A virtual synchronous machine-sliding mode collaborative control-based voltage stability control method and system for a micro-grid with photovoltaic and energy storage

Abstract

The application discloses a kind of photovoltaic energy storage micro-grid voltage stability control method and system based on virtual synchronous machine-sliding mode collaborative control, and relates to the technical field of power system control, which comprises: photovoltaic array realizes maximum power point tracking by Boost voltage increasing circuit and perturbation and observation method;The hybrid energy storage system consisting of battery and super capacitor respectively passes through bidirectional DC / DC converter to suppress low-frequency and high-frequency power disturbance;Grid-connected inverter is controlled by virtual synchronous machine collaborative sliding mode control link, wherein active frequency control sub-link generates frequency and phase reference value according to rotor inertia equation, and sliding mode control sub-link generates voltage amplitude reference value based on third-order virtual synchronous machine model, integral type sliding surface and super-spiral approach law to replace traditional reactive voltage link.The application realizes the fast, robust stable control of micro-grid voltage, effectively suppresses voltage overshoot and oscillation under disturbance condition.

Description

Technical Field

[0001] This invention relates to the field of power system control technology, specifically to a voltage stability control method and system for a photovoltaic-storage microgrid based on virtual synchronous machine-sliding mode cooperative control. Background Technology

[0002] With the rapid development of distributed energy, photovoltaic microgrids, as an important form of clean energy utilization, have been widely used in scenarios such as power supply in remote areas, self-consumption in industrial parks, and emergency backup power. Photovoltaic microgrids typically consist of photovoltaic arrays, energy storage systems, and grid-connected inverters. Their core control objective is to maintain the stability of grid-connected voltage and frequency under disturbances such as fluctuations in sunlight and changes in load.

[0003] Virtual Synchronous Generator (VSG) control technology has attracted widespread attention in recent years. This technology simulates the rotor inertia equations and excitation characteristics of a synchronous generator, enabling the inverter to exhibit similar external characteristics, thus providing inertia and voltage support for microgrids. Traditional VSG control typically includes active-frequency control and reactive-voltage control, with the reactive-voltage link often employing droop control or PI control strategies. However, when faced with large disturbances (such as sudden load changes, sudden drops in illumination, and short-circuit faults), the transient response speed of the reactive-voltage link in traditional VSG control is limited, easily leading to significant voltage overshoot and prolonged oscillations, making it difficult to meet the requirements of applications with high voltage quality.

[0004] Furthermore, the intermittency and volatility of photovoltaic power output pose a significant challenge to the power balance of microgrids. A single energy storage method is insufficient to simultaneously cope with low-frequency gradual power fluctuations and high-frequency instantaneous surges, necessitating the coordinated use of multiple energy storage methods. At the control level, traditional PI controllers are prone to performance degradation and lack sufficient robustness when system parameters change or external disturbances are significant. Therefore, how to combine the power hierarchical management capabilities of hybrid energy storage systems with advanced nonlinear control technologies to achieve rapid, stable, and robust voltage control of microgrids is a pressing technical problem that needs to be solved in this field. Summary of the Invention

[0005] To address the shortcomings of existing technologies, the present invention aims to provide a voltage stability control method and system for photovoltaic-storage microgrids based on virtual synchronous machine-sliding mode cooperative control. This method achieves rapid and robust voltage stability control of the microgrid and effectively suppresses voltage overshoot and oscillation under disturbance conditions.

[0006] To achieve the above objectives, the embodiments of this application provide the following technical solutions:

[0007] This application provides a voltage stability control method for a photovoltaic-storage microgrid based on virtual synchronous machine-sliding mode cooperative control, including the following steps: S1, the output of the photovoltaic array is boosted by a Boost circuit, and the duty cycle is adjusted by a maximum power point tracking (MPPT) stage based on the disturbance observation method to make the photovoltaic array work at its maximum power point. S2, the output of the Boost circuit is connected to a hybrid energy storage system composed of a battery and a supercapacitor; the battery is connected to the DC bus via a first bidirectional DC / DC converter to smooth low-frequency slow-changing disturbances; the supercapacitor is connected to the DC bus via a second bidirectional DC / DC converter to smooth high-frequency instantaneous disturbances. S3, the DC bus power is inverted into AC power by a grid-connected inverter and connected to the grid. The grid-connected inverter is controlled by a virtual synchronous machine cooperative sliding mode control stage; the active frequency control sub-stage of this stage generates frequency and phase reference values ​​based on the rotor inertia equation, and the sliding mode control sub-stage generates voltage amplitude reference values ​​based on a third-order virtual synchronous machine model, an integral sliding surface, and a super-spiral approaching law, replacing the traditional reactive voltage stage. S4. Combine the frequency phase reference value and the voltage amplitude reference value into an inverter voltage command, and generate a modulation signal through a voltage and current dual closed loop to drive the grid-connected inverter.

