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MDPSO-based parameter identification method for permanent magnet direct-driven wind driven generator

A wind power generator, permanent magnet direct drive technology, applied in the control of generators, motor generator control, electronic commutation motor control, etc., can solve poor convergence accuracy, difficult multi-parameter identification of permanent magnet direct drive wind power generators, Problems such as low wind energy utilization rate of permanent magnet direct drive wind turbines

Inactive Publication Date: 2019-11-22
XINJIANG UNIVERSITY
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Problems solved by technology

[0004] The present invention provides a parameter identification method of permanent magnet direct drive wind power generator based on MDPSO, which overcomes the deficiencies of the above-mentioned prior art, and can effectively solve the problem of difficult multi-parameter identification of permanent magnet direct drive wind power generator, and further solve the problem of The traditional parameter identification method has poor convergence accuracy and slow convergence speed, which affects the control effect of the wind turbine and makes the wind energy utilization rate of the permanent magnet direct drive wind turbine low.

Method used

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  • MDPSO-based parameter identification method for permanent magnet direct-driven wind driven generator
  • MDPSO-based parameter identification method for permanent magnet direct-driven wind driven generator
  • MDPSO-based parameter identification method for permanent magnet direct-driven wind driven generator

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Embodiment 1

[0075] Embodiment 1: as attached figure 1 , 2 , 3, and 4, the MDPSO-based permanent magnet direct drive wind turbine parameter identification method includes the following steps:

[0076] S1: Sampling and identifying the required parameters of the wind turbine, select the motor speed measured at the motor outlet and the three-phase current output by the motor, and use the direct axis voltage u of the current controller d and quadrature voltage u q , to establish the permanent magnet direct drive wind turbine stator voltage and current model:

[0077]

[0078] Among them: u d , u q are the d-axis and q-axis components of the stator voltage, respectively; i d i q are the d-axis and q-axis components of the stator current; R is the resistance of the stator; ω r is the electrical angular velocity; L d , L q is the inductance component of the d-axis and q-axis; ψ represents the flux linkage of the permanent magnet; p=d / dt;

[0079] S2: Carry out pade approximation and...

Embodiment 2

[0143] Embodiment 2: as attached Figures 6 to 11 As shown and as shown in Table 1 and 2, the present embodiment is to build a permanent magnet direct drive wind turbine under the Simulink platform in MATLAB, and the simulation sampling time is set to be T s = 0.00001s, the SVPWM modulation frequency is set to 20KHz, the parameters of the permanent magnet synchronous generator model are shown in Table 1.

[0144] The permanent magnet direct drive wind turbine is under the condition that the d-axis current is 0, the constant torque is 2N·m, and the speed is 500r / min, and 4000 sets of data are obtained, and the sampling frequency is 20kHz. The particle swarm parameters are set as follows: the particle swarm dimension is 7, the population number is 80, the number of iterations is 30, and c1, c2, and c3 are all set to 1.59.

[0145] In this embodiment, the number of iterations of the fitness function value obtained by PSO, DPSO, and MDPSO three methods is as follows: Image 6As ...

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Abstract

The invention relates to the technical field of parameter identification of permanent magnet wind driven generators, in particular to an MDPSO-based parameter identification method for a permanent magnet direct-driven wind driven generator. The method comprises the following steps of S1, sampling and identifying required parameters of a wind driven generator, and establishing a stator voltage andcurrent model of the permanent magnet direct-driven wind driven generator; S2, establishing and obtaining a permanent magnet direct-driven wind power generation identification model; S3, establishingan error objective function J (theta); S4, optimizing and solving the error objective function J (theta) by using an MDPSO algorithm to obtain optimal solutions of aq, bq, cq and dq; S5, calculating parameters R, Ld, Lq and psi of the wind driven generator to be identified; and S6, dynamically setting the PI parameter controlled by the current inner loop of the machine-side converter according tothe Mrmin criterion to obtain a new PI parameter value. According to the improved particle swarm optimization algorithm MDPSO of the self-adaptive space search vector and the average optimal positionvariable, the improved MDPSO algorithm has high robustness, high convergence precision and high convergence speed, and the problem that a common particle swarm optimization algorithm is prone to falling into a local optimal solution is solved.

Description

technical field [0001] The invention relates to the technical field of parameter identification of a permanent magnet wind power generator, and relates to a parameter identification method of a permanent magnet direct drive wind power generator based on MDPSO. Background technique [0002] Today, there are two types of variable-speed constant-frequency wind turbines that are widely used: doubly-fed induction wind turbines (DFIG) and permanent magnet direct-drive wind turbines (D-PMSG). Compared with DFIG, D-PMSG has the characteristics of simple structure, high power generation rate, low noise and small maintenance workload, and has received more and more attention in the field of wind power generation. Generally speaking, the vector control system of the PMSG machine-side converter is usually an outer speed loop and an inner current loop (usually the inner and outer loop controllers are mainly PI controllers), and the vector control performance is also affected by the quali...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H02P21/00H02P21/14H02P21/22
CPCH02P21/0003H02P21/14H02P21/22
Inventor 蔺红吴章晗
Owner XINJIANG UNIVERSITY
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