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The Road to Deep Decarbonization (bnef.com)
Michael Liebreich, writing for Bloomberg New Energy Finance: In the past fifteen years we have witnessed several pivotal points along the route towards clean energy and transport. In 2004, renewables were poised for explosive growth; in 2008, the world's power system started to go digital; in 2012, it became clear that EVs would take over light ground transportation. Today I believe it is the turn of sectors that have resisted change so far -- heavy ground transportation, industry, chemicals, heat, aviation and shipping, agriculture. One after the other, or more likely as a tightly-coupled system, they are all going to go clean during the coming decades.
Astonishing progress is being made on super-efficient industrial processes, connected and shared vehicles, electrification of air transport, precision agriculture, food science, synthetic fuels, industrial biochemistry, new materials like graphene and aerogels, energy and infrastructure blockchain, additive manufacturing, zero-carbon building materials, small nuclear fusion, and so many other areas. These technologies may not be cost-competitive today, but they all benefit from the same fearsome learning curves as we have seen in wind, solar and batteries. In addition, in the same way that ubiquitous sensors, cloud and edge-of-grid computing, big data and machine learning have enabled the transformation of our electrical system, they will unlock sweeping changes to the rest of our energy, transportation and industrial sectors.
Astonishing progress is being made on super-efficient industrial processes, connected and shared vehicles, electrification of air transport, precision agriculture, food science, synthetic fuels, industrial biochemistry, new materials like graphene and aerogels, energy and infrastructure blockchain, additive manufacturing, zero-carbon building materials, small nuclear fusion, and so many other areas. These technologies may not be cost-competitive today, but they all benefit from the same fearsome learning curves as we have seen in wind, solar and batteries. In addition, in the same way that ubiquitous sensors, cloud and edge-of-grid computing, big data and machine learning have enabled the transformation of our electrical system, they will unlock sweeping changes to the rest of our energy, transportation and industrial sectors.
You would only need a lamp post per address, if the *average* requirement was that every address needs to charge an EV every night. That is just nowhere near the truth:
1. Only about 50% of London households have a car
2. About 25% of London households have off-street parking
3. Given average British mileage of 150 miles per week, most EVs will only need recharging once per week (today, a Zoe, Leaf, Tesla can all manage that). That's a substantial over-estimate, given London driving distances are much shorter than average British which includes rural drivers covering much longer distances
So the average percentage of EVs that would need charging overnight on any one night is: 50% * 75% * 14% = about 5%. If you could get 1 lamp post per 10 households done with Ubitricity, you'd be more than fine with a hefty margin of error built in.