scholarly journals Electromechanical Transient Modeling and LVRT Parameter Identification of Large Capacity Full Power Converter Wind Turbines Based on PSASP Program

2021 ◽  
Vol 2108 (1) ◽  
pp. 012002
Author(s):  
Guoqiang Lu ◽  
Xiangyu Tao ◽  
Chunmeng Chen ◽  
Jiatian Gan ◽  
Xufeng Zhao
Keyword(s):  
Parameter Identification ◽  
Wind Turbine ◽  
Low Voltage ◽  
Recovery Period ◽  
Power Converter ◽  
Control Mode ◽  
Model Parameters ◽  
Model Structure ◽  
Identification Method ◽  
Full Power

Abstract Full power converter wind turbine is the main type of wind power, so the simulation calculation needs to establish accurate model parameters. This paper analyzes the model structure of PSASP program according to its low voltage ride through control and physical characteristics, and puts forward the parameter identification method of LVRT characteristics of full power converter wind turbine, and to use the LVRT data of 5. 5MW unit for parameter identification and simulation verification. This paper proposes that the electromechanical transient simulation can ignore the part of the generator model of the full power converter wind turbine, and simulates the grid side converter with the controlled current source. The main characteristics of LVRT are determined by the control system of the converter. In order to do the parameter identification, it is necessary to calculate and analyze the control characteristics of multiple measured data. First, determine the control mode, then determine the control parameters to complete the parameter identification. In this paper, the modeling conditions and model structure of the full power converter wind turbine are confirmed. The correlation between the parameters during the LVRT fault and the parameters during the LVRT recovery period and the LVRT characteristics is analyzed. In this paper, a parameter identification method is proposed to analyze the active current and reactive current during the LVRT fault, which has strong physical significance and operability. Based on the actual LVRT characteristics of 5. 5MW wind turbine, the parameter identification and simulation are carried out to verify the correctness of the method.

Parameter Identification for Nonlinear Dry-Friction Structure of Metallic Rubber

2011 ◽  
Vol 52-54 ◽  
pp. 494-499
Author(s):  
Yu Yan Li ◽  
Xie Qing Huang ◽  
Kai Song
Keyword(s):  
Parameter Identification ◽  
Dry Friction ◽  
Friction Angle ◽  
Element Model ◽  
Parameters Identification ◽  
Axial Stiffness ◽  
Model Parameters ◽  
Structural Element ◽  
Identification Method ◽  
Metallic Rubber

In order to reduce workload of parameter identification for nonlinear mechanical model of metallic rubber, in this paper, based on parameters identification method of static experimental curves, experiments were designed, and data were processed, further aimed at hollow cylindrical metallic rubber, nonlinear dry-friction structural element model’ parameters were identified, what’s more, friction coefficient, radial stiffness, axial stiffness, and friction angle of stainless wire under room temperature were obtained. It was proved by simulation that parameters identification method in this paper was effective and accurate. Based on this, errors of simulation were analyzed elaborately.

Parameter Identification for HAPC System in Hot Tandem Mill

2010 ◽  
Vol 154-155 ◽  
pp. 781-786
Author(s):  
Xu Li ◽  
Wen Xue Zhang ◽  
Dian Hua Zhang ◽  
Dan Yan
Keyword(s):  
Experimental Data ◽  
Mathematical Model ◽  
Parameter Identification ◽  
Actual Data ◽  
Automation System ◽  
Model Parameters ◽  
Simulation Data ◽  
Matlab Software ◽  
Identification Method ◽  
Curve Fit

Under condition that exact values of model parameters can not be calculated accurately in hot tandem mill system and change with the time passing, model parameters are identified by adopting identification method based on the parameter model and sampling the datum on site; Basic automation system is used for the sampling of actual data, MATLAB software is adopted for curve fit. By comparing the experimental data and simulation data, the consequence of simulation testifies the accuracy of identified mathematical model.

A UAV MODEL PARAMETER IDENTIFICATION METHOD: A SIMULATION STUDY

2009 ◽  
Vol 06 (04) ◽  
pp. 225-238 ◽  
Author(s):  
K. S. HATAMLEH ◽  
O. MA ◽  
R. PAZ
Keyword(s):  
Parameter Identification ◽  
Control Strategies ◽  
Least Square ◽  
Model Parameters ◽  
Dynamics Modeling ◽  
Recursive Least Square ◽  
Nonlinear Dynamical ◽  
Model Parameter ◽  
Identification Method ◽  
Model Parameter Identification

Dynamics modeling of Unmanned Aerial Vehicles (UAVs) is an essential step for design and evaluation of an UAV system. Many advanced control strategies for nonlinear dynamical or robotic systems which are applicable to UAVs depend upon known dynamics models. The accuracy of a model depends not only on the mathematical formulae or computational algorithm of the model but also on the values of model parameters. Many model parameters are very difficult to measure for a given UAV. This paper presents the results of a simulation based study of an in-flight model parameter identification method. Assuming the motion state of a flying UAV is directly or indirectly measureable, the method can identify the unknown inertia parameters of the UAV. Using the recursive least-square technique, the method is capable of updating the model parameters of the UAV while the vehicle is in flight. A scheme of estimating an upper bound of the identification error in terms of the input data errors (or sensor errors) is also discussed.

