Battery energy storage converter control method based on error model and electronic equipment

Abstract

The invention relates to a battery energy storage converter control method based on an error model and electronic equipment, and the method comprises the steps: obtaining a voltage and a current value in a battery energy storage converter under an abc coordinate system, and converting the voltage and the current value into a voltage and a current value under an alpha-beta coordinate system through Cracker transformation; respectively calculating reference values of the voltage and current values under the alpha-beta coordinate system according to the voltage and current values under the alpha-beta coordinate system; respectively calculating errors between reference values and actual values of the voltage and current values under the alpha-beta coordinate system, and constructing an error model; based on the error model, solving the output voltage of the alternating current side under the alpha-beta coordinate system within the limited convergence time, and realizing the control of the battery energy storage converter; wherein the voltage and current values comprise filter capacitor voltage, inner side current and outer side current. Compared with the prior art, the method has the advantages that convergence control of the battery energy storage converter within finite time is achieved, control is fast, and system robustness is high.

Description

Technical Field

[0001] The present invention relates to the technical field of battery energy storage converter control, and in particular to a battery energy storage converter control method and electronic equipment based on an error model. Background Art

[0002] The battery energy storage system is an important component of the renewable energy power generation system. It can be used to reduce peak loads and fill valleys, and compensate for the volatility of renewable energy power generation. Batteries generally output direct current and cannot be directly connected to the grid, so it is necessary to introduce battery energy storage converter equipment. Through the high-frequency operation of semiconductor switching devices, the electric energy is converted into standard industrial frequency alternating current and connected to the grid, and it can realize the bidirectional flow of power, and finally realize the function of storing or releasing the electric energy generated by renewable energy. The power quality and response speed are the core parameters of the battery energy storage converter. On the other hand, sliding mode control, as a typical nonlinear control method, has a wide range of applications in many fields including battery energy storage converters.

[0003] However, traditional sliding mode control has risks such as uncertain convergence time and jitter near the sliding mode surface. In order to ensure the dynamic response time of the battery energy storage converter, take into account the steady-state power quality, and prevent jitter and filter resonance, the existing sliding mode control method of the battery energy storage converter should be improved to achieve finite time convergence sliding mode control that can ensure the rapid convergence of the control loop. Finite time convergence sliding mode control can further guarantee the convergence response speed in the control process. In applications with high requirements for convergence time, it has obvious advantages over traditional proportional integral differential control and sliding mode control. However, this type of algorithm cannot be directly applied to battery energy storage systems.

[0004] How to achieve faster convergence control of the battery energy storage converter within a limited time has become a technical problem that needs to be solved. Summary of the invention

[0005] The purpose of the present invention is to provide a battery energy storage converter control method and electronic equipment based on an error model in order to overcome the defects of the above-mentioned prior art.

[0006] The purpose of the present invention can be achieved by the following technical solutions:

[0007] According to one aspect of the present invention, a battery energy storage converter control method based on an error model is provided, the method comprising:

[0008] Obtain the voltage and current values ​​of the battery energy storage converter in the abc coordinate system, and convert them into the voltage and current values ​​in the αβ coordinate system through Clark transformation;

[0009] According to the voltage and current values ​​in the αβ coordinate system, the reference values ​​of the voltage and current values ​​in the αβ coordinate system are calculated respectively;

[0010] Calculate the errors between the reference value and the actual value of the voltage and current in the αβ coordinate system respectively, and construct an error model;

[0011] Based on the error model, the output voltage of the AC side in the αβ coordinate system is solved within a limited convergence time to realize the control of the battery energy storage converter;

[0012] The voltage and current values ​​include filter capacitor voltage, inner current and outer current.

[0013] Preferably, the reference value of the outer current in the αβ coordinate system is specifically calculated as:

[0014]

[0015] Among them, I 2R Indicates the effective value of the phase current expected to be fed into the grid; θ g Indicates the grid angle; Indicates the power factor angle between the grid voltage and grid current signals; and are the reference values ​​of the components of the outer current on the α / β axis respectively.

