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Inverter model parameter self-adaptive identification method based on steepest descent method

A technology of adaptive identification and steepest descent method, applied in the field of power electronics and parameter identification, to achieve the effects of improving robustness, good dynamic and steady state tracking, fast dynamic and steady state tracking

Active Publication Date: 2020-10-02
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

However, at present, the existing parameter identification methods are mostly aimed at the L filter, and there are few studies on the LCL filter. However, in the model predictive control, in order to realize the accurate modeling of the system, it is necessary to know the precise parameters of the filter circuit, so it is urgent A complete LCL-type parameter identification method is required

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  • Inverter model parameter self-adaptive identification method based on steepest descent method
  • Inverter model parameter self-adaptive identification method based on steepest descent method
  • Inverter model parameter self-adaptive identification method based on steepest descent method

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[0052] The technical solutions will be clearly and completely described below with reference to the preferred examples of the present invention and the accompanying drawings.

[0053] like figure 1 As shown, the three-phase grid-connected inverter topology consists of a DC power supply, a three-phase inverter bridge, an LCL filter, and an AC grid. L 1 is the inverter side inductance, L 2 is the grid-side inductance, L 1 and L 2 The parasitic resistances are R 1 and R 2 , C is the filter capacitor, i 1a , i 1b , i 1c is the inverter side current, i ga, i gb , i gc is the grid-side current, v ca , v cb , v cc is the terminal voltage of the filter capacitor, v a , v b , v c is the inverter output voltage, v ga , v gb , v gc is the grid voltage.

[0054] Since the research object is a three-phase symmetrical system, the above formula can be simplified to a single-phase expression; the system state variable is selected as x(t)=[i 1 ,i g ,v c ] T , u(t)=[v,v...

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Abstract

The invention provides an inverter model prediction control parameter self-adaptive identification method based on a steepest descent method in order to solve the problem that inverter control robustness is affected by parameter mismatch of an LCL type grid-connected inverter filter. According to the method, an error between a state vector prediction value and a sampling value at the current moment is calculated; an objective function is established with the purpose of minimizing the error vector; gradient derivation is conducted on the objective function in the parameter matrix direction based on a steepest descent method; and the minimum value of the objective function is searched, and the parameter matrix is adjusted in real time through an adaptive algorithm, so that the parameter matrix is gradually converged to be close to the true value of the parameter matrix, and therefore, the inductance and capacitance parameters of the filter can be identified online, the filter parametersin the controller can be corrected online, and the robustness of the grid-connected inverter can be improved.

Description

technical field [0001] The invention belongs to the technical field of power electronics and parameter identification, and in particular relates to an inverter model parameter adaptive identification method based on the steepest descent method. Background technique [0002] With the energy crisis and environmental deterioration, my country is paying more and more attention to the development of renewable energy. In new energy power generation, grid-connected inverter is used as a bridge to convert DC power into high-quality AC power, and its performance directly affects the quality of grid-connected power. The robustness research of grid-connected inverter is also a new An important research topic of energy grid-connected power generation. [0003] The parameters of the power electronic system are an important factor affecting the control performance of the system, and the related theoretical research and practical application are also more and more concerned. On the one h...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H02M1/12H02M7/5387H02J3/38H02J3/01G06F30/20
CPCH02M1/126H02M7/5387H02J3/38H02J3/01G06F30/20H02J2203/20H02J2203/10Y02E40/40
Inventor 龙波朱子林李凌阳廖勇曹天旭
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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