CN109149620A - One kind is from the soft straight system control method of energy storage multiterminal and system - Google Patents

Abstract

The invention discloses a control method and system for a self-storage multi-terminal flexible DC system. A system controller is designed by a reverse inference method to realize DC voltage stability and fast independent control of active and reactive power. At the same time, a constraint command filter is introduced to solve the problem. The differential expansion and control saturation problems of the inverse control, and design the compensation signal to solve the error problem of the filter, introduce the adaptive control to ensure the robustness of the system to the uncertain parameters, and use the projection operator to optimize the adaptive uncertain parameters , the control law of the system is designed based on the Lyapunov stability theory, which improves the anti-interference ability of the system and realizes the asymptotic stability of the whole system. Finally, a simulation model is built in the simulation software, and compared with the traditional PID control algorithm and the command filtering inverse algorithm, the simulation results show that the control method of the present invention has better robustness and dynamic response performance, and is a self-storage multi-terminal flexible The control algorithm of the direct system provides theoretical basis and technical support.

Description

A kind of self-energy storage multi-terminal flexible straight system control method and system

technical field

The invention belongs to the technical field of flexible direct current transmission control, and in particular relates to a control method and system for a self-storage multi-terminal flexible direct current system.

Background technique

In recent years, with the sustained and rapid economic and social development, the structure of power grids at all levels has been significantly strengthened. Subsequently, high-reliability power supply and friendly access to distributed energy with high penetration rate have put forward higher requirements for power transmission technology in distribution network. Back-to-Back VSC-HVDC is the latest developed power grid flexible control technology. Decoupling and interconnection can realize long-term safe closed loop operation of any feeder, greatly improving the reliability of power supply of the power grid; PQ four-quadrant control can precisely regulate the power flow distribution of the power grid and improve the economical operation of the power grid; omit the DC line link and reduce the cost of the control system and complexity, more suitable for the actual operation of the distribution network. The power flow control technology represented by back-to-back flexibility and straightness is still essentially the regulation at the power level. In the energy level, the power grid provides an "energy container" on the spatial axis. If the adjustable capacity of the interconnected feeder is small, the distribution will be limited. Grid operation optimization effect. As the "energy container" of the time axis, energy storage essentially changes/improves the simultaneity of electric energy production, transmission and consumption, and can play a role in controlling the DC bus voltage and the shift of the grid's peak-shaving and valley-filling energy.

Self-storage multi-terminal back-to-back flexible straightening technology realizes unified application of energy regulation technology in two different dimensions of space axis and time axis, which can further strengthen the control capability of multi-terminal flexible straightening system, and build a "source, network, load, storage, control system". "Flexible interconnected distribution network. It will play a huge role in friendly grid connection of high-penetration distributed energy and high-reliability power supply of urban power grids. Traditionally, PID control is used in DC transmission systems, which has problems such as a large number of controllers, difficulty in parameter tuning, and poor transient performance. When the system is disturbed or faulty, the overshoot of the DC voltage is too large, the system response time is long, and it is difficult to recover quickly.

SUMMARY OF THE INVENTION

Aiming at the above problems, the present invention proposes a control method and system for a self-storage multi-terminal flexible straight system. First, the SES-MBTB nonlinear mathematical model is established, and the back-calculation method is used to design the controllers of each subsystem respectively. The DC voltage control introduces a constraint command filter to solve the differential expansion problem of the reverse thrust control, and the filter compensation signal is designed to solve the problem of the error of the filter itself and the saturation of the controller input. The adaptive control is introduced to ensure the robustness of the system to uncertain parameters, and the projection operator is used to optimize the adaptive uncertain parameters. Based on the Lyapunov stability theory, the asymptotic stability of the system is proved. Finally, the simulation verifies that the projection-adaptive command filter-backward control has good robustness and dynamic responsiveness.

To achieve the above-mentioned technical purpose and achieve the above-mentioned technical effect, the present invention is realized through the following technical solutions:

In a first aspect, the present invention provides a method for controlling a self-storage multi-terminal flexible straightening system, comprising:

The energy storage controller and the voltage source converter controller are designed by the inverse method, and the control laws corresponding to the energy storage controller and the voltage source converter controller are obtained respectively;

Based on the adaptive control, using the projection method to optimize the adaptive parameters in each of the control laws, respectively, to obtain the energy storage controller and the voltage source converter controller;

The energy storage controller outputs the control parameters to the energy storage device in the self-storage multi-terminal flexible DC system to realize the control of the energy storage device; the voltage source converter controller outputs the control parameters to the self-energy storage multi-terminal flexible DC The corresponding voltage source converter in the system realizes the control of the corresponding voltage source converter.

