A High Resolution Ensemble to Quantify Wind Energy Resources in Saudi Arabia

• Activity Number: 64 - Modeling Uncertainty in Energy Systems
• Type: Topic Contributed
• Date/Time: Sunday, July 28, 2019 : 4:00 PM to 5:50 PM
• Sponsor: Section on Statistics and the Environment
• Author(s): Paolo Giani* and Wanfang Chen and Felipe Tagle and Stefano Castruccio and Marc Genton and Paola Crippa
• Companies: University of Notre Dame and King Abdullah University of Science and Technology and University of Notre Dame and University of Notre Dame and King Abdullah University of Science and Technology and University of Notre Dame
• Keywords: wind power; numerical weather models; stochastic generators; saudi arabia; WRF

Abstract

Saudi Arabia’s energy portfolio has historically been dominated by fossil fuels due to their abundance in the country. However the country is currently investing significant research efforts for the development of technologies to harness alternative, renewable energy sources to meet the increasing demands resulting from Saudi Arabia’s economic growth and population increase expected over the next decades. Recent studies, based on coarse climate model simulations and in-situ measurements, have indicated that wind resources are naturally abundant in Saudi Arabia, especially in its mountain and coastal regions. Here we present the first ensemble of high-resolution simulations of the Weather and Research Forecasting (WRF) model performed over the region to quantify wind energy potential. Simulated wind speeds are evaluated against a range of observations to identify model settings that allow optimal representation of wind fields. In the next phase of the project, computationally affordable stochastic generators will be developed to generate additional runs, in order to quantify the uncertainty in wind power estimates, which is a critical component for a wind farm feasibility study.