CN118646243B - Converter control method, controller and power grid power conversion system - Google Patents
Converter control method, controller and power grid power conversion system Download PDFInfo
- Publication number
- CN118646243B CN118646243B CN202411089549.2A CN202411089549A CN118646243B CN 118646243 B CN118646243 B CN 118646243B CN 202411089549 A CN202411089549 A CN 202411089549A CN 118646243 B CN118646243 B CN 118646243B
- Authority
- CN
- China
- Prior art keywords
- model
- converter
- state
- state observer
- observer model
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 74
- 238000006243 chemical reaction Methods 0.000 title claims abstract description 13
- 238000012545 processing Methods 0.000 claims abstract description 24
- 230000005540 biological transmission Effects 0.000 claims abstract description 20
- 239000011159 matrix material Substances 0.000 claims description 42
- 230000006870 function Effects 0.000 claims description 24
- 238000005070 sampling Methods 0.000 claims description 22
- 238000012546 transfer Methods 0.000 claims description 22
- 238000004590 computer program Methods 0.000 claims description 6
- 230000000694 effects Effects 0.000 abstract description 4
- 230000014509 gene expression Effects 0.000 description 32
- 238000010586 diagram Methods 0.000 description 15
- 230000008859 change Effects 0.000 description 13
- 238000010276 construction Methods 0.000 description 8
- 230000008878 coupling Effects 0.000 description 7
- 238000010168 coupling process Methods 0.000 description 7
- 238000005859 coupling reaction Methods 0.000 description 7
- 230000008569 process Effects 0.000 description 7
- 238000013178 mathematical model Methods 0.000 description 5
- 238000004891 communication Methods 0.000 description 4
- 238000011217 control strategy Methods 0.000 description 4
- 230000009286 beneficial effect Effects 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 230000005764 inhibitory process Effects 0.000 description 3
- 230000003287 optical effect Effects 0.000 description 3
- 238000010248 power generation Methods 0.000 description 3
- 230000006978 adaptation Effects 0.000 description 2
- 239000003990 capacitor Substances 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 230000001629 suppression Effects 0.000 description 2
- 238000013016 damping Methods 0.000 description 1
- 230000006866 deterioration Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000000802 evaporation-induced self-assembly Methods 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 239000000446 fuel Substances 0.000 description 1
- 230000001939 inductive effect Effects 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02M—APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF
- H02M1/00—Details of apparatus for conversion
- H02M1/0003—Details of control, feedback or regulation circuits
- H02M1/0025—Arrangements for modifying reference values, feedback values or error values in the control loop of a converter
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/048—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators using a predictor
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for AC mains or AC distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02M—APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF
- H02M1/00—Details of apparatus for conversion
- H02M1/0003—Details of control, feedback or regulation circuits
- H02M1/0016—Control circuits providing compensation of output voltage deviations using feedforward of disturbance parameters
- H02M1/0019—Control circuits providing compensation of output voltage deviations using feedforward of disturbance parameters the disturbance parameters being load current fluctuations
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02M—APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF
- H02M1/00—Details of apparatus for conversion
- H02M1/12—Arrangements for reducing harmonics from AC input or output
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02M—APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF
- H02M7/00—Conversion of AC power input into DC power output; Conversion of DC power input into AC power output
- H02M7/42—Conversion of DC power input into AC power output without possibility of reversal
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Health & Medical Sciences (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Computation (AREA)
- Medical Informatics (AREA)
- Software Systems (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Feedback Control In General (AREA)
Abstract
The embodiment of the application provides a control method of a converter, a controller and a power grid power conversion system. The method is applied to a converter, the converter is used for converting electric energy of a power transmission network, the method comprises the steps of obtaining electric power data of the converter, and processing the electric power data by utilizing a pre-built converter control model to obtain control data of the converter, wherein the control data are used for controlling the running state of the converter, and the converter control model is obtained by dispersing a state observer model built by electric power parameters of a filter and parameter variation of the converter. The method is used for achieving the effect of improving the control performance of the converter.
Description
Technical Field
The present application relates to the field of electric energy conversion technologies, and in particular, to a control method of a converter, a controller, and a power grid power conversion system.
Background
With the shortage of energy and the environmental deterioration caused by fuel, renewable energy has entered a rapid development period as a new energy source, and distributed power generation systems based on renewable energy have become an important point of current research, and energy conversion of a main part of the distributed power generation systems has become more and more important. In order to attenuate the switching ripple of the output current, a filter is usually placed between the current transformer of the voltage source and the grid, and in different filter topologies, the filter is usually used as an interface between grid-connected converter and utility, since the filter performs better in terms of higher harmonic attenuation, achieves a smaller inductive voltage drop and saves physical size.
In order to reduce the influence that the filter may have on the stability of the distributed power generation system, the control mode of the current transformer in the conventional technology has the problem that the interference of the power grid voltage is restrained through a control strategy of an observer.
However, the control strategy for the current transformer in the conventional technology has a problem of low control performance.
Disclosure of Invention
Based on the foregoing, it is necessary to provide a control method, a controller and a power grid power conversion system for a converter according to the embodiments of the present application to achieve the effect of improving the control performance of the control strategy.
In a first aspect, an embodiment of the present application provides a method for determining a control model of a current transformer, where the method is applied to a current transformer, and the current transformer is used for converting electric energy of a power transmission network, and the method includes:
Acquiring power data of a converter;
And processing the electric power data by using a pre-constructed converter control model to obtain control data of the converter, wherein the control data are used for controlling the running state of the converter, and the converter control model is obtained by dispersing a state observer model constructed by electric power parameters of a filter and parameter variation of the converter.
In one possible embodiment, the method further comprises:
Acquiring power parameters of a filter and parameter variation of a converter, and acquiring observer parameters corresponding to a pre-constructed state observer model based on the power parameters and the parameter variation;
obtaining a state observer model aiming at the converter according to the observer parameters and the pre-constructed state observer model;
acquiring current data and voltage data of a power transmission network, and processing the current data and the voltage data by using a state observer model to obtain a discrete state observer model;
And constructing a converter control model based on the discrete state observer model.
