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.
Highlights
With the rising emerging energy crisis and environmental problems, governments around the world are actively investing in the utilization and development of new renewable energy [1]
The overall power reference of the doubly-fed induction generator (DFIG)-energy storage (ES) system was calculated on the basis of the frequency response characteristic of synchronous generators
Considering that the capacity of ES is a main factor influencing the frequency regulating of wind farms, especially in the case where DFIG is unable to respond to frequency deviation under capability of wind farms, especially in the case where DFIG is unable to respond to frequency extreme wind speed, a capacity allocation scheme of ES will be discussed later in the paper
Summary
With the rising emerging energy crisis and environmental problems, governments around the world are actively investing in the utilization and development of new renewable energy [1]. The power reference was modified as the frequency deviation was set as input variable in the MPPT control link This scheme enables DFIG to utilize its inertial energy to realize fast-frequency response, DFIG would absorb much energy from the grid to recover its rotor speed, which would lead to the secondary frequency drop. This scheme increases the number of ES systems and creates unnecessary maintenance and management cost when the ES system is embedded at the DC bus of DFIG. The test results, which were based on the simulation system on MATLAB/Simulink software, verified the effectiveness of the proposed control scheme 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
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