A method for analyzing stability of an energy storage converter control system

Abstract

The application provides a kind of energy storage converter control system stability analysis method, the method will model predictive control as the virtual synchronous generator control upper control system of energy storage converter, will model predictive control output value as the active power, reactive power reference value of virtual synchronous generator.This application realizes real-time correction virtual synchronous generator power, improves the stability of control system, avoids frequency oscillation.

Description

Technical Field

[0001] This invention relates to the field of energy storage converter technology, specifically a method for stability analysis of an energy storage converter control system. Background Technology

[0002] Energy storage technology, as one of the key technologies for my country's energy transformation, has received widespread attention in recent years because it can provide various ancillary services to the power grid, such as peak shaving, frequency regulation, and emergency response. To achieve grid-friendly integration of energy storage systems and provide stable voltage and frequency support to the power grid, research on control strategies for energy storage converters is necessary.

[0003] Currently, in the field of energy storage converter control, most systems employ dual closed-loop control and deadbeat control to achieve dynamic voltage and frequency response. However, conventional control strategies cannot maintain the stability of asynchronous energy storage converter control systems under conditions of high distributed power penetration. Summary of the Invention

[0004] This application provides a stability analysis method for an energy storage converter control system, which at least solves the problem in related technologies that it is impossible to maintain the stability of asynchronous energy storage converter control systems under high penetration rates of distributed power sources.

[0005] This application proposes a stability analysis method for an energy storage converter control system, the method comprising:

[0006] A rate-of-change equation for the energy storage converter is constructed, and based on this equation, the energy storage converter's state at rest in two phases is obtained. αβ Mathematical models of current rate of change and voltage rate of change in coordinate system;

[0007] The active power mathematical model and reactive power mathematical model of the energy storage converter output are obtained based on the current change rate mathematical model and the voltage change rate mathematical model.

[0008] Based on the mathematical model of the rate of change of current, the mathematical model of the rate of change of voltage, the mathematical model of active power, and the mathematical model of reactive power, the mathematical models of the rate of change of active power and the rate of change of reactive power of the energy storage converter in the two-phase stationary αβ coordinate system are obtained.

[0009] Based on the active power change rate mathematical model and the reactive power change rate mathematical model, the discrete domain matrix equation for the power model prediction control of the energy storage converter at time k+2 is established.

[0010] Establish a two-step model to predict the control frequency deviation power constraint function;

[0011] Using the minimum value of the two-step model predictive control frequency deviation power constraint function as the target parameter, the active power reference value of the virtual synchronous generator is updated, and the energy storage converter is predictively controlled using the updated virtual synchronous generator active power reference value.

[0012] The technical solutions provided by the embodiments of this application bring at least the following beneficial effects:

[0013] This invention provides a stability analysis method for an energy storage converter control system. This application employs model predictive control and virtual synchronous generator coordinated control. Model predictive control continuously corrects the power reference value of the virtual synchronous generator, solving the frequency deviation and power oscillation problems that occur in the power regulation process of traditional virtual synchronous generator control. A small-signal model of the grid-connected operation of the energy storage system is constructed to verify the stability of the energy storage converter control system using model predictive control and virtual synchronous generator coordinated control.

[0014] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0015] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0016] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0017] Figure 1 This is a flowchart of a stability analysis method for an energy storage converter control system provided in an embodiment of this disclosure;

[0018] Figure 2 This is a circuit topology diagram of an energy storage converter in a stability analysis method for an energy storage converter control system provided in this embodiment of the disclosure;

[0019] Figure 3 This is a block diagram of energy storage model predictive control and virtual synchronous generator coordinated control in a stability analysis method for an energy storage converter control system provided in this disclosure embodiment;

[0020] Figure 4 This is a schematic diagram of the connection between energy storage and transmission lines in a stability analysis method for an energy storage converter control system provided in this embodiment of the present disclosure;

[0021] Figure 5a and Figure 5b This is the root locus of virtual parameters in the energy storage converter control system in a stability analysis method for an energy storage converter control system provided in this embodiment of the disclosure. Detailed Implementation