[0008] Further, in S1, the perturbation observation method includes: real-time detection of the output voltage and output current of the photovoltaic array, and calculation of the real-time output power of the photovoltaic array; comparison of the output power at the current sampling moment with the output power at the previous sampling moment, comparison of the output voltage at the current sampling moment with the output voltage at the previous sampling moment, and adjustment of the duty cycle according to the combination relationship between the power and voltage change directions, so that the operating point of the photovoltaic array gradually approaches and stabilizes at the maximum power point.

[0009] Furthermore, in step S2, the hybrid energy storage system satisfies the power balance relationship, with the battery and supercapacitor jointly undertaking the task of power disturbance mitigation. The battery branch obtains the battery output power by collecting the DC bus voltage and current and processing it through a DC / DC converter. The difference between this output power and the expected active power is then used by a PI controller and PWM calculation to mitigate low-frequency, slow-changing disturbances. The supercapacitor branch uses the DC bus voltage deviation as the control target and uses a PI controller and PWM calculation to mitigate high-frequency, instantaneous power disturbances. The two bidirectional DC / DC converters operate in Buck mode and Boost mode, respectively, enabling bidirectional energy flow.

[0010] Furthermore, in step S3, the active frequency control sub-loop calculates the virtual rotor angular velocity and voltage phase reference values ​​by simulating the rotor inertial response and damping characteristics of the synchronous generator through virtual moment of inertia and damping coefficient based on the active-frequency rotor inertia equation.

[0011] Furthermore, in step S3, the third-order virtual synchronous machine mathematical model adds an excitation dynamic equation to the second-order model to describe the dynamic change process of the transient excitation electromotive force; at the same time, a transient voltage output equation is established to describe the relationship between the dq axis output voltage and the transient excitation electromotive force, current and reactance.

[0012] Furthermore, in step S3, the sliding mode control sub-loop adopts an integral sliding surface, using the voltage tracking error and its integral as state variables to construct the sliding surface function; the control law adopts an equivalent control plus switching control structure, wherein the equivalent control is obtained by setting the sliding surface derivative to zero and solving it in combination with the excitation dynamic equation, and the switching control adopts a super-spiral algorithm, which includes nonlinear terms related to the square root of the absolute value of the sliding surface and integral terms of the sign function; finally, the control law is substituted into the excitation electromotive force as the excitation dynamic equation, and the transient excitation electromotive force is solved as the voltage amplitude reference value.

[0013] This application also provides a photovoltaic-sliding mode cooperative control system for a photovoltaic-storage microgrid, which is used to execute the above method. The system includes a photovoltaic array, a boost converter, a maximum power point tracking controller, a hybrid energy storage system, a grid-connected inverter, and a VSG-sliding mode cooperative controller.

[0014] Furthermore, both the first bidirectional DC / DC converter and the second bidirectional DC / DC converter are half-bridge bidirectional Buck-Boost converters, which respectively achieve charging and discharging management of the battery and the supercapacitor through power deviation PI control and voltage deviation PI control.

[0015] Furthermore, the sliding mode control module includes a sliding mode surface calculation unit, an equivalent control calculation unit, a super-helical switching control calculation unit, and an excitation electromotive force solution unit. Each unit works together to complete the calculation of the voltage amplitude reference value based on the integral sliding mode surface and the super-helical approach law.

[0016] The beneficial effects of this invention are:

[0017] (1) By using the collaborative architecture of virtual synchronous machine and sliding mode control, sliding mode control replaces the reactive power-voltage link of traditional VSG. Based on the third-order virtual synchronous machine model, integral sliding surface and super-spiral maximization law to generate voltage amplitude reference value, the speed and robustness of voltage transient response are realized. The integral sliding surface eliminates steady-state voltage error, and the super-spiral maximization law effectively weakens the chattering phenomenon of traditional sliding mode control.