In one possible embodiment, processing the current data and the voltage data using a state observer model to obtain a discrete state observer model, comprising:
Processing the current data and the voltage data by using a state observer model to obtain a state observer model matrix;
Based on the state observer model matrix, a discrete state observer model is obtained.
In one possible implementation, after deriving the discrete state observer model based on the state observer model matrix, it includes:
Obtaining pole parameters of the discrete state observer model according to the sampling frequency corresponding to the state observer model and the state estimation parameters of the state observer model;
and obtaining the stability degree of the discrete state observer model according to the pole parameters of the discrete state observer model.
In one possible implementation, constructing a current transformer control model based on a discrete state observer model includes:
Constructing a state space current controller according to the current data of the filter;
and obtaining a converter control model based on the state space current controller and the discrete state observer model.
In one possible implementation, after constructing the state space current controller according to the current data of the filter, the method further includes:
Acquiring a sampling frequency corresponding to a state observer model;
Acquiring discrete pole parameters of a state space current controller according to the sampling frequency;
And obtaining the stability degree of the state space current controller based on the discrete pole parameter.
In one possible implementation manner, based on the power parameter and the parameter variation, obtaining the observer parameter corresponding to the pre-constructed state observer model includes:
Based on the electric power parameters and the parameter variation, a state space model representing the state variation of the converter is obtained;
and obtaining observer parameters according to the state space model and the pre-constructed state observer model.
In one possible implementation, obtaining observer parameters according to the state space model and the pre-constructed state observer model includes:
Acquiring an error model between a state space model and a pre-constructed state observer model;
obtaining an error state matrix corresponding to the error model according to the error model;
based on the error state matrix, observer parameters are obtained.
In one possible implementation manner, after obtaining the state observer model for the converter according to the observer parameters and the pre-constructed state observer model, the method further comprises:
acquiring a transfer function model corresponding to the state observer model;
and processing the initial output voltage of the converter by using the transfer function model to obtain the stable state of the state observer model.
In a second aspect, an embodiment of the present application provides a method for determining a control model of a current transformer, where the method includes:
Acquiring power parameters of a filter and parameter variation of a converter, and acquiring observer parameters corresponding to a pre-constructed state observer model based on the power parameters and the parameter variation;
obtaining a state observer model aiming at the converter according to the observer parameters and the pre-constructed state observer model;
acquiring current data and voltage data of a power transmission network, and processing the current data and the voltage data by using a state observer model to obtain a discrete state observer model;
And constructing a converter control model based on the discrete state observer model.
In a third aspect, an embodiment of the present application provides a controller, including a memory, a processor;
the memory stores computer-executable instructions;
The processor executes the computer-executable instructions stored in the memory to cause the processor to perform the method as described above.
In a fourth aspect, an embodiment of the present application provides a power grid power conversion system, including:
a converter for providing power to a load;
The filter is connected with the converter and is also used for connecting a power transmission network;
The controller is respectively connected with the converter and the filter and is also used for connecting a power transmission network.
In a fifth aspect, embodiments of the present application provide a computer-readable storage medium having stored therein computer-executable instructions for performing, when executed by a processor, the various possible implementations of the method as described above.
In a sixth aspect, embodiments of the present application provide a computer program product comprising a computer program which, when executed by a processor, implements the various possible implementations of the method as described above.
The control method of the converter, the controller and the power grid power conversion system comprise the steps of obtaining power data of the converter, processing the power data by utilizing a pre-built converter control model to obtain the control data of the converter, wherein the converter control model is obtained by dispersing a state observer model built by power parameters of a filter and parameter variation of the converter, and controlling the running state of the converter according to the control data. Compared with the prior art, the application can construct the state observer aiming at the power parameter change through the power parameter of the output filter and the parameter change quantity of the converter, and can obtain the converter control model after discretizing the state observer, so that the state observer can be used for compensating the disturbance quantity of the converter, thereby improving the high-performance control of the converter.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.
Fig. 1 is a schematic view of a scenario of a power grid power conversion system provided by the present application;
Fig. 2 is a schematic flow chart of a control method of a current transformer according to the present application;
fig. 3 is a schematic flow chart II of a control method of the current transformer provided by the application;
fig. 4 is a schematic flow chart III of a control method of the current transformer provided by the application;
FIG. 5 is a schematic diagram of a discrete state observer model according to the present application;
FIG. 6 is a schematic diagram of the influence of the parameter variation on the stability of the control model based on the Bode diagram provided by the application;
fig. 7 is a schematic flow chart of a control method of the current transformer provided by the application;
Fig. 8 is a flow chart of a method for determining a control model of a current transformer according to the present application;
FIG. 9 is a schematic diagram of a state observer model according to an embodiment of the present application;
FIG. 10 is a schematic diagram of a root track according to an embodiment of the present application;
fig. 11 is a schematic flow chart of a control method of a current transformer provided by the present application;
Fig. 12 is a logic schematic diagram of a control method of the current transformer provided by the present application;
Fig. 13 is a schematic structural diagram of a control device of a current transformer according to the present application;
Fig. 14 is a schematic structural diagram of a controller according to the present application.
Specific embodiments of the present application have been shown by way of the above drawings and will be described in more detail below. The drawings and the written description are not intended to limit the scope of the inventive concepts in any way, but rather to illustrate the inventive concepts to those skilled in the art by reference to the specific embodiments.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present application more apparent, exemplary embodiments thereof will be described herein in detail, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the application. Rather, they are merely examples of means and implementations consistent with aspects of the application as set forth in the following claims. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
The terms "first," "second," "third," "fourth" and the like in the description and in the claims and in the above drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented, for example, in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a list of elements, systems, products, or devices is not necessarily limited to those elements expressly listed or inherent to such product or device, but may include other elements not expressly listed or inherent to such product or device.