[0016] Preferably, the reference values ​​of the filter capacitor voltage and the inner current in the αβ coordinate system are calculated as follows:

[0017]

[0018] in, and are the reference values ​​of the filter capacitor voltage components on the α / β axis respectively; and are the reference values ​​of the inner current components on the α / β axis respectively; ω represents the angular velocity of the grid; u gα and u gβ They represent the grid voltage components on the α / β axis in the αβ coordinate system; I 2R Indicates the effective value of the phase current expected to be fed into the grid; θ g Indicates the grid angle; Indicates the power factor angle between the grid voltage and the grid current signal; L2 is the second inductance value of the battery energy storage converter; L3 and C f are the inductance and capacitance of the middle branch of the battery energy storage converter respectively.

[0019] Preferably, the error model includes:

[0020] Definition 1α =i 1α * -i 1α , e 1β =i1β * -i 1β , which represents the error between the reference value and the actual value of the inner current;

[0021] Definition 2α =i 2α * -i 2α , e 2β =i 2β * -i 2β , which represents the error between the reference value and the actual value of the outer current;

[0022] Definition 3α =u cα * -u cα , e 3β =u cβ * -u cβ , which represents the error between the reference value and the actual value of the filter capacitor voltage;

[0023] It is deduced that:

[0024]

[0025] Among them, e 1α and e 1β 、e 2α and e 2β 、e 3α and e 3β Respectively represent the errors of the components of the inner current, outer current, and filter capacitor voltage on the α / β axis; and are the reference values ​​of the inner current components on the α / β axis respectively; i 1α and i 1β are the actual values ​​of the components of the inner current on the α / β axis respectively; and and and Respectively represent the differential errors of the inner current, outer current, and filter capacitor voltage on the α / β axis; u mα 、u mβ They represent the components of the intermediate branch voltage on the α / β axis in the αβ coordinate system respectively; and They represent the reference values ​​of the intermediate branch voltage components on the α / β axis in the αβ coordinate system; u iα and u iβ They represent the α / β axis components of the AC side output voltage in the αβ coordinate system; L3 and C fare the inductance and capacitance of the middle branch of the battery energy storage converter respectively; L1 and L2 represent the inductance of the first inductor and the second inductor in the battery energy storage converter respectively; u cα and u cβ Respectively represent the components of the filter capacitor voltage on the α / β axis; and are the reference values ​​of the filter capacitor voltage components on the α / β axis respectively; and They represent the differential of the reference value of the components of the outer current on the α / β axis respectively; and Respectively represent the differential of the inner current component on the α / β axis; u cα and u cβ Respectively represent the components of the filter capacitor voltage on the α / β axis; and They respectively represent the differential of the reference value of the component of the filter capacitor voltage on the α / β axis.

[0026] More preferably, the calculation of the intermediate branch voltage component on the α / β axis and its reference value in the αβ coordinate system is specifically as follows:

[0027]

[0028] The dots above the variables represent differential operations; u mα 、u mβ They represent the components of the intermediate branch voltage on the α / β axis in the αβ coordinate system respectively; and They represent the reference values ​​of the components of the intermediate branch voltage on the α / β axis in the αβ coordinate system respectively; and They represent the differential of the reference value of the components of the outer current on the α / β axis respectively; and Respectively represent the differential of the inner current component on the α / β axis; u cα and u cβ They respectively represent the components of the filter capacitor voltage on the α / β axis; L3 represents the inductance value of the middle branch.

[0029] More preferably, the error model further includes:

[0030] Let vector e α =[e 1α e 2α e 3α ] T , vector e β =[e 1β e 2β e 3β ] T , define LΣ =L1L2+L2L3+L1L3, the error model state space equation can be solved by elimination method. The standard form of the error model state space equation is as follows:

[0031]

[0032] in,

[0033]

[0034] u iα 、u iβ It represents the component of the AC side output voltage on the α / β axis in the αβ coordinate system.