[0018] (2) By using a hybrid energy storage system consisting of batteries and supercapacitors in conjunction with their respective bidirectional DC / DC converters for power tiered management, the system achieves differentiated suppression of low-frequency slow-change disturbances and high-frequency instantaneous disturbances, extends the battery life, and improves the system's resistance to sudden disturbances.

[0019] (3) By using the four-quadrant judgment logic of power and voltage change direction of the perturbation observation method, the photovoltaic array realizes adaptive maximum power point tracking when the illumination conditions change rapidly, which improves the energy utilization efficiency of the photovoltaic power generation system.

[0020] (4) By simulating the rotor inertia and damping characteristics of a synchronous generator through the active-frequency rotor inertia equation, the photovoltaic inverter provides virtual inertia support for the microgrid, effectively suppressing power oscillations and frequency fluctuations.

[0021] (5) The technology of introducing the excitation dynamic equation through the mathematical model of the third-order virtual synchronous machine to fully characterize the electromagnetic transient process of the inverter has realized the provision of an accurate controlled object model for sliding mode control, and improved the accuracy and stability of voltage control.

[0022] (6) The technology of converting the VSG-sliding mode collaborative control output into the grid-connected inverter modulation signal through the voltage and current dual closed-loop control structure realizes multi-level control from the power layer to the switching layer, ensuring the grid-connected power quality. Attached Figure Description

[0023] Figure 1 A flowchart illustrating a voltage stability control method for a photovoltaic-storage microgrid based on virtual synchronous machine-sliding mode cooperative control, provided for an embodiment of this application;

[0024] Figure 2 A logical schematic diagram of the perturbation observation method provided in the embodiments of this application;

[0025] Figure 3 A schematic diagram of system power relationships provided for embodiments of this application;

[0026] Figure 4 This is a schematic diagram of the system collaboration process provided in the embodiments of this application;

[0027] Figure 5 This is a schematic diagram of the output power waveform of a hybrid energy storage system in steady state, provided in an embodiment of this application.

[0028] Figure 6 A schematic diagram of the output power waveform of the hybrid energy storage system under a voltage sag of 20% for 0.15s, provided for an embodiment of this application;

[0029] Figure 7 A schematic diagram of the output power waveform of a hybrid energy storage system under a voltage dip of 20% for 0.5s, provided for an embodiment of this application;

[0030] Figure 8This is a schematic diagram of a voltage stability control system for a photovoltaic-storage microgrid based on virtual synchronous machine-sliding mode cooperative control, provided as an embodiment of this application. Detailed Implementation

[0031] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the scope of the present invention.

[0032] In this invention, the terms "system" and "network" are used interchangeably. "Multiple" refers to two or more; therefore, in this invention, "multiple" can also be understood as "at least two." "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. Additionally, the character " / ", unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship. Furthermore, it should be understood that in the description of this invention, terms such as "first" and "second" are used only for descriptive purposes and should not be construed as indicating or implying relative importance or order.

[0033] Example 1:

[0034] like Figures 1-7 As shown, this application provides a voltage stability control method for a photovoltaic-storage microgrid based on virtual synchronous machine-sliding mode cooperative control, including: S1, the output of the photovoltaic array is boosted by a Boost circuit, and the duty cycle is adjusted by a maximum power point tracking (MPPT) stage based on a disturbance observation method to make the photovoltaic array operate at its maximum power point; S2, the output of the Boost circuit is connected to a hybrid energy storage system composed of a battery and a supercapacitor; the battery is connected to the DC bus via a first bidirectional DC / DC converter to smooth out low-frequency slow-changing disturbances; the supercapacitor is connected to the DC bus via a second bidirectional DC / DC converter. Smoothing high-frequency transient disturbances; S3, DC bus power is converted into AC power by the grid-connected inverter and connected to the grid. The grid-connected inverter is controlled by a virtual synchronous machine and a sliding mode control loop. The active frequency control sub-loop of this loop generates frequency and phase reference values ​​based on the rotor inertia equation. The sliding mode control sub-loop generates voltage amplitude reference values ​​based on a third-order virtual synchronous machine model, an integral sliding surface, and a super-spiral approaching law, replacing the traditional reactive voltage loop; S4, the frequency and phase reference values ​​and the voltage amplitude reference values ​​are combined into an inverter voltage command, which is then used to generate a modulation signal through a voltage and current dual closed loop to drive the grid-connected inverter.

