Lucy Pao

Dr. Lucy Pao

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Academic Career Length

31Years (1996-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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25 October 2019 in Science
Verified
Journal Article
Open access
PDF file
PVPaul Veers
Paul Veers
KDKatherine Dykes
Katherine Dykes
ELEric Lantz
Eric Lantz
SBStephan Barth
Stephan Barth
CBCarlo L. Bottasso
Carlo L. Bottasso
RWRyan Wiser
Ryan Wiser
A multifaceted future for wind power: Modern wind turbines already represent a tightly optimized confluence of materials science and aerodynamic engineering. Veers et al. review the challenges and opportunities for further expanding this technology, with an emphasis on the need for interdisciplinary collaboration. They highlight the need to better understand atmospheric physics in the regions where taller turbines will operate as well as the materials constraints associated with the scale-up. The mutual interaction of turbine sites with one another and with the evolving features of the overall electricity grid will furthermore necessitate a systems approach to future development. Science , this issue p. eaau2027
1 July 2007 in American Control Conference (ACC)
Verified
Conference Paper
Closed access
DADaniel Y. Abramovitch
Daniel Y. Abramovitch
SASean Andersson
Sean Andersson
LPLucy Pao
Lucy Pao
GSGeorg Schitter
Georg Schitter
The atomic force microscope (AFM) is one of the most versatile tools in nanotechnology. For control engineers this instrument is particularly interesting, since its ability to image the surface of a sample is entirely dependent upon the use of a feedback loop. This paper will present a tutorial on the control of AFMs. We take the reader on a walk around the control loop and discuss each of the individual technology components. The major imaging modes are described from a controls perspective and recent advances geared at increasing the performance of these microscopes are highlighted.
1 November 2004 in Journal of Solar Energy Engineering
Verified
Journal Article
Closed access
PDF file
KJKathryn E. Johnson
Kathryn E. Johnson
LFLee J. Fingersh
Lee J. Fingersh
MBMark J. Balas
Mark J. Balas
LPLucy Pao
Lucy Pao
The standard region 2 control scheme for a variable-speed wind turbine, τc=Kω2, has several shortcomings that can result in significant power loss. The first of these is that there is no accurate way to determine the gain K; modeling programs are not accurate enough to represent all of the complex aerodynamics, and these aerodynamics change over time. Furthermore, it is not certain whether the value of K used in the standard control even provides for the maximum energy capture under real-world turbulent conditions. We introduce new control methods to address these issues. First, we show in simulation that using smaller values of K than the standard can result in increased energy capture. Second, we give simulation results showing that an optimally tracking rotor control scheme can improve upon the standard scheme by assisting the rotor speed in tracking wind-speed fluctuations more rapidly. Finally, we propose an adaptive control scheme that allows for maximum power capture despite parameter uncertainty.
1 January 2021 in Annual Reviews in Control
Verified
Journal Article
Closed access
LPLucy Pao
Lucy Pao
DZDaniel S. Zalkind
Daniel S. Zalkind
TGTodd Griffith
Todd Griffith
MCMayank Chetan
Mayank Chetan
MSMichael S. Selig
Michael S. Selig
ELEric Loth
Eric Loth
1 March 2009 in Asian Journal of Control
Verified
Journal Article
Closed access
PDF file
JBJ. A. Butterworth
J. A. Butterworth
LPLucy Pao
Lucy Pao
DAD. Y. Abramovitch
D. Y. Abramovitch
3 February 2021 in IEEE Transactions on Control Systems Technology
Verified
Journal Article
Closed access
MVMehdi Vali
Mehdi Vali
VPVlaho Petrovic
Vlaho Petrovic
LPLucy Pao
Lucy Pao
MKMartin Kuhn
Martin Kuhn
In this article, we propose a model predictive active power control (APC) enhanced by the optimal coordination of the structural loadings of wind turbines (WTs) operating with fully developed wind farm (WF) flows that have extensive interactions with the atmospheric boundary layer. In general, the APC problem, that is, distributing a WF power reference among the operating WTs, does not have a unique solution; this fact can be exploited for structural load alleviation of the individual WTs. Therefore, we formulated a constrained optimization problem to simultaneously minimize the WF power reference tracking errors and the structural load deviations of the WTs from their mean value. The wind power plant is represented by a dynamic 3-D large-eddy simulation model, whereas the predictive controller employs a simplified, computationally inexpensive model to predict the dynamic power and load responses of the turbines that experience turbulent WF flows and wakes. An adjoint approach is an efficient tool used to iteratively compute the gradient of the formulated parameter-varying optimal control problem over a finite prediction horizon. We have discussed the applicability, key features, and computational complexity of the controller by using a WF example consisting of $3\times 4$ turbines with different wake interactions for each row. The performance of the proposed adjoint-based model predictive control for APC was evaluated by measuring power reference tracking errors and the corresponding damage equivalent fatigue loads of the WT towers; we compared our proposed control design with recently published proportional–integral-based APC approaches.