A fast modeling method and system for DC microgrid converter

Abstract

The present invention relates to the field of power electronics technology, and in particular to a method and system for rapid modeling of a DC microgrid converter, including fitting the harmonic components of a discontinuous converter switching function based on a trigonometric Fourier series to generate a fitting switch model; obtaining a photovoltaic improved time domain model using a maximum power point tracking algorithm according to the fitting switch model; constructing an energy storage improved time domain model using the fitting switch model; defining a bipolar switching function according to a three-phase inverter circuit topology, and obtaining an inverter improved time domain model based on the bipolar switching function; integrating the photovoltaic improved time domain model, the energy storage improved time domain model, and the inverter improved time domain model into a DC microgrid architecture to construct a photovoltaic storage DC microgrid joint simulation model. The present invention achieves rapid and accurate modeling of a DC microgrid converter by fitting a discontinuous converter switching function based on a trigonometric Fourier series, thereby providing technical support for the safe and stable operation of the microgrid.

Description

Technical Field

[0001] The present invention relates to the field of power electronics technology, and in particular to a method and system for rapid modeling of a DC microgrid converter. Background Art

[0002] In the context of the current energy transformation, DC microgrids, as a key platform for integrating renewable energy and power electronic equipment, play an increasingly important role in modern power systems. However, the inherent intermittent output characteristics of renewable energy and the random volatility of power loads are superimposed on each other, resulting in highly nonlinear operating conditions of the system, which poses severe challenges to the stability and efficient operation of DC microgrids. The current mainstream modeling methods have significant limitations in meeting the above requirements.

[0003] The current converter modeling methods are mainly divided into three categories. The first category is the modeling method based on the average idea. This method simplifies the model structure by ignoring the high-frequency components of the switching action, thereby reducing the complexity of the model. However, due to its simplified processing, the modeling accuracy is limited, especially in the case of high-frequency switching and variable frequency control. It cannot accurately capture the dynamic characteristics of the system and cannot be applied to variable frequency control scenarios; the second category of methods is the modeling method that considers the dominant frequency, such as the dynamic phasor method, TIMF method, etc. This type of method can describe the steady-state and dynamic characteristics of the system with higher accuracy by retaining the dominant frequency components of the system. However, when it is necessary to retain higher-order harmonic components, the analysis process of these methods becomes It is extremely cumbersome, the computational complexity is significantly increased, and some methods are limited to steady-state analysis and cannot effectively track the dynamic changes of variables, limiting their application in dynamic system analysis; the third type of method is the modeling method that considers all harmonic frequencies, such as the harmonic state space model. Although this type of method can accurately describe the difference frequency oscillation phenomenon caused by harmonics of different frequencies by considering all harmonic components, it is suitable for accurate modeling of complex systems. However, the solution and analysis process of this type of method is extremely complicated and the amount of calculation is huge, especially when there are many high-order harmonic components, the calculation efficiency is significantly reduced, which to a certain extent hinders its wide application in practical engineering, especially in scenarios that require rapid response.

[0004] In summary, the existing converter modeling methods have shown obvious limitations when facing the complex and changeable operating environment of DC microgrids. These problems seriously hinder the effective application of converter rapid modeling methods in important scenarios such as new energy microgrids, which in turn affects the stable and efficient operation of DC microgrids. Therefore, a more sophisticated and efficient modeling method is urgently needed to provide strong technical support for the safe and stable operation of DC microgrids. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a method and system for rapid modeling of a DC microgrid converter.

[0006] In a first aspect, the present invention provides a method for rapid modeling of a DC microgrid converter, the method comprising the following steps:

[0007] Perform harmonic component fitting on the discontinuous converter switching function based on the triangular Fourier series to generate a fitting switch model; the fitting switch model includes a pulse width modulation fitting switch model of a DC-DC circuit and a sinusoidal pulse width modulation fitting switch model of a DC-AC circuit;

[0008] According to the fitting switch model, a maximum power point tracking algorithm is used to model the photovoltaic array cascade Boost converter to obtain a photovoltaic improved time domain model;

[0009] Based on the bidirectional DC-DC converter topology, the fitted switch model is used to construct an improved time domain model of energy storage for the dynamic characteristics of charge and discharge of the energy storage battery;

[0010] A bipolar switching function is defined according to the three-phase inverter circuit topology, and sideband harmonic analysis is performed based on the bipolar switching function to obtain an improved inverter time domain model including carrier and modulation wave coupling effects;

[0011] The improved photovoltaic time domain model, the improved energy storage time domain model and the improved inverter time domain model are integrated into the DC microgrid architecture to construct a photovoltaic energy storage DC microgrid joint simulation model.

[0012] In a further embodiment, the step of performing harmonic component fitting on the discontinuous converter switching function based on the trigonometric Fourier series to generate a fitting switching model comprises:

[0013] According to the duty cycle of the pulse width modulation signal in the DC-DC circuit, a pulse width modulation switching function under a preset switching period is obtained;

[0014] Using a triangular Fourier series to perform harmonic decomposition on the pulse width modulation switching function, and solving to obtain harmonic coefficients of each order;

[0015] According to the harmonic coefficients of each order and the preset harmonic order, a pulse width modulation fitting switch model formed by superposition of trigonometric function signals of different switching frequency multiples is generated using a Fourier series expansion;

[0016] Establishing a sine wave pulse width modulation switching function of a sine wave pulse width modulation signal modulation process in a DC-AC circuit, and based on the sine wave pulse width modulation switching function, generating a switch trigger pulse switching function by utilizing the phase angle relationship between the modulation wave of the sine wave pulse width modulation signal and the triangular carrier;

[0017] The switch trigger pulse switch function is fitted by using a double Fourier decomposition method to generate a sinusoidal pulse width modulation fitting switch model including a sideband harmonic coupling effect.

[0018] In a further embodiment, the step of fitting the switch trigger pulse switch function using a double Fourier decomposition method to generate a sinusoidal pulse width modulation fitting switch model including a sideband harmonic coupling effect comprises:

[0019] The switch trigger pulse switch function is decomposed into a DC component, a modulation wave fundamental frequency component, a carrier harmonic component and a sideband harmonic component generated by the interaction of the modulation wave and the carrier harmonic using a double Fourier decomposition method;

[0020] According to the preset carrier frequency multiples and modulation wave frequency multiples, the corresponding key harmonic components are intercepted from the carrier harmonic components and the sideband harmonic components;

[0021] A sinusoidal pulse width modulation fitting switch model including sideband harmonic coupling effect is generated according to the DC component, the modulation wave fundamental frequency component and the key harmonic component.

[0022] In a further embodiment, the mathematical expression of the fitted switch model is:

[0023]

[0024]

[0025] In the formula, is the pulse width modulation fitting switch model; d is the duty cycle of the pulse width modulation signal in a single switching cycle; n is the preset harmonic order; is the switching angular frequency; t is the time; is the fitting switch model of sinusoidal pulse width modulation; M is the modulation ratio; is the phase angle of the modulated wave; i is the multiple of the carrier frequency; is the zero-order Bessel function among the Bessel functions of the first kind; is the phase angle of the triangular carrier; j is the modulating wave frequency multiple; is infinite; is the Bessel function of the first kind.