[0035] In one possible embodiment, this embodiment is applied to a photovoltaic-storage microgrid system comprising a photovoltaic array, a hybrid energy storage system, and a grid-connected inverter. The photovoltaic array serves as the DC-side power source, and its output is boosted by a Boost converter before being connected to the DC bus. The hybrid energy storage system consists of batteries and supercapacitors, which are connected in parallel to the DC bus via bidirectional DC / DC converters. The grid-connected inverter converts the DC bus power into AC power for grid connection, and is controlled by a virtual synchronous machine in conjunction with a sliding mode controller.

[0036] First, in S1: the DC power output from the photovoltaic array is boosted to the required voltage level on the DC bus by the Boost circuit. The Maximum Power Point Tracking (MPPT) stage is based on the perturbation observation method, which detects the output voltage and current of the photovoltaic array in real time, calculates the real-time output power, and adaptively adjusts the duty cycle of the Boost circuit according to the power and voltage change trends, so that the photovoltaic array always operates at the maximum power point under the current irradiance and temperature conditions. The Boost circuit not only realizes the voltage boosting function, but also acts as the actuator of MPPT, indirectly controlling the operating voltage of the photovoltaic array through duty cycle adjustment. Second, in S2: the output of the Boost circuit is connected to a hybrid energy storage system composed of batteries and supercapacitors. Due to its high energy density, the battery is suitable for handling power fluctuations (i.e., low-frequency disturbances) that last for a long time but change slowly, and is connected to the DC bus via the first bidirectional DC / DC converter; the supercapacitor, due to its high power density and millisecond-level response speed, is suitable for handling power surges (i.e., high-frequency disturbances) that last for a short time but change drastically, and is connected to the DC bus via the second bidirectional DC / DC converter. The complementary combination of the two energy storage components covers the power fluctuation frequency band from milliseconds to minutes, avoiding the contradiction between response speed and continuous capability in a single energy storage method. Next, S3 is executed: DC bus power is inverted into AC power by the grid-connected inverter and connected to the grid. The grid-connected inverter is controlled by a virtual synchronous machine (VSG) cooperative sliding mode control loop. This cooperative control loop contains two core sub-loops: the active frequency control sub-loop generates frequency and phase reference values ​​based on the rotor inertia equation, i.e., the differential equation simulating the rotor motion law of a synchronous generator, so that the inverter exhibits inertial response characteristics similar to a synchronous generator; the sliding mode control sub-loop generates voltage amplitude reference values ​​based on a third-order virtual synchronous machine model (i.e., introducing excitation dynamic equations on the basis of the traditional second-order model, adding a description of the transient process of the excitation winding), an integral sliding surface (i.e., a switching function surface constructed with voltage tracking error and its time integral as state variables), and a super-spiral reaching law. This sliding mode control sub-loop completely replaces the reactive power-voltage droop control loop in the traditional virtual synchronous machine, fundamentally improving the transient response speed and control robustness of the voltage loop. Then, S4 is executed: the frequency and phase reference values ​​output from the active power frequency control sub-loop are combined with the voltage amplitude reference value output from the sliding mode control sub-loop to form the inverter voltage command vector. This voltage command vector is then processed by a voltage-current dual closed-loop control structure—a cascaded PI control structure with an outer voltage loop and an inner current loop—to generate a pulse width modulation (PWM) signal. This PWM signal drives the switching transistors of the grid-connected inverter to turn on and off according to a specific timing sequence, ultimately achieving precise control of the grid-connected output voltage and current.Finally, through the coordinated execution of S1 to S4, the entire system forms a complete voltage stability control link for the photovoltaic-storage microgrid: the photovoltaic side achieves maximum power point tracking to maximize energy harvesting, the energy storage side implements graded smoothing of power fluctuations to maintain DC bus voltage stability, and the inverter side achieves high-quality grid-connected voltage and frequency output through VSG-sliding mode coordinated control. Throughout the control process, each sub-link operates independently yet in coordination, jointly ensuring the stable voltage operation of the microgrid under various disturbance conditions.

