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Finite control set model predictive control method of LCL energy storage converter

A technology of model predictive control and finite control set, applied in the direction of converting AC power input to DC power output, output power conversion device, electrical components, etc. Performance and other issues

Active Publication Date: 2019-12-03
安徽船途数字科技有限公司
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Problems solved by technology

[0004] In addition, traditional control methods do not take into account the impact of delay on the control system in practical applications, which greatly reduces system performance and affects the quality of incoming current

Method used

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  • Finite control set model predictive control method of LCL energy storage converter
  • Finite control set model predictive control method of LCL energy storage converter
  • Finite control set model predictive control method of LCL energy storage converter

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Embodiment Construction

[0073] The invention discloses an improved finite control set model predictive control method for a battery energy storage converter including an LCL filter.

[0074] state variable estimation

[0075] The first content of the present invention is to estimate the converter side current, capacitor voltage and grid current according to the measured grid current. For the specific estimation method, see figure 1 . First, the LCL model is transformed into a state space equation, and then it is discretized to obtain a discretized LCL model.

[0076] x=[i 1 i 2 u c ] represent three state variables, v i Indicates the converter output voltage, v g Indicates the grid voltage, T s represents the sampling time; the state-space equation:

[0077]

[0078] in, B=[1 / L 1 0 0] T ,B d =[0-1 / L 2 0] T ,

[0079] Discretized LCL model:

[0080] x(k+1)=A 1 x(k)+B 1 v i (k)+B 2 v g (k) (2)

[0081]

[0082] Since the variable sampled in this example is the grid volt...

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Abstract

The invention discloses a finite control set model predictive control method of an LCL type energy storage converter. The state variable estimation is combined with delay compensation. The converter side current, the capacitor voltage and the grid current are estimated by sampling grid current, and the error between the sampled grid current and the estimated grid current is subjected to a correction matrix to reduce the influence caused by model mismatch and parameter drift, and then the estimated state variables are subjected to the finite control set model predictive control algorithm with the delay compensation link so as to improve the system performance and finally realize the control of the LCL energy storage converter. The number of sensors can be reduced, the cost can be reduced and the reliability of the system can be enhanced; and the influence of calculation delay on the system performance is eliminated through combination of the delay compensation algorithm and thus the quality of incoming current is improved.

Description

technical field [0001] The invention relates to the technical field of electrical automation and new energy electric energy conversion equipment, in particular to a finite control set model predictive control method for an LCL type energy storage converter. Background technique [0002] The energy storage converter (hereinafter referred to as the converter) is one of the key components in the distributed energy storage system, which can convert the DC power generated by the battery into AC power and integrate it into the grid, and realize the two-way transmission of energy. In order to make the incoming current conform to the harmonic standard, in addition to adopting many linear control strategies, many nonlinear control strategies are gradually applied to the energy storage converter. For example, with the improvement of DSP and FPGA computing speed in recent years, finite control set model predictive control has been widely used. The control method is simple to implement...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H02J3/32H02M7/5387
CPCH02J3/32H02M7/53871
Inventor 高宁陈小涛吴卫民陈昊李波
Owner 安徽船途数字科技有限公司
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