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Wind Farm Control for Optimal Power Generation and Fatigue Reduction: Strategies and Experimentation in Wind Tunnel

Wang, Fa
http://orcid.org/0000-0002-8040-8676
http://rave.ohiolink.edu/etdc/view?acc_num=case1491350425071592

Abstract Details

2017, Doctor of Philosophy, Case Western Reserve University, EECS - System and Control Engineering.
This work presents and validates experimentally new methodologies to design Maximum Power Point Tracking (MPPT) control strategies for variable speed wind turbines. The first technique of this study is an Extremum Seeking (ES) control strategy with no requirements for wind turbine model or wind speed measurements. As a comparison, Perturb and Observe (P&O) and Power Signal Feedback (PSF) are also designed and tested. All of the approaches are verified in Matlab simulations and experimentally tested with a lab-scale wind turbine and a fully instrumented wind tunnel. As a result, this work presents a new ES control algorithm that takes into account the energy production and rotor life expectancy. Furthermore, this work also considers wind farm level optimal control. The power generation of a wind farm depends on the efficiency of the individual wind turbines in the farm. In large wind farms, wind turbines affect aerodynamically each other. Previous studies suggest that a way to maximize the power generation of the wind farm is to reduce the generation of the wind turbines of the first rows to allow the next rows to generate more power (Case 2). Yet, other studies indicate that the maximum generation of the wind farm is reached when every wind turbine works at its optimum power coefficient Cp (Case 1). This work studies this controversy and proposes a method to evaluate when the wind farm should be coordinated as Case 1 or as Case 2. The discussion is based on the mathematical model of the wind farm, numerical computations and wind tunnel experiments.
Mario Garcia-Sanz (Advisor)
Vira Chankong (Committee Member)
Chris Papachristou (Committee Member)
Sree Sreenath (Committee Member)
101 p.
Electrical Engineering; Energy
Wind Energy; MPPT; Wind Farm Control; Fatigue Reduction; Extremum Seeking Control

Recommended Citations

Citations

  • Wang, F. (2017). Wind Farm Control for Optimal Power Generation and Fatigue Reduction: Strategies and Experimentation in Wind Tunnel [Doctoral dissertation, Case Western Reserve University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=case1491350425071592

    APA Style (7th edition)

  • Wang, Fa. Wind Farm Control for Optimal Power Generation and Fatigue Reduction: Strategies and Experimentation in Wind Tunnel. 2017. Case Western Reserve University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=case1491350425071592.

    MLA Style (8th edition)

  • Wang, Fa. "Wind Farm Control for Optimal Power Generation and Fatigue Reduction: Strategies and Experimentation in Wind Tunnel." Doctoral dissertation, Case Western Reserve University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=case1491350425071592

    Chicago Manual of Style (17th edition)

case1491350425071592
182
© 2017, all rights reserved.
This open access ETD is published by Case Western Reserve University School of Graduate Studies and OhioLINK.