[0035] Preferably, the process of solving the output voltage on the AC side within a limited convergence time includes:

[0036] Define the function N(x) as:

[0037]

[0038] Defining functions for:

[0039]

[0040] In the formula, x represents the function independent variable; α0, β0, γ, k, σ are all control parameters adjusted according to needs; sgn(x) represents the sign function;

[0041] The sliding surface expression in the αβ coordinate system is:

[0042]

[0043] Among them, S fα and S fβ They represent the sliding surface of the α-axis subsystem and the sliding surface of the β-axis subsystem respectively; t represents the current moment; k1 and α1 both represent control parameters that can be adjusted according to needs; e 1α and e 1β 、e 3α and e 3β Respectively represent the errors of the inner current and filter capacitor voltage on the α / β axis; λ p and λ i All are adjustable control coefficients;

[0044] By taking the derivative of the sliding surface in the αβ coordinate system, we can obtain:

[0045]

[0046] in, and denote the differentials of the sliding surface of the α-axis subsystem and the sliding surface of the β-axis subsystem respectively; and and Respectively represent the differential of the error of the inner current and filter capacitor voltage components on the α / β axis;

[0047] The expected convergence laws of the two coordinate axis subsystems in the αβ coordinate system are the same, which can be expressed as:

[0048]

[0049] Wherein, k2 represents a control parameter adjusted as needed; α2 represents a control parameter adjusted as needed, but different from α1; and They represent the expected reaching laws of the α and β axis subsystems respectively;

[0050] Let the sliding surface of each axis subsystem in the αβ coordinate system be equal to the expected reaching law of the corresponding subsystem, and substitute it into the error model to obtain the output voltage expression of the AC side of the battery energy storage converter in the αβ coordinate system:

[0051]

[0052] in,

[0053]

[0054] e 1α and e 1β 、e 2α and e 2β 、e 3α and e 3β They represent the errors of the inner current, outer current, and filter capacitor voltage on the α / β axis respectively; L3 and C f are the inductance and capacitance of the middle branch of the battery energy storage converter respectively; L1 and L2 represent the inductance of the first inductor and the second inductor in the battery energy storage converter respectively; and They represent the differential of the reference value of the components of the outer current on the α / β axis respectively; and Respectively represent the differential of the inner current component on the α / β axis; u cα and u cβ They represent the components of the filter capacitor voltage on the α / β axis respectively.

[0055] Preferably, the method further comprises: subjecting the output voltage of the AC side in the αβ coordinate system to a Clark inverse transformation to obtain a voltage control quantity in the abc coordinate system, and obtaining a pulse control signal of the battery energy storage converter by SPWM modulation.

[0056] Preferably, the voltage and current in the battery energy storage converter in the abc coordinate system are obtained through sensors and sampling.

[0057] According to another aspect of the present invention, an electronic device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the method described above is implemented when the processor executes the program.

[0058] Compared with the prior art, the present invention has the following beneficial effects:

[0059] 1) The present invention establishes an error model of a battery energy storage converter, which describes the error relationship between the reference value and the actual value of the inner current, the outer current and the filter capacitor voltage, and can effectively reflect the dynamic characteristics of the battery energy storage converter during the convergence process; then, based on the error model, a calculation formula for the sliding mode control of the output voltage is derived to achieve convergence control of the battery energy storage converter within a limited time, with extremely strong rapidity and robustness, and achieves rapid tracking of the reference value, which can improve the dynamic response performance of the battery energy storage converter and ensure the quality of the grid-connected current.

[0060] 2) The present invention first converts the three-phase variables in the abc coordinate system into two-phase variables in the αβ coordinate system through Clark transformation. After the output voltage in the αβ coordinate system is output by sliding mode control based on the error model, the error model makes the structure of the control quantity simple and is easy to promote practical applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a schematic diagram of the overall circuit structure of the battery energy storage converter in the present invention;

[0062] Figure 2 It is a schematic diagram of the control principle of the battery energy storage converter in the present invention;

[0063] Figure 3 It is a flowchart of a battery energy storage converter control method based on an error model in the present invention;

[0064] FIG4( a ) is a schematic diagram of a discharge waveform of an energy storage converter in an experiment of the control method of the present invention;

[0065] FIG4( b ) is a schematic diagram of a steady-state charging waveform of an energy storage converter in an experiment of the control method of the present invention;

[0066] FIG4( c ) is a schematic diagram of the dynamic switching waveform from charging to discharging of the energy storage converter in the control method experiment of the present invention;

[0067] FIG4( d ) is a schematic diagram of the waveform of the dynamic switching from discharge to charge of the energy storage converter in the control method experiment of the present invention. DETAILED DESCRIPTION

[0068] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0069] Example 1

[0070] This embodiment relates to a battery energy storage converter control method based on an error model, which improves the existing finite time convergence sliding mode control theory and applies it to the battery energy storage converter.

[0071] Firstly, a new error model of the controlled object is established according to the topological structure of the battery energy storage converter. This error model is different from the traditional converter state space model. This model describes the relationship between the difference between the given quantity and the actual quantity and the system input. It is used to characterize the dynamic characteristics of the control convergence process of the battery energy storage converter and is the basis for the design of various control systems. Then, based on this error model, the design of the control method is completed, and the structure of the control quantity is made simple for practical application. The control algorithm designed based on this error model can converge within a limited time, realize fast tracking control of the reference current, improve the dynamic response performance of the system, ensure the quality of the grid current, and realize efficient control of the battery energy storage converter.

[0072] For the convenience of description, the overall circuit structure of the battery energy storage converter is first given. Figure 1 As shown, the battery energy storage converter is based on a two-level voltage source bidirectional inverter circuit, and introduces inductors and capacitors to filter the grid current. The first inductor and the second inductor with inductance values ​​of L1 and L2 are the main inductors of the battery energy storage converter, which filter out the high-order harmonics generated by the switching process of the voltage source converter based on high-frequency inductive reactance. The third inductor L3 and the capacitor C f The intermediate branch is used to filter the harmonics near the switching frequency, which can optimize the filtering performance. The grid voltage can be recorded as u ga 、u gb 、u gc The remaining variables are defined as follows:

[0073] u ia 、u ib and u ic It represents the instantaneous value of the output phase voltage on the AC side of the voltage source type bidirectional inverter circuit obtained by sinusoidal pulse width modulation. 1a 、i 1b 、i 1cIt represents the instantaneous value of the current inside the battery energy storage converter (i.e. flowing through the first inductor L1), and the current flowing to the grid side is positive. 2a 、i 2b 、i 2c Indicates the current outside the battery energy storage converter (i.e., flowing through the second inductor L2), that is, the instantaneous value of the grid-side current. The current flowing to the grid side is positive. ma 、u mb 、u mc Indicates L3-C f The instantaneous value of the voltage from the upper end of the branch to point N2, u ca 、u cb 、u cc Indicates the instantaneous value of the filter capacitor voltage, i 3a 、i 3b 、i 3c Indicates that the flow passes through L3-C f The instantaneous value of the current in the branch.

[0074] Among the above variables, all three-phase variables can be converted into variables in the αβ coordinate system (i.e., two-phase stationary coordinate system) by Clark transformation, and the variables in the αβ coordinate system can also be converted into variables in the abc coordinate system (i.e., three-phase stationary coordinate system) by Clark inverse transformation. 1a 、i 1b 、i 1c After Clark transformation, it is converted to i 1α and i 1β , on the contrary, 1α and i 1β It can be converted to i by Clark inverse transformation 1a 、i 1b 、i 1c By analogy, the expanded variables can be further defined as follows: gα 、u gβ represents the grid voltage in the αβ coordinate system, u iα 、u iβ represents the AC side output voltage of the bidirectional inverter circuit in the αβ coordinate system, i 1α 、i 1β represents the internal current of the battery energy storage converter in the αβ coordinate system, i 2α 、i 2β represents the external (grid side) current of the battery energy storage converter in the αβ coordinate system, u mα 、u mβ Indicates L3-C in the αβ coordinate system f Branch voltage, u cα 、u cβ Represents the component of the filter capacitor voltage on the α / β axis, i 3α 、i 3β Indicates that the flow passes through L3-Cf The component of the branch current on the α / β axis.

[0075] Among the above variables, i 1a 、i 1b 、i 1c 、i 2a 、i 2b 、i 2c Both can be obtained by sampling the current sensor, u ga 、u gb 、u gc 、u ca 、u cb 、u cc It can be sampled by a voltage sensor and sent to the control circuit for calculation.

[0076] The control algorithm and modeling method described in the present invention application hereinafter are all performed in the αβ coordinate system and will not be described in detail.

[0077] The reference value of the variable is represented by a star superscript *. Usually, the reference value of the grid current can be expressed as:

[0078]

[0079] Among them, I 2R Indicates the effective value of the phase current expected to be fed into the grid; θ g Indicates the grid angle, when the grid A phase voltage passes through zero point, θ g =0; Indicates the power factor angle between the grid voltage and the grid current signal. When it is set to 0, it means unity power factor discharge. When set to 180°, it indicates unity power factor charging; and They are the reference values ​​of the grid current components on the α / β axes respectively.

[0080] Further, for the inductor and capacitor circuit, based on the phasor method, the reference values ​​of the filter capacitor voltage and the inner current can be derived from the above formula:

[0081]

[0082] Where, ω represents the grid angular velocity; and are the reference values ​​of the filter capacitor voltage components on the α / β axis respectively; and are the reference values ​​of the inner current components on the α / β axis respectively; u gα 、u gβ They represent the grid voltage components on the α / β axis in the αβ coordinate system; I 2RIndicates the effective value of the phase current expected to be fed into the grid; θ g Indicates the grid angle; Indicates the power factor angle between the grid voltage and the grid current signal; L2 is the second inductor of the battery energy storage converter; L3 and C f They are respectively the inductance and capacitance of the middle branch of the battery energy storage converter, and the middle branch is used to perform notch filtering on the harmonics near the switching frequency.

[0083] The voltage of the intermediate branch of the output filter circuit of the battery energy storage converter has the following quantitative relationship:

[0084]

[0085] The dots above the variables represent differential operations; u mα 、u mβ They represent the components of the intermediate branch voltage on the α / β axis in the αβ coordinate system respectively; and They represent the reference values ​​of the components of the intermediate branch voltage on the α / β axis in the αβ coordinate system respectively; and They represent the differential of the components of the external current of the battery energy storage converter on the α / β axis in the αβ coordinate system respectively; and They represent the differential of the reference value of the component of the external current of the battery energy storage converter on the α / β axis in the αβ coordinate system respectively; and They represent the differential of the components of the current inside the battery energy storage converter on the α / β axis respectively; and They represent the differential of the reference value of the components of the current inside the battery energy storage converter on the α / β axis; u cα and u cβ They represent the components of the filter capacitor voltage on the α / β axis respectively.

[0086] Definition 1α =i 1α * -i 1α , e 1β =i 1β * -i 1β , which represents the error between the reference value and the actual value of the variable, can be deduced as:

[0087]

[0088] Similarly, we can define e 2α =i 2α * -i 2α , e 2β =i 2β* -i 2β , it can be deduced that:

[0089]

[0090] Finally, define e 3α =u cα * -u cα , e 3β =u cβ * -u cβ . It can also be deduced that:

[0091]

[0092] Let vector e α =[e 1α e 2α e 3α ] T , vector e β =[e 1β e 2β e 3β ] T , define L Σ =L1L2+L2L3+L1L3, the state space equation can be solved by elimination method and can be expressed as follows

[0093]

[0094] in,

[0095]

[0096] u iα 、u iβ It represents the component of the AC side output voltage of the bidirectional inverter circuit on the α / β axis in the αβ coordinate system.

[0097] At this point, the error model of the battery energy storage converter has been established. Based on this error model, the finite time convergence control of the battery energy storage converter can be further realized. The specific scheme will be described later. First, define the function N(x) as

[0098]

[0099] Defining functions for

[0100]

[0101] In the above two equations, x represents the function variable, α0, β0, γ, k, σ are all control parameters that can be adjusted as needed; sgn(x) represents the sign function, which outputs 1 when the independent variable x is greater than zero, -1 when x is less than zero, and zero when x is equal to zero.

[0102] The sliding surface expression under the two-phase stationary coordinate system (αβ coordinate system) is selected as follows:

[0103]

[0104] Among them, S fα and S fβ They represent the sliding surface of the α-axis subsystem and the sliding surface of the β-axis subsystem respectively; t represents the current time, and the time when the system starts running is the zero time; k1 represents an adjustable control coefficient, similar to k in formula (11); λ p and λ i are all adjustable control coefficients, and their derivatives can be obtained:

[0105]

[0106] The expected convergence law of the two coordinate axis subsystems under the stationary coordinate is the same, which can be expressed as

[0107]

[0108] Wherein, k2 represents an adjustable control coefficient (similar to k in formula (11)), and α2 represents an adjustable control coefficient different from α1, also derived from formula (11).