[0026] In a further embodiment, the step of modeling the photovoltaic array cascaded Boost converter using a maximum power point tracking algorithm based on the fitted switch model to obtain a photovoltaic improved time domain model includes:

[0027] According to the physical parameters of photovoltaic cells, a single diode equivalent circuit model of photovoltaic cells is constructed;

[0028] Under constant temperature and irradiance conditions, the output side voltage and output side current of the photovoltaic cell are obtained through the single diode equivalent circuit model;

[0029] The photovoltaic array cascade boost converter is selected as the DC-DC converter, and the voltage and current behaviors of the DC-DC converter under different switch working states are analyzed according to the topological structure and switch working state of the DC-DC converter, and the photovoltaic original time domain model of the photovoltaic array cascade boost converter is established;

[0030] In the process of controlling the DC-DC converter by using a preset first-order ripple, the pulse width modulation fitting switch model is introduced into the photovoltaic original time domain model, and the maximum power point tracking algorithm is used to control the output power of the photovoltaic cell to obtain a control reference voltage;

[0031] A photovoltaic improved time domain model of a photovoltaic array cascade Boost converter is constructed according to the control reference voltage, the output side voltage and the output side current of the photovoltaic cell.

[0032] In a further embodiment, the step of controlling the output power of the photovoltaic cell using the maximum power point tracking algorithm to obtain the control reference voltage includes:

[0033] The maximum power point tracking algorithm is used to adjust the duty cycle of the photovoltaic array cascade boost converter in real time, and the output power of the photovoltaic cell is dynamically converged to the maximum power point through closed-loop control to generate a control reference voltage.

[0034] In a further embodiment, the step of constructing an improved time domain model of energy storage of the dynamic characteristics of charge and discharge of an energy storage battery based on the bidirectional DC-DC converter topology using the fitted switch model comprises:

[0035] According to the physical parameters of the energy storage battery, an electromagnetic transient model of the energy storage battery in the DC microgrid is constructed, and through the electromagnetic transient model, a dynamic relationship equation between the output voltage and the output current of the energy storage battery in the charging and discharging states is established;

[0036] Based on the topological structure of the bidirectional DC-DC converter in the energy storage battery and its switch working state, the voltage-current dynamic behavior of the bidirectional DC-DC converter under different switch working states is analyzed, and the energy storage original time domain model of the bidirectional DC-DC converter is established;

[0037] In the process of controlling the bidirectional DC-DC converter by using a preset first-order ripple, the pulse width modulation fitting switch model is introduced into the energy storage original time domain model to obtain an improved energy storage switch model of the bidirectional DC-DC converter;

[0038] Based on the dynamic relationship equation between the output voltage and the output current of the energy storage battery in the charging and discharging states, an improved energy storage time domain model of the energy storage battery controlling the DC bus voltage through a bidirectional DC-DC converter is constructed through the improved energy storage switch model.

[0039] In a further embodiment, the steps of defining a bipolar switching function according to the three-phase inverter circuit topology, performing sideband harmonic analysis based on the bipolar switching function, and obtaining an improved inverter time domain model including carrier and modulation wave coupling effects include:

[0040] When the DC microgrid is connected to the grid through a three-phase inverter, a bipolar switching function is defined according to the circuit topology of the three-phase inverter and its switch working state;

[0041] A three-phase coupling control model of a three-phase inverter is established by using Kirchhoff's voltage law, and the three-phase coupling control model is decoupled into an independent virtual loop voltage representation for each phase by introducing a virtual three-phase neutral point voltage;

[0042] Analyzing the voltage-current dynamic behavior of the three-phase inverter in the switching state according to the bipolar switching function and the virtual loop voltage representation, and obtaining the original time domain model of the three-phase inverter;

[0043] In the process of controlling the DC-AC converter of the three-phase inverter using the preset first-order carrier and second-order sideband harmonics, the sinusoidal wave pulse width modulation fitting switch model is introduced into the original time domain model of the three-phase inverter to obtain an improved time domain model of the inverter including the carrier and modulation wave coupling effect.

[0044] In a further embodiment, the bipolar switching function is specifically:

[0045] When the upper bridge arm switch device of each phase of the three-phase inverter is turned on and the lower bridge arm switch device is turned off, the bipolar switching function is defined as positive one;

[0046] When the lower bridge arm switch devices of each phase of the three-phase inverter are turned on and the upper bridge arm switch devices are turned off, the bipolar switching function is defined as negative one.

[0047] In a second aspect, the present invention provides a DC microgrid converter rapid modeling system, the system comprising:

[0048] A switch fitting module, used for performing harmonic component fitting on the discontinuous converter switch function based on the triangular Fourier series to generate a fitting switch model; the fitting switch model includes a pulse width modulation fitting switch model of a DC-DC circuit and a sine wave pulse width modulation fitting switch model of a DC-AC circuit;

[0049] The first modeling module is used to model the photovoltaic array cascade Boost converter according to the fitting switch model and use the maximum power point tracking algorithm to obtain a photovoltaic improved time domain model;

[0050] A second modeling module is used to construct an improved time domain model of energy storage of the dynamic characteristics of charge and discharge of the energy storage battery based on a bidirectional DC-DC converter topology by using the fitted switch model;

[0051] A third modeling module is used to define a bipolar switching function according to the three-phase inverter circuit topology, and perform sideband harmonic analysis based on the bipolar switching function to obtain an improved inverter time domain model including carrier and modulation wave coupling effects;

[0052] The model integration module is used to integrate the photovoltaic improved time domain model, the energy storage improved time domain model and the inverter improved time domain model into the DC microgrid architecture to build a photovoltaic-storage-DC microgrid joint simulation model.

[0053] The present invention provides a method and system for rapid modeling of a DC microgrid converter. The method performs harmonic component fitting on a discontinuous converter switch function through a triangular Fourier series to generate a fitted switch model; based on the fitted switch model, a maximum power point tracking algorithm is used to model a photovoltaic array cascade Boost converter to obtain an improved photovoltaic time domain model; based on a bidirectional DC-DC converter topology, an improved energy storage time domain model of the dynamic characteristics of energy storage battery charging and discharging is constructed using the fitted switch model; a bipolar switching function is defined according to a three-phase inverter circuit topology, and sideband harmonic analysis is performed based on the bipolar switching function to obtain an improved inverter time domain model including carrier and modulation wave coupling effects; the improved photovoltaic time domain model, the improved energy storage time domain model and the improved inverter time domain model are integrated into a DC microgrid architecture to construct a photovoltaic storage DC microgrid joint simulation model. Compared with the existing technology, this method fits the harmonic components of the discontinuous converter switching function based on the trigonometric Fourier series, and constructs an improved time domain model based on the fitted switching model to achieve fast and accurate modeling of the DC microgrid converter, providing efficient and accurate technical support for the safe and stable operation of the microgrid. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 It is a schematic diagram of the flow chart of the DC microgrid converter rapid modeling method provided by an embodiment of the present invention;

[0055] Figure 2 It is a schematic diagram of the structure of a photovoltaic-storage DC microgrid system provided by an embodiment of the present invention;

[0056] Figure 3 is a schematic diagram of a single diode equivalent circuit model provided by an embodiment of the present invention;

[0057] Figure 4 is a schematic diagram of a photovoltaic array cascade Boost converter provided by an embodiment of the present invention;

[0058] Figure 5 is a schematic diagram of a three-phase inverter topology provided by an embodiment of the present invention;

[0059] Figure 6 is a schematic diagram comparing DC bus voltages of a DC microgrid provided by an embodiment of the present invention under different modeling methods;

[0060] Figure 7 is a schematic diagram comparing the alternating current of a DC microgrid provided by an embodiment of the present invention under different modeling methods;

[0061] Figure 8 is a schematic diagram for comparing DC bus voltages under different harmonic components provided by an embodiment of the present invention;

[0062] Fig. 9 is a schematic diagram for comparing alternating currents under different harmonic components provided by an embodiment of the present invention;

[0063] Fig.10 It is a block diagram of a DC microgrid converter rapid modeling system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0064] The following specifically illustrates the implementation mode of the present invention in conjunction with the accompanying drawings. The embodiments are provided for illustrative purposes only and cannot be understood as limiting the present invention. The accompanying drawings are provided for reference and illustration only and do not constitute a limitation on the scope of patent protection of the present invention, because many changes can be made to the present invention without departing from the spirit and scope of the present invention.