Fig. 1 is a schematic view of a scenario of a power grid power conversion system provided by the present application, and as shown in fig. 1, a specific application scenario of the present application may be applied to control a converter 101. The converter may be a grid-connected converter with an LCL filter for converting electrical energy from the grid.
According to the method for determining the control model of the current transformer, provided by the application, discretization of processing current data and voltage data can be realized by utilizing the state observer model by constructing the state observer aiming at power parameter change, and the construction of the control model of the current transformer can be better realized by utilizing the discretization state observer, so that the technical problem of low control performance of a control strategy of the current transformer is solved.
The following describes the technical scheme of the present application and how the technical scheme of the present application solves the above technical problems in detail with specific embodiments. The following embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.
Fig. 2 is a schematic flow chart of a method for determining a control model of a current transformer according to the present application, as shown in fig. 2, the method may be applied to a current transformer, where the current transformer is used to convert electric energy of a power transmission network, and the method includes S201 to S203, where:
S201, acquiring power data of the converter.
The power data of the converter may be current data, voltage data, and the like acquired from the converter.
The current data of the transformer can be acquired through the current sensor, the voltage data of the transformer can be acquired through the voltage sensor, and the controller can directly acquire the current data and the voltage data through the current sensor and the voltage sensor so as to acquire the power data of the converter.
S202, processing electric power data by using a pre-constructed converter control model to obtain control data of the converter, wherein the control data are used for controlling the running state of the converter, and the converter control model is obtained by dispersing a state observer model constructed by electric power parameters of a filter and parameter variation of the converter.
The filter may be an LCL filter, and the filter may be a filter of the current transformer. The control data may be pulse data.
The controller may construct a state observer model in advance according to the power parameter of the filter and the parameter variation of the converter, and may further discretize the state observer model to obtain a discrete state observer model, and obtain a converter control model based on the discrete state observer model.
Optionally, the controller processes the power data of the converter by using a converter control model to obtain control data for controlling the converter, so as to compensate the state change of the converter by using the control data.
In practical application, the controller can acquire current data and voltage data of the power transmission network, and can process the current data and the voltage data by utilizing the state observer model to realize discretization of the state observer model and acquire a discrete state observer model. Furthermore, the discrete state observer model can be utilized to construct a control model of the converter, and the discrete state observer model is constructed to be beneficial to realizing high-performance control of the control model of the converter.
For example, the controller may output control data to the current transformer to enable control of the current transformer.
The embodiment of the application provides a control method of a current transformer, wherein a state observer aiming at the change of the power parameter can be constructed through the power parameter of a filter and the parameter variation of the current transformer, and the state observer is discretized to obtain a control model of the current transformer, so that the state observer can be utilized to compensate the disturbance quantity of the current transformer, the high inhibition performance of external disturbance, internal coupling and parameter variation is realized, and the high performance control of the current transformer is improved, and the high inhibition performance is realized.
In an exemplary embodiment, fig. 3 is a second flow chart of a method for determining a control model of a current transformer according to the present application, as shown in fig. 3, the method further includes S301 to S304, where:
S301, acquiring power parameters of a filter and parameter variation of a converter, and acquiring observer parameters corresponding to a pre-constructed state observer model based on the power parameters and the parameter variation.
The filter may be an LCL filter, may be a circuit device composed of an inductor and a capacitor, and may be a filter (filter circuit portion) as shown in fig. 1. The power parameters of the filter may be the capacitance, inductance, current, etc. parameters of the filter. The parameter variation of the current transformer refers to the output voltage, output current, variation of inductance and the like of the current transformer.
For example, the controller may collect power parameters of the filter and power parameters of the converter and determine a change in the parameters of the converter. Further, the controller can obtain observer parameters corresponding to the state observer model according to the pre-constructed state observer model, the power parameters and the parameter variation, and can construct a complete state observer model by utilizing the observer parameters.
For example, the controller may derive a state space model based on the power parameter and the parameter variation, which may characterize the state change of the current transformer.
S302, obtaining a state observer model for the converter according to observer parameters and a pre-constructed state observer model.
The controller may analyze the power parameter and the parameter variation to obtain an observer parameter corresponding to the pre-constructed state observer model, and the controller may obtain a state observer model that is compensated for the state transformation of the converter after the construction based on the observer parameter and the pre-constructed state observer model.
In practical application, the following-net type converter with the LCL filter can apply kirchhoff's law and convert the following expressions (1) to (3) into a mathematical model under the dq coordinate system:
(1);
(2);
(3);
wherein L 2 is the second net side inductance, C f is the converter output capacitance, L 1 is the converter side inductance, The output current of the inductance at the net side under the dq coordinate system,The capacitor voltage is output by the converter under the dq coordinate system,For the PCC voltage in the dq coordinate system,For the angular frequency of the voltage of the power grid,The output current of the inductor at the converter side in the dq coordinate system,The output voltage of the converter in the dq coordinate system.
Based on the parameter change of the converter, combining the expression (1) to the expression (3), the output current dynamic expression (4) of the inductance at the net side under the dq coordinate system is obtained as follows:
(4);
Wherein, For the output current of the inductance at the net side under the dq coordinate systemB0 is a coefficient, b0=1/L 1L2Cf,Is the resonant frequency of the wave, wherein,、Is the total disturbance of the converter,An output current of the inductance at the lower net side of the d coordinate system,An output current of the inductance at the lower net side of the q coordinate system,For the voltage of the PCC in the d-coordinate system,Is the voltage angular frequency of the power transmission network,Is the converter parameter change corresponding to L 1,Is thatCorresponding converter parameter variation,Is thatThe corresponding converter parameters vary.
