Empirical estimates of installed capacity density for solar photovoltaic and onshore and offshore wind power plants

Abstract Large-scale deployment of wind and solar power is essential for climate change mitigation but requires substantial land and offshore area due to their relatively low installed capacity densities. However, wide variation in installed capacity density estimates creates major uncertainty in projecting future spatial requirements. Here, we apply multiple spatial methods to satellite imagery to estimate installed capacity densities for 60 onshore wind, 24 offshore wind, and 54 utility-scale solar PV plants (including 36 fixed-tilt and 18 single-axis tracking) across six countries: Australia, China, Germany, India, United Kingdom, and the United States. For wind power plants, mean estimates of installed capacity density using the 8 D buffer method (eight times the rotor diameter), the convex hull method with a 5 D buffer, and the median Voronoi polygon (bounded by an 8 D buffer) method are similar (4.0, 4.4, and 4.9 MW km −2 for onshore wind and 4.6, 5.2, and 5.4 MW km −2 for offshore wind, respectively) but the 5 D buffer method provides a relatively larger estimate because of unaccounted areas within power plant boundaries. Single-axis tracking solar PV power plants have an approximately 33% lower mean installed capacity density than fixed-tilt power plants, with estimates of 36 and 29 MW km −2 (without and with a 50 m buffer, respectively), compared to 54 and 43 MW km −2 for fixed-tilt systems. Estimates vary more within countries and across methods than between countries, underscoring the importance of methods and assumptions in estimating spatial requirements for large-scale wind and solar deployment.