[0065] refer to Figure 1 , the embodiment of the present invention provides a method for fast modeling of a DC microgrid converter, such as Figure 1 As shown, the method comprises the following steps:

[0066] S1. Perform harmonic component fitting on the discontinuous converter switching function based on the triangular Fourier series to generate a fitting switch model; the fitting switch model includes a pulse width modulation fitting switch model of a DC-DC circuit and a sinusoidal pulse width modulation fitting switch model of a DC-AC circuit.

[0067] In some embodiments, the discontinuous converter switching function includes a pulse width modulation switching function of a DC-DC circuit and a sinusoidal pulse width modulation switching function of a DC-AC circuit; the step of performing harmonic component fitting on the discontinuous converter switching function based on a triangular Fourier series to generate a fitting switching model includes:

[0068] According to the duty cycle of the pulse width modulation signal in the DC-DC circuit, a pulse width modulation switching function under a preset switching period is obtained;

[0069] Using a triangular Fourier series to perform harmonic decomposition on the pulse width modulation switching function, and solving to obtain harmonic coefficients of each order;

[0070] According to the harmonic coefficients of each order and the preset harmonic order, a pulse width modulation fitting switch model formed by superposition of trigonometric function signals of different switching frequency multiples is generated using a Fourier series expansion;

[0071] Establishing a sine wave pulse width modulation switching function of a sine wave pulse width modulation signal modulation process in a DC-AC circuit, and based on the sine wave pulse width modulation switching function, generating a switch trigger pulse switching function by utilizing the phase angle relationship between the modulation wave of the sine wave pulse width modulation signal and the triangular carrier;

[0072] The switch trigger pulse switch function is fitted by using a double Fourier decomposition method to generate a sinusoidal pulse width modulation fitting switch model including a sideband harmonic coupling effect.

[0073] Specifically, in the field of power electronics, direct current-direct current (DC-DC) circuits and direct current-alternating current (DC-AC) circuits are two common types of circuits. In this embodiment, pulse width modulation (PWM) control is used in the DC-DC circuit to adjust the output voltage by adjusting the pulse width. When pulse width modulation control is used, it is necessary to determine the duty cycle d of the PWM signal. The duty cycle represents the ratio of the time when the switch is in a closed state to the total cycle time in a switching cycle. Then, a switching function of the PWM signal under a certain duty cycle is established. Assuming that the PWM under a certain duty cycle can be used express:

[0074]

[0075] Where T is the switching period; d is the duty cycle of the PWM signal within one switching period.

[0076] When the switch is in the closed or open state, the system model is linear. However, due to the switching process of the switch, the model is discontinuous in time. In addition, in a closed-loop system, the switching function is affected by the system state variables and the carrier, resulting in nonlinear characteristics of the system. Traditional theories are mostly based on linear systems for analysis, so the model needs to be linearized. The state space averaging method is a commonly used method. The state space averaging method obtains the corresponding model by weighted averaging of all variables in a switching cycle. Therefore, the switching function can be expressed as:

[0077]

[0078] For periodic signals, since the trigonometric Fourier series can well represent periodic discontinuous signals, in order to improve the accuracy, the present embodiment preferentially uses the trigonometric Fourier expansion to model the switching function. For a given periodic signal, it can be expanded into the Fourier series form, and the corresponding trigonometric series coefficients can be derived according to the duty cycle. By selecting a suitable n value, the trigonometric function signals of different switching frequency multiples can be used to fit the switching function with different accuracy, thereby obtaining a model with better fitting effect. If the period of the periodic signal is , the angular frequency is , then the signal can be expanded into a triangular Fourier series, specifically:

[0079]

[0080] In the formula, is a periodic signal; is the DC component; is the cosine component coefficient of the nth order harmonic; is the sinusoidal component coefficient of the nth order harmonic; t is time.

[0081] For a PWM wave with a known duty cycle, this embodiment can derive the corresponding triangular series coefficients (Fourier series coefficients), which represent the proportion of each order harmonic in the signal. The specific calculation formula is as follows:

[0082]

[0083]

[0084]

[0085] In this embodiment, the above integral calculation can be used to obtain the harmonic coefficients of each order: and , thereby obtaining the harmonic decomposition result of the PWM switching function. In practical applications, technicians in this field need to select the harmonic order n according to the actual accuracy requirements. The selection of n will affect the accuracy and complexity of the fitting model. The higher the order, the higher the fitting accuracy, but the greater the calculation complexity. Then, the calculated harmonic coefficients of each order and the preset harmonic order n are used to construct a fitting model using the Fourier series expansion. The model is composed of the superposition of trigonometric function signals of different switching frequency multiples. The fitting effect is verified by comparing the original switching function with the fitted switching model. If the fitting accuracy does not meet the requirements, the harmonic order n can be adjusted and the harmonic coefficients can be recalculated. In this embodiment, through the above-mentioned Fourier series expansion and the selected size of n, the trigonometric function signals of different switching frequency multiples can be used to fit the switching function with different accuracy:

[0086]

[0087] In the formula, is the pulse width modulation fitting switch model; d is the duty cycle of the pulse width modulation signal in a single switching cycle; n is the harmonic order; is the switching angular frequency; t is the time; Is infinite.

[0088] At the same time, this embodiment adopts sinusoidal pulse width modulation (SPWM) control in the DC-AC circuit. The sinusoidal pulse width modulation technology uses a sine wave as a modulation wave to synthesize a square wave with a sinusoidal change pattern on the basis of PWM. This embodiment adopts sinusoidal pulse width modulation control, which requires determining the waveform and parameters of the modulation wave and the triangular carrier. Assume that the modulation wave is , the triangular carrier is , and its corresponding mathematical expression is:

[0089]

[0090] Where, M is the modulation ratio; is the phase angle of the modulated wave; is the phase angle of the triangular carrier; k is an integer, which represents the period interval in which the phase angle of the triangular carrier is located; is the starting point of the triangular carrier phase angle cycle, and The interval between represents one and a half cycles of the triangular carrier.