Alternatively, the total disturbance may be estimated by a state observer modelAnd on-line compensation is carried out to lead the total disturbanceAs an additional state of the LCL filter, wherein the additional state is expressed as: Total disturbance of To enhance the additional state of the LCL filter, the response state space model around by the expression (4) is expressed as the following expression (5) and expression (6):
(5);
(6);
Wherein, A state variable of x,A is a state matrix, B is an output matrix, E is a disturbance matrix, and h represents total disturbanceY is the output state and C is the output matrix.
Alternatively, the pre-built state observer model may be expressed as (7):
(7)
Wherein, The derivative of z, z being a variable of the state observer model, which is an estimate of the state variable x, L c being a gain vector of the state observer model, i.e. the observer parameter to which the state observer model corresponds, wherein,。
In practical application, through the expression (5) and the expression (7), the L c can be analyzed, and the L c can be further utilized to construct and obtain a state observer model.
S303, acquiring current data and voltage data aiming at a power transmission network, and processing the current data and the voltage data by using a state observer model to obtain a discrete state observer model.
The current data of the power transmission network can be the output current of a network side inductor of the current transformer, and the voltage data can be the output voltage of the current transformer.
For example, the controller may acquire current data and voltage data of the power transmission network, and may implement discretization of the state observer model by processing the current data and the voltage data with the state observer model, resulting in a discrete state observer model. Furthermore, the discrete state observer model can be utilized to construct a control model of the converter, and the discrete state observer model is constructed to be beneficial to realizing high-performance control of the control model of the converter.
S304, constructing a converter control model based on the discrete state observer model.
Wherein the converter control model may be a zero-order hold discrete time model.
For example, the controller may construct a current transformer control model from a discrete state observer model and a state space current controller. For example, the control structure of the current transformer control model may include two parts, a discrete state observer model and a state space current controller. Through the constructed converter control model, high-performance control of the converter can be realized, so that the accuracy of controlling the converter can be improved, and the control performance of the converter can be improved.
In this embodiment, a state observer for power parameter variation can be constructed through the power parameter of the filter and the parameter variation of the converter, so that the disturbance quantity of the converter can be compensated by using the state observer, high suppression performance for external disturbance, internal coupling and parameter variation is achieved.
In an exemplary embodiment, fig. 4 is a flowchart of a determining method of a current transformer control model, as shown in fig. 4, where the step of S303 is described in detail on the basis of the embodiment of fig. 2, and in the step of S303, using a state observer model, current data and voltage data are processed to obtain a discrete state observer, which includes:
S401, processing the current data and the voltage data by using the state observer model to obtain a state observer model matrix.
Wherein the state observer model matrix may be a parameter matrix for constructing a discrete state observer model.
Illustratively, the controller may implement discretization of the state observer model matrix by processing the current data and the voltage data by using the state observer model to obtain a state observer model matrix corresponding to the state observer model, and further, may implement discretization of the state observer model by using the state observer model matrix.
S402, obtaining a discrete state observer model based on the state observer model matrix.
For example, the controller may discretize the state observer model using a state observer model matrix to construct a discrete state observer model.
In practical application, the discrete state observer model may be expressed as follows (8):
(8)
Wherein, For the observer state estimation at time k +1,For the state observer model matrix,The current estimate of the observer at time k, i.e. the current observer.Is the reference value of the output voltage of the converter under the dq coordinate system at the k moment,An input matrix of x.
Alternatively, the current observer can be obtained by the following expression (9):
(9)
Wherein, For the observer state estimation at time k,Gain matrix parameters for a discrete state observer model,Wherein L d may be as described aboveObtained by either。
In this embodiment, through the state observer model matrix, a discrete state observer model can be constructed, so that construction of a control model of the current transformer is facilitated, high control performance of the current transformer control is improved, and effectiveness of the current transformer control is improved.
Optionally, at step S402, after obtaining the discrete state observer model based on the state observer model matrix, the method further includes:
S403, obtaining pole parameters of the discrete state observer model according to the sampling frequency corresponding to the state observer model and the state estimation parameters of the state observer model.
S404, obtaining the stability degree of the discrete state observer model according to the pole parameter of the discrete state observer model.
The sampling frequency refers to the sampling frequency of the state observer, and the state estimation parameter refers to a parameter value corresponding to the state estimation of the observer. The pole parameter may be a pole representation of the discrete state observer model.
For example, the controller may obtain a sampling frequency corresponding to the state observer model and a state estimate of the state observer model, and may determine pole parameters of the discrete state observer model based on the sampling frequency corresponding to the state observer model and the state estimate parameters of the state observer model. The stability of the discrete state observer model may further be analyzed based on pole parameters of the discrete state observer model.
In practical application, the pole of the discrete state observer model is represented as expression (10):
(10)
Wherein, For the poles of the discrete state observer model, z is the state estimate of the observer model, i.e. the state estimation parameter,For the desired bandwidth of the state observer model,Is the sampling frequency of the state observer model.
In this embodiment, the pole of the discrete state observer model can be obtained through sampling frequency and state estimation, so that stability of the discrete state observer model can be analyzed through the pole, parameter adjustment of the discrete state observer can be realized through stability analysis, stability of the control model of the converter can be improved, and high-performance control of the converter can be improved.
In one possible implementation, as shown in fig. 5, an embodiment of the present application provides a schematic diagram of a discrete state observer model, where,Output current of network side inductance at k timeIs used to determine the state variable of (1),Is thatAndDifference between them. The discrete state observer model can be obtained from the parameters L d of the state observer model of e (k), and further from the expression (8) and the expression (9).
In practical application, as shown in fig. 6, the embodiment of the application provides a schematic diagram of the influence of the parameter change based on the baud diagram on the stability of the control model, and the stability of the discrete state observer model can be analyzed through fig. 6.
In an exemplary embodiment, fig. 7 is a flowchart of a method for determining a control model of a current transformer, as shown in fig. 7, where the step of S304 is described in detail on the basis of the embodiment of fig. 3, and in the step of S304, the method for constructing a control model of a current transformer based on a discrete state observer model includes:
s701, constructing a state space current controller according to current data of the filter.