Control Strategy of Full Power Converter for Wind Turbine under Grid Voltage Swell

2013 ◽  
Vol 448-453 ◽  
pp. 1815-1818 ◽  
Author(s):  
Zi Xu Lin ◽  
Hong Hua Xu ◽  
Wang Jian
Keyword(s):  
Wind Turbine ◽  
Control Strategy ◽  
Reactive Power ◽  
Power Converter ◽  
Grid Voltage ◽  
Dynamic Voltage ◽  
Voltage Swell ◽  
Voltage Swells ◽  
Full Power ◽  
The Impact

LVRT technology is currently a hot research of wind power, but the impact on the wind turbine of grid voltage swells and HVRT technology have not been given sufficient attention. This article analyzed the converter problems of full power wind turbine on grid voltage swells and used the control strategy of reactive power control, dynamic voltage and over-modulation to enhance the full power wind turbines HVRT capability.

scholarly journals An Asymmetric Hysteresis Model and Parameter Identification Method for Piezoelectric Actuator

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Haichen Qin ◽  
Ningbin Bu ◽  
Wei Chen ◽  
Zhouping Yin
Keyword(s):  
Parameter Identification ◽  
Smart Materials ◽  
Model Parameters ◽  
Hysteresis Model ◽  
Pzt Actuator ◽  
Modified Particle Swarm Optimization ◽  
Identification Method ◽  
Model Based ◽  
Asymmetric Factor ◽  
Hysteresis Behaviour

Hysteresis behaviour degrades the positioning accuracy of PZT actuator for ultrahigh-precision positioning applications. In this paper, a corrected hysteresis model based on Bouc-Wen model for modelling the asymmetric hysteresis behaviour of PZT actuator is established by introducing an input biasφand an asymmetric factorΔΦinto the standard Bouc-Wen hysteresis model. A modified particle swarm optimization (MPSO) algorithm is established and realized to identify and optimize the model parameters. Feasibility and effectiveness of MPSO are proved by experiment and numerical simulation. The research results show that the corrected hysteresis model can represent the asymmetric hysteresis behaviour of the PZT actuator more accurately than the noncorrected hysteresis model based on the Bouc-Wen model. The MPSO parameter identification method can effectively identify the parameters of the corrected and noncorrected hysteresis models. Some cases demonstrate the corrected hysteresis model and the MPSO parameter identification method can be used to model smart materials and structure systems with the asymmetric hysteresis behaviour.

Simultaneous structure and parameter identification of multivariate systems by matrix decomposition

2016 ◽  
Vol 38 (12) ◽  
pp. 1411-1420 ◽  
Author(s):  
Benben Jiang ◽  
Fan Yang ◽  
Dexian Huang
Keyword(s):  
Parameter Identification ◽  
Structure Determination ◽  
Information Matrix ◽  
Matrix Decomposition ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Model Structure ◽  
Multiple Model ◽  
Process Data ◽  
Multivariate Systems

Structure determination and parameter identification of multivariate systems are crucial but rather difficult issues in system identification. Due to the explosive growth of process data along with the scale increase of industrial processes, directional links between variables of such complex processes are often undistinguishable, which is indispensable to model structure determination but is often assumed to be known beforehand in most identification methods. In this article, a new modelling approach is developed to simultaneously estimate the model parameters and structures (including model orders as well as the directional links between different process variables) of multivariate systems. A vector auto-regressive (VAR) form is utilized as the model formulation in this algorithm. The key technique lies in constructing an interleaved information matrix with respect to a multiple model structure formulated for the VAR representation. Then by utilizing the upper diagonal factorization, all the parameter estimates of all path models with orders from zero to m, as well as the corresponding cost function values, can be obtained simultaneously. The effectiveness of the proposed method is demonstrated via a numerical example and a distillation column system.

An Investigation of the Low Voltage Ride through Function of GE DFIG Wind Turbines for Electro-Mechanical Simulations

2012 ◽  
Vol 608-609 ◽  
pp. 537-542
Author(s):  
Zhao Jun Meng
Keyword(s):  
Wind Turbine ◽  
Large Scale ◽  
Low Voltage ◽  
Short Circuit ◽  
Wind Farms ◽  
Power Converter ◽  
System Stability ◽  
Total System ◽  
Detailed Model ◽  
Low Voltage Ride Through

Doubly-fed induction generator (DFIG) wind turbine has become the most widely used wind turbine in wind farms, since it presents noticeably advantages such as decoupled controls of active and reactive powers, and the use of a power converter with a rated power of 25% of total system power. As the penetration of wind power in power system increases, it is required that the wind turbine remained connected and actively contributed to the system stability during and after faults and disturbance. One common approach for a DFIG to obtain such low voltage ride through (LVRT) function is to install a crowbar circuit across its rotor terminals, which short circuit the rotor side converter when over-current is detected in the rotor. A detailed model of LVRT function normally requires electromagnetic simulations. However, the time consuming computational process is prohibitive for the studies of the integration of wind farms into large scale power systems. Electromechanical simulations are more suitable for such engineering applications. GE has incorporated the LVRT function into its recently released DFIG wind turbine model for Electro-mechanical simulations. This paper has implemented this model and verified the effectiveness of the LVRT function.

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