Further, the design of the energy storage controller and/or the voltage source converter controller using the inverse method is specifically:

The Lyapunov function and the virtual control law are designed respectively. The virtual control law is used to ensure the absolute convergence of the energy storage device or the voltage source converter in the self-storage multi-terminal flexible DC system.

Further, the self-energy storage multi-terminal flexible straightening system is a self-energy storage back-to-back multi-terminal flexible straightening system,

The control method further includes obtaining a mathematical model of the self-energy storage back-to-back multi-terminal flexible straight system; the mathematical model of the self-energy storage back-to-back multi-terminal flexible straight system is specifically:

In the formula, C represents the DC side capacitance, U _dc represents the DC bus voltage, represents the derivative of the voltage U _dc with respect to time t, U _sdi and i _di represent the d-axis components of the AC voltage and current of the voltage source converter, respectively, U _b represents the outlet voltage of the energy storage device, and i _b represents the current on the outlet side of the energy storage device.

Further, designing the energy storage controller by the inverse method to obtain the corresponding control law includes: designing the energy storage controller by using the inverse method, first obtaining the virtual control quantity in the energy storage controller. for:

where: represents the DC bus voltage reference value, express The first derivative of , k ₁ represents an adjustable parameter greater than 0, z ₁ represents the voltage tracking error, U _dc represents the DC bus voltage;

the virtual control It is used as the command value of the inner loop controller and participates in the inner loop current control.

Further, the control method of the self-energy storage multi-terminal flexible straightening system further includes:

Use adaptive estimates Replace the capacitor C in the energy storage controller;

A new virtual control variable is obtained that takes into account the adaptive estimation for:

Further, the control method for a self-storage multi-terminal flexible straightening system further includes: introducing a constraint command filter into the energy storage controller; the new virtual control variable Output signal after passing through constraint command filter and its derivatives The state space expression of the constraint instruction filter is:

In the formula: y ₁ =x ^c , δ=x ^d , x ^d is the input quantity, x ^c is the output quantity, is the derivative of the output quantity, ξ is the damping of the command filter, ω _n is the bandwidth, _SR ( ) and _SM ( ) represent the rate and amplitude constraints, respectively;

A compensation signal is designed to compensate for the error of the constraint command filter, and the calculation formula of the compensation signal is:

In the formula: ε is the compensation signal, is the derivative of the compensation signal, k ₁ represents an adjustable parameter greater than 0, is the reference value of the energy storage current.

Further, the control method for the self-energy storage multi-terminal flexible straightening system further includes: based on and the positive definite Lyapunov function The control law of the energy storage controller is obtained by using the inverse method:

In the formula, U _rb represents the bridge arm side voltage of the energy storage device, k ₁ and k ₂ are adjustment parameters greater than 0, is the derivative of the reference value of the energy storage current; L _b represents the inductance on the outlet side of the energy storage device, and R _b represents the resistance on the outlet side of the energy storage device, which are respectively used to replace the resistance R and the inductance L in the energy storage controller; z ₂ represents the current tracking error of the energy storage device, The calculation formula is:

in, is the adaptive estimate error, e ₁ is the adaptive estimated value reference value.

Further, the adaptive law of uncertain parameters obtained by optimizing the adaptive estimated value in the control law of the energy storage controller using the projection method is specifically:

In the formula: Proj(,·,) is the projection operator, and γ ₁ , γ ₂ , and γ ₃ are the error coefficients.

Further, the adaptive estimation is defined as L ₁ represents the grid-side equivalent inductance, R ₁ represents the grid-side equivalent resistance, and the estimated value error is e ₄ and e ₅ are the adaptive estimated values, respectively and The reference value of , the positive definite Lyapunov function is The voltage source converter controller is designed by the inverse method, and the control law in the voltage source converter controller is obtained as follows:

In the formula: U _rd1 and U _rq1 are the components of the d-axis and q-axis of the AC side outlet voltage vector of the voltage source converter, respectively, k ₃ and k ₄ are adjustable parameters greater than 0, and i _d1 and i _q1 are the voltage source respectively The components of the d-axis and q-axis of the AC side current vector of the converter, ω ₁ is the grid angular frequency; is the reference quantity of the d-axis component of the AC side current vector of the voltage source converter, for the first derivative of ; is the reference quantity of the q-axis component of the AC side current vector of the voltage source converter, for The first derivative of ; U _sd1 and U _sq1 are the components of the d-axis and q-axis of the grid-side voltage vector of the voltage source converter, respectively.