S702, obtaining a converter control model based on the state space current controller and the discrete state observer model.
The current data of the LCL filter may be an output current of the network side inductor.
For example, the controller may construct a state space current controller that achieves current control based on the current data of the LCL filter. Further, the controller can complete the construction of the converter control model based on the state space current controller and the discrete state observer model. That is, the control structure of the current transformer control model may mainly include two parts of a state space current controller and a discrete state observer model.
In practical application, the state space current controller may be expressed as follows (11):
(11);
Wherein, The output voltage of the converter in the dq coordinate system at the k moment,The gain of the state feedback is respectively calculated,State feedback gain for time kIs used to determine the state variable of (1),State feedback gain for time kIs used to determine the state variable of (1),Is the reference value of the output current of the network side inductor under the dq coordinate system at the k moment,Is the total disturbance at the moment KState variables of (2).
Alternatively, the converter control model may be expressed as the following expression (12) and expression (13):
(12);
(13);
wherein x (k+1) is a state variable at time x of k+1, x (k) is a state variable at time x of k, An input matrix of x is provided which is,For the state observer model matrix,Is the reference value of the output voltage of the converter under the dq coordinate system at the k moment,The disturbance matrix for x is given by,As the disturbance quantity at the moment k,The output current of the inductance at the net side under the dq coordinate system at the k moment,An output matrix of x.
In this embodiment, through the discrete state observer model and the state space current controller, a converter control model can be obtained, and the converter control model can be a zero-order discrete time-keeping model, so that equivalent control of the converter can be realized, and high-performance control of the converter is facilitated.
Optionally, at step S702, after constructing the state space current controller according to the current data of the LCL filter, the method further includes:
s703, acquiring the sampling frequency corresponding to the state observer model.
S704, acquiring discrete pole parameters of the state space current controller according to the sampling frequency.
And S705, obtaining the stability degree of the state space current controller based on the discrete pole parameter.
Wherein the discrete pole parameter may be a pole representation of the state space current controller.
For example, the controller may obtain a sampling frequency corresponding to the state observer model, and based on the sampling frequency, may determine a discrete pole representation of the state space current controller, further may analyze the stability of the state space current controller according to the discrete pole parameters of the state space current controller.
In practical application, discrete poles of the state space current controller are expressed as expression (14) and expression (15):
(14);
(15);
Wherein, A discrete pole for the first state space current controller,Discrete poles for the second and third state space current controllers,For a desired bandwidth of the state observer model, T s is the sampling frequency of the state observer model,For the angular frequency of the voltage of the power grid,Is a damping ratio,,Is the natural frequency of the resonant pole.
In this embodiment, the discrete pole of the state space current controller can be obtained through the sampling frequency, which is favorable for analyzing the stability of the state space current controller through the pole, and the high suppression performance on external interference, internal coupling and parameter variation can be realized through the design of the current controller with direct pole arrangement, and the parameter adjustment on the state space current controller is realized through the stability analysis, so that the stability of the control model of the current transformer can be improved, and the high performance control on the current transformer can be improved.
In an exemplary embodiment, fig. 8 is a flowchart of a current transformer control model determining method provided by the present application, as shown in fig. 8, and in this embodiment, on the basis of the embodiment of fig. 3, the step of S301 is described in detail, and in the step of S301, based on the power parameter and the parameter variation, obtaining the observer parameter corresponding to the pre-built state observer model may include:
S801, obtaining a state space model representing the state change of the converter based on the power parameters and the parameter variation;
S802, obtaining observer parameters according to the state space model and the pre-constructed state observer model.
The state space model may be a model characterizing a parameter variation of the current transformer.
For example, the controller may build a state space model characterizing the parameter variation of the current transformer from the power parameter and the parameter variation. For example, the state expression of the LCL filter may be converted into a mathematical model in the dq coordinate system by applying kirchhoff's law, and a state space model may be further built by the mathematical model.
In practical application, the state space model can be obtained by the above expressions (1) to (6). Further, observer parameters of the state observer model can be obtained based on the state observer model represented by the expression (5) and the expression (7) so as to realize construction of the state observer model.
In this embodiment, the state space model is obtained through the power parameter and the parameter variation, so that the observer parameter can be obtained based on the state space model and the pre-constructed state observer model, which is beneficial to constructing the state observer model, thereby improving the control performance of the converter.
Optionally, in step S802, obtaining observer parameters according to the state space model and the pre-constructed state observer model may specifically include:
An error model between the state space model and the pre-built state observer model is obtained.
And obtaining an error state matrix corresponding to the error model according to the error model.
Based on the error state matrix, observer parameters are obtained.
The error equation may be a model built by an error between the state space model and the pre-built state observer model.
For example, the controller may subtract the pre-built state observer model from the state space model to obtain an error between the state space model and the pre-built state observer model, and may build a corresponding error model based on the error. The controller can determine an error state matrix corresponding to the error model according to the error model, and can analyze the error state matrix to obtain observer parameters corresponding to the state observer model, so that the state observer model can be constructed by utilizing the observer parameters.
In practical application, the error model may be expressed as the following expression (16):
(16);
Wherein, As a derivative of the difference value e,The state matrix, which is the difference e, e is the error (difference) between the state space model and the pre-built state observer model.
Wherein e = x-z;
Alternatively, it may be determined from expression (15), The root of the feature polynomial of (2) is in the left half plane and the state observer model is stable, so the gain parameters of the state observer model are expressed as follows (17):
(17);
Wherein, As an intermediate variable, the number of the variables,For the first extended state observer gain parameter,For the second extended state observer gain parameter,For the third extended state observer gain parameter,For the fourth extended state observer gain parameter,Is the initial bandwidth of the state observer model.
