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As we aim to accelerate the transition towards a carbon-neutral economy, the performance of such solutions as wind turbines and solar power is a major innovation challenge to achieve a sustainable future.
We know by now that these natural elements that technology turns into energy can be intrinsically inefficient. By their nature, they are intermittent, bound to never be available 24/7, year-round: as the wind stills and the sun comes and goes. If we aren’t able to predict how much energy a plant will be able to produce, it is harder to make the most of this energy and make it reliable enough to supplant more polluting, but consistent, sources.
Fortunately, recent developments are enabling scientists and businesses to optimise the use and production of renewables. Through a combination of Artificial Intelligence, computing and more accurate weather forecasts, a range of studies have granted access to more precise wind and sun power data, fuelling a flurry of projects to improve the efficiency of renewables. Here’s a taste of some that are worth tracking:
BETTER WEATHER FORECASTS
At Google, energy is in high demand. Its portfolio uses as much power as two times the city of San Francisco, according to Forbes, and the company has long tried to pivot to renewable energy.
POWER OF WIND
Wind power is surging around the world — growing 19% in 2019 alone, thanks to several major projects in the US and China.
SUN AND CLOUDS
Like wind turbines, the output of solar energy systems also depends largely on the weather — in this case, cloud cover. A recent study proposed a new method to use data from recently launched NASA satellites to predict the optical effects of clouds and the output of solar panels around the world.
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