Further, using the projection method to adaptively estimate the control law in the voltage source converter controller After optimization, the adaptive law of uncertain parameters is obtained as:

In the formula, Proj(,·,) is the projection operator, and γ ₄ and γ ₅ are the error coefficients.

In a second aspect, the present invention provides a self-energy storage multi-terminal back-to-back flexible straightening system control system, comprising:

The control law acquisition module of the controller is used to design the energy storage controller and the voltage source converter controller by using the inverse method to obtain the corresponding control law;

The self-adaptive parameter optimization module is used to optimize the self-adaptive parameters in each of the control laws based on the self-adaptive control by using the projection method to obtain the energy storage controller and the voltage source converter controller. Compared with the prior art, the beneficial effects of the present invention:

The invention proposes a control method and system for a self-energy storage multi-terminal flexible DC system. First, the entire system is decomposed into multiple subsystems, and the subsystems are energy storage devices or voltage source converters; Controller for each subsystem. Because the DC voltage control introduces the constraint command filter to solve the differential expansion problem of the reverse control, the filter compensation signal is designed to solve the error of the constraint command filter itself and the problem of the controller input saturation; the introduction of the adaptive control ensures the self-storage multi-terminal flexible direct system For the robustness of uncertain parameters, the projection operator is used to optimize the adaptive uncertain parameters, and the asymptotic stability of the self-storage multi-terminal flexible straight system is proved based on the Lyapunov stability theory. Finally, simulation verifies that the control method of the present invention (ie, the projection adaptive command filtering inverse control) has good robustness and dynamic responsiveness.

Description of drawings

1 is a schematic structural diagram of an SES-MBTB system according to an embodiment of the present invention;

2 is a schematic diagram of a topology structure of an energy storage device according to an embodiment of the present invention;

3 is a schematic diagram of a VSC topology structure according to an embodiment of the present invention;

4 is a system control block diagram of an embodiment of the present invention;

5 is a schematic structural diagram of a constraint instruction filter according to an embodiment of the present invention;

Fig. 6 is a PID and PACBC control comparison diagram of an embodiment of the present invention;

FIG. 7 is a comparison diagram of CBC and PACBC control according to an embodiment of the present invention.

Detailed ways

In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.

The application principle of the present invention will be described in detail below with reference to the accompanying drawings.

The main idea of the present invention is:

(1) Establish the nonlinear mathematical model of the self-storage multi-terminal flexible straight system;

(2) Decomposing the self-energy storage multi-terminal flexible straight system into several subsystems, and the subsystems are energy storage devices or voltage source converters;

(3) The controller of each subsystem is designed respectively by adopting the reverse inference method; the port of the voltage source converter adopts constant power control; the energy storage device is controlled by the DC voltage, and a constraint command filter is introduced into the DC voltage control The controller solves the differential expansion problem of the inverse control, and the filter compensation signal is designed to solve the problem of the error of the filter itself and the saturation of the controller input; further, the adaptive control is introduced to ensure the robustness of the system to uncertain parameters, and the projection algorithm is used. The self-storage multi-terminal flexible straight system is proved to be asymptotically stable based on Lyapunov stability theory by optimizing the adaptive uncertain parameters.

(4) The simulation verifies that the projection adaptive command filter inverse control has good robustness and dynamic responsiveness.

Example 1

In the embodiment of the present invention, the control method of the present invention is described by taking the self-energy storage multi-terminal back-to-back flexible straightening system as an example.

Step 1. Establish a nonlinear mathematical model of the self-energy storage based multiport back-to-back VSC-HVDC (SES-MBTB) system

The self-energy storage multi-terminal back-to-back flexible direct system in the prior art has three wiring modes: series, parallel, and mixed connection. The self-energy storage multi-terminal back-to-back flexible direct system proposed in the embodiment of the present invention adopts the parallel mode, omitting the DC line link. The energy storage device is provided with a DC/DC converter, and the DC/DC converter is shared with the DC side of all voltage source converters, which is conducive to the stability of the DC side voltage of the flexible DC system, and the control is simple and flexible. Easy to expand, the five-port SES-MBTB device structure topology is shown in Figure 1.