In this embodiment, an error state matrix corresponding to the error model is obtained through an error model between the state space model and the pre-constructed state observer model, and observer parameters can be obtained based on the error state matrix, so that observer parameters for constructing the state observer model can be accurately and effectively obtained, and control performance of the converter can be improved.
Optionally, in step S802, after obtaining the state observer model for the converter according to the observer parameters and the pre-constructed state observer model, the method further includes:
s803, a transfer function model corresponding to the state observer model is obtained;
S804, processing the initial output voltage of the converter by using the transfer function model to obtain the stable state of the state observer model.
Wherein the transfer function model may characterize the transfer function.
Illustratively, the controller may convert the above expression (7) into a transfer function form, and the transfer function model may be expressed as the following expression (18):
(18)
Wherein, Is a transfer function of the state observer model (transfer function model),In order for the transfer function to fall off,The initial output voltage of the converter under the dq coordinate system is represented by s which is a pull operator,In order to perturb the transfer function to the input,Is the transfer function of the disturbance to the output.
Within the bandwidth of the state observer model, the transfer function of the state observer model falls down by the following expression (19):
(19);
At high frequencies beyond the observer frequency, the transfer function of the modified state observer model represents the following expression (20):
(20);
Wherein, Is the initial bandwidth of the state observer model, ω is the bandwidth of the state observer model.
Alternatively, the transfer function of the state observer model is derived by expression (19) without total interference within the observer's bandwidth, and the modified extended state observer transfer function is derived by expression (20) to return to the original grid-tie converter at the high frequency of the state observer model, and the transition from the low frequency grid-tie converter to the high frequency grid-tie converter is obtained by expression (18).
In practical application, as shown in fig. 9, the schematic diagram of a state observer model provided by the embodiment of the application can realize state observation of a converter through the state observer model shown in fig. 9. Wherein the parameters in fig. 9 may be as explained above for the parameters.
Alternatively, the frequency domain analysis of the state observer model may be implemented through the root track schematic provided by the embodiment of the present application as shown in fig. 10, and the parameter adjustment for compensating the interference is performed by knowing the state observer model.
In this embodiment, through the transfer function model, the initial output voltage of the converter can be processed, and the stable state of the state observer model is analyzed, so that the stability of the state observer model is improved, and the high-performance control of the converter is facilitated.
In an exemplary embodiment, fig. 11 is a schematic flow chart of a control method of a current transformer according to the present application, where the method includes:
s1101, establishing a mathematical model of the LCL filter and establishing a mathematical model of the state observer.
S1102, constructing a state observer model.
S1103, discretizing the state observer model.
S1104, analyzing the stability of the designed state observer model.
It can be appreciated that each step in fig. 10 may be implemented by the foregoing embodiments or a combination of embodiments, and a corresponding implementation may be obtained from the foregoing embodiments, which is not described herein.
Optionally, fig. 12 is a logic schematic diagram of a control method of a current transformer provided by the present application, as shown in fig. 12, where the method may be applied to a current transformer with an LCL filter, where the current state control in fig. 12 may be implemented by a state space current controller of expression (11), the extended state observer in fig. 12 may be implemented by a discrete state observer model of expression (8), and each parameter in fig. 12 may be explained with reference to the above parameters, which is not repeated herein.
In the embodiment, the high inhibition performance on external interference, internal coupling and parameter change can be realized through the construction of a state observer model and the design of a current controller with direct poles arranged in a discrete time domain, the principle of compensating interference by the state observer model is deeply known through the frequency domain analysis of the state observer model, the discrete state observer model for an LCL filter is provided, the parameter adjustment and stability of the discrete state observer model are discussed, and the stability of the state observer model in a high-order system is improved.
Fig. 13 is a schematic structural diagram of a current transformer control device according to the present application, as shown in fig. 13, a current transformer control model determining device 130 according to the present embodiment is applied to a current transformer with an LCL filter, where the current transformer is used for converting electric energy of a power transmission network, and the device includes:
the power data acquisition module 1301 is configured to acquire power data of the converter.
The pulse data acquisition module 1302 is configured to process the power data by using a pre-constructed converter control model to obtain the control data of the converter, where the converter control model is obtained by dispersing a state observer model constructed by power parameters of the LCL filter and parameter variation of the converter.
The control module 1303 is configured to control an operation state of the current transformer according to the control data.
In an exemplary embodiment, the apparatus further comprises:
the parameter acquisition module is used for acquiring the power parameter of the LCL filter and the parameter variation of the converter and acquiring observer parameters corresponding to the pre-constructed state observer model based on the power parameter and the parameter variation;
the observer acquisition module is used for obtaining a state observer model aiming at the converter according to the observer parameters and the pre-constructed state observer model;
The discrete observer acquisition module is also used for acquiring current data and voltage data aiming at the power transmission network, and processing the current data and the voltage data by utilizing the state observer model to obtain a discrete state observer model;
And the control model construction module is used for constructing a converter control model based on the discrete state observer model.
In one exemplary embodiment, the discrete observer acquisition module is configured to process the current data and the voltage data using a state observer model to obtain a state observer model matrix, and to obtain a discrete state observer model based on the state observer model matrix.
In an exemplary embodiment, the discrete observer obtaining module is further configured to obtain a pole parameter of the discrete state observer model according to the sampling frequency corresponding to the state observer model and the state estimation parameter of the state observer model, and obtain a stability degree of the discrete state observer model according to the pole parameter of the discrete state observer model.
In one exemplary embodiment, the control model building module is configured to build a state space current controller based on current data of the LCL filter, and obtain a current transformer control model based on the state space current controller and the discrete state observer model.
In an exemplary embodiment, the control model building module is further configured to obtain a sampling frequency corresponding to the state observer model, obtain a discrete pole parameter of the state space current controller according to the sampling frequency, and obtain a stability degree of the state space current controller based on the discrete pole parameter.