[0109] Let equation (13) be equal to equation (14), and substitute the specific expression of the error model into it, and we can solve the output voltage expression of the converter circuit in the αβ coordinate system as follows:

[0110]

[0111] in

[0112]

[0113] e 1α and e 1β 、e 2α and e 2β 、e 3α and e 3β They represent the errors of the inner current, outer current, and filter capacitor voltage on the α / β axis respectively; L3 and C f are the inductance and capacitance of the middle branch of the battery energy storage converter respectively; L1 and L2 represent the inductance of the first inductor and the second inductor in the battery energy storage converter respectively; and They represent the differential of the reference value of the components of the outer current on the α / β axis respectively; and Respectively represent the differential of the inner current component on the α / β axis; u cα and u cβ They represent the components of the filter capacitor voltage on the α / β axis respectively.

[0114] For the α-axis component, the Lyapunov function V can be defined as:

[0115]

[0116] It can be proved that the corresponding convergence time t c The upper limit of is bounded as follows:

[0117]

[0118] Where V0 represents the initial value of the Lyapunov function V at time zero. Based on the same principle, it can be proved that the convergence time of the β subsystem also has a clear upper limit. In summary, taking the α-axis subsystem as an example, the specific control algorithm block diagram of the battery energy storage converter can be obtained by Figure 2 express.

[0119] According to the above figure, the specific operation process of the algorithm is as follows Figure 3 shown.

[0120] The above algorithm is executed in a cycle with the controller sampling rate, which can realize the sliding mode control of the battery energy storage converter. In addition, in some cases, Figure 2 The ξ2 module in the circuit can also be used as a proportional resonant regulator G PR (s) is replaced, and the Laplace domain (s domain) expression of the regulator is as follows:

[0121]

[0122] Among them, k p Represents the proportional coefficient of the proportional resonant regulator, ω c represents its bandwidth, ω0 represents the resonant frequency of the regulator, k r represents the coefficient of the resonance term.

[0123] Based on the above theory, a battery energy storage converter prototype was built to implement and experimentally verify the algorithm. The experimental results at different times are presented in the form of oscilloscope voltage / current waveforms. Figure 4(a) to Figure 4(d) In the figure, the energy storage converter discharge, charging steady-state waveform, charging->discharging dynamic switching waveform and discharging->charging dynamic switching waveform are respectively represented. ga The signal represents the phase voltage of phase A of the power grid, marked as u gbThe signal represents the phase voltage of phase B of the power grid. Since it is a three-phase three-wire power grid, u gc No measurement is required, it can be inferred from the voltage of phases A and B. 2a Indicates the A-phase grid current, i 2b Represents the grid current of phase B. It can be seen that the steady-state output current of the energy storage converter prototype is sinusoidal, without obvious harmonic distortion, which can verify the correctness of the modeling and algorithm. When a given change occurs, the switching can be completed in a relatively fast time, and its dynamic response process has finite time convergence.

[0124] After the feedback quantity required by the sliding mode control strategy with finite time convergence is sent to the control circuit, the voltage control quantity is calculated through the error model shown in equation (9) and the method shown in equation (15), and the voltage control quantity of the three phases abc is obtained through Clark inverse transformation. The pulse control signal of the converter can be obtained through SPWM modulation. The error model of the system makes the structure of the control quantity simple and easy to promote practical application. This control method can achieve finite time convergence of the controlled object, has extremely strong rapidity and robustness, and thereby achieves optimal control of the battery energy storage converter.

[0125] Example 2

[0126] The electronic device of the present invention includes a central processing unit (CPU), which can perform various appropriate actions and processes according to computer program instructions stored in a read-only memory (ROM) or loaded from a storage unit into a random access memory (RAM). In the RAM, various programs and data required for device operation can also be stored. The CPU, ROM and RAM are connected to each other via a bus. An input / output (I / O) interface is also connected to the bus.

[0127] Multiple components in the device are connected to the I / O interface, including: input units, such as keyboards, mice, etc.; output units, such as various types of displays, speakers, etc.; storage units, such as disks, optical disks, etc.; and communication units, such as network cards, modems, wireless communication transceivers, etc. The communication unit allows the device to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunication networks.