The self-storage back-to-back flexible direct system is composed of a 4-terminal voltage source converter and a 1-terminal energy storage device. Under normal operation, the energy storage device is used as a slack node for constant DC voltage control, and at the same time, the active power balance of the system is realized; The AC side of the converter is respectively connected with each feeder of the distribution network to realize flexible interconnection (AC-DC-AC decoupling) between multiple feeders, and the voltage source converter adopts constant power control. Since the SES-MBTB system in the embodiment of the present invention adds an energy storage device, and the energy storage device has the ability to adjust the energy sequence, the entire flexible direct system becomes a highly integrated comprehensive energy conversion device.

The energy storage device takes charging as the positive direction, and its topology is shown in Figure 2. The mathematical model of the energy storage device can be obtained from Figure 2 as follows:

where L _b is the equivalent impedance, i _b is the current at the outlet side of the energy storage device, represents the derivative of current i _b with respect to time t, R _b is the equivalent resistance, U _b is the outlet voltage of the energy storage device, U _rb is the side voltage of the bridge arm of the energy storage device, Ur _rb =dU _dc , where d is the duty cycle, U _dc is the DC bus voltage.

The voltage source converter takes the power injected into the AC network as the positive direction, and its topology is shown in Figure 3. The mathematical model of the voltage source converter can be obtained from Figure 3:

In the formula, L is the equivalent reactance of the AC side reactor, i _i is the grid current on the AC side, Represents the derivative of current i _i to time t, R is the equivalent resistance of the AC side reactor, U _ri is the AC side voltage value of the voltage source converter, and U _si is the AC side grid voltage.

Converting equation (2) into the dq synchronous rotating coordinate system, taking the voltage source converter as an example, for the voltage source converter that outputs power (that is, the output of the voltage source converter is power), the mathematical model is:

In the formula, respectively represent the derivatives of currents i _d1 and i _q1 to time t, i _d1 and i _q1 are the components of the d-axis and q-axis of the grid-side current vector of the voltage source converter, respectively, ω ₁ is the grid angular frequency, U _sd1 , U _sq1 are the d-axis and q-axis components of the grid-side voltage vector of the voltage source converter, respectively, U _rd1 and U _rq1 are the d-axis and q-axis components of the AC side outlet voltage vector of the voltage source converter, respectively, L ₁ represents the grid side, etc. Effective inductance value; R ₁ represents the equivalent resistance value on the grid side.

For voltage source converters of the absorbing power type, the current flow is reversed.

The AC outlet reactor of the voltage source converter mainly plays the role of current limiting and filtering. The actual reactor is weak resistance, the resistance R is very small, and the loss can be ignored. In the steady state, the active and reactive power of the voltage source converter can be Expressed as:

The d-axis is located in the direction of the grid voltage vector through the phase-locked loop, so U _sq1 =0, U _sd1 =U _s , U _s represents the grid voltage, and equation (4) can be expressed as:

It can be known from equation (5) that active power and reactive power can be independently controlled by controlling the current dq-axis component of the voltage source converter. Excluding the converter loss, the powers at both ends of the AC and DC terminals of the self-storage multi-terminal flexible direct system are equal. Therefore, the mathematical model of the self-storage multi-terminal back-to-back flexible direct system is obtained as follows:

In the formula, C is the DC side capacitance of the self-energy storage multi-terminal back-to-back flexible direct system, U _dc is the DC bus voltage of the self-energy storage multi-terminal back-to-back flexible direct system, represents the derivative of the voltage U _dc with respect to time t, U _sdi and i _di represent the d-axis components of the AC voltage and current of the voltage source converter, U _b is the voltage at the outlet side of the energy storage device, and i _b is the current at the outlet side of the energy storage device.

It can be seen from equation (6) that the stability of the DC voltage can be maintained by controlling the current. In the steady-state operation mode, the DC voltage remains constant. It can be known that the inflow power of each port (that is, the energy storage port and the flexible DC port) is equal to the outflow power. Therefore, in order to smoothly transmit the active power of the self-storage multi-terminal flexible DC system, the DC voltage must be kept stable. When the power is unbalanced, the DC voltage will fluctuate. The energy storage device with a constant DC voltage is a power balance point. The charging and discharging characteristics of the energy storage device can balance the system power and reduce the impact of power imbalance on the DC voltage.