In one exemplary embodiment, the parameter acquisition module is configured to obtain a state space model representing a state change of the converter based on the power parameter and the parameter variation, and obtain the observer parameter according to the state space model and the pre-constructed state observer model.
In an exemplary embodiment, the parameter acquisition module is configured to acquire an error model between the state space model and the pre-constructed state observer model, obtain an error state matrix corresponding to the error model according to the error model, and obtain observer parameters based on the error state matrix.
In an exemplary embodiment, the observer obtaining module is further configured to obtain a transfer function model corresponding to the state observer model, and process the initial output voltage of the converter by using the transfer function model to obtain a stable state of the state observer model.
In an exemplary embodiment, the present embodiment further provides a control device for a current transformer, where the device includes:
the control model acquisition module is used for obtaining the converter control model according to the converter control model determination method.
And the control data acquisition module is used for acquiring control data of the converter according to the converter control model and the power data of the converter.
The current transformer control model determining device and the current transformer control device provided in this embodiment may execute the method provided in the foregoing method embodiment, and the implementation principle and the technical effect are similar, which are not described in detail herein.
Fig. 14 is a schematic structural diagram of a controller according to the present application. As shown in fig. 14, the electronic device 140 provided in this embodiment includes at least one processor 1401 and a memory 1402. Optionally, the device 140 further comprises a communication component 1403. Wherein the processor 1401, the memory 1402 and the communication unit 1403 are connected via a bus 1404.
In a particular implementation, at least one processor 1401 executes computer-executable instructions stored in memory 1402, causing the at least one processor 1401 to perform the method described above.
The specific implementation process of the processor 1401 may refer to the above-mentioned method embodiment, and its implementation principle and technical effects are similar, and this embodiment will not be described herein again.
In the above embodiment, it should be understood that the Processor may be a central processing unit (english: central Processing Unit, abbreviated as CPU), or may be other general purpose processors, digital signal processors (english: DIGITAL SIGNAL Processor, abbreviated as DSP), application specific integrated circuits (english: application SPECIFIC INTEGRATED Circuit, abbreviated as ASIC), or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor for execution, or in a combination of hardware and software modules in a processor for execution.
The Memory may include high-speed Memory (Random Access Memory, RAM) or may further include Non-volatile Memory (NVM), such as at least one disk Memory.
The bus may be an industry standard architecture (Industry Standard Architecture, ISA) bus, an external device interconnect (PERIPHERAL COMPONENT, PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, among others. The buses may be divided into address buses, data buses, control buses, etc. For ease of illustration, the buses in the drawings of the present application are not limited to only one bus or to one type of bus.
The application also provides a power grid power conversion system, which comprises:
a converter for providing power to a load;
The LCL filter is connected with the converter and is also used for connecting a power transmission network;
The controller is respectively connected with the converter and the LCL filter and is also used for connecting a power transmission network.
The application also provides a computer program product comprising a computer program which, when executed by a processor, implements the method described above.
The application also provides a computer readable storage medium, wherein computer execution instructions are stored in the computer readable storage medium, and when a processor executes the computer execution instructions, the method is realized.
The above-described readable storage medium may be implemented by any type or combination of volatile or non-volatile memory devices, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk. A readable storage medium can be any available medium that can be accessed by a general purpose or special purpose computer.
An exemplary readable storage medium is coupled to the processor such the processor can read information from, and write information to, the readable storage medium. In the alternative, the readable storage medium may be integral to the processor. The processor and the readable storage medium may reside in an Application SPECIFIC INTEGRATED Circuits (ASIC). The processor and the readable storage medium may reside as discrete components in a device.
The division of units is merely a logical function division, and there may be another division manner in actual implementation, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method of the embodiments of the present invention. The storage medium includes a U disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, an optical disk, or other various media capable of storing program codes.
Those of ordinary skill in the art will appreciate that all or a portion of the steps of implementing the various method embodiments described above may be implemented by hardware associated with program instructions. The foregoing program may be stored in a computer readable storage medium. The program, when executed, performs the steps comprising the method embodiments described above, and the storage medium described above includes various media capable of storing program code, such as ROM, RAM, magnetic or optical disk.
Finally, it should be noted that other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any adaptations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains and as may be applied to the precise construction hereinbefore set forth and shown in the drawings and as follows in the scope of the appended claims. The scope of the invention is limited only by the appended claims.
Claims (10)
1. The control method of the converter is characterized by being applied to the converter, wherein the converter is used for converting electric energy of a power transmission network, and the method comprises the following steps of:
Acquiring power data of the converter;
Processing the electric power data by utilizing a pre-constructed converter control model to obtain control data of the converter, wherein the control data is used for controlling the running state of the converter;
The method further comprises the steps of:
Acquiring power parameters of a filter and parameter variation of the converter, and obtaining a state space model representing state variation of the converter based on the power parameters and the parameter variation;
Acquiring an error model between the state space model and a pre-constructed state observer model;
obtaining an error state matrix corresponding to the error model according to the error model;
Obtaining observer parameters corresponding to the pre-constructed state observer based on the error state matrix;
Obtaining a state observer model aiming at the converter according to the observer parameters and the pre-constructed state observer model;
acquiring current data and voltage data of the power transmission network, and processing the current data and the voltage data by using the state observer model to obtain a discrete state observer model;
And constructing the converter control model based on the discrete state observer model.
2. The method of claim 1, wherein processing the current data and voltage data using the state observer model to obtain a discrete state observer model comprises:
Processing the current data and the voltage data by using the state observer model to obtain a state observer model matrix;
And obtaining a discrete state observer model based on the state observer model matrix.
3. The method according to claim 2, wherein after deriving a discrete state observer model based on the state observer model matrix, comprising:
Obtaining pole parameters of the discrete state observer model according to the sampling frequency corresponding to the state observer model and the state estimation parameters of the state observer model;
and obtaining the stability degree of the discrete state observer model according to the pole parameter of the discrete state observer model.