[0022] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0023] This application proposes a stability analysis method for an energy storage converter control system, comprising: constructing an energy storage converter rate of change equation, and obtaining the energy storage converter's stability under two-phase stationary conditions based on the energy storage converter rate of change equation. αβ The following mathematical models are established: current rate of change and voltage rate of change in a coordinate system; active power and reactive power output models of the energy storage converter are obtained based on the current rate of change and voltage rate of change models; active power and reactive power rate of change models of the energy storage converter in the two-phase stationary αβ coordinate system are obtained based on the current rate of change, voltage rate of change, active power, and reactive power models; discrete domain matrix equations for power model predictive control of the energy storage converter at time k+2 are established based on the active power rate of change and reactive power rate of change models; a two-step model predictive control frequency deviation power constraint function is established; the virtual synchronous generator active power reference value is updated with the minimum value of the two-step model predictive control frequency deviation power constraint function as the target parameter; and predictive control of the energy storage converter is performed using the updated virtual synchronous generator active power reference value. This application employs model predictive control and virtual synchronous generator coordinated control. Model predictive control is used to continuously correct the power reference value of the virtual synchronous generator, thereby solving the frequency deviation and power oscillation problems that occur in the power regulation process of traditional virtual synchronous generator control. A small-signal model of the grid-connected operation of the energy storage system is constructed to verify the stability of the energy storage converter control system using model predictive control and virtual synchronous generator coordinated control.

[0024] Among them, the power converter (PCS) and virtual synchronous generator (VSG) model predictive control (MPC) are existing technologies and will not be elaborated on here.

[0025] The following describes, with reference to the accompanying drawings, a method and system for calculating the critical suction force during the leveling stage of a single-barrel, multi-compartment barrel-type foundation according to an embodiment of this application.

[0026] Example 1

[0027] Figure 1 A flowchart of a stability analysis method for an energy storage converter control system provided in this disclosure is shown below. Figure 1 The method includes:

[0028] Step 1: Construct the rate of change equation for the energy storage converter, and obtain the energy storage converter's state when both phases are stationary based on the rate of change equation. αβ Mathematical models of current rate of change and voltage rate of change in coordinate system.

[0029] In the embodiments disclosed herein, a rate of change equation for the energy storage converter is constructed, and the energy storage converter at two-phase stationary states is obtained based on the rate of change equation. αβ Mathematical models of current rate of change and voltage rate of change in coordinate system include:

[0030] F1: Construct the rate of change equation for the energy storage converter based on Kirchhoff's voltage law;

[0031] Figure 2 This is a circuit topology diagram of an energy storage converter in a stability analysis method for an energy storage converter control system provided in this embodiment of the disclosure, such as... Figure 2 As shown, U dc This refers to the DC bus voltage of the energy storage converter. R f , L f , C f Construct an LC filter circuit, L g , R g For the equivalent load, the rate of change equation for the energy storage converter is calculated as follows:

[0032]

[0033] In the formula, L is the equivalent inductance of the line, and R is the equivalent resistance of the line and , u abc For the three-phase AC voltage of the energy storage converter, i abc For the three-phase AC current of the energy storage converter, e abc This refers to the three-phase voltage of the AC power grid.

[0034] F2: Performing a Clark transform on the rate-of-change equation of the energy storage converter, we obtain the energy storage converter at rest in the two phases. αβ Mathematical model of the rate of change of current in a coordinate system;

[0035] Energy storage converter at two-phase standstill αβ The mathematical formula for calculating the rate of change of current in the coordinate system is as follows:

[0036]

[0037] In the formula, i α , i β AC three-phase current for energy storage converter i abc exist a axis, β Axial components, i.e. i α , i β Output current for energy storage system i abc exist a axis, β Axial components; u α , u β AC three-phase voltage for energy storage converter u abc exist a axis, β Axial components, i.e. u α , u β Output voltage for energy storage system u abc exist a axis, β Axial components; e α e β Three-phase voltage of AC power grid e abc exist a axis, β Axial components; L f For filtering capacitors; R f This is the filter resistor.

[0038] F3: Based on the mathematical model of current change rate, the energy storage converter is obtained when the two phases are stationary. αβ The mathematical model of the rate of change of voltage in the coordinate system.

[0039] Energy storage converter at two-phase standstill αβ The mathematical model for calculating the rate of change of voltage in the coordinate system is as follows:

[0040]

[0041] In the formula, E is the voltage amplitude on the grid side. ω is the angular frequency.