[0091] This embodiment uses the phase angle relationship between the modulation wave and the triangular carrier to generate the switching function of the switch trigger pulse , which represents the triggering time and duration of the switch. Specifically, it is expressed as:

[0092]

[0093] Since the SPWM signal involves two frequency components, namely the modulation wave and the carrier wave, in order to model the SPWM switch function, the present embodiment adopts a dual Fourier decomposition method to fit the switch trigger pulse switch function, and an expression including a DC component, a modulation wave component, a carrier harmonic component and a sideband harmonic component can be obtained. The model can more accurately reflect the actual characteristics of the SPWM signal. In some embodiments, the step of fitting the switch trigger pulse switch function using the dual Fourier decomposition method to generate a sinusoidal pulse width modulation fitting switch model including a sideband harmonic coupling effect includes:

[0094] The switch trigger pulse switch function is decomposed into a DC component, a modulation wave fundamental frequency component, a carrier harmonic component and a sideband harmonic component generated by the interaction of the modulation wave and the carrier harmonic using a double Fourier decomposition method;

[0095] According to the preset carrier frequency multiples and modulation wave frequency multiples, the corresponding key harmonic components are intercepted from the carrier harmonic components and the sideband harmonic components;

[0096] A sinusoidal pulse width modulation fitting switch model including sideband harmonic coupling effect is generated according to the DC component, the modulation wave fundamental frequency component and the key harmonic component.

[0097] For the sine wave pulse width modulation fitting switch model, this embodiment assumes that i is a multiple of the carrier frequency and j is a multiple of the modulation wave frequency. Therefore, the switch trigger pulse switch function is decomposed by double Fourier to obtain:

[0098]

[0099] Among them, the first item on the right side of the equation is the DC component; the second item is the modulation wave component; the third item is the carrier harmonic component; the fourth item is the sideband harmonic component, which is determined by the modulation wave and the carrier harmonic; is the fitting switch model of sinusoidal pulse width modulation; M is the modulation ratio; is the phase angle of the modulated wave; i is the multiple of the carrier frequency; is the zero-order Bessel function among the Bessel functions of the first kind; is the phase angle of the triangular carrier; j is the modulating wave frequency multiple; is infinite; is the Bessel function of the first kind.

[0100] It should be noted that, in this embodiment, the fitting effect can be verified by comparing the original switch function and the fitted switch model. If the fitting accuracy does not meet the requirements, the decomposition method and parameters can be adjusted and the fitting coefficients can be recalculated.

[0101] S2. Based on the fitting switch model, the photovoltaic array cascade Boost converter is modeled using a maximum power point tracking algorithm to obtain a photovoltaic improved time domain model.

[0102] In some implementations, the step of modeling the photovoltaic array cascaded Boost converter using a maximum power point tracking algorithm according to the fitted switch model to obtain a photovoltaic improved time domain model includes:

[0103] According to the physical parameters of photovoltaic cells, a single diode equivalent circuit model of photovoltaic cells is constructed;

[0104] Under constant temperature and irradiance conditions, the output side voltage and output side current of the photovoltaic cell are obtained through the single diode equivalent circuit model;

[0105] The photovoltaic array cascade boost converter is selected as the DC-DC converter, and the voltage and current behaviors of the DC-DC converter under different switch working states are analyzed according to the topological structure and switch working state of the DC-DC converter, and the photovoltaic original time domain model of the photovoltaic array cascade boost converter is established;

[0106] In the process of controlling the DC-DC converter by using a preset first-order ripple, the pulse width modulation fitting switch model is introduced into the photovoltaic original time domain model, and the maximum power point tracking algorithm is used to control the output power of the photovoltaic cell to obtain a control reference voltage;

[0107] A photovoltaic improved time domain model of a photovoltaic array cascade Boost converter is constructed according to the control reference voltage, the output side voltage and the output side current of the photovoltaic cell.

[0108] In a specific embodiment, the DC microgrid model of the fine converter considered in this embodiment specifically includes a detailed model of each microelement of the microgrid, such as Figure 2 As shown in the figure, the photovoltaic array cascade Boost converter achieves maximum power output through the MPPT algorithm, and the MPPT algorithm adopts the perturbation observation method; the energy storage battery controls the DC bus voltage through the bidirectional DC / DC circuit, and the DC bus is connected to the AC grid through the VSC. Since photovoltaic cells usually use a single diode model, is the current of the nth photovoltaic connected to the DC bus, The current connected to the DC bus for energy storage, is the current value of the current loop, such as Figure 3As shown, this embodiment constructs a single diode equivalent circuit model of a photovoltaic cell based on the physical parameters of the photovoltaic cell. The physical parameters of the photovoltaic cell include the number of cells in parallel and series in the photovoltaic array, shunt resistance, series resistance, diode voltage, diode current and other parameters. This model can simulate the electrical behavior of the photovoltaic cell under specific conditions. At the same time, under constant temperature and irradiance conditions, this embodiment uses the constructed single diode equivalent circuit model to calculate the output side voltage and output side current of the photovoltaic cell by numerical method. The specific calculation formula is:

[0109]

[0110]

[0111] In the formula, is the output current of the photovoltaic cell; is the output voltage of the photovoltaic cell; It is the photocurrent generated by the photovoltaic cell under illumination conditions, which is the ideal value of the photovoltaic cell output current, ignoring the influence of the diode and shunt resistor; is the diode current; is the diode voltage; is the shunt resistor; is the series resistance.

[0112] Then, this embodiment selects a photovoltaic array cascade Boost converter as a DC-DC converter, and analyzes the voltage and current behavior of the DC-DC converter under different switch working states according to the topological structure of the DC-DC converter and its switch working state, so as to establish a photovoltaic original time domain model of the photovoltaic array cascade Boost converter. This model can reflect the dynamic characteristics of the converter under the switch working state, such as Figure 4 As shown, in this embodiment, according to the switching state of the Boost converter, the switching model can be written as:

[0113]

[0114]

[0115] In the formula, is the input voltage; is the output voltage; is the input current; is the output current; L is the inductance value; C is the capacitance value.

[0116] This embodiment obtains the original time domain model of the photovoltaic array cascade Boost converter based on the above switch model. The model describes the voltage and current behaviors under different switch states. In the process of controlling the DC-DC converter by using the preset first-order ripple, this embodiment introduces the pulse width modulation fitting switch model into the photovoltaic original time domain model to obtain a more accurate description of the switching behavior of the converter. Specifically, the pulse width modulation fitting switch model is substituted into the photovoltaic original time domain model to obtain the photovoltaic improved time domain model:

[0117]

[0118] When the DC-DC converter is controlled by using a preset first-order ripple, the present embodiment fits the first switching function and the second switching function according to the pulse width modulation fitting switch model, wherein the fitted first switching function and the fitted second switching function are respectively:

[0119]

[0120] In the formula, is the first switching function of the photovoltaic Boost circuit; is the second switching function of the energy storage DC-DC circuit; and are the duty cycles of the photovoltaic and energy storage DC-DC circuits, respectively; is the angular frequency of the switching function.

[0121] On the basis of the above embodiments, this embodiment uses a maximum power point tracking (MPPT) algorithm to control the output power of photovoltaic cells. The maximum power point tracking algorithm continuously adjusts the duty cycle of the converter so that the photovoltaic cells always operate near the maximum power point, thereby maximizing the output power. In this process, this embodiment obtains a control reference voltage, which is an important basis for subsequent calculations and analyses. Finally, this embodiment constructs an improved time domain model of the photovoltaic array based on the control reference voltage, the output side voltage and the output side current of the photovoltaic cell.