4. The method of claim 1, wherein the constructing the converter control model based on the discrete state observer model comprises:
constructing a state space current controller according to the current data of the filter;
And obtaining the converter control model based on the state space current controller and the discrete state observer model.
5. The method of claim 4, wherein after constructing a state space current controller from the current data of the filter, further comprising:
acquiring a sampling frequency corresponding to the state observer model;
acquiring discrete pole parameters of the state space current controller according to the sampling frequency;
and obtaining the stability degree of the state space current controller based on the discrete pole parameter.
6. The method according to any one of claims 1-5, wherein said deriving a state observer model for said current transformer from said observer parameters and said pre-built state observer model further comprises:
Acquiring a transfer function model corresponding to the state observer model;
And processing the initial output voltage of the converter by using the transfer function model to obtain the stable state of the state observer model.
7. A controller is characterized by comprising a memory and a processor;
The memory stores computer-executable instructions;
The processor executing computer-executable instructions stored in the memory, causing the processor to perform the method of any one of claims 1-6.
8. A grid power conversion system, the system comprising:
a converter for providing power to a load;
the filter is connected with the converter and is also used for connecting a power transmission network;
The controller of claim 7, connected to the converter and the filter, respectively, and further configured to connect to a power transmission grid.
9. A computer readable storage medium having stored therein computer executable instructions which when executed by a processor are adapted to carry out the method of any one of claims 1-6.
10. A computer program product comprising a computer program which, when executed by a processor, implements the method of any of claims 1-6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202411089549.2A CN118646243B (en) | 2024-08-09 | 2024-08-09 | Converter control method, controller and power grid power conversion system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202411089549.2A CN118646243B (en) | 2024-08-09 | 2024-08-09 | Converter control method, controller and power grid power conversion system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN118646243A CN118646243A (en) | 2024-09-13 |
| CN118646243B true CN118646243B (en) | 2025-01-14 |
Family
ID=92663434
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202411089549.2A Active CN118646243B (en) | 2024-08-09 | 2024-08-09 | Converter control method, controller and power grid power conversion system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN118646243B (en) |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115001016A (en) * | 2022-06-09 | 2022-09-02 | 山东大学 | Converter grid-connected optimization control method and system based on model-free prediction |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103346585B (en) * | 2013-07-08 | 2015-05-27 | 合肥工业大学 | Grid-connected inverter control method based on state observer |
| CN105720856B (en) * | 2016-04-22 | 2018-08-28 | 哈尔滨工业大学 | LCL type control method of grid-connected inverter based on capacitance voltage single-sensor |
| TWI626459B (en) * | 2016-08-17 | 2018-06-11 | 財團法人工業技術研究院 | Sensorless measurement method and device for filter capacitor current by using a state observer |
| TWI792934B (en) * | 2021-12-27 | 2023-02-11 | 財團法人工業技術研究院 | Dc-ac inverter system using state observer and control method thereof |
| CN116667439A (en) * | 2023-05-30 | 2023-08-29 | 国网江苏省电力有限公司电力科学研究院 | Repeated active disturbance rejection control method and system for T-type three-level LCL-type inverter |
-
2024
- 2024-08-09 CN CN202411089549.2A patent/CN118646243B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115001016A (en) * | 2022-06-09 | 2022-09-02 | 山东大学 | Converter grid-connected optimization control method and system based on model-free prediction |
Also Published As
| Publication number | Publication date |
|---|---|
| CN118646243A (en) | 2024-09-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Zadeh et al. | Stability analysis and dynamic performance evaluation of a power electronics-based DC distribution system with active stabilizer | |
| CN111551848B (en) | Motor experience distortion index testing method, electronic equipment and storage medium | |
| CN111709107A (en) | A power network simulation method and system including large-scale power electronic equipment | |
| CN103077268B (en) | Towards the state space method for automatic modeling of electromagnetic transient in power system emulation | |
| Garanayak et al. | Fast and accurate measurement of harmonic parameters employing hybrid adaptive linear neural network and filtered‐x least mean square algorithm | |
| CN111628504B (en) | Inverter modeling method containing amplitude limiter and related device | |
| CN103810646A (en) | Improved projection integral algorithm based active power distribution system dynamic simulation method | |
| Theodoro et al. | A flexible co-simulation framework for penetration studies of power electronics based renewable sources: A new algorithm for phasor extraction | |
| CN115422869A (en) | Load model parameter identification method, system, computer device and storage medium | |
| Ufa et al. | The hybrid model of VSC HVDC | |
| Chen et al. | DC network stability and dynamic analysis using virtual impedance method | |
| D'Arco et al. | Analysis of accuracy versus model order for frequency-dependent Pi-model of HVDC cables | |
| CN106602610B (en) | A kind of method for building up of wind power plant Equivalent Model | |
| CN118646243B (en) | Converter control method, controller and power grid power conversion system | |
| Huang et al. | Estimation of interarea modes in large power systems | |
| López-Alcolea et al. | 2DOF-based current controller for single-phase grid-connected voltage source inverter applications | |
| US20120221270A1 (en) | Capacitance Placement in wind farms | |
| CN116613751B (en) | A small interference stability analysis method and system for new energy grid-connected systems | |
| Alekseevskiy et al. | Procedure for the synthesis of models of electrotechnical complexes | |
| CN116094003A (en) | Method, device, equipment and medium for optimal configuration of virtual inertia of independent micro-grid | |
| Braga et al. | Robust stability analysis of grid-connected converters based on parameter-dependent lyapunov functions | |
| Shabestari et al. | Hardware-in-the-Loop Demonstration of a Grid-Connected Voltage-Sourced Converter with an LCL Filter | |
| CN119561363B (en) | Method, system, device and medium for suppressing DC fluctuation of unbalanced down-converter | |
| Liu et al. | General Modeling of Converter in Power Electronic Distribution System | |
| CN116127765B (en) | State space modeling method and device for electric power system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |