Solar Power Comes To Sub-Saharan Africa
You may not even consider Africa when thinking about all the places that make use of solar power technologies, and before now, you were probably right not to. But, thanks to a start-up company, D.Light, solar energy has been made a viable option for those…
You may not even consider Africa when thinking about all the places that make use of solar power technologies, and before now, you were probably right not to. But, thanks to a start-up company, D.Light, solar energy has been made a viable option for those in even the remotest of areas in the form of solar-powered lanterns.
D.light was founded around a decade ago by two Stanford entrepreneurs and has now bought off-grid solar power to over 60 million people. Just recently they announced a massive $22.5 million in funding had been received which would be used to grow its home solar business further. Some of the investors from this time around included KawiSafi Ventures Fund, Energy Access Ventures, and the Shell Foundation.
So far, d.light has sold around 250,000 of their home solar systems, with around half of them being funded by micro-financing groups, while the other half are being paid for on a pay-as-you-go type scheme. M-KOPA previously supplied d.light with a pay-as-you-go payment system, but the companies have now parted ways. M-KOPA has investors including David Blood, former Vice President Al Gore, Virgin’s Richard Branson, and AOL’s Steve Case.
Other start-up companies that are also delving into this pay-as-you-go market are Off Grid Electric and Azuri Technologies. Off Grid Electric have the pleasure of backers including Tesla and SolarCity, and Vulcan Capital. Although that may seem like quite a few companies on board, there is still room for more, but with d.light looking to sell enough solar systems and lanterns to impact 100 million people by 2018, they may want to think about getting in there soon.
Image credit: weforum.org, opic.gov
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Daniel Okafor
Daniel Okafor is the Senior AI Reporter at TrendinTech, where he covers large language models, machine learning research and the practical use of artificial intelligence across business and government. He previously reported on artificial intelligence for MIT Technology Review, covering the labs behind the current generation of frontier models and the policy debates in Washington and Brussels. Daniel holds a Master of Science in Machine Learning from Carnegie Mellon University and follows the research community closely, attending NeurIPS and ICML each year to speak with the people behind the papers. He has a particular interest in evaluation: how models are benchmarked, where those benchmarks fail and what that means for the companies betting on them.
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