[0122] In some implementations, the step of controlling the output power of the photovoltaic cell using a maximum power point tracking algorithm to obtain a control reference voltage includes:

[0123] The maximum power point tracking algorithm is used to adjust the duty cycle of the photovoltaic array cascade boost converter in real time, and the output power of the photovoltaic cell is dynamically converged to the maximum power point through closed-loop control to generate a control reference voltage.

[0124] Therefore, in this embodiment, the improved time domain model of the photovoltaic array cascade Boost converter outputting the maximum power through the MPPT algorithm is obtained as follows:

[0125]

[0126] In the formula, is the photovoltaic inductor; is the capacitance value; and All are control coefficients; is the output current of the photovoltaic array; is the DC bus voltage; is an intermediate variable; is the output side voltage of the photovoltaic array; To control the reference voltage; is the duty cycle of the PV array; The current of the photovoltaic connected to the DC bus; is the differential of the state variable.

[0127] In summary, the improved time domain model of the PV array not only takes into account the physical characteristics of the PV cells and the switching behavior of the converter, but also incorporates the control strategy of the MPPT algorithm, so it can more accurately reflect the dynamic characteristics of the PV array in actual operation.

[0128] S3. Based on the bidirectional DC-DC converter topology, the fitted switch model is used to construct an improved time domain model of energy storage for the dynamic characteristics of charging and discharging of the energy storage battery.

[0129] In some embodiments, the step of constructing an improved time domain model of energy storage of the dynamic characteristics of charge and discharge of an energy storage battery based on the bidirectional DC-DC converter topology using the fitted switch model comprises:

[0130] According to the physical parameters of the energy storage battery, an electromagnetic transient model of the energy storage battery in the DC microgrid is constructed, and through the electromagnetic transient model, a dynamic relationship equation between the output voltage and the output current of the energy storage battery in the charging and discharging states is established;

[0131] Based on the topological structure of the bidirectional DC-DC converter in the energy storage battery and its switch working state, the voltage-current dynamic behavior of the bidirectional DC-DC converter under different switch working states is analyzed, and the energy storage original time domain model of the bidirectional DC-DC converter is established;

[0132] In the process of controlling the bidirectional DC-DC converter by using a preset first-order ripple, the pulse width modulation fitting switch model is introduced into the energy storage original time domain model to obtain an improved energy storage switch model of the bidirectional DC-DC converter;

[0133] Based on the dynamic relationship equation between the output voltage and the output current of the energy storage battery in the charging and discharging states, an improved energy storage time domain model of the energy storage battery controlling the DC bus voltage through a bidirectional DC-DC converter is constructed through the improved energy storage switch model.

[0134] Specifically, in order to simplify the processing, the energy storage part of the traditional DC microgrid is usually replaced by a DC source during modeling. However, the DC power supply operation state lacks a dynamic adjustment process and cannot reflect the dynamic characteristics of energy storage. In order to more accurately reflect the dynamic characteristics of energy storage, this embodiment selects a lithium battery as the energy storage model of the DC microgrid, and establishes an electromagnetic transient model of the energy storage battery in the DC microgrid. The dynamic relationship equation between the output voltage and the output current of the energy storage battery under charging and discharging conditions is established through the electromagnetic transient model of the energy storage battery in the DC microgrid. When the influence of ambient temperature and battery aging is not considered, the electromagnetic transient model of the lithium battery includes four different links: charging, discharging, nonlinearity and attenuation. Among them, when the battery current When <0, the battery working mode is charging state, and the voltage mathematical expression of lithium battery is:

[0135]

[0136] In the formula, is the voltage of the lithium battery in the charging state; is a constant voltage; k is a polarization constant; is the maximum capacity of lithium battery; is the filter current; A and B are the exponential voltages of the lithium battery; it is the remaining capacity of the lithium battery.

[0137] When the battery current >0, the battery working mode is the discharge process, and the lithium battery voltage expression is:

[0138]

[0139] In the formula, is the lithium battery voltage in the discharged state.

[0140] Among them, the relationship between the remaining capacity and battery current of the lithium battery during operation is:

[0141]

[0142] The actual output voltage equation of a lithium battery is:

[0143]

[0144] In the formula, is the battery terminal voltage; is the battery current; r is the battery internal resistance; E is the lithium battery voltage in the charging or discharging state.

[0145] Therefore, based on the analysis process of the above photovoltaic improved time domain model, combined with the charging and discharging state of the energy storage battery and the output side voltage and current, the duty cycle is dynamically adjusted through the dual closed-loop control strategy of the voltage loop and the current loop to stabilize the DC bus voltage at the reference value. Therefore, the improved time domain model of the energy storage battery controlling the DC bus voltage through the bidirectional DC / DC converter is:

[0146]

[0147] In the formula, is the circuit inductance; is the capacitance value; , , , is the control coefficient; and They are the reference values ​​of the voltage loop and the current loop respectively; is the output current of the energy storage battery; The current connected to the DC bus for energy storage; and is an intermediate variable; Control duty cycle for energy storage; is the differential of the state variable; is the output voltage of the energy storage battery; is the voltage value of the voltage loop.

[0148] S4. A bipolar switching function is defined according to the three-phase inverter circuit topology, and sideband harmonic analysis is performed based on the bipolar switching function to obtain an improved time domain model of the inverter including the carrier and modulation wave coupling effect.

[0149] In some embodiments, the step of defining a bipolar switching function according to the three-phase inverter circuit topology, and performing sideband harmonic analysis based on the bipolar switching function to obtain an improved inverter time domain model including carrier and modulation wave coupling effects includes:

[0150] When the DC microgrid is connected to the grid through a three-phase inverter, a bipolar switching function is defined according to the circuit topology of the three-phase inverter and its switch working state;

[0151] A three-phase coupling control model of a three-phase inverter is established by using Kirchhoff's voltage law, and the three-phase coupling control model is decoupled into an independent virtual loop voltage representation for each phase by introducing a virtual three-phase neutral point voltage;

[0152] Analyzing the voltage-current dynamic behavior of the three-phase inverter in the switching state according to the bipolar switching function and the virtual loop voltage representation, and obtaining the original time domain model of the three-phase inverter;

[0153] In the process of controlling the DC-AC converter of the three-phase inverter using the preset first-order carrier and second-order sideband harmonics, the sinusoidal wave pulse width modulation fitting switch model is introduced into the original time domain model of the three-phase inverter to obtain an improved time domain model of the inverter including the carrier and modulation wave coupling effect.

[0154] Specifically, when the DC microgrid is connected to the grid through a three-phase inverter, Figure 5 As shown, this embodiment defines a bipolar switching function according to the circuit topology of the three-phase inverter and its switch working state. , is the switching state of the k-th phase bridge arm, ; Since the switch on the VSC bridge arm has only two states, on and off, this embodiment defines a bipolar switching function (i.e., a bipolar binary logic switching function) to represent the switching state of each phase. When the upper bridge arm switching device of each phase of the three-phase inverter is turned on and the lower bridge arm switching device is turned off, the bipolar switching function is defined as positive one, indicating that the switch is turned on; when the lower bridge arm switching device of each phase of the three-phase inverter is turned on and the upper bridge arm switching device is turned off, the bipolar switching function is defined as negative one, indicating that the switch is turned off. The specific formula of the bipolar switching function is expressed as:

[0155]

[0156] At the same time, this embodiment uses Kirchhoff's voltage law (KVL) to obtain the voltage equation of each phase, thereby establishing a three-phase coupling control model of the three-phase inverter. The specific formula is expressed as follows:

[0157]

[0158] Since there is a coupling relationship between the three phases in the three-phase inverter, direct analysis is relatively complicated. Therefore, this embodiment introduces a virtual three-phase neutral point voltage to decouple the three-phase coupling control model into an independent virtual loop voltage representation for each phase, and obtains an independent voltage equation for each phase, so that subsequent analysis can be performed independently for each phase, which greatly simplifies the complexity of the problem. The independent virtual loop voltage representation for each phase is specifically:

[0159]

[0160] In the formula, is the voltage of phase a relative to the virtual neutral point N in the three-phase inverter, is the voltage of the virtual neutral point N relative to the actual neutral point 0, and the sum of the two gives the total voltage of phase a , thereby achieving independent analysis and control of each phase voltage.

