Abstract
The traditional additional inertial control (T-AIC) strategy can provide frequency support for the directly-driven wind turbine with a permanent magnet synchronous generator (D-PMSG). However, due to the fixed control coefficients, the frequency modulation effect is poor under load and wind speed disturbances. In order to improve the frequency transient response of D-PMSG, a fuzzy adaptive additional inertial control strategy (FA-AIC) is proposed in this paper. A simplified D-PMSG model is established for the complexity and low calculation speed. A single-machine grid-connected system composed of a D-PMSG and an equivalent synchronous generator set (ESGS) is taken as the background and analysis of the principle of T-AIC. The proportional and derivative coefficient initial values in T-AIC are tuned by simulating the static characteristics and inertial response characteristics of the conventional synchronous generator set, and fuzzy control technology is introduced to adjust the proportional and derivative coefficients adaptively based on the frequency deviation and the frequency deviation change rate under load or wind speed disturbances. The simulation verification indicates that T-AIC, kinetic energy (KE)-based gain-AIC and FA-AIC all can utilize the D-PMSG additional inertial response to provide frequency support for grid-connected systems. Compared with T-AIC and KE-based gain-AIC, the proposed FA-AIC can not only provide more effective frequency support during load disturbances, but also suppress the frequency fluctuation caused by the wind speed variation and displays a better dynamic frequency regulation effect.
Highlights
As the main steam of renewable energy, wind power has become the fastest-growing new energy and will be a major source of electrical power in the near future [1,2,3]
In a traditional additional inertial control (AIC) (T-AIC) strategy, the proportional and derivative coefficients related to the system frequency deviation and frequency deviation change rate in the auxiliary control loops are usually predetermined to fixed values [15,16,17,18]
This means that under wind speed or load disturbances, a large coefficient can improve the D-PMSG frequency minimum value, but it might result in a minimum speed limit and participate in frequency regulation excessively, which is determined by the capacity of D-PMSG converter [19]
Summary
As the main steam of renewable energy, wind power has become the fastest-growing new energy and will be a major source of electrical power in the near future [1,2,3]. In a traditional AIC (T-AIC) strategy, the proportional and derivative coefficients related to the system frequency deviation and frequency deviation change rate in the auxiliary control loops are usually predetermined to fixed values [15,16,17,18] This means that under wind speed or load disturbances, a large coefficient can improve the D-PMSG frequency minimum value, but it might result in a minimum speed limit and participate in frequency regulation excessively, which is determined by the capacity of D-PMSG converter [19]. Since the T-AIC model for the D-PMSG wind turbine is nonlinear and the relations between the proportional/derivative coefficients and the frequency deviation under wind speed or load disturbances are complicated, the fuzzy logic control method is chosen as the adaptive controller in this paper.
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