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santos-da-silva_etal_2021_erl

The implications of uncertain renewable resource potentials for global solar and wind electricity projections

Silvia R. Santos da Silva^1,2*, Gokul Iyer², Thomas B. Wild^2,4,5, Mohamad I. Hejazi³, Chris R. Vernon^2,6, Matthew Binsted², Fernando Miralles-Wilhelm^4,7

¹ Department of Atmospheric and Oceanic Science, University of Maryland, College Park, Maryland, United States of America

² Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, Maryland, United States of America

³ King Abdullah Petroleum Studies and Research Center, Riyadh, Saudi Arabia

⁴ Earth System Science Interdisciplinary Center, College Park, Maryland, United States of America

⁵ Department of Civil and Environmental Engineering, University of Maryland, College Park, Maryland, United States of America

⁶ Pacific Northwest National Laboratory, Richland, Washington, United States of America

⁷ College of Science, George Mason University, Fairfax, Virginia, United States of America

* corresponding author: silviameteoro@gmail.com

Abstract

Studies exploring long-term energy system transitions rely on resource cost-supply curves derived from estimates of renewable energy (RE) potentials to generate solar and wind power projections. However, estimates of RE potentials are characterized by large uncertainties stemming from methodological assumptions that vary across studies, including factors such as the suitability of land and the performance and configuration of technology. Based on a synthesis of modeling approaches and parameter values used in prior studies, we explore the implications of these uncertain assumptions for solar PV and onshore wind electricity generation projections globally using the Global Change Analysis Model (GCAM). We show that variability in parametric assumptions related to land use (e.g. land suitability) are responsible for the most substantial uncertainty in both wind and solar generation projections. Additionally, assumptions about the average turbine installation density and turbine technology are responsible for substantial uncertainty in wind generation projections. Under scenarios that account for climate impacts on solar and wind power, we find that these parametric uncertainties are far more significant than those emerging from differences in climate models and scenarios in a global assessment, but uncertainty surrounding climate impacts (across models and scenarios) have significant effects regionally, especially for wind. Our analysis suggests the need for studies focusing on long-term energy system transitions to account for this uncertainty.

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Script Name	Description	How to Run
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