[0161] After obtaining an independent virtual loop voltage representation for each phase, this embodiment can specifically analyze the voltage-current dynamic behavior of the three-phase inverter in the switching state according to the bipolar switching function and the virtual loop voltage representation to obtain the original time domain model of the three-phase inverter, specifically:

[0162] When the bipolar switch function hour, ; When the bipolar switch function hour, , is the switching state of the a-phase bridge arm, so:

[0163]

[0164] Then the independent virtual circuit voltage representation of each phase is organized as:

[0165]

[0166] Under the condition of three-phase symmetry of the system, we have:

[0167]

[0168] Therefore, we can get:

[0169]

[0170] The voltage of the upper and lower bridge arms of VSC can be further obtained as:

[0171]

[0172] Substituting into the three-phase coupling control model, the switching model of VSC can be obtained as follows:

[0173]

[0174] Finally, in the process of controlling the DC-AC converter of the three-phase inverter by using the preset first-order carrier and second-order sideband harmonics, the present embodiment introduces the sinusoidal pulse width modulation fitting switch model into the original time domain model of the three-phase inverter. Specifically, the switching function is replaced by the double Fourier expansion, and the coupling effect of the carrier and the modulation wave is taken into account. By controlling the DC-AC converter by the preset first-order carrier and second-order sideband harmonics, the fitted switching function expression can be obtained. The fitted switching function expression is:

[0175]

[0176] In the formula, is the bipolar switching function at time t; is the second-order Bessel function of the first kind.

[0177] Substituting the fitted switching function expression into the original time domain model of the three-phase inverter, the improved time domain model of the inverter including the coupling effect of the carrier and the modulation wave can be obtained. The improved time domain model of the inverter is specifically:

[0178]

[0179] Applying it to the microgrid of this application, the improved time domain model of the DC / AC circuit is obtained as follows:

[0180]

[0181] In the formula, is the filter inductor; is the filter resistor; , and is the three-phase voltage; , and is the three-phase current; , and The three-phase voltage of the main grid; is the differential of the three-phase current.

[0182] S5. Integrate the improved photovoltaic time domain model, the improved energy storage time domain model and the improved inverter time domain model into the DC microgrid architecture to construct a photovoltaic energy storage DC microgrid joint simulation model.

[0183] This embodiment applies the improved modeling method to the DC microgrid, and solves the simulation model through simulation software (such as Dymola), simulates the photovoltaic storage DC microgrid simulation model, and obtains the operating characteristics of the DC microgrid under different working conditions. This embodiment can analyze the simulation results and evaluate the performance of different modeling methods in terms of modeling accuracy, calculation efficiency, etc., by evaluating the advantages and disadvantages of different modeling methods in an open-loop system environment. Specifically, this embodiment sets the voltage curve of the time domain simulation output As a reference, the improved modeling method of this embodiment solves the results By comparison, the modeling error e between different mathematical models and simulation models is calculated, which is:

[0184]

[0185] In order to quantify the model accuracy, this embodiment selects the maximum value and average value of the error curve in steady state as key evaluation indicators, and verifies the accuracy and efficiency of the improved modeling method of this embodiment. In summary, the time domain modeling method based on Fourier expansion proposed in this embodiment uses a triangular Fourier expansion to fit the non-continuous switching function. This strategy not only significantly improves the model accuracy, but also effectively avoids the problem of decreased computational efficiency caused by the increase in dependent variables. Compared with the traditional switching model, the proposed method improves the modeling accuracy and solution efficiency without adding additional variables. At the same time, it can improve the filtering accuracy in dynamic state estimation, thereby enhancing the control effect. In microgrid modeling applications, this method has achieved significant improvements in modeling accuracy and computational efficiency, and can enhance the filtering accuracy in the dynamic state estimation process, thereby optimizing the control effect, solving the shortcomings of traditional modeling methods in modeling accuracy and solution efficiency. These defects limit the wide application of converter rapid modeling methods in scenarios such as new energy microgrids.

[0186] In order to fully verify the effectiveness of the modeling method proposed in this embodiment, this embodiment takes the DC converter and the three-phase inverter circuit as examples to compare and analyze the advantages and disadvantages of different modeling methods in open-loop and closed-loop systems. Figure 6 , Figure 7 As shown in the figure, in the Boost circuit scenario, this embodiment compares the model accuracy of various modeling methods, among which the time domain simulation model, the state space average model, the dynamic phasor model and the switch model are all models in the prior art, among which the switch model is a model in the prior art that considers the switch action in detail and describes the dynamic behavior of the switch device in the system; the improved time domain model is the DC microgrid converter fast modeling method proposed in this embodiment, which improves the accuracy and solution efficiency of the model by considering the first-order carrier and the corresponding sideband harmonic components. In a closed-loop system, although the state space average method has a high solution efficiency, it cannot capture the ripple characteristics of the state variables, and therefore cannot meet the needs of high-precision modeling; although the switch model can The dynamic phasor method performs well in modeling ripple in DC-DC circuits, but in DC-AC circuits, due to the greater influence of sideband harmonics, its modeling error will increase accordingly. In addition, as the system scale increases and the number of considered ripple orders increases, the solution time of the dynamic phasor method will be further extended. However, when modeling the AC side, since only the fundamental frequency component is considered, the modeling effect is similar to the state space average model. In contrast, the improved time domain model proposed in this embodiment can better fit the voltage ripple after incorporating the first-order carrier and the corresponding sideband harmonic components, and its model accuracy exceeds that of the dynamic phasor method.

[0187] In order to further study the influence of different harmonic orders on improving the accuracy and solution efficiency of the time domain model, since the harmonic components on the DC side and the AC side are different, this embodiment discusses the DC side and the AC side respectively. Figure 8 , Fig. 9 As shown in the figure, with the increase of the harmonic order considered, the fitting effect of the improved time domain method on the voltage ripple and the AC current is gradually improved. However, when enough harmonic components are considered, the effect of improving the model accuracy is no longer obvious, but the solution time is still increasing. Considering the accuracy and efficiency comprehensively, when the second-order components are considered on the DC side and the double frequency and double sideband harmonics are considered on the AC side, the improved time domain method can achieve the accuracy of the approximate switch model, and it has a solution efficiency better than the switch model. In summary, the DC microgrid converter fast modeling method proposed in this embodiment improves the model accuracy while effectively avoiding the problem of reduced computational efficiency caused by the increase in variables. It shows excellent performance in the modeling of DC converters and three-phase inverter circuits, and provides technical support for the safe and stable operation of microgrids.