[0037] Through a collaborative architecture of virtual synchronous machine and sliding mode control, the photovoltaic grid-connected inverter simultaneously possesses the inertia support characteristics of a synchronous generator and the fast and robust voltage regulation capability of sliding mode control. The active frequency control sub-loop simulates the rotor inertial response of a synchronous generator, providing virtual inertia support for the microgrid; the sliding mode control sub-loop replaces the traditional reactive power-voltage loop, and based on a third-order model and a superspiral reaching law, achieves both fast and robust voltage transient response, effectively suppressing voltage overshoot and oscillation under disturbance conditions, and significantly improving the voltage stability control performance.

[0038] In this embodiment of the application, in step S1, the perturbation observation method includes: real-time detection of the photovoltaic array output voltage. and output current And calculate the real-time output power of the photovoltaic array. ; Output power at the current sampling time Output power at the previous sampling time Compare the output voltage at the current sampling time. Output voltage at the previous sampling time Compare and adjust the duty cycle according to the following logic: when and At that time, if Then the duty cycle increases positively: ;like Then the duty cycle decreases in the opposite direction: ;when and At that time, if Then the duty cycle decreases in the opposite direction: ;like Then the duty cycle increases positively: ;when At this time, the duty cycle remains unchanged: ;in, Let be the output voltage of the photovoltaic array at the k-th sampling time. Let be the output current of the photovoltaic array at the k-th sampling time. Let be the output power of the photovoltaic array at the k-th sampling time. The output voltage of the photovoltaic array at the (k-1)th sampling time is... Let be the output power of the photovoltaic array at the (k-1)th sampling time. The reference voltage at the k-th sampling time. Let be the reference voltage at the (k-1)th sampling time. The voltage is varied in fixed steps.

[0039] In one possible embodiment, the MPPT controller first detects the output voltage of the photovoltaic array in real time at a preset sampling frequency. and output current And calculate the real-time output power of the photovoltaic array. The output power at the current sampling time k. Output power at the previous sampling time k-1 Compare the output voltage at the current sampling time. Output voltage at the previous sampling time A comparison is then made. The selection of the sampling frequency needs to balance tracking speed and computational burden, and is generally in the kilohertz range. Secondly, based on the directional combination of the power difference and voltage difference, the duty cycle is adjusted according to the following four-quadrant judgment logic: when... and When this occurs, it indicates that the power is increasing. At this point, it's necessary to further determine the voltage direction. If... This means the voltage also increases, indicating that the current operating point is to the left of the maximum power point on the PV curve and is moving towards the maximum power point. Adjustment should continue in this direction, with the duty cycle increasing positively, meaning the reference voltage increases by a fixed step from its current value. : ;like This means that the voltage decreases, indicating that the current operating point is to the right of the maximum power point and is moving towards it. Adjustment should continue in this direction, with the duty cycle decreasing in the opposite direction, meaning the reference voltage is reduced by a fixed step from its current value. : Then, when and When this happens, it indicates that the power is decreasing and is currently deviating from the maximum power point, requiring adjustment in the opposite direction. This indicates that increasing the voltage is deviating from the intended direction; the voltage should be decreased in the opposite direction, and the duty cycle should be decreased accordingly. ;like This indicates that decreasing the voltage is deviating from the correct direction; the voltage should be increased in the opposite direction, and the duty cycle should increase in the positive direction. Then, when When the output power stops changing, the photovoltaic array has reached and stabilized near its maximum power point, and the duty cycle remains constant. The current operating point is maintained. Finally, the above judgment process is repeated in each sampling cycle, forming a continuous "perturbation-observation-judgment-adjustment" closed loop. When illumination conditions change (such as cloud cover reducing irradiance), the shape of the PV curve changes, and the position of the maximum power point shifts. The perturbation-observation method can automatically detect the change in the direction of power change and adjust the tracking direction accordingly, causing the operating point to approach the new maximum power point again. The voltage changes in fixed step sizes. The size of the step size affects the balance between tracking accuracy and speed: a larger step size results in faster tracking speed but larger steady-state oscillations, while a smaller step size results in higher steady-state accuracy but slower tracking speed.

[0040] By employing a four-quadrant judgment logic (i.e., power change direction × voltage change direction) based on the perturbation-observation method, adaptive maximum power point tracking (MPPT) of a photovoltaic array under rapidly changing illumination conditions is achieved. This method does not require establishing a precise mathematical model of the photovoltaic array; it determines the duty cycle adjustment direction simply by detecting the direction of power and voltage changes. The logic is simple, the implementation cost is low, and it can stably track and lock the maximum power point, achieving the technical effect of maximizing photovoltaic energy utilization efficiency.

[0041] In this embodiment of the application, the power balance relationship of the hybrid energy storage system in step S2 is as follows: ;in, For the output power of the photovoltaic array, For the output power of the storage battery, This refers to the output power of the supercapacitor. Power loss is caused by line resistance and parasitic resistance. The inverter output power; the total power that the hybrid energy storage system needs to smooth is: ;in, For the power to be mitigated in the hybrid energy storage system; the battery branch collects the DC bus voltage and current values, and calculates the battery branch voltage and current values ​​through the voltage and current conversion of the first bidirectional DC / DC converter, and calculates the battery output power. and will Compared with the preset expected active power value The difference is calculated and input into the PI controller, and then the modulation signal of the first bidirectional DC / DC converter is obtained through PWM calculation, thereby suppressing low-frequency, slowly changing disturbances. The supercapacitor branch collects the DC bus voltage and current values, and obtains the voltage and current values ​​of the supercapacitor branch through the voltage and current conversion of the second bidirectional DC / DC converter. Using the DC bus voltage deviation as the control target, the modulation signal of the second bidirectional DC / DC converter is obtained through PI controller and PWM calculation, thereby suppressing high-frequency, instantaneous power disturbances. The first bidirectional DC / DC converter and the second bidirectional DC / DC converter operate in Buck mode and Boost mode, respectively: in Buck mode, energy flows from the DC bus to the energy storage element, and in Boost mode, energy flows from the energy storage element to the DC bus.

[0042] In one possible implementation, firstly, the power balance relationship of the hybrid energy storage system is established. According to the law of conservation of energy, in a photovoltaic-storage microgrid, the output power of the photovoltaic array... Battery output power Supercapacitor output power The sum of these equals the power loss caused by the line resistance and parasitic resistance. With inverter output power The sum of these satisfies the following power balance equation: When the photovoltaic output power exceeds the load demand, the excess energy is absorbed by the hybrid energy storage system (charging batteries and / or supercapacitors). and (Negative values); when the photovoltaic output power is insufficient to meet the load demand, the hybrid energy storage system releases energy to fill the gap (batteries and / or supercapacitors discharge). and (Positive value). The total power deviation that the hybrid energy storage system needs to smooth is... This refers to the difference between the inverter's output power and the photovoltaic output power, reflecting the amount of power the system needs to obtain from or release to the energy storage system. Secondly, the control process of the battery branch: The battery branch collects the DC bus voltage and current values ​​through voltage and current sensors. The voltage and current values ​​of the battery branch are then obtained through voltage-to-current conversion (i.e., voltage-to-current conversion based on the converter's turns ratio) using the first bidirectional DC / DC converter, and subsequently, the battery output power is calculated. The calculated Compared with the preset expected active power value The difference is calculated to obtain the power deviation. This power deviation is input to the PI controller, which outputs a control signal. This signal is then used by PWM (Pulse Width Modulation) to generate the modulation signal for the first bidirectional DC / DC converter. When the battery output power is less than the expected value (the power deviation is negative, i.e., the system power is insufficient), the PI controller increases the duty cycle of the converter's Boost mode, allowing the battery to release more power; conversely, it decreases the duty cycle or switches to Buck mode for charging. Since the battery's response characteristics are suitable for handling slowly changing power components, this branch mainly smooths out low-frequency, slowly changing disturbances (such as gradual changes in light intensity or slow changes in load). Next, the control process of the supercapacitor branch: The supercapacitor branch also collects the DC bus voltage and current values, and obtains the voltage and current values ​​of the supercapacitor branch through voltage and current conversion of the second bidirectional DC / DC converter. Unlike the battery branch, the supercapacitor branch uses the DC bus voltage deviation (the difference between the actual bus voltage and the rated bus voltage) as the control target, and generates the modulation signal for the second bidirectional DC / DC converter through PI controller and PWM calculation. When the DC bus voltage drops due to insufficient power, the supercapacitor rapidly releases power to support the bus voltage; when the bus voltage rises due to excess power, the supercapacitor quickly absorbs the excess power to suppress the rise in bus voltage. Due to the extremely fast response speed of the supercapacitor, this branch primarily mitigates high-frequency, instantaneous power disturbances (such as sudden load shedding or surges, or the instantaneous impact of short-circuit faults). Then, the first and second bidirectional DC / DC converters operate in Buck mode and Boost mode, respectively. Buck mode, or buck mode, reduces the higher DC bus voltage to a lower voltage suitable for charging the energy storage element, with energy flowing from the DC bus to the energy storage element, corresponding to the charging process. Boost mode, or boost mode, increases the lower voltage of the energy storage element to the higher voltage required by the DC bus, with energy flowing from the energy storage element to the DC bus, corresponding to the discharging process. The switching between the two modes is automatically determined by the output signals of their respective PI controllers: when the PI output requires an increase in duty cycle exceeding a certain threshold, it naturally enters Boost mode; otherwise, it enters Buck mode, requiring no additional mode-determining logic. Finally, through the constraints of the aforementioned power balance equations and the independent coordinated control of the two branches, the hybrid energy storage system achieves graded suppression of power fluctuations: the supercapacitor, with its millisecond-level response capability, first absorbs or releases high-frequency instantaneous power components, effectively buffering the impact of sudden shocks on the DC bus voltage; while the battery, over a longer timescale, bears the low-frequency, slowly changing power components, maintaining the overall power balance of the system. This synergistic cooperation ensures voltage stability and avoids the battery from frequently experiencing large current surges, thus extending its lifespan.