In step 2, the energy storage controller and the voltage source converter controller are designed using the inverse method. designed by the inverse method;

Since the DC voltage may fluctuate or even exceed the limit when the power fluctuates, the embodiment of the present invention applies the inverse method to the controller design, and adds a constraint command filter for the constant DC voltage control to solve the differential expansion and constraint problems of the inverse control. , and design a compensation signal to solve the error problem of the filter itself, and introduce an adaptive projection operator to the uncertain parameters in the self-storage multi-terminal flexible straight system to ensure the boundedness of the estimated value.

First, the complete self-energy storage multi-terminal flexible direct system is decomposed into several subsystems, and the subsystems are energy storage devices or voltage source converters;

Then, the Lyapunov function and the virtual control law are designed in each subsystem, and the complete control system is obtained by inversion. With tracking performance and better stability, the overall control block diagram of the self-energy storage multi-terminal flexible straight system is shown in Figure 4.

The specific design of the energy storage controller is as follows:

Define the voltage and current tracking errors:

where U _dc is the DC bus voltage, is the reference value of the DC bus, i _b is the outlet side current of the energy storage device, is the current reference value of the outlet side of the energy storage device. According to equations (6) and (7), the derivative of the voltage tracking error can be expressed as:

Let the first positive definite Lyapunov function be:

Taking the derivative of formula (10), we get:

In the formula, k ₁ is an adjustable parameter greater than 0, let get virtual control for:

Substituting Equation (12) into Equation (11), we can see that Therefore, it conforms to the Lyapunov function control law.

Fourth, in the actual control system, since the capacitance C, the resistance R and the inductance L cannot obtain accurate values, the self-adaptive estimated value is used in the embodiment of the present invention. Replace, where L _b represents the inductance on the outlet side of the energy storage device, and R _b represents the resistance on the outlet side of the energy storage device, which are respectively used to replace the resistance R and the inductance L in the energy storage controller, and the error of the adaptive estimated value is defined as e ₁ , e ₂ and e ₃ are respectively and The reference value of , so equation (12) can be rewritten as:

Step 5: Introduce a constrained command filter to solve the differential expansion and control saturation problems of the inverse control, and design a compensation signal to solve the error problem of the filter;

In order to obtain the output signal, the virtual control variable needs to be derived, which not only increases the complexity of the system, but also increases the influence of measurement noise. Constrained command filters can be used to solve the differential expansion and control saturation problems of inverse control. The basic idea is: the virtual control The filtered output signal is obtained by a second-order constrained filter and its derivatives The filter structure is shown in Figure 5, x ^d is the input quantity, ξ is the damping of the command filter, ω _n is the bandwidth, x ^c is the output quantity, is the derivative of the output quantity, Represents the integral process. The derivation process of the virtual control variable is obtained through the integration process in the constraint command filter, which avoids the direct derivation of the virtual control variable. The state space expression of the constraint instruction filter is expressed as:

In the formula, y ₁ =x ^c , δ=x ^d , ξ is the damping of the command filter, ω _n is the bandwidth, S _R ( ) and S _M ( ) represent the rate and amplitude constraints, respectively. When the amplitude and rate of the virtual control variable are greater than the system can When the maximum value it bears, there must be an error x ^c -x ^d , and the virtual control signal x ^d can converge faster and more accurately by adjusting the bandwidth ω _n . ω _n needs to select a reasonable value according to the frequency range of the input signal x ^d . When the value of ω _n is much larger than the frequency of the input signal x ^d , the input signal x ^d can pass through the filter without attenuation, greatly reducing the impact of high-frequency noise. .

When the flexible straightening system cannot track the actual given value, it will cause error accumulation, reduce the dynamic response performance of the flexible straightening system, and even lead to the divergence of the flexible straightening system. Therefore, the influence of the constraint command filter error needs to be considered in the controller design. Redefine the voltage tracking error as:

The compensation signal is designed as:

In the formula: ε is the compensation signal, is the derivative of the compensation signal, k ₁ represents an adjustable parameter greater than 0, is the reference value of the energy storage current.

