Research on DFIG-ES System to Enhance the Fast-Frequency Response Capability of Wind Farms

Abstract

With the increasing penetration of wind power generation, the frequency regulation burden on conventional synchronous generators has become heavier, as the rotor speed of doubly-fed induction generator (DFIG) is decoupled with the system frequency. As the frequency regulation capability of wind farms is an urgent appeal, the inertia control of DFIG has been studied by many researchers and the energy storage (ES) system has been installed in wind farms to respond to frequency deviation with doubly-fed induction generators (DFIGs). In view of the high allocation and maintenance cost of the ES system, the capacity allocation scheme of the ES system—especially for fast-frequency response—is proposed in this paper. The capacity allocation principle was to make the wind farm possess the same potential inertial energy as that of synchronous generators set with equal rated power. After the capacity of the ES system was defined, the coordinated control strategy of the DFIG-ES system with consideration of wind speed was proposed in order to improve the frequency nadir during fast-frequency response. The overall power reference of the DFIG-ES system was calculated on the basis of the frequency response characteristic of synchronous generators. In particular, once the power reference of DFIG was determined, a novel virtual inertia control method of DFIG was put forward to release rotational kinetic energy and produce power surge by means of continuously modifying the proportional coefficient of maximum power point tracking (MPPT) control. During the deceleration period, the power reference smoothly decreased with the rotor speed until it reached the MPPT curve, wherein the rotor speed could rapidly recover by virtue of wind power so that the secondary frequency drop could be avoided. Afterwards, a fuzzy logic controller (FLC) was designed to distribute output power between the DFIG and ES system according to the rotor speed of DFIG and S o C of ES; thus the scheme enabled the DFIG-ES system to respond to frequency deviation in most cases while preventing the secondary frequency drop and prolonging the service life of the DFIG-ES system. Finally, the test results, which were based on the simulation system on MATLAB/Simulink software, verified the effectiveness of the proposed control strategy by comparison with other control methods and verified the rationality of the designed fuzzy logic controller and proposed capacity allocation scheme of the ES system.

Research on Coordinated Control Strategy of DFIG-ES System Based on Fuzzy Control

“…Using the ES system to compensate the virtual inertia control of the wind turbine can improve the energy utilization rate of the ES battery, significantly reduce the power system's rotating reserve capacity, and achieve the goal of lowering the overall system cost [19]. Droop control is commonly used in ES systems to participate in system frequency modulation.…”

Wind-Storage Combined Virtual Inertial Control Based on Quantization and Regulation Decoupling of Active Power Increments

“…The power tracking curve described by Equation ( 3) can also be written as Equation (15). It can be seen that the curve can be 'shifted' by changing its coefficient k opt , to adjust the active power output of the DFIG unit [36]. As shown in Figure 4, the unit operates at point A in a steady-state in MPPT mode.…”