Scientists Mapped Every Large Solar Plant On The Planet Using Satellites And Machine Learning

An astonishing 82 percent decrease in the cost of solar photovoltaic energy since 2010 has given the world a fighting chance to build a zero-emissions energy system which might be less costly than the fossil-fueled system it replaces. The International Energy Agency projects that PV solar generating capacity must grow ten-fold by 2040 if we are to meet the dual tasks of alleviating global poverty and constraining warming to well below 2°C.

Policy must also be designed to ensure solar energy reaches the furthest corners of the world and places where it is most needed. There will be inevitable tradeoffs between solar energy and other uses for the same land, including conservation and biodiversity, agriculture and food systems, and community and indigenous uses.

Researchers have built a machine learning system to detect these solar facilities in satellite imagery and then deployed the system on over 550 terabytes of imagery using several human lifetimes of computing.

Using the area of these facilities, and controlling for the uncertainty in the machine learning system, they obtain a global estimate of 423 gigawatts of installed generating capacity at the end of 2018.

The study shows solar PV generating capacity grew by a remarkable 81 percent between 2016 and 2018, the period for which they had timestamped imagery.

Grid operators and electricity market participants need to know precisely where solar facilities are in order to know accurately the amount of energy they are generating or will generate. As solar becomes more predictable, grid operators will need to keep fewer fossil fuel power plants in reserve, and fewer penalties for over- or under-generation will mean more marginal projects will be unlocked.

Policymakers can provide incentives to instead install solar generation on rooftops which cause less land-use competition, or other renewable energy options.