A business in the Indian Ocean is developing solar forecasting tech
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The Sun has been around for roughly 4.5 billion years and is crucial to life on Earth, providing our planet with an abundance of light and warmth.
As technology has developed, humans have come up with increasingly sophisticated methods of harnessing the Sun’s vast energy.
One such way is through solar photovoltaic systems, which directly convert light from the sun into electricity.
While the potential of solar power is clear, there are undoubted challenges too. According to the U.S. Energy Information Administration, these “limitations” include the fact that “the amount of sunlight that arrives at the Earth’s surface is not constant.”
The EIA adds that several factors — from location and the time of day to weather — influence the amount of sunlight on the Earth’s surface.
There are ways to overcome such issues, though. On Reunion Island, a French island located in the Indian Ocean, one firm specializes in solar energy forecasting and develops technology to “improve the short-term predictability of solar generation.”
Called Reuniwatt, the business offers a range of services including day-ahead, intra-day and intra-hour solar forecasts.
The firm has worked on experiments in the U.S. alongside the National Oceanic and Atmospheric Administration and its technology is also being used by solar projects around the world.
In February 2019, for example, the Moroccan Agency for Sustainable Energy chose to use the firm’s forecasting services for photovoltaic and concentrated solar power plants.
Caroline Lallemand is a geographic information system engineer at Reuniwatt. “In order to measure, then forecast, solar energy, Reuniwatt uses a multitude of data sources: satellite observations, weather models, ground sensor measurements and sky images,” she told CNBC’s “Sustainable Energy.”
“I design the pipelines to collect, clean, aggregate and share the data with the rest of the team,” she added. “The goal is to make sure that the forecasts that we send to our clients are always the most accurate.”
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