(6) The adaptive control is introduced to ensure the robustness of the system to uncertain parameters, and the parameter projection method is used to optimize the adaptive control, specifically:

According to equations (6), (13) and (16), we can get:

According to equations (1) and (8), the derivative of the current tracking error can be obtained as:

Let the second positive definite Lyapunov function be:

In the formula, γ ₁ , γ ₂ , and γ ₃ are the error coefficients, and the derivation of formula (19) can be obtained:

where k ₁ and k ₂ are adjustment parameters greater than 0, and the control law calculated from equation (20) is:

The parameter projection method is used to optimize the adaptive parameters in the control law in equation (21), and the adaptive law of the adaptive parameters is obtained as:

In the formula, Proj(,·,) is the projection operator.

Compared with the traditional controller, the controller of the present invention simplifies the program, reduces the calculation amount, can obtain better stability and dynamic tracking effect, and is more suitable for engineering applications.

In the embodiment of the present invention, the voltage source converter adopts constant power control, and takes VSC1 as an example to define an adaptive estimated value The adaptive estimator error is e ₄ and e ₅ are respectively and The reference value of the VSC1 controller design process is given below:

(1) Define the VSC1 current tracking error:

In the formula, is the current reference value, according to equations (3), (23) and (24), the derivative of the tracking error can be expressed as:

(2) Set the third positive definite Lyapunov function as:

In the formula, γ ₄ and γ ₅ are error coefficients;

(3) Differentiate formula (27) to get:

Among them, k ₃ and k ₄ are adjustable parameters greater than 0, and the control law calculated by equation (28) is:

The parameter projection method is used to optimize the adaptive parameters in the control law of the voltage source converter controller, and the adaptive law of the adaptive parameters is obtained as:

The voltage source converter controllers of the remaining VSCs are of the same design as the voltage source converter controllers of the VSC1, and will not be repeated here.

The stability of the energy storage controller is analyzed below, and the projection operator is defined as follows:

in is the estimated value of θ, for The maximum and minimum values of , x is a definite adaptive function, and two important properties of the projection operator are:

property 1

nature 2

Ω _θ is the defined constraint set, according to property 1, it can be known that:

From property 2, it can be seen that the adaptive function can make The boundedness of uncertain parameters is guaranteed.

According to equations (20), (21) and (33), we can get:

It can be known from equation (19) that V ₂ is a positive definite function, and it can be known from equation (34) that is a negative definite function, for the energy storage controller V ₂ ≥ 0, Therefore, according to the Lyapunov stability theory, under the action of the control quantity U _rb , the energy storage device will eventually become asymptotically stable. Similarly, it can be proved that V ₃ ≥ 0, VSC1 will eventually be gradually stabilized under the action of control quantities U _rd1 and U _rq1 . To sum up, the whole self-storage multi-terminal flexible straightening system meets the stability conditions.

Example 2

In order to verify the feasibility and effectiveness of the control algorithm proposed in the present invention, a five-terminal SES-MBTB system simulation model as shown in Figure 1 is built based on Matlab/Simulink.

The parameter settings of the simulation model are shown in Table 1:

Table 1 Simulation parameters

Table 2 shows the active power changes of VSC1, VSC2, VSC3, and VSC4 in different time periods. The simulation results are compared under the traditional PID control algorithm and the projection adaptive command filter-backward control (PACBC) algorithm of the present invention.

Table 2 Simulation conditions

Figure 6 shows the comparison of the effects of PID control and PACBC. In Figure 6, (a) (c) (e) are the active power, DC bus voltage, and AC side current harmonic distortion (THD) of each converter station controlled by PID. Control effect diagram, Figure 6(b)(d)(f) is the control effect diagram of active power, DC bus voltage, and AC side current THD of each PACBC converter. Due to the actual loss, each converter cannot fully emit power according to the command value. In Figure 6, the power value fluctuates slightly around the command value, and the energy storage device compensates for the power shortage by charging and discharging. At 0.4s, the power of VSC1 suddenly changes from 2MW to 4MW, and the energy storage device fluctuates downward by 2MW to maintain the system power balance to compensate for the power shortage. At 0.6s, the power of VSC2 suddenly changes from 3MW to 1MW, and the energy storage device operates, and the power rises from -2MW to 0, which effectively balances the system power. As can be seen from Figure 6, PACBC has better power tracking performance and dynamic response capability than PID control, and the power fluctuation is smaller. The DC bus voltage of the self-storage multi-terminal flexible DC system fluctuates at 0.4s and 0.6s due to power changes. It can be seen from Figure 6 that the PACBC voltage overshoot is significantly smaller than that of the PID control, and the tracking error is smaller. The PID control VSC AC side current THD is 5.38%, which does not meet the national standard of 5%. The PACBC algorithm AC side current THD reaches 1.50%, and a good control effect is obtained.

