Aerodynamic interaction among turbines grouped together in wind farms causes a decrease in the total energy extracted from the wind when compared to an equal number of widely dispersed turbines operating under the same wind input conditions as the wind farm. Extremum seeking control (ESC) is one strategy that holds promise for reducing this impact under certain wind input conditions. In this paper, we evaluate the effectiveness of ESC under different turbulence conditions, describing methods for addressing the complexities caused by the turbulent wind input and time-varying delay of the wind between turbines, where these two elements are the most important contributions compared to other wind farm control research. The results show that energy capture can be increased in low turbulence intensity conditions, but perhaps not in high turbulence conditions.
ManwellJ. F.McGowanJ. G.RogersA. L., Wind Energy Explained: Theory, Design, and Application. West Sussex, England: John Wiley & Sons Ltd, 2002.
2.
PaoL.JohnsonK., “Control of wind turbines: Approaches, challenges, and recent developments,”IEEE Control Systems Magazine, Vol. 31, no. 2, pp. 44–62, 2011.
3.
LiuM.YockeM.MyersT., “Mathematical model for the analysis of wind-turbine wakes,”J. Energy, Vol. 7, no. 1, pp. 73–78, 1983.
4.
SchepersJ. G.van der PijlS. P., “Improved modeling of wake aerodynamics and assessment of new farm control strategies,”J. Physics: Conference Series, Vol. 75, Paper # 012039, 2007.
5.
SteinbuchM.de BoerW. W.BosgraO. H.PetersS. A. W. M.PloegJ., “Optimal control of wind power plants,”J. Wind Energy and Industrial Aerodynamics, Vol. 27, pp. 237–246, 1988.
6.
BjarnasonB.SveinssonO., “Wind farm controller: Optimization of power production,”M.S. thesis, Technical University of Denmark, 2010.
7.
SoleimanzadehM.WisniewskiR., “Controller design for a wind farm, considering both power and load aspects,”Mechatronics, Vol. 21, no. 4, pp. 720–727, 2011.
8.
MardenJ.RubenS.PaoL., “Surveying game theoretic approaches for wind farm optimization,”Proc. AIAA Aerospace Sciences Meeting, Nashville, TN, Jan. 2012, pp. 1–10.
9.
CreabyJ., “Maximizing wind power capture using multi-variable extremum seeking control,”M.S. thesis, University of Wisconsin-Milwaukee, 2008.
10.
GodoyB.BraslavskyJ.AgueroJ., “A simulation study on model predictive control and extremum seeking control for heap bioleaching processes,”Proc. IFAC World Congress, 2008.
11.
DochainD.PerrierM.GuayM., “Extremum seeking control and its application to process and reaction systems: A survey,”Mathematics and Computers in Simulation, to be published.
12.
LeyvaR.ArtillanP.CabalC.EstibalsB.AlonsoC., “Dynamic performance of maximum power point tracking circuits using sinusoidal extremum seeking control for photovoltaic generation,”Int. J. Electronics, Vol. 98, no. 4, pp. 529–542, 2011.
13.
LeiP.LiY.SeemJ., “Sequential ESC-Based Global MPPT Control for Photovoltaic Array With Variable Shading,”IEEE Trans. Sustainable Energy, Vol. 2, no. 3, pp. 348–358, 2011.
14.
BruntonS.RowleyC.KulkarniS.ClarksonC., “Maximum power point tracking for photovoltaic optimization using ripple-based extremum seeking control,”IEEE Trans. Power Electronics, Vol. 25, no. 10, pp. 2531–2540, 2010.
15.
LuJ.ZahediA., “Maximum efficiency point tracking control for fuel cell power systems,”Proc. 2010 Int. Conf. Power System Technology, Hangzhou, Oct., pp. 1–6.
16.
BizonN., “On tracking robustness in adaptive extremum seeking control on the fuel cell power plants,”Applied Energy, Vol. 87, pp. 3115–3130, 2010.
17.
AWSTruewind, OPENWIND: Theoretical Basis and Validation, September 2008. Available at http://www.awsopenwind.org/.
18.
KaticI.HøjstrupJ.JensenN. O., “A Simple Model for Cluster Efficiency”. Proc. European Wind Energy Conference and Exhibition, Rome, pp. 407–410, 1986.
19.
GrunnetJ. D.SoltaniM.KnudsenT.KragelundM.BakT., “Aeolus Toolbox for Dynamic Wind Farm Model, Simulation and Control,”Proc. of the 2010 European Wind Energy Conf., 2010. Available at http://www.ict-aeolus.eu/SimWindFarm/index.html.
JohnsonK.ThomasN., “Wind farm control: Addressing the aerodynamic interaction among wind turbines,”Proc. American Control Conf., 2010.
22.
KrstićM.WangH. H., “Stability of extremum seeking feedback for general nonlinear dynamic systems,”Automatica, Vol. 36, no. 4, pp. 595–601, 2000.
23.
KrstićM., “Performance improvements and limitations in extremum seeking control,”Systems & Control Letters, Vol. 39, pp. 313–326, 2000.
24.
BanavarR. N.ChichkaD. F.SpeyerJ. L., “Convergence and synthesis issues in extremum seeking control,”Int. J. Adaptive Control and Signal Processing, Vol. 17, pp. 751–762, 2003.
25.
TanY.NeŝićD.MareelsI., “On non-local stability properties of extremum seeking control,”Automatica, Vol. 42, pp. 889–903, 2006.
26.
MoaseW.ManzieC.BrearM., “Newton-like extremum-seeking for the control of thermoelastic instability,”IEEE Trans. on Automatic Control, Vol. 55, no. 9, pp. 2094–2105, 2010.