[0042] Step 2: Based on the mathematical model of the current rate of change and the mathematical model of the voltage rate of change, obtain the mathematical model of the active power output and the mathematical model of the reactive power output of the energy storage converter;

[0043] In this embodiment of the disclosure, the mathematical models for calculating the active power and reactive power output of the energy storage converter are as follows:

[0044] ;

[0045] In this embodiment of the disclosure, after obtaining the active power mathematical model and reactive power mathematical model of the energy storage converter output based on the current rate of change mathematical model and the voltage rate of change mathematical model, the method further includes:

[0046] The energy storage converter is simulated as a synchronous generator model. Based on the active power mathematical model, the reactive power mathematical model, and the synchronous generator model, the rotor motion equation and reactive power regulation equation of the virtual synchronous generator are obtained.

[0047] The formula for calculating the rotor motion equation is as follows:

[0048]

[0049] In the formula, J This is a virtual moment of inertia; T m , T e , T d These are the mechanical torque, electromagnetic torque, and damping torque of the virtual synchronous generator, respectively. P ref This is a reference value for active power. P e To output active power for the virtual synchronous generator; D The damping coefficient; The rated angular frequency; θ For virtual synchronous generators, virtual electrical angle;

[0050] The virtual synchronous generator control also exhibits excitation regulation inertia, and the calculation formula for the reactive power regulation equation is as follows:

[0051]

[0052] In the formula, u The virtual internal potential of the virtual synchronous generator; u 0 represents the effective value of the rated voltage; Δ uThis represents the deviation between the virtual internal potential and the rated voltage. k q This is the reactive power regulation coefficient; Q e Output reactive power for the virtual synchronous generator; Q ref This is a reference value for reactive power.

[0053] Step 3: Based on the mathematical model of the current rate of change, the mathematical model of the voltage rate of change, the mathematical model of the active power, and the mathematical model of the reactive power, obtain the mathematical model of the active power rate of change and the mathematical model of the reactive power rate of change of the energy storage converter in the two-phase stationary αβ coordinate system.

[0054] In this embodiment of the disclosure, based on the mathematical models of current rate of change, voltage rate of change, active power, and reactive power, the mathematical models of active power rate of change and reactive power rate of change of the energy storage converter in the two-phase stationary αβ coordinate system are obtained, including:

[0055] G1: Differentiate the active power mathematical model and the reactive power mathematical model with respect to time to obtain the instantaneous rate of change mathematical model of the output power of the energy storage converter;

[0056] G2: Substitute the mathematical model of the current rate of change and the mathematical model of the voltage rate of change into the mathematical model of the instantaneous rate of change to obtain the mathematical model of the active power rate of change and the mathematical model of the reactive power rate of change of the energy storage converter in the two-phase stationary αβ coordinate system.

[0057] Figure 3 This is a block diagram of energy storage model predictive control and virtual synchronous generator coordinated control in a stability analysis method for an energy storage converter control system provided in this embodiment of the disclosure, which is used for the energy storage converter when two phases are stationary. αβ The mathematical model of the active power mathematical model and the reactive power mathematical model in the coordinate system are differentiated with respect to time to obtain the mathematical model of the instantaneous rate of change of the output power of the energy storage converter.

[0058] The mathematical model for calculating the instantaneous rate of change of the output power of the energy storage converter is as follows:

[0059]

[0060] Specifically, by substituting the mathematical model of current change rate in formula (2) and the mathematical model of voltage change rate in formula (3) into formula (7), we can obtain the result of the energy storage converter in two-phase static state. αβ Mathematical models of active power change rate and reactive power change rate in coordinate system, and the energy storage converter in two-phase stationary state. αβThe mathematical formulas for the rate of change of active power and the rate of change of reactive power in the coordinate system are as follows:

[0061]

[0062] Step 4: Based on the mathematical model of the rate of change of active power and the mathematical model of the rate of change of reactive power, establish... The discrete domain matrix equation for the power model predictive control of the energy storage converter at time k is given, where k is a positive integer.

[0063] In this embodiment of the disclosure, a mathematical model of the rate of change of active power and the mathematical model of the rate of change of reactive power are established. The discrete-domain matrix equations for the power model predictive control of the energy storage converter at time t include:

[0064] H1: Discretize the mathematical model of the rate of change of active power and the mathematical model of the rate of change of reactive power to obtain... The active power model predictive control mathematical model and the reactive power model predictive control mathematical model of the energy storage converter output at any given time, and Discrete domain matrix equations of active power and reactive power output of the energy storage converter at time t.

[0065] Specifically, the mathematical models of the active power change rate and the reactive power change rate are discretized to obtain... The active power model predictive control mathematical model and the reactive power model predictive control mathematical model of the energy storage converter output at any given time, and The discrete-domain matrix equations for active power and reactive power output of the energy storage converter at time t include:

[0066] A1: Discretize the mathematical model of the rate of change of active power and the mathematical model of the rate of change of reactive power to obtain the... The active power model predictive control mathematical model and the reactive power model predictive control mathematical model of the energy storage converter output at any time are obtained by discretizing formula (8). The active power model predictive control mathematical model and the reactive power model predictive control mathematical model of the output of the energy storage converter at any time.

[0067] Furthermore, The mathematical formulas for the active power model predictive control and reactive power model predictive control of the energy storage converter output at any given time are as follows:

[0068]

[0069] In the formula, Ts For sampling control period, L g , R g Equivalent load; Line equivalent resistance .

[0070] A2: The standard form equation of the discrete-domain mathematical model is obtained. The discrete domain matrix equations of active power and reactive power output from the energy storage converter at time t.

[0071] That is, based on the standard form equation of the discrete domain mathematical model, formula (9) is transformed to obtain... The discrete domain matrix equations of active power and reactive power output of the energy storage converter at time t;

[0072] The standard form equation of the discrete-domain mathematical model is calculated as follows:

[0073]

[0074] In the formula, G and H are coefficient matrices, and x represents a variable.

[0075] The calculation formulas for the discrete-domain matrix equations of active power and reactive power output from the energy storage converter at time t are as follows:

[0076]

[0077] In the formula,

[0078]

[0079] H2: A two-step model predictive control method is adopted, and based on the above... The active power model predictive control mathematical model, the reactive power model predictive control mathematical model, the active power discrete domain matrix equation, and the reactive power discrete domain matrix equation at time t are used to establish the... Discrete domain matrix equations for predictive control of the energy storage converter power model at time t.

[0080] Furthermore, due to the inherent periodic delay in the sampling and calculation stages of the energy storage converter control system, the model predictive control stage experiences delays at time k. e abcThe sampled values ​​cannot be applied to the sampling period. As the error accumulates, it will lead to a large deviation in the control system. In order to suppress the control deviation caused by the period delay, this invention adopts a two-period delay compensation control strategy, namely a two-step model predictive control method, to perform advance control on the system variables, accurately sample and offset the effect of the delay, and improve the control accuracy. According to formula (9), a control system can be established. The discrete-domain matrix equations for the power model predictive control of the energy storage converter at time t, and The discrete-domain matrix equation for the power model predictive control of the energy storage converter at time t is calculated as follows:

[0081]

[0082] It should be noted that the two-step model predictive control method is combined with virtual synchronous generator control to form a closed-loop control system.

[0083] In this embodiment of the disclosure, a mathematical model of the rate of change of active power and the mathematical model of the rate of change of reactive power are established. After determining the discrete-domain matrix equations for the energy storage converter power model predictive control at time 10:00, the method further includes:

[0084] The The discrete domain matrix equation of the energy storage converter power model predictive control at any given time serves as the upper-level control system for the rotor motion equation and the reactive power regulation equation.

[0085] The The output value of the discrete domain matrix equation of the power model predictive control of the energy storage converter at any given time is used as the active power reference value and reactive power reference value of the virtual synchronous generator. The power of the virtual synchronous generator is corrected in real time, thereby improving the stability of the control system and avoiding frequency oscillation.

[0086] Figure 4 This is a schematic diagram of the connection between energy storage and transmission lines in a stability analysis method for an energy storage converter control system provided in this disclosure embodiment, as shown below. Figure 4 As shown, in order to verify the stability of the energy storage voltage converter control system using model predictive control and virtual synchronous engine coordinated control, this invention constructs a small-signal model of the energy storage system for grid-connected operation.

[0087] U This refers to the output voltage amplitude of the energy storage system. For the angle of attack; For the line equivalent impedance, according to Figure 4 The power transfer equation on the AC side of an energy storage voltage converter can be expressed as:

[0088]

[0089] According to formula (12), the complex power transmitted by the energy storage voltage converter can be obtained. S Model:

[0090]

[0091] Based on equation (13), a small-signal model for the transmission of active and reactive power by an energy storage voltage converter is established:

[0092]

[0093] When the energy storage converter control system is in grid-connected operation, the system frequency change is assumed to be very small, i.e.: Based on formulas (13) and (14), the calculation formula for the small-signal model of the energy storage converter control system can be derived as follows:

[0094]

[0095] In the formula: s For the Laplace operator; T a The time constant of the delay element in the control system; k p This is the reactive power regulation proportional coefficient; k i This is the reactive power regulation integral coefficient.

