Constrained power reference control for wind turbines

Zalkind, Daniel; Nicotra, Marco M.; Pao, Lucy Y.

doi:10.1002/we.2705

Cited by 13 publications

(7 citation statements)

References 22 publications

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“…When wind speeds exceed the typical cut-out wind speed threshold set at 25 m/s, wind turbines stop operating and can potentially be damaged (Zalkind et al, 2022). The percentage of area for extremes exceeding the cut-out wind speed under different scenarios is summarized in Table S3 in Supporting Information S1.…”

Section: Projected Changes In Extremes Exceeding the Cut-out Wind Speedmentioning

confidence: 99%

Ensemble Bayesian Model Averaging Projections of Wind‐Speed Extremes for Wind Energy Applications Over China Under Climate Change

Zhao,

Huang,

et al. 2024

JGR Atmospheres

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Wind energy has grown rapidly in recent years as a measure to control carbon emissions and mitigate climate change. Extreme wind can damage wind turbines, cause losses to wind power plants, limit economic benefits of wind energy facilities, and disrupt regional grid balance. Therefore, an accurate assessment of extreme wind speeds at wind turbine hub height and their spatiotemporal variation under climate change is critical for the planning of wind energy and for guaranteeing regional energy security. In this study, the 100‐m extreme wind speeds in China are estimated using an empirical downscaling and Bayesian model averaging ensemble method with the latest ERA5 reanalysis and 20 global climate models (GCMs) from the Coupled Model Intercomparison Project phase 6 (CMIP6). Two shared socioeconomic pathways (SSP), that is, SSP2‐4.5 and SSP5‐8.5, are considered to account for the uncertainty in anthropogenic emissions. According to the results, the highest extreme wind speeds are primarily found in Inner Mongolia, northeast China, western Tibet, and the eastern coastal region. Extreme wind speeds in central and southeastern China are projected to increase by approximately 2% in the middle (2031–2060) and the end (2071–2100) of the 21st century relative to the baseline period (1985–2014). Summer extreme wind speeds in northwestern Tibet are expected to increase by more than 9% at the end of the century. The findings of this study indicate that it is important to take the present and projected changes in local wind extremes into account when choosing locations for wind power plants and wind energy installations.

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Section: Projected Changes In Extremes Exceeding the Cut-out Wind Speedmentioning

confidence: 99%

Ensemble Bayesian Model Averaging Projections of Wind‐Speed Extremes for Wind Energy Applications Over China Under Climate Change

Zhao,

Huang,

et al. 2024

JGR Atmospheres

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“…As this was only a software algorithm change and did not require any new hardware or sensors, the increase in power capture meant a direct increase in revenue. Similarly, many controllers have been developed and experimentally shown to lead to lower structural loads (Bossanyi, 2003;Stol et al, 2006;Laks et al, 2011;Dunne et al, 2011;Bottasso et al, 2014a;Petrović and Bottasso, 2017;Sinner et al, 2021;Zalkind et al, 2021). Individual pitch controllers that vary the pitch angle of each blade independently (Bossanyi, 2003;Stol et al, 2006) can both improve the regulation of the generator speed as well as reduce structural loading compared to simpler collective blade pitch controllers wherein the pitch angles of all the blades are controlled collectively.…”

Section: Control and Co-designmentioning

confidence: 99%

Grand challenges in the design, manufacture, and operation of future wind turbine systems

Veers¹,

Bottasso²,

Manuel³

et al. 2023

Wind Energ. Sci.

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Abstract. Wind energy is foundational for achieving 100 % renewable electricity production, and significant innovation is required as the grid expands and accommodates hybrid plant systems, energy-intensive products such as fuels, and a transitioning transportation sector. The sizable investments required for wind power plant development and integration make the financial and operational risks of change very high in all applications but especially offshore. Dependence on a high level of modeling and simulation accuracy to mitigate risk and ensure operational performance is essential. Therefore, the modeling chain from the large-scale inflow down to the material microstructure, and all the steps in between, needs to predict how the wind turbine system will respond and perform to allow innovative solutions to enter commercial application. Critical unknowns in the design, manufacturing, and operability of future turbine and plant systems are articulated, and recommendations for research action are laid out. This article focuses on the many unknowns that affect the ability to push the frontiers in the design of turbine and plant systems. Modern turbine rotors operate through the entire atmospheric boundary layer, outside the bounds of historic design assumptions, which requires reassessing design processes and approaches. Traditional aerodynamics and aeroelastic modeling approaches are pressing against the limits of applicability for the size and flexibility of future architectures and flow physics fundamentals. Offshore wind turbines have additional motion and hydrodynamic load drivers that are formidable modeling challenges. Uncertainty in turbine wakes complicates structural loading and energy production estimates, both around a single plant and for downstream plants, which requires innovation in plant operations and flow control to achieve full energy capture and load alleviation potential. Opportunities in co-design can bring controls upstream into design optimization if captured in design-level models of the physical phenomena. It is a research challenge to integrate improved materials into the manufacture of ever-larger components while maintaining quality and reducing cost. High-performance computing used in high-fidelity, physics-resolving simulations offer opportunities to improve design tools through artificial intelligence and machine learning, but even the high-fidelity tools are yet to be fully validated. Finally, key actions needed to continue the progress of wind energy technology toward even lower cost and greater functionality are recommended.

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“…The pitch controller proportional and integral gains are optimized to minimize tower base fore‐aft DELs without violating a 20% rotor overspeed constraint. This design objective, as suggested by Zalkind et al, 44 was chosen to ensure sufficient rotor speed tracking without imposing unnecessary loading on the wind turbine tower. The resulting tuning parameters from this optimization are shown in Table 2, and the complete DLC results from the BAR‐USC rotor with this controller tuning are used as the baseline in Section 6.6.…”

Section: Controller Formulationmentioning

confidence: 99%

Aero‐servo‐elastic co‐optimization of large wind turbine blades with distributed aerodynamic control devices

et al. 2023

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This work introduces automated wind turbine optimization techniques based on full aero‐servo‐elastic models and investigates the potential of trailing edge flaps to reduce the levelized cost of energy (LCOE) of wind turbines. The Wind Energy with Integrated Servo‐control (WEIS) framework is improved to conduct the presented research. Novel methods for the generic implementation and tuning of trailing edge flap devices and their controller are also introduced. Primary flap and controller parameters are optimized to demonstrate potential maximum blade tip deflection reductions of 21%. Concurrent design optimization (i.e., co‐design) of a novel segmented wind turbine blade with trailing edge flaps and its controller is then conducted to demonstrate blade cost savings of 5%. Additionally, rotor diameter co‐design optimization is demonstrated to reduce the LCOE by 1.3% without significant load increases to the tower. These results demonstrate the efficacy of control co‐design optimization using trailing edge flaps, and the entirety of this work provides a foundation for numerous control co‐design‐oriented studies for distributed aerodynamic control devices.

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Constrained power reference control for wind turbines

Cited by 13 publications

References 22 publications

Ensemble Bayesian Model Averaging Projections of Wind‐Speed Extremes for Wind Energy Applications Over China Under Climate Change

Ensemble Bayesian Model Averaging Projections of Wind‐Speed Extremes for Wind Energy Applications Over China Under Climate Change

Grand challenges in the design, manufacture, and operation of future wind turbine systems

Aero‐servo‐elastic co‐optimization of large wind turbine blades with distributed aerodynamic control devices

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