Wind Could Provide 26% of China's Electricity by 2030

Despite increasingly severe curtailment of Chinese wind farms in favor of coal-fired generation, a first-of-a-kind energy dispatch model finds that the country can accommodate a lot of additional wind power

2 min read
A truck drives past a wind farm in Xinjiang, China.
Installing wind farms in China's gusty northern provinces, such as here in Xinjiang, may produce more costly energy due to grid integration challenges.
Photo: Paul Springett/Alamy

Last month Energywise argued that the primary reason Chinese wind farms underperform versus their U.S.-based counterparts is that China’s grid operators deliberately favor operation of coal-fired power plants. Such curtailment of wind power has both economic and technical roots, and it has raised serious questions about whether China can rely on an expanding role for wind energy. New research published today appears to put those concerns to rest, arguing that wind power in China should still grow dramatically. 

The report today in the journal Nature Energy projects that wind energy could affordably meet over one-quarter of China's projected 2030 electricity demand—up from just 3.3 percent of demand last year.

In fact the researchers, from MIT and Tsinghua University, project that modest improvements to the flexibility of China’s grid would enable wind power to grow a further 17 percent. That, they argue, means that China's non-fossil resources could grow well beyond the 20 percent level that China pledged to achieve under the Paris Climate Agreement.

These projections come at an important moment. Curtailment of wind farms nearly doubled last year from 8 percent to 15 percent of total wind output, according to InsideClimate News. Curtailment jumped the most in northern provinces that boast some of China’s best wind resources. Wind farms in Gansu province, the hardest hit, lost 39 percent of their generation. 

In response, Chinese officials ordered a moratorium on wind farm approvals in Gansu and five other northern regions. They also have begun to question wind power’s future potential, according to Jiahai Yuan, an environmental economist at Beijing's North China Electric Power University. Growing curtailment has "raised calls for a radical rethinking on wind policy,” writes Yuan in an accompanying essay in Nature Energy.

Today's MIT-Tsinghua report relies on an hourly dispatch model for China’s grids that Yuan calls a "first of its kind." The model determines the optimal hourly output of various classes of generators to meet electricity demand at least cost, subject to various operational constraints. The latter include the availability of flexible power plants to back-up variable wind power, must-run generation such as coal-fired plants that provide steam to cities in winter, and transmission bottlenecks. 

As a base case the MIT-Tsinghua team finds that 2,590 terawatt-hours of wind energy could be accommodated in 2030 at roughly the current cost of wind energy. The projected generation would be 26 percent of anticipated demand in 2030.

Cheap wind generation projected for 2030 rises to over 3,000 TWh with improved grid flexibility. Flexibility measures include enabling coal generators to ramp down to 40 percent of rated capacity when winds are strong (rather than the current 50 percent limit) and scheduling power plant operation daily instead of weekly or monthly.

Interestingly, the MIT-Tsinghua model also affirms Chinese energy officials’ reticence to rely on additional wind power in the windy north. Their 2030 projection instead tilts wind farm installations toward central and eastern provinces, which need more power and have fewer must-run coal plants. 

As the authors put it, geographic detail is an important output from the model that could help energy planners worldwide:

“Failing to consider the grid-integration step … when developing national blueprints for the spatial distribution of future electricity capacity can yield vastly different recommendations for planning. Integration cost should not be overlooked.”

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Smokey the AI

Smart image analysis algorithms, fed by cameras carried by drones and ground vehicles, can help power companies prevent forest fires

7 min read
Smokey the AI

The 2021 Dixie Fire in northern California is suspected of being caused by Pacific Gas & Electric's equipment. The fire is the second-largest in California history.

Robyn Beck/AFP/Getty Images

The 2020 fire season in the United States was the worst in at least 70 years, with some 4 million hectares burned on the west coast alone. These West Coast fires killed at least 37 people, destroyed hundreds of structures, caused nearly US $20 billion in damage, and filled the air with smoke that threatened the health of millions of people. And this was on top of a 2018 fire season that burned more than 700,000 hectares of land in California, and a 2019-to-2020 wildfire season in Australia that torched nearly 18 million hectares.

While some of these fires started from human carelessness—or arson—far too many were sparked and spread by the electrical power infrastructure and power lines. The California Department of Forestry and Fire Protection (Cal Fire) calculates that nearly 100,000 burned hectares of those 2018 California fires were the fault of the electric power infrastructure, including the devastating Camp Fire, which wiped out most of the town of Paradise. And in July of this year, Pacific Gas & Electric indicated that blown fuses on one of its utility poles may have sparked the Dixie Fire, which burned nearly 400,000 hectares.

Until these recent disasters, most people, even those living in vulnerable areas, didn't give much thought to the fire risk from the electrical infrastructure. Power companies trim trees and inspect lines on a regular—if not particularly frequent—basis.

However, the frequency of these inspections has changed little over the years, even though climate change is causing drier and hotter weather conditions that lead up to more intense wildfires. In addition, many key electrical components are beyond their shelf lives, including insulators, transformers, arrestors, and splices that are more than 40 years old. Many transmission towers, most built for a 40-year lifespan, are entering their final decade.

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