Atmospheric pressure gradients and Coriolis forces provide geophysical limits to power density of large wind farms. (1st January 2021)

• Record Type: Journal Article
• Authors: Antonini, Enrico G.A.; Caldeira, Ken
• Is Part Of: Applied energy. Volume 281(2021)
• Publication Date: 2021-01-01
• Subjects: Wind farm efficiency -- Power density -- Geophysical limits -- Coriolis force -- Pressure gradient -- Turbine-atmosphere interaction; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2020.116048
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: We provide a theoretical basis for upper limits of power density in large wind farms. Pressure gradients within the Ekman layer supply energy to large wind power plants. Interacting pressure-gradient, Coriolis and drag forces control the power density. The power density of regional-scale wind farms is resource- and geographic-dependent. Abstract: The geophysical limit to maximum land-area power density of large wind farms is related to the rate of replenishment of kinetic energy removed from the atmosphere by wind turbines. Although observations and numerical simulations have indicated an upper bound to the power density in the order of 1 W/m 2, no theoretical foundation has yet been provided. Here, we study the role of atmospheric pressure gradients and the latitude-dependent Coriolis parameter in the power density of large-scale wind farms by means of both numerical atmospheric simulations and analytic expressions. We illustrate that energy transport to regional-scale wind farms is primarily governed by horizontal pressure gradients and their interaction with the Coriolis force and turbine-induced surface drag within the latitude-dependent Ekman layer. Higher pressure gradients and lower Coriolis parameters promote higher energy availability and, consequently, higher potential power density, suggesting that the power density of regional-scale wind farms is largely resource- and location-dependent.