[0188] The embodiment of the present invention provides a method for rapid modeling of a DC microgrid converter. The method performs harmonic component fitting on a discontinuous converter switch function based on a triangular Fourier series to generate a fitting switch model; based on the fitting switch model, a photovoltaic improved time domain model is obtained using a maximum power point tracking algorithm; an energy storage improved time domain model of the energy storage battery charging and discharging dynamic characteristics is constructed using the fitting switch model; a bipolar switching function is defined according to a three-phase inverter circuit topology, and sideband harmonic analysis is performed based on the bipolar switching function to obtain an inverter improved time domain model including carrier and modulation wave coupling effects; the photovoltaic improved time domain model, the energy storage improved time domain model and the inverter improved time domain model are integrated into a DC microgrid architecture to construct a photovoltaic storage DC microgrid joint simulation model. Compared with the prior art, the method fits the harmonic components of the discontinuous converter switch function based on a triangular Fourier series, and constructs an improved time domain model in combination with the fitting switch model to achieve rapid and accurate modeling of a DC microgrid converter, providing efficient and accurate technical support for the safe and stable operation of the microgrid.

[0189] It should be noted that the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0190] In one embodiment, Fig.10 As shown, an embodiment of the present invention provides a DC microgrid converter rapid modeling system, the system comprising:

[0191] The switch fitting module 101 is used to perform harmonic component fitting on the discontinuous converter switch function based on the triangular Fourier series to generate a fitting switch model; the fitting switch model includes a pulse width modulation fitting switch model of a DC-DC circuit and a sine wave pulse width modulation fitting switch model of a DC-AC circuit;

[0192] A first modeling module 102 is used to model the photovoltaic array cascade Boost converter according to the fitting switch model using a maximum power point tracking algorithm to obtain a photovoltaic improved time domain model;

[0193] A second modeling module 103 is used to construct an improved time domain model of energy storage of the dynamic characteristics of charge and discharge of the energy storage battery based on the bidirectional DC-DC converter topology by using the fitting switch model;

[0194] The third modeling module 104 is used to define a bipolar switching function according to the three-phase inverter circuit topology, and perform sideband harmonic analysis based on the bipolar switching function to obtain an improved inverter time domain model including the carrier and modulation wave coupling effect;

[0195] The model integration module 105 is used to integrate the photovoltaic improved time domain model, the energy storage improved time domain model and the inverter improved time domain model into the DC microgrid architecture to construct a photovoltaic storage DC microgrid joint simulation model.

[0196] For the specific limitations of a DC microgrid converter rapid modeling system, please refer to the above-mentioned limitations on a DC microgrid converter rapid modeling method, which will not be repeated here. A person of ordinary skill in the art will appreciate that the various modules and steps described in conjunction with the embodiments disclosed in this application can be implemented in hardware, software, or a combination of both. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0197] An embodiment of the present invention provides a DC microgrid converter rapid modeling system, wherein a switch fitting module of the system performs harmonic component fitting on a discontinuous converter switch function based on a trigonometric Fourier series to generate a fitted switch model; a first modeling module obtains a photovoltaic improved time domain model using a maximum power point tracking algorithm according to the fitted switch model; a second modeling module constructs an energy storage improved time domain model of the energy storage battery charging and discharging dynamic characteristics using the fitted switch model; a third modeling module defines a bipolar switching function according to a three-phase inverter circuit topology, and performs sideband harmonic analysis based on the bipolar switching function to obtain an inverter improved time domain model including carrier and modulation wave coupling effects; a model integration module integrates the photovoltaic improved time domain model, the energy storage improved time domain model and the inverter improved time domain model into a DC microgrid architecture to construct a photovoltaic storage DC microgrid joint simulation model. Compared with the existing technology, the system fits the harmonic components of the discontinuous converter switching function based on the trigonometric Fourier series, and builds an improved time domain model based on the fitted switching model to achieve fast and accurate modeling of the DC microgrid converter, providing efficient and accurate technical support for the safe and stable operation of the microgrid.

[0198] The above-mentioned embodiments only express several preferred implementation modes of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in the technical field, several improvements and substitutions can be made without departing from the technical principles of the present invention, and these improvements and substitutions should also be regarded as the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be based on the protection scope of the claims.

Claims

1. A DC microgrid converter rapid modeling method, characterized in that: The following steps are involved: Perform harmonic component fitting on the discontinuous converter switching function based on the triangular Fourier series to generate a fitting switch model; the fitting switch model includes a pulse width modulation fitting switch model of a DC-DC circuit and a sinusoidal pulse width modulation fitting switch model of a DC-AC circuit; According to the fitting switch model, a maximum power point tracking algorithm is used to model the photovoltaic array cascade Boost converter to obtain a photovoltaic improved time domain model; Based on the bidirectional DC-DC converter topology, the fitted switch model is used to construct an improved time domain model of energy storage for the dynamic characteristics of charge and discharge of the energy storage battery; A bipolar switching function is defined according to the three-phase inverter circuit topology, and sideband harmonic analysis is performed based on the bipolar switching function to obtain an improved inverter time domain model including carrier and modulation wave coupling effects; Integrate the photovoltaic improved time domain model, the energy storage improved time domain model and the inverter improved time domain model into the DC microgrid architecture to construct a photovoltaic storage DC microgrid joint simulation model; The discontinuous converter switching function includes a pulse width modulation switching function of a DC-DC circuit and a sinusoidal pulse width modulation switching function of a DC-AC circuit; the step of performing harmonic component fitting on the discontinuous converter switching function based on a triangular Fourier series to generate a fitting switching model includes: According to the duty cycle of the pulse width modulation signal in the DC-DC circuit, a pulse width modulation switching function under a preset switching period is obtained; Using a triangular Fourier series to perform harmonic decomposition on the pulse width modulation switching function, and solving to obtain harmonic coefficients of each order; According to the harmonic coefficients of each order and the preset harmonic order, a pulse width modulation fitting switch model formed by superposition of trigonometric function signals of different switching frequency multiples is generated using a Fourier series expansion; Establishing a sine wave pulse width modulation switching function of a sine wave pulse width modulation signal modulation process in a DC-AC circuit, and based on the sine wave pulse width modulation switching function, generating a switch trigger pulse switching function by utilizing the phase angle relationship between the modulation wave of the sine wave pulse width modulation signal and the triangular carrier; The switch trigger pulse switch function is fitted by using a double Fourier decomposition method to generate a sinusoidal pulse width modulation fitting switch model including a sideband harmonic coupling effect.

2. A DC microgrid converter rapid modeling method as claimed in claim 1, characterized in that: The step of fitting the switch trigger pulse switch function by using the double Fourier decomposition method to generate a sine wave pulse width modulation fitting switch model including the sideband harmonic coupling effect comprises: The switch trigger pulse switch function is decomposed into a DC component, a modulation wave fundamental frequency component, a carrier harmonic component, and a sideband harmonic component generated by the interaction of the modulation wave and the carrier harmonic using a double Fourier decomposition method; According to the preset carrier frequency multiples and modulation wave frequency multiples, the corresponding key harmonic components are intercepted from the carrier harmonic components and the sideband harmonic components; A sinusoidal pulse width modulation fitting switch model including sideband harmonic coupling effect is generated according to the DC component, the modulation wave fundamental frequency component and the key harmonic component.

