A global inventory of photovoltaic solar energy generating units

• Published in: Nature (London) 2021-10, Vol.598 (7882), p.604-610
• Main Authors: Kruitwagen, L., Story, K. T., Friedrich, J., Byers, L., Skillman, S., Hepburn, C.
• Format: Article
• Language: English
• Subjects: 639/166/4073/4100; 704/844/4066/4076; 704/844/4081; 704/844/682; Agricultural land; Alternative energy sources; Analysis; Biodiversity; Climate change; Climate change mitigation; Coal-fired power plants; Conservation; Datasets; Electric power production; Electricity; Electricity distribution; Energy; Energy utilization; Environmental aspects; Environmental risk; Generating capacity; Grasslands; Humanities and Social Sciences; Inventory; Land conservation; Land cover; Land use; Learning algorithms; Machine learning; multidisciplinary; Neural networks; Photovoltaic cells; Photovoltaic power generation; Photovoltaics; Remote sensing; Science; Science (multidisciplinary); Solar energy; Spatial data; Sustainable development; Wildlife conservation
• ISSN: 0028-0836; 1476-4687
• DOI: 10.1038/s41586-021-03957-7

Photovoltaic (PV) solar energy generating capacity has grown by 41 per cent per year since 2009 1 . Energy system projections that mitigate climate change and aid universal energy access show a nearly ten-fold increase in PV solar energy generating capacity by 2040 2 , 3 . Geospatial data describing the energy system are required to manage generation intermittency, mitigate climate change risks, and identify trade-offs with biodiversity, conservation and land protection priorities caused by the land-use and land-cover change necessary for PV deployment. Currently available inventories of solar generating capacity cannot fully address these needs 1 – 9 . Here we provide a global inventory of commercial-, industrial- and utility-scale PV installations (that is, PV generating stations in excess of 10 kilowatts nameplate capacity) by using a longitudinal corpus of remote sensing imagery, machine learning and a large cloud computation infrastructure. We locate and verify 68,661 facilities, an increase of 432 per cent (in number of facilities) on previously available asset-level data. With the help of a hand-labelled test set, we estimate global installed generating capacity to be 423 gigawatts (−75/+77 gigawatts) at the end of 2018. Enrichment of our dataset with estimates of facility installation date, historic land-cover classification and proximity to vulnerable areas allows us to show that most of the PV solar energy facilities are sited on cropland, followed by aridlands and grassland. Our inventory could aid PV delivery aligned with the Sustainable Development Goals. A global inventory of utility-scale solar photovoltaic generating units, produced by combining remote sensing imagery with machine learning, has identified 68,661 facilities — an increase of over 400% on previously available asset-level data —  the majority of which were sited on cropland.