Dynamic programming strategy in optimal controller design for a wind turbine system

Figures & data

Table 1. Value of aerodynamic power coefficient (Cortes-Vega et al., 2021).

Variable	$C_1$	$C_2$	$C_3$	$C_4$	$C_5$
Value	0.51760	116.00	0.40	5.00	21.00

Figure 1. C_p versus TSR with different pitch angles.

Figure 2. Mechanical power versus rotor speed for different wind speeds.

Figure 3. Recursive dynamic programming algorithm flow chart.

Figure 4. DPM and STC wind energy capture using piecewise wind speed.

Figure 5. DPM and STC wind energy capture using randomly generated wind speed.

Table 2. Parameters of the wind turbine system.

Rated power, Prated	100 KW
Rotor moment of inertia, Jr	2.6 × 10^4 Kg.m^2
Rotor diameter, Dr	18 m
Gear ratio, Gr	21.5858
Max. turbine rotor speed, (𝜔r) max	12 rad/sec
Min. turbine rotor speed, (𝜔r)min	2.75 rad/sec
Max. blade pitch angle,	25 degree
Min. blade pitch angle, 𝛽min	0 degree
Max. Generator input torque, (𝜏g)max	1500 Nm
Min. Generator input torque, (𝜏g)min	0 Nm
Global max. value of Cp (Cp)max	0.4212
Value of 𝜆 corresponding to (Cp)max, 𝜆∗	8.0
Value of 𝛽 corresponding to (Cp)max, 𝛽∗	0°
Rated wind speed	12.5 m/s

Cortes-Vega, D., Ornelas-Tellez, F., & Anzurez-Marin, J. (2021). Nonlinear optimal control for PMSG-based wind energy conversion systems in advances in industrial control series. IEEE Latin America Transactions, 19(7), 1191–1198. https://doi.org/10.1109/TLA.2021.9461848

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