3. A DC microgrid converter rapid modeling method as claimed in claim 1, characterized in that: The mathematical expression of the fitting switch model is: In the formula, is the pulse width modulation fitting switch model; d is the duty cycle of the pulse width modulation signal in a single switching cycle; n is the preset harmonic order; is the switching angular frequency; t is the time; is the fitting switch model of sinusoidal pulse width modulation; M is the modulation ratio; is the phase angle of the modulated wave; i is the multiple of the carrier frequency; is the zero-order Bessel function among the Bessel functions of the first kind; is the phase angle of the triangular carrier; j is the modulating wave frequency multiple; is infinite; is the Bessel function of the first kind.

4. A DC microgrid converter rapid modeling method as claimed in claim 1, characterized in that: The step of modeling the photovoltaic array cascade Boost converter according to the fitting switch model using the maximum power point tracking algorithm to obtain the photovoltaic improved time domain model includes: According to the physical parameters of photovoltaic cells, a single diode equivalent circuit model of photovoltaic cells is constructed; Under constant temperature and irradiance conditions, the output side voltage and output side current of the photovoltaic cell are obtained through the single diode equivalent circuit model; The photovoltaic array cascade boost converter is selected as the DC-DC converter, and the voltage and current behaviors of the DC-DC converter under different switch working states are analyzed according to the topological structure and switch working state of the DC-DC converter, and the photovoltaic original time domain model of the photovoltaic array cascade boost converter is established; In the process of controlling the DC-DC converter by using a preset first-order ripple, the pulse width modulation fitting switch model is introduced into the photovoltaic original time domain model, and the maximum power point tracking algorithm is used to control the output power of the photovoltaic cell to obtain a control reference voltage; A photovoltaic improved time domain model of a photovoltaic array cascade Boost converter is constructed according to the control reference voltage, the output side voltage and the output side current of the photovoltaic cell.

5. A DC microgrid converter rapid modeling method as claimed in claim 4, characterized in that: The step of controlling the output power of the photovoltaic cell by using the maximum power point tracking algorithm to obtain a control reference voltage comprises: The maximum power point tracking algorithm is used to adjust the duty cycle of the photovoltaic array cascade boost converter in real time, and the output power of the photovoltaic cell is dynamically converged to the maximum power point through closed-loop control to generate a control reference voltage.

6. A DC microgrid converter rapid modeling method according to claim 1, characterized in that: The step of constructing an improved time domain model of energy storage for the dynamic characteristics of charge and discharge of an energy storage battery based on a bidirectional DC-DC converter topology by using the fitted switch model comprises: According to the physical parameters of the energy storage battery, an electromagnetic transient model of the energy storage battery in the DC microgrid is constructed, and through the electromagnetic transient model, a dynamic relationship equation between the output voltage and the output current of the energy storage battery in the charging and discharging states is established; Based on the topological structure of the bidirectional DC-DC converter in the energy storage battery and its switch working state, the voltage-current dynamic behavior of the bidirectional DC-DC converter under different switch working states is analyzed, and the energy storage original time domain model of the bidirectional DC-DC converter is established; In the process of controlling the bidirectional DC-DC converter by using a preset first-order ripple, the pulse width modulation fitting switch model is introduced into the energy storage original time domain model to obtain an improved energy storage switch model of the bidirectional DC-DC converter; Based on the dynamic relationship equation between the output voltage and the output current of the energy storage battery in the charging and discharging states, an improved energy storage time domain model of the energy storage battery controlling the DC bus voltage through a bidirectional DC-DC converter is constructed through the improved energy storage switch model.

7. A DC microgrid converter rapid modeling method according to claim 1, characterized in that: The steps of defining a bipolar switching function according to the three-phase inverter circuit topology, performing sideband harmonic analysis based on the bipolar switching function, and obtaining an improved inverter time domain model including carrier and modulation wave coupling effects include: When the DC microgrid is connected to the grid through a three-phase inverter, a bipolar switching function is defined according to the circuit topology of the three-phase inverter and its switch working state; A three-phase coupling control model of a three-phase inverter is established by using Kirchhoff's voltage law, and the three-phase coupling control model is decoupled into an independent virtual loop voltage representation for each phase by introducing a virtual three-phase neutral point voltage; Analyzing the voltage-current dynamic behavior of the three-phase inverter in the switching state according to the bipolar switching function and the virtual loop voltage representation, and obtaining the original time domain model of the three-phase inverter; In the process of controlling the DC-AC converter of the three-phase inverter using the preset first-order carrier and second-order sideband harmonics, the sinusoidal wave pulse width modulation fitting switch model is introduced into the original time domain model of the three-phase inverter to obtain an improved time domain model of the inverter including the carrier and modulation wave coupling effect.

8. A DC microgrid converter rapid modeling method according to claim 7, characterized in that: The bipolar switching function is specifically: When the upper bridge arm switch device of each phase of the three-phase inverter is turned on and the lower bridge arm switch device is turned off, the bipolar switching function is defined as positive one; When the lower bridge arm switch devices of each phase of the three-phase inverter are turned on and the upper bridge arm switch devices are turned off, the bipolar switching function is defined as negative one.

9. A DC microgrid converter rapid modeling system, characterized in that: The system comprises: A switch fitting module, used for performing harmonic component fitting on the discontinuous converter switch function based on the triangular Fourier series to generate a fitting switch model; the fitting switch model includes a pulse width modulation fitting switch model of a DC-DC circuit and a sine wave pulse width modulation fitting switch model of a DC-AC circuit; The first modeling module is used to model the photovoltaic array cascade Boost converter according to the fitting switch model and use the maximum power point tracking algorithm to obtain a photovoltaic improved time domain model; A second modeling module is used to construct an improved time domain model of energy storage of the dynamic characteristics of charge and discharge of the energy storage battery based on a bidirectional DC-DC converter topology by using the fitted switch model; A third modeling module is used to define a bipolar switching function according to the three-phase inverter circuit topology, and perform sideband harmonic analysis based on the bipolar switching function to obtain an improved inverter time domain model including carrier and modulation wave coupling effects; A model integration module, used to integrate the photovoltaic improved time domain model, the energy storage improved time domain model and the inverter improved time domain model into the DC microgrid architecture to construct a photovoltaic storage DC microgrid joint simulation model; The discontinuous converter switching function includes a pulse width modulation switching function of a DC-DC circuit and a sinusoidal pulse width modulation switching function of a DC-AC circuit; the switch fitting module is specifically used for: According to the duty cycle of the pulse width modulation signal in the DC-DC circuit, a pulse width modulation switching function under a preset switching period is obtained; Using a triangular Fourier series to perform harmonic decomposition on the pulse width modulation switching function, and solving to obtain harmonic coefficients of each order; According to the harmonic coefficients of each order and the preset harmonic order, a pulse width modulation fitting switch model formed by superposition of trigonometric function signals of different switching frequency multiples is generated using a Fourier series expansion; Establishing a sine wave pulse width modulation switching function of a sine wave pulse width modulation signal modulation process in a DC-AC circuit, and based on the sine wave pulse width modulation switching function, generating a switch trigger pulse switching function by utilizing the phase angle relationship between the modulation wave of the sine wave pulse width modulation signal and the triangular carrier; The switch trigger pulse switch function is fitted by using a double Fourier decomposition method to generate a sinusoidal pulse width modulation fitting switch model including a sideband harmonic coupling effect.

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