[0128] The processing unit performs the various methods and processes described above. For example, in some embodiments, the method can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit. In some embodiments, part or all of the computer program can be loaded and / or installed on the device via a ROM and / or a communication unit. When the computer program is loaded into RAM and executed by the CPU, one or more steps of the method described above can be performed. Alternatively, in other embodiments, the CPU can be configured to perform the method in any other appropriate manner (e.g., by means of firmware).

[0129] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0130] The program code for implementing the method of the present invention can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code can be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0131] In the context of the present invention, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0132] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A battery energy storage converter control method based on an error model, characterized in that: The method includes: Obtain the voltage and current values ​​of the battery energy storage converter in the abc coordinate system, and convert them into the voltage and current values ​​in the αβ coordinate system through Clark transformation; According to the voltage and current values ​​in the αβ coordinate system, the reference values ​​of the voltage and current values ​​in the αβ coordinate system are calculated respectively; Calculate the errors between the reference value and the actual value of the voltage and current in the αβ coordinate system respectively, and construct an error model; Based on the error model, the output voltage of the AC side in the αβ coordinate system is solved within a limited convergence time to realize the control of the battery energy storage converter; The voltage and current values ​​include filter capacitor voltage, inner current and outer current.

2. A battery energy storage converter control method based on an error model according to claim 1, characterized in that: The reference value of the outer current in the αβ coordinate system is specifically calculated as: Among them, I 2R Indicates the effective value of the phase current expected to be fed into the grid; θ g Indicates the grid angle; Indicates the power factor angle between the grid voltage and grid current signals; and are the reference values ​​of the components of the outer current on the α / β axis respectively.

3. A battery energy storage converter control method based on an error model according to claim 1, characterized in that: The reference values ​​of the filter capacitor voltage and inner current in the αβ coordinate system are calculated as follows: in, and are the reference values ​​of the filter capacitor voltage components on the α / β axis respectively; and are the reference values ​​of the inner current components on the α / β axis respectively; ω represents the angular velocity of the grid; u gα and u gβ They represent the grid voltage components on the α / β axis in the αβ coordinate system; I 2R Indicates the effective value of the phase current expected to be fed into the grid; θ g Indicates the grid angle; Indicates the power factor angle between the grid voltage and the grid current signal; L2 is the second inductance value of the battery energy storage converter; L3 and C f are the inductance and capacitance of the middle branch of the battery energy storage converter respectively.

4. A battery energy storage converter control method based on an error model according to claim 1, characterized in that: The error model includes: Definition 1α =i 1α * -i 1α , e 1β =i 1β * -i 1β , which represents the error between the reference value and the actual value of the inner current; Definition 2α =i 2α * -i 2α , e 2β =i 2β * -i 2β , which represents the error between the reference value and the actual value of the outer current; Definition 3α =u cα * -u cα , e 3β =u cβ * -u cβ , which represents the error between the reference value and the actual value of the filter capacitor voltage; It is deduced that: Among them, e 1α and e 1β 、e 2α and e 2β 、e 3α and e 3β Respectively represent the errors of the components of the inner current, outer current, and filter capacitor voltage on the α / β axis; and are the reference values ​​of the inner current components on the α / β axis respectively; i 1α and i 1β are the actual values ​​of the components of the inner current on the α / β axis respectively; and and and Respectively represent the differential errors of the inner current, outer current, and filter capacitor voltage on the α / β axis; u mα 、u mβ They represent the components of the intermediate branch voltage on the α / β axis in the αβ coordinate system respectively; and They represent the reference values ​​of the intermediate branch voltage components on the α / β axis in the αβ coordinate system; u iα and u iβ They represent the α / β axis components of the AC side output voltage in the αβ coordinate system; L3 and C f are the inductance and capacitance of the middle branch of the battery energy storage converter respectively; L1 and L2 represent the inductance of the first inductor and the second inductor in the battery energy storage converter respectively; u cα and u cβ Respectively represent the components of the filter capacitor voltage on the α / β axis; and are the reference values ​​of the filter capacitor voltage components on the α / β axis respectively; and They represent the differential of the reference value of the components of the outer current on the α / β axis respectively; and Respectively represent the differential of the inner current component on the α / β axis; u cα and u cβ Respectively represent the components of the filter capacitor voltage on the α / β axis; and They respectively represent the differential of the reference value of the component of the filter capacitor voltage on the α / β axis.