[0096] Defined transition matrix for energy storage voltage converter control system Y for:

[0097]

[0098] In the formula: .

[0099] According to formulas (15) and (16), the small-signal model of the energy storage voltage converter control system using model predictive control and virtual synchronous generator coordinated control is as follows:

[0100]

[0101] In the formula:

[0102]

[0103]

[0104] Step 5: Establish a two-step model predictive control frequency deviation power constraint function.

[0105] In the embodiments of this disclosure, a two-step model predictive control frequency deviation power constraint function is established, including:

[0106] B1: Transform the rotor motion equation and reactive power regulation equation into a mathematical model of virtual angular frequency change rate;

[0107] The mathematical formula for calculating the rate of change of the virtual angular frequency is as follows:

[0108]

[0109] In the formula, Δ is the virtual angular frequency adjustment amount. P = P ref - P e This represents the change in output power of the virtual synchronous generator.

[0110] B2: Refer to the above The discrete domain matrix equation of the energy storage converter power model predictive control at time t is used to transform the mathematical model of virtual angular frequency change rate into the discrete domain mathematical equation of virtual angular frequency adjustment model predictive control.

[0111] The calculation formula for the discrete-domain mathematical equation of the virtual angular frequency adjustment model predictive control is as follows:

[0112]

[0113] In the formula, , T s Let t be the system sampling time, e be the natural logarithm, and τ be the time constant.

[0114] B3: In order to suppress frequency oscillation, the two-step model predictive control frequency deviation power constraint function is established based on the discrete domain mathematical equation of the virtual angular frequency adjustment model predictive control.

[0115] The formula for calculating the two-step model predictive control frequency deviation power constraint function is as follows:

[0116]

[0117] In the formula, express The system frequency deviation weighting function at any given time. For virtual angular frequency adjustment variables, express Weighting function for the active power output of the virtual synchronous generator with energy storage at all times. This is a power or angular frequency adjustment variable.

[0118] Step 6: Using the minimum value of the predicted control frequency deviation power constraint function of the two-step model as the target parameter, update the active power reference value of the virtual synchronous generator, and perform predictive control on the energy storage converter using the updated active power reference value of the virtual synchronous generator.

[0119] In this embodiment of the disclosure, the virtual synchronous generator active power reference value is updated using the minimum value of the two-step model predictive control frequency deviation power constraint function as the target parameter. Predictive control of the energy storage converter is then performed using the updated virtual synchronous generator active power reference value, including:

[0120] D1: Using the minimum value of the power constraint function for predicting the control frequency deviation in the two-step model as the target parameter, the power of the virtual synchronous generator is corrected in real time.

[0121] D2: The The output value of the discrete domain matrix equation for the power model prediction control of the energy storage converter at a given time is vector-sumped with the active power reference value of the virtual synchronous generator to obtain the updated active power reference value of the virtual synchronous generator.

[0122] D3: The updated active power reference value of the virtual synchronous generator is incorporated into the power control of the virtual synchronous generator to perform predictive control of the energy storage converter.

[0123] Furthermore, using the minimum value of the power constraint function for predicting the control frequency deviation in the two-step model as the objective parameter, the power of the virtual synchronous generator is corrected in real time. The output value of the discrete domain matrix equation for predictive control of the energy storage converter power model at a given time is vector-added with the active power reference value of the virtual synchronous generator to obtain a new active power reference value, which is then used in the power control of the virtual synchronous generator to perform predictive control of the energy storage converter power model.

[0124] It is important to note that in order to correct the virtual synchronous generator power in real time, improve the stability of the control system, and avoid frequency oscillations, the power constraint function value of the model predicts the control frequency deviation needs to be minimized.

[0125] Specifically, when the grid-side frequency rises, the model predictive control active power output is negative, reducing the virtual synchronous generator's active power reference value and thus lowering its output power, thereby suppressing the rise in grid-side frequency. Conversely, when the grid-side frequency falls, the model predictive control active power output is positive, increasing the virtual synchronous generator's active power reference value and thus lowering its output power. P e This increases the frequency and thus suppresses the decrease in the network-side frequency.

