Statistical characteristics and mapping of near-surface and elevated wind resources in the Middle East

  • Chak Man Andrew Yip

Student thesis: Doctoral Thesis

Abstract

Wind energy is expected to contribute to alleviating the rise in energy demand in the Middle East that is driven by population growth and industrial development. However, variability and intermittency in the wind resource present significant challenges to grid integration of wind energy systems. The first chapter addresses the issues in current wind resource assessment in the Middle East due to sparse meteorological observations with varying record lengths. The wind field with consistent space-time resolution for over three decades at three hub heights over the whole Arabian Peninsula is constructed using the Modern Era Retrospective-Analysis for Research and Applications (MERRA) dataset. The wind resource is assessed at a higher spatial resolution with metrics of temporal variations in the wind than in prior studies. Previously unrecognized locations of interest with high wind abundance and low variability and intermittency have been identified in this study and confirmed by recent on-site observations. The second chapter explores high-altitude wind resources that may provide alternative energy resources in this fossil-fuel-dependent region. This study identifies areas favorable to the deployment of airborne wind energy (AWE) systems in the Middle East and computes the optimal heights at which such systems would best operate. AWE potential is estimated using realistic AWE system specifications and assumptions about deployment scenarios and is compared with the near-surface wind generation potential concerning diurnal and seasonal variability. The results show the potential utility of AWE in areas in the Middle East where the energy demand is high. The third chapter investigates the potential for wind energy to provide a continuous energy supply in the region. We characterize the wind power variability at various time-scales of power operations to illustrate its effects across the Middle East via spectral analysis and clustering. Using a high-resolution dataset obtained from Weather Forecasting and Research (WRF) model simulations, this study showcases how aggregate variability may impact operation, and informs the planning of large-scale wind power integration in the Middle East in light of the scarcity of observational data.
Date of AwardNov 28 2018
Original languageEnglish
Awarding Institution
  • Computer, Electrical and Mathematical Science and Engineering
SupervisorGeorgiy Stenchikov (Supervisor)

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