5. A battery energy storage converter control method based on an error model according to claim 4, characterized in that: The calculation of the intermediate branch voltage component on the α / β axis and its reference value in the αβ coordinate system is specifically as follows: The dots above the variables represent differential operations; u mα 、u mβ They represent the components of the intermediate branch voltage on the α / β axis in the αβ coordinate system respectively; and They represent the reference values ​​of the components of the intermediate branch voltage on the α / β axis in the αβ coordinate system respectively; and They represent the differential of the reference value of the components of the outer current on the α / β axis respectively; and Respectively represent the differential of the inner current component on the α / β axis; u cα and u cβ They respectively represent the components of the filter capacitor voltage on the α / β axis; L3 represents the inductance value of the middle branch.

6. A battery energy storage converter control method based on an error model according to claim 5, characterized in that: The error model also includes: Let vector e α =[e 1α e 2α e 3α ] T , vector e β =[e 1β e 2β e 3β ] T , define L Σ =L1L2+L2L3+L1L3, the error model state space equation can be solved by elimination method. The standard form of the error model state space equation is as follows: in, u iα 、u iβ It represents the component of the AC side output voltage on the α / β axis in the αβ coordinate system.

7. A battery energy storage converter control method based on an error model according to claim 1, characterized in that: The process of solving the output voltage on the AC side within a finite convergence time includes: Define the function N(x) as: Defining functions for: In the formula, x represents the function independent variable; α0, β0, γ, k, σ are all control parameters adjusted according to needs; sgn(x) represents the sign function; The sliding surface expression in the αβ coordinate system is: Among them, S fα and S fβ They represent the sliding surface of the α-axis subsystem and the sliding surface of the β-axis subsystem respectively; t represents the current moment; k1 and α1 both represent control parameters that can be adjusted according to needs; e 1α and e 1β 、e 3α and e 3β Respectively represent the errors of the inner current and filter capacitor voltage on the α / β axis; λ p and λ i All are adjustable control coefficients; By taking the derivative of the sliding surface in the αβ coordinate system, we can obtain: in, and denote the differentials of the sliding surface of the α-axis subsystem and the sliding surface of the β-axis subsystem respectively; and and Respectively represent the differential of the error of the inner current and filter capacitor voltage components on the α / β axis; The expected convergence laws of the two coordinate axis subsystems in the αβ coordinate system are the same, which can be expressed as: Wherein, k2 represents a control parameter adjusted as needed; α2 represents a control parameter adjusted as needed, but different from α1; and They represent the expected reaching laws of the α and β axis subsystems respectively; Let the sliding surface of each axis subsystem in the αβ coordinate system be equal to the expected reaching law of the corresponding subsystem, and substitute it into the error model to obtain the output voltage expression of the AC side of the battery energy storage converter in the αβ coordinate system: in, <h2 style=";text-align:left;direction:ltr">L<h2 style=";text-align:left;direction:ltr"> Σ <h2 style=";text-align:left;direction:ltr"> (L1L2+L2L3+L1L3) e 1α and e 1β 、e 2α and e 2β 、e 3α and e 3β They represent the errors of the inner current, outer current, and filter capacitor voltage on the α / β axis respectively; L3 and C f are the inductance and capacitance of the middle branch of the battery energy storage converter respectively; L1 and L2 represent the inductance of the first inductor and the second inductor in the battery energy storage converter respectively; and They represent the differential of the reference value of the components of the outer current on the α / β axis respectively; and Respectively represent the differential of the inner current component on the α / β axis; u cα and u cβ They represent the components of the filter capacitor voltage on the α / β axis respectively.

8. A battery energy storage converter control method based on an error model according to claim 1, characterized in that: The method further comprises: performing a Clark inverse transformation on the output voltage of the AC side in the αβ coordinate system to obtain a voltage control quantity in the abc coordinate system, and obtaining a pulse control signal of the battery energy storage converter by SPWM modulation.

9. A battery energy storage converter control method based on an error model according to claim 1, characterized in that: The voltage and current in the battery energy storage converter in the abc coordinate system are obtained through sensors and sampling.

10. An electronic device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the processor executes the program, the method according to any one of claims 1 to 9 is implemented.

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