Abstract
The accuracy of doubly fed induction generator (DFIG) models and parameters plays an important role in power system operation. This paper proposes a parameter identification method based on the hybrid genetic algorithm for the control system of DFIG converters. In the improved genetic algorithm, the generation gap value and immune strategy are adopted, and a strategy of “individual identification, elite retention, and overall identification” is proposed. The DFIG operation data information used for parameter identification considers the loss of rotor current, stator current, grid-side voltage, stator voltage, and rotor voltage. The operating data of a wind farm in Zhangjiakou, North China, were used as a test case to verify the effectiveness of the proposed parameter identification method for the Maximum Power Point Tracking (MPPT), constant speed, and constant power operation conditions of the wind turbine.
Highlights
State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, College of Artificial Intelligence and Data Science, Hebei University of Technology, Tianjin 300401, China; Abstract: The accuracy of doubly fed induction generator (DFIG) models and parameters plays an important role in power system operation
Considering the depletion of fossil fuels and the threat that greenhouse gas emissions pose to the global climate, the proportion of renewable energy will continue to expand [1], and wind power is poised to be a major contributor to this expansion
As large-scale wind turbine integration will greatly affect the stability of the power system, the accuracy of the power system model has become an important technical issue in the operation, which needs to be consistent with the physical system, and the accuracy of the parameters is the key to ensuring model correctness
Summary
Transmission chain system, wound induction generator, and control system has beenwidely widely usedinin power systems and is mainly composed of a used wind power systems and is mainly composed ofsystem, a wind [22]. 1 been shows the structure ofwind the DFIG-based wind power generation wind turbine, transmission chain system, wound induction generator, and control system turbine, transmission chainare system, wound induction generator, system [22]. Where the stator windings directly connected to the grid andand the control rotor windings are [22]. Figure shows the structure of the power generation system, power generation system, where directly connected to the external power grid through back-to-back converters [23]. The back-toplitude, frequency, and phase, andgrid ensures thatback-to-back the slip powerconverters can flow in both directions. Back-to-back converter provides three-phase rotor excitation with adjustable amback converter provides three-phase rotor excitation power power with adjustable amplitude, plitude, frequency, and phase, and ensures that the slip power can flow in both directions. Frequency, and phase, and ensures that the slip power can flow in both directions
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