[0126] Furthermore, the energy storage converter control system combines a two-step power model predictive control strategy with virtual synchronous generator control to form a closed-loop control system. The output of the model predictive control is compared with the active power reference value of the virtual synchronous generator. P ref A new active power reference value is obtained by vector addition, which is then incorporated into the power control of the virtual synchronous generator. The virtual synchronous generator outputs active power. P e reactive power Q e and the side angle frequency ɷ This is the input to model predictive control. The virtual synchronous generator power reference value is continuously corrected through a two-step model predictive control frequency deviation power constraint function. When the grid-side frequency rises, the active power output of the model predictive control becomes negative, thus adjusting the virtual synchronous generator active power reference value. P ref Reduce, thereby lowering the output power of the virtual synchronous generator. P e This helps suppress the rise in grid-side frequency. When the grid-side frequency decreases, the model predicts that the active power output will be positive, thus ensuring the reference value of the virtual synchronous generator's active power. P ref Increase, thereby increasing the output power of the virtual synchronous generator. P e This helps to suppress the decrease in network-side frequency.

[0127] Figure 5a and Figure 5b Figure 5 shows the root locus of virtual parameters in the energy storage converter control system, which is part of a stability analysis method for an energy storage converter control system provided in this embodiment of the disclosure. s 1. s 2. s 3. s 4 represents the four characteristic roots of the control system's root locus change, with the arrows indicating the increasing trend of the characteristic following parameter. Regardless of... J Root locus or D Root locus s 3. s 4. There is essentially no change on the real axis, and it does not affect the dynamic performance of the energy storage converter control system. s 1. s As the dominant characteristic root, 2 plays a major role in influencing the dynamic performance of the control system.

[0128] like Figure 5a As shown, it can be seen that when the virtual moment of inertia... J When the damping is small, it is in an overdamped state; as the damping decreases... J The increase, s 1. s2. When the negative poles approach each other, they form a pair of conjugate poles. At this point, the control system is in an underdamped state. J Further increase, conjugate poles s 1. s As the system moves closer to the imaginary axis, the system damping ratio decreases further, leading to increased low-frequency power oscillations.

[0129] like Figure 5b As shown, it can be seen that when the virtual damping coefficient D When the frequency is small, it cannot effectively suppress frequency deviation and power oscillation; as... D The increase s 1. s 2. A pair of conjugate poles are formed, and the system damping ratio is less than 0.707. As... D Further increase, conjugate poles s 3. s 4. As the system gradually moves closer to the real axis, the damping ratio increases, enhancing the suppression of power oscillations. D Continue to increase, s 1. s 2. They move away from each other, at this time s 1 becomes the dominant pole, and the power regulation response speed slows down as it approaches the imaginary axis. In the energy storage voltage converter control system, a two-step power model predictive control strategy is combined with model predictive control, and the power model predictive control output is introduced into the virtual synchronous generator control, which can address the virtual moment of inertia. J and virtual damping coefficient D The two inherent characteristics are optimized to ensure that the control system is always in an overdamped state, suppressing frequency deviation and power oscillation, and providing strong robustness to system sampling communication delay.

[0130] In summary, this application provides a stability analysis method for an energy storage converter control system, comprising: constructing a rate-of-change equation for the energy storage converter, and obtaining the stability of the energy storage converter under two-phase static conditions based on the rate-of-change equation. αβ Mathematical models of current and voltage change rates in a coordinate system are established; based on the current and voltage change rate mathematical models, mathematical models of active and reactive power output of the energy storage converter are obtained; based on the current, voltage, active, and reactive power mathematical models, mathematical models of active and reactive power change rates of the energy storage converter in the two-phase stationary αβ coordinate system are obtained; based on the active and reactive power change rate mathematical models, a mathematical model of active and reactive power change rates of the energy storage converter in the two-phase stationary αβ coordinate system is established. The discrete domain matrix equations for the power model predictive control (MPC) of the energy storage converter at each time step are established. A two-step MPC frequency deviation power constraint function is established. The minimum value of the two-step MPC frequency deviation power constraint function is used as the target parameter to update the active power reference value of the virtual synchronous generator (PSG). The updated PSG active power reference value is then used to perform predictive control on the energy storage converter. This application employs model predictive control and PSG coordinated control. Model predictive control continuously corrects the PSG power reference value, solving the frequency deviation and power oscillation problems that occur in the power regulation process of traditional PSG control. A small-signal model of the grid-connected operation of the energy storage system is constructed to verify the stability of the energy storage converter control system using model predictive control and PSG coordinated control.