The DC side capacitor plays a role in maintaining the bus voltage, and it is difficult to obtain an accurate value in engineering applications. In order to verify the robustness of PACBC to uncertain parameters, the DC side capacitance C was increased by twice the original value, and simulations were carried out under the command filter inverse control (CBC) and PACBC algorithms, respectively, and the DC voltage error z ₁ was analyzed. Figure 7(a) shows the simulation results of the CBC voltage error under different capacitance parameters, and Figure 7(b) shows the simulation results of the PACBC voltage error under different capacitance parameters.

It can be seen from Figure 7(a) that the DC voltage has a large error in steady state and disturbance under different capacitance parameters, indicating that CBC is more sensitive to parameters, and the change of capacitance parameters in Figure 7(b) affects the voltage. The comparison shows that PACBC has better robustness to uncertain parameters than CBC algorithm, and is more suitable for engineering applications.

As will be appreciated by those skilled in the art, the embodiments of the present application may be provided as a method, a system, or a computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present application. It will be understood that each process and/or block in the flowchart illustrations and/or block diagrams, and combinations of processes and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to the processor of a general purpose computer, special purpose computer, embedded processor or other programmable data processing device to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing device produce Means for implementing the functions specified in a flow or flow of a flowchart and/or a block or blocks of a block diagram.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory result in an article of manufacture comprising instruction means, the instructions The apparatus implements the functions specified in the flow or flow of the flowcharts and/or the block or blocks of the block diagrams.

These computer program instructions can also be loaded on a computer or other programmable data processing device to cause a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process such that The instructions provide steps for implementing the functions specified in the flow or blocks of the flowcharts and/or the block or blocks of the block diagrams.

The embodiments of the present invention have been described above with reference to the accompanying drawings, but the present invention is not limited to the above-mentioned specific embodiments. The above-mentioned specific embodiments are only illustrative rather than restrictive. Under the inspiration of the present invention, without departing from the scope of protection of the present invention and the claims, many forms can be made, which all belong to the protection of the present invention.

Claims (11)

