Pat Moriarty: 2013 Sandia National Laboratoies Wind Plant Reliability Workshop
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Pat Moriarty: 2013 Sandia National Laboratoies Wind Plant Reliability Workshop

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Complex Flow Research and It's Relation to Reliablity

Complex Flow Research and It's Relation to Reliablity

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    Pat Moriarty: 2013 Sandia National Laboratoies Wind Plant Reliability Workshop Pat Moriarty: 2013 Sandia National Laboratoies Wind Plant Reliability Workshop Presentation Transcript

    • NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC. Complex Flow Research and Its Relation to Reliability Pat Moriarty Matt Churchfield Sang Lee Paul Fleming Julie Lundquist John Michalakes Avi Purkayastha Mike Sprague
    • 2 Motivation • Development of validated simulation tools for wind plant operation within complex flow environment • Complex flow affects: o Power production o Fatigue loads o Both influence revenue generated • Current models lack physics Wind speed contours through the Lillgrund wind plant
    • 3 Underperformance and Uncertainty Industry average bias ~ -9% Uncertainty overestimated Johnson, AWEA WRC 2012
    • 4 Structural Loads Atmospheric state (stable vs. unstable) Kelley, 2011
    • 5 Wind Plant Modeling Research • Simulator fOr Wind Farm Applications (SOWFA) • High performance computing and engineering modules • Outcome – Improve industry tools – Guide experimentalists and understand physics TurbineFarm ArrayMesoscale Tools: Scale: WRF OpenFOAM FAST SOWFA
    • 6
    • 7 Results – Power Reasonable agreement with field data
    • 8 Results – Structural Loads Row D No field data
    • 9
    • 10 • SCADA data analysis • Detailed flow measurements o Turbine Wind and Inflow Characterization Study (TWICS) • Wake and inflow measurements of 2.3 MW turbine at NWTC • Influence of complex terrain and stability o Crop Wind Energy Experiment (CWEX) • Impact of changing roughness (i.e. corn) on wind farm performance • Impact of wind farm on crops • IEA Task 31: Wakebench Complex Flow Observation Research Figure courtesy A. Brewer Figure courtesy J. Lundquist
    • 11 SCADA Data Analysis Gaumond et al. (2011) Data is often highly averaged - physics are lost and model validation is suspect
    • 12 Complex Flow Field Campaigns • Full scale measurements o Higher resolution but expensive – New instrumentation developing quickly o Some physics only at full scale o Smaller scale testing o Combined observation and simulation Banta et al. 2013
    • 13 Wake Model Validation Higher fidelity models often do better, but not always! decreasing simulation fidelity Simulation Type From IEA Task 31: Sexbierum Single Wake Benchmark
    • 14 What can we do about it? • Complex flow will continue to exist • Improved plant layout and turbine design using better tools and physical understanding • Improved control systems
    • 15 Controls Research • Reacts to existing flow • Greedy turbines • Modify complex flow between turbines • Good neighbors Turbine Control Plant Control
    • 16 Wind Plant Control • Heat and flux • Wake steering – yaw, tilt, turbine motion
    • 17 Power Best case: Yaw: 4.6% Tilt: 7.1% Pos: 41%
    • 18 Structural Loading
    • 19 Conclusions • Complex flow is complex o Better understanding required to improve reliability o Many flow scales interact o Terrain and vegetation make things more complex o Combined observation and simulation required • Improvements possible using design and control • Future needs o Simulation tools now outpacing observations o Need data for validation – Higher fidelity flow and SCADA data – Data mining techniques – QA/QC – Good meteorological data on operating wind plants – Structural loading data o Technology transfer to industry tools