[0131] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0132] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0133] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A stability analysis method for an energy storage converter control system, characterized in that, The method includes: A rate-of-change equation for the energy storage converter is constructed, and based on this equation, the energy storage converter's state at rest in two phases is obtained. αβ Mathematical models of current rate of change and voltage rate of change in coordinate system; Based on the mathematical model of the rate of change of current and the mathematical model of the rate of change of voltage, the active power mathematical model and the reactive power mathematical model of the energy storage converter are obtained. Based on the mathematical model of the rate of change of current, the mathematical model of the rate of change of voltage, the mathematical model of active power, and the mathematical model of reactive power, the mathematical models of the rate of change of active power and the rate of change of reactive power of the energy storage converter in the two-phase stationary αβ coordinate system are obtained. Based on the active power change rate mathematical model and the reactive power change rate mathematical model, the discrete domain matrix equation for the power model prediction control of the energy storage converter at time k+2 is established, where k is a positive integer; Establish a two-step model to predict the control frequency deviation power constraint function; Using the minimum value of the two-step model predictive control frequency deviation power constraint function as the target parameter, the active power reference value of the virtual synchronous generator is updated. Predictive control of the energy storage converter is then performed using the updated virtual synchronous generator active power reference value, including: real-time correction of the virtual synchronous generator power using the minimum value of the two-step model predictive control frequency deviation power constraint function as the target parameter; The output value of the discrete-domain matrix equation of the energy storage converter power model predictive control at any given time is vector-sumped with the active power reference value of the virtual synchronous generator to obtain an updated virtual synchronous generator active power reference value. This updated virtual synchronous generator active power reference value is then incorporated into the power control of the virtual synchronous generator to perform predictive control of the energy storage converter. Specifically, when the grid-side frequency rises, the model predictive control active power output is negative, reducing the virtual synchronous generator active power reference value and lowering the virtual synchronous generator output power, thereby suppressing the rise in grid-side frequency. Conversely, when the grid-side frequency falls, the model predictive control active power output is positive, increasing the virtual synchronous generator active power reference value and lowering the virtual synchronous generator output power. P e This increases the frequency, thereby suppressing the decrease in network-side frequency. The process involves constructing the rate of change equation for the energy storage converter, and then using this equation to obtain the energy storage converter's state at rest in both phases. αβ Mathematical models of current rate of change and voltage rate of change in coordinate system include: The rate of change equation of the energy storage converter is constructed based on Kirchhoff's voltage law; Performing a Clarke transform on the rate-of-change equation of the energy storage converter, we obtain the equation for the energy storage converter when the two phases are stationary. αβ The mathematical model of the rate of change of current in the coordinate system; Based on the mathematical model of the current change rate, the energy storage converter is obtained when the two phases are stationary. αβ The mathematical model of the rate of change of voltage in the coordinate system; The calculation formula for the rate of change equation of the energy storage converter is as follows: In the formula, L is the equivalent inductance of the line, and R is the equivalent resistance of the line. u abc For the three-phase AC voltage of the energy storage converter, i abc For the three-phase AC current of the energy storage converter, e abc The three-phase voltage of the AC power grid; The mathematical formula for calculating the rate of change of current is as follows: In the formula, i α , i β Output current for energy storage system i abc exist a axis, β Axial components; u α , u β Output voltage for energy storage system u abc exist a axis, β Axial components; e α e β Three-phase voltage of AC power grid e abc exist a axis, β Axial components; L f For filtering capacitors; R f For filtering resistors; The mathematical formula for calculating the rate of change of voltage is as follows: In the formula, E is the voltage amplitude on the grid side. ω is the angular frequency.

2. The method according to claim 1, characterized in that, After obtaining the active power mathematical model and reactive power mathematical model of the energy storage converter output based on the current rate of change mathematical model and the voltage rate of change mathematical model, the method further includes: The energy storage converter is simulated as a synchronous generator model. Based on the active power mathematical model, the reactive power mathematical model, and the synchronous generator model, the rotor motion equation and reactive power regulation equation of the virtual synchronous generator are obtained. The formula for calculating the rotor motion equation is as follows: In the formula, J This is a virtual moment of inertia; T m , T e , T d These are the mechanical torque, electromagnetic torque, and damping torque of the virtual synchronous generator, respectively. P ref This is a reference value for active power. P e To output active power for the virtual synchronous generator; D The damping coefficient; 0 is the rated angular frequency; θ For virtual synchronous generators, virtual electrical angle; The calculation formula for the reactive power regulation equation is as follows: In the formula, u The virtual internal potential of the virtual synchronous generator; u 0 represents the effective value of the rated voltage; Δ u This represents the deviation between the virtual internal potential and the rated voltage. k q This is the reactive power regulation coefficient; Q e Output reactive power for the virtual synchronous generator; Q ref This is a reference value for reactive power.

