Boundary Layer Science Challenges in the Context of Wind Energy

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1 Boundary Layer Science Challenges in the Context of Wind Energy WILLIAM J. SHAW 1 Pacific Northwest National Laboratory National Academies of Sciences, Engineering, and Medicine Workshop on the Future of Atmospheric Boundary Layer Observing Airlie House, Warrenton, Virginia 24 October 2017

2 The Wind Energy Context for Atmospheric Boundary Layer Science Wind energy an emerging application Currently 5% of U.S. electrical power; 20% by 2030, 35% by 2050 Information needed Hub-height (~100 m) wind speed climatology for siting Hub-height turbulence and shear climatologies for loads Wind speed forecasts at 100 m for power markets Impact of errors Forecast errors cause costly mispricing in power markets Poor shear and turbulence estimates raise costs either through over-engineering or shortened turbine lifetimes Errors in hub-height wind speed climatology raise costs of plant financing Need for quantified uncertainty Well-founded uncertainty estimates can reduce risk premiums in financing November 21,

3 Notable Science Challenges of Complex Terrain Diurnal heating, channeling, and blocking Terrain modulations on scales ~10 km significant Cold pools Erosion associated with large, difficult-to-predict wind shears Terrain-induced gravity waves Potentially significant cause of turbulence intermittency in nocturnal stable boundary layers Wakes downstream of significant geographic features Wakes have significant variability on scales of ~10 km and represent a forecasting challenge Progressive violation of assumptions that vertical gradients control subgrid-scale processes with increasing model resolution Increased spatial resolution may be desirable to improve accuracy of power production

4 WFIP 2 - Topographic Wake Horizontal Velocity Courtesy of NCAR; simulation by Pedro Jimenez Munoz, visualization Scott Pearse Topographic wake and gap flow in simulation for March 07 08, 2016

5 Toward Addressing the Challenges of Understanding the Complex Terrain BL Computational advances support higher NWP model resolutions A potential boon to forecasting for boundary layers in complex terrain But can we properly represent the subgrid-scale physics? LES may provide helpful guidance Both NWP and LES models need validation Validation of models in complex terrain Requires measurements resolving many spatial scales Could greatly benefit from the measurement of fields Should include uncertainty quantification, including that of the observations UQ performed ideally under full spectrum of expected conditions Computational and instrumentation advances promise new kinds of measurements from multi-system integrated sampling Examples: Virtual stress tensor towers, multiple virtual wind towers Remote sensing systems increasingly amenable to long-term, unattended deployment

6 WFIP 2 An Example of a Validation and Physics Study in Complex Terrain DOE Coastal Profilers BPA Service Area SEW PQR OTX PDT 11 wind profiling radars 17 sodars 5 wind profiling lidars 4 scanning lidars 4 radiometers 10 microbarographs 1 Ceilometer 2 scanning radars 28 sonic anemometers 5 radiative flux systems & soil moisture >100 NWS supplemental raobs NWS Forecast Offices 915 Radar Wind Profiler Sodar Lidar Image contributions from multiple WFIP 2 participants 10-20m Tower 80m Tower Physics Site 2 km Biglow Canyon Tower

7 XPIA Assessment of State-of-the-Art in Probing the ABL (March May 2015) Evaluated instrument performance For conventional remote sensing such as MWR and RASS For conventional and novel scanning Doppler strategies For challenging variables, such as WPR dissipation rate Virtual tower scanning configuration with three lidars (from Lundquist et al., ) XPIA instrument arrangement at the Boulder Atmospheric Observatory (from Lundquist et al., 2017) Documented uncertainties Used BAO Tower as reference Evaluated impact on uncertainties from tradeoffs such as stare duration versus field coverage Provided significant new information about instrument capabilities for ABL studies 1 Lundquist, J. K., and Coauthors, 2017: Assessing state of the art capabilities for probing the atmospheric boundary layer: The XPIA field campaign. Bull. Amer. Meteor. Soc., 98, , doi: D

8 Summary Wind energy provides a significant motivation for improved ability to simulate the ABL in complex terrain New metrics for model performance include winds and turbulence ~100m above the surface Strong ABL inhomogeneity in complex terrain will be best addressed by a combined measurements and modeling approach LES models may provide insights to improve NWP model parameterizations Validation will be needed for both and will benefit from measurements of fields Uncertainty quantification Is needed for both measurements and models Should be based as much as possible on the full range of anticipated conditions Recent work has explored and documented novel ways to extract new information from boundary layer measurement systems