1. a self-energy storage multi-terminal flexible straight system control method, is characterized in that, comprises: The energy storage controller and the voltage source converter controller are designed by the inverse method, and the control laws corresponding to the energy storage controller and the voltage source converter controller are obtained respectively; Based on the adaptive control, using the projection method to optimize the adaptive parameters in each of the control laws, respectively, to obtain the energy storage controller and the voltage source converter controller; The energy storage controller outputs the control parameters to the energy storage device in the self-storage multi-terminal flexible DC system to realize the control of the energy storage device; the voltage source converter controller outputs the control parameters to the self-energy storage multi-terminal flexible DC The corresponding voltage source converter in the system realizes the control of the corresponding voltage source converter. 2. a kind of self-energy storage multi-terminal flexible direct system control method according to claim 1, is characterized in that: described adopting inverse push method to design energy storage controller and voltage source converter controller is specifically: The Lyapunov function and the virtual control law are designed respectively. The virtual control law is used to ensure the absolute convergence of the energy storage device and the voltage source converter in the self-storage multi-terminal flexible DC system. 3. The control method of a self-energy storage multi-terminal flexible straightening system according to claim 1, wherein the self-energy storage multi-terminal flexible straightening system is a self-energy storage back-to-back multi-terminal flexible straightening system, The control method further includes obtaining a mathematical model of the self-energy storage back-to-back multi-terminal flexible straight system; the mathematical model of the self-energy storage back-to-back multi-terminal flexible straight system is specifically: In the formula, C represents the DC side capacitance, U _dc represents the DC bus voltage, represents the derivative of the voltage U _dc with respect to time t, U _sdi and i _di represent the d-axis components of the AC voltage and current of the voltage source converter, respectively, U _b represents the outlet voltage of the energy storage device, and i _b represents the current on the outlet side of the energy storage device. 4. A self-energy storage multi-terminal flexible straight system control method according to any one of claims 1-3, characterized in that: the design of the energy storage controller by the inverse method is used to obtain a corresponding control law, comprising: : The energy storage controller is designed by the inverse method, and the virtual control quantity in the energy storage controller is obtained first. for: where: represents the DC bus voltage reference value, express The first derivative of , k ₁ represents an adjustable parameter greater than 0, z ₁ represents the voltage tracking error, U _dc represents the DC bus voltage; the virtual control It is used as the command value of the inner loop controller and participates in the inner loop current control. 5. a kind of self-energy storage multi-terminal flexible straight system control method according to claim 4, is characterized in that: also comprises: Use adaptive estimates Replace the capacitor C in the energy storage controller; A new virtual control variable is obtained that takes into account the adaptive estimation for: 6 . The method for controlling a self-storage multi-terminal flexible direct system according to claim 5 , further comprising: introducing a constraint command filter into the energy storage controller; the new virtual control quantity Output signal after passing through constraint command filter and its derivatives The state space expression of the constraint instruction filter is: In the formula: y ₁ =x ^c , δ=x ^d , x ^d is the input quantity, x ^c is the output quantity, is the derivative of the output quantity, ξ is the damping of the command filter, ω _n is the bandwidth, _SR ( ) and _SM ( ) represent the rate and amplitude constraints, respectively; A compensation signal is designed to compensate for the error of the constraint command filter, and the calculation formula of the compensation signal is: In the formula: ε is the compensation signal, is the derivative of the compensation signal, k ₁ represents an adjustable parameter greater than 0, is the reference value of the energy storage current. 7. A self-energy storage multi-terminal flexible straight system control method according to claim 6, characterized in that, further comprising: based on and the positive definite Lyapunov function The control law of the energy storage controller is obtained by using the inverse method: In the formula, U _rb represents the bridge arm side voltage of the energy storage device, k ₁ and k ₂ are adjustment parameters greater than 0, is the derivative of the reference value of the energy storage current; L _b represents the inductance on the outlet side of the energy storage device, R _b represents the resistance on the outlet side of the energy storage device, which are used to replace the resistance R and the inductance L in the energy storage controller respectively; z ₂ represents the current tracking error of the energy storage device, The calculation formula is: in, is the adaptive estimate error, e ₁ is the adaptive estimated value reference value. 8. A self-energy storage multi-terminal back-to-back flexible-straightening system control method according to claim 6, characterized in that: an uncertain parameter obtained by using a projection method to optimize the adaptive estimated value in the control law of the energy storage controller The adaptive law of , specifically: In the formula: Proj(,·,) is the projection operator, and γ ₁ , γ ₂ , and γ ₃ are the error coefficients. 9. A self-energy storage multi-terminal back-to-back flexible straightening system control method according to any one of claims 1-3, characterized in that: the self-adaptive estimated value is defined as L ₁ represents the grid-side equivalent inductance, R ₁ represents the grid-side equivalent resistance, and the estimated value error is e ₄ and e ₅ are the adaptive estimated values, respectively and The reference value of , the positive definite Lyapunov function is The voltage source converter controller is designed by the inverse method, and the control law in the voltage source converter controller is obtained as follows: In the formula: U _rd1 and U _rq1 are the components of the d-axis and q-axis of the AC side outlet voltage vector of the voltage source converter, respectively, k ₃ and k ₄ are adjustable parameters greater than 0, and i _d1 and i _q1 are the voltage source respectively The components of the d-axis and q-axis of the AC side current vector of the converter, ω ₁ is the grid angular frequency; is the reference quantity of the d-axis component of the AC side current vector of the voltage source converter, for the first derivative of ; is the reference quantity of the q-axis component of the AC side current vector of the voltage source converter, for The first derivative of ; U _sd1 and U _sq1 are the components of the d-axis and q-axis of the grid-side voltage vector of the voltage source converter, respectively. 10. A self-energy storage multi-terminal back-to-back flexible straight system control method according to claim 9, characterized in that: using the projection method to estimate the adaptive value in the control law in the voltage source converter controller After optimization, the adaptive law of uncertain parameters is obtained as: In the formula, Proj(,·,) is the projection operator, and γ ₄ and γ ₅ are the error coefficients. 11. A self-energy storage multi-end back-to-back flexible straightening system control system, characterized in that, comprising: The control law acquisition module of the controller is used to design the energy storage controller and the voltage source converter controller by using the inverse method to obtain the corresponding control law; The self-adaptive parameter optimization module is used to optimize the self-adaptive parameters of each control law based on the self-adaptive control by using the projection method to obtain the energy storage controller and the voltage source converter controller.