3. The method according to claim 2, characterized in that, The process of obtaining the active power change rate mathematical model and reactive power change rate mathematical model of the energy storage converter in the two-phase stationary αβ coordinate system based on the current change rate mathematical model, the voltage change rate mathematical model, the active power mathematical model, and the reactive power mathematical model includes: The active power mathematical model and the reactive power mathematical model are differentiated with respect to time to obtain the instantaneous rate of change mathematical model of the output power of the energy storage converter. Substituting the mathematical models of current change rate and voltage change rate into the mathematical model of instantaneous change rate, we obtain the mathematical models of active power change rate and reactive power change rate of the energy storage converter in the two-phase stationary αβ coordinate system.

4. The method according to claim 3, characterized in that, The mathematical model of the rate of change of active power and the mathematical model of the rate of change of reactive power are established. The discrete-domain matrix equations for the power model predictive control of the energy storage converter at time t include: Discretize the mathematical models of the active power change rate and the reactive power change rate to obtain... The active power model predictive control mathematical model and the reactive power model predictive control mathematical model of the energy storage converter output at any given time, and Discrete domain matrix equations of active power and reactive power output of the energy storage converter at time t. A two-step model predictive control method is adopted, and based on the above... The active power model predictive control mathematical model, the reactive power model predictive control mathematical model, the active power discrete domain matrix equation, and the reactive power discrete domain matrix equation at time t are used to establish the... Discrete domain matrix equations for predictive control of the energy storage converter power model at time t.

5. The method according to claim 4, characterized in that, The active power change rate mathematical model and the reactive power change rate mathematical model are discretized to obtain... The active power model predictive control mathematical model and the reactive power model predictive control mathematical model of the energy storage converter output at any given time, and The discrete-domain matrix equations for active power and reactive power output of the energy storage converter at time t are as follows: Discretize the mathematical model of the rate of change of active power and the mathematical model of the rate of change of reactive power to obtain the... The active power model predictive control mathematical model and the reactive power model predictive control mathematical model of the output of the energy storage converter at any time; The standard form equation of the discrete-domain mathematical model is obtained by applying the above. The discrete domain matrix equations of active power and reactive power output of the energy storage converter at time t; The standard form equation of the discrete-domain mathematical model is calculated as follows: In the formula, G and H are coefficient matrices, and x represents a variable.

6. The method according to claim 2, characterized in that, Based on the mathematical model of the rate of change of active power and the mathematical model of the rate of change of reactive power, the following is established: After determining the discrete-domain matrix equations for the energy storage converter power model predictive control at time 10:00, the method further includes: The The discrete domain matrix equation of the energy storage converter power model predictive control at any given time serves as the upper-level control system for the rotor motion equation and the reactive power regulation equation. The The output value of the discrete domain matrix equation of the power model prediction control of the energy storage converter at any given time is used as the active power reference value and reactive power reference value of the virtual synchronous generator, and the power of the virtual synchronous generator is corrected in real time.

7. The method according to claim 2, characterized in that, The establishment of the two-step model predictive control frequency deviation power constraint function includes: The rotor motion equation and reactive power regulation equation are transformed into a mathematical model of virtual angular frequency change rate. Referring to the above The discrete domain matrix equation of the energy storage converter power model predictive control at time t is used to transform the mathematical model of virtual angular frequency change rate into the discrete domain mathematical equation of virtual angular frequency adjustment model predictive control. The two-step model predictive control frequency deviation power constraint function is established based on the discrete domain mathematical equations of the virtual angular frequency adjustment model predictive control. The mathematical formula for calculating the rate of change of the virtual angular frequency is as follows: In the formula, Δ is the virtual angular frequency adjustment amount. P = P ref - P e This represents the change in output power of the virtual synchronous generator. The calculation formula for the discrete-domain mathematical equation of the virtual angular frequency adjustment model predictive control is as follows: In the formula, , T s Let τ be the system sampling time, e be the natural logarithm, and τ be the time constant. The formula for calculating the two-step model predictive control frequency deviation power constraint function is as follows: In the formula, express The system frequency deviation weighting function at any given time. express Weighting function for the active power output of the virtual synchronous generator with energy storage at all times. For virtual angular frequency adjustment variables, This is a power or angular frequency adjustment variable.

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