[0043] By employing a hybrid energy storage system consisting of batteries and supercapacitors, coupled with independent bidirectional DC / DC converter control strategies, graded mitigation of low-frequency, slow-varying power fluctuations and high-frequency, instantaneous power surges is achieved. The batteries handle the majority of the power deficit (low-frequency component), while the supercapacitors, with their rapid response capabilities, absorb the instantaneous surge component, resulting in a rational power distribution. The power relationship between each component is precisely quantified using a power balance formula, and bidirectional energy flow is achieved through Buck / Boost mode switching between the dual DC / DC converters. This enables precise power balance management of the microgrid and extends the lifespan of the energy storage components.

[0044] In this embodiment of the application, in step S3, the active frequency control sub-loop is based on the active-frequency rotor inertia equation: ;in, For virtual rotational inertia, The damping coefficient is... For virtual rotor angular velocity, The preset active power reference value, To output electromagnetic power to the inverter, The angular velocity is the power grid angular velocity; the angular velocity is calculated using the active-frequency rotor inertia equation. and voltage phase reference value The virtual moment of inertia The photovoltaic inverter simulates the rotor inertial response of a synchronous generator, wherein the damping coefficient Provides damping support to the system to suppress power oscillations.

[0045] In one possible embodiment, firstly, the active-frequency rotor inertia equation is established: The physical meaning of this equation is: virtual moment of inertia. Multiply by angular acceleration It equals the difference between input power and output power minus the damping power. Wherein, This is a virtual moment of inertia, a control parameter rather than the actual mechanical inertia. Its function is to enable the photovoltaic inverter to simulate the rotor inertial response of a synchronous generator. The larger the value, the slower the frequency changes, the stronger the inertial support, but the longer the recovery time. The damping coefficient provides damping support to the system to suppress power oscillations, enabling the frequency to recover smoothly without continuous oscillations after deviating from the rated value. The virtual rotor angular velocity is obtained by integrating the angular acceleration and reflects the frequency state of the inverter's output power. This is the preset active power reference value, which is the active power that the system expects to output. The electromagnetic power output by the inverter, i.e., the actual output power; The grid angular velocity. Secondly, under steady-state operating conditions, the inverter output power... Equal to active power reference value Virtual rotor angular velocity Equal to the angular velocity of the power grid The left side of the equation The system is in equilibrium. At this point, by... Integrating the values ​​yields the virtual rotor angle, which serves as the voltage phase reference value and is used for subsequent Park conversion and inverter modulation. ,in, For the Laplace operator, This is the damping coefficient, used to suppress power oscillations. For power deviation, Then, when the system is subjected to disturbances (such as a sudden increase in load), the inverter outputs electromagnetic power. Instantly increased, and Keeping unchanged, making Substituting into the equation, angular acceleration... The virtual rotor angular velocity becomes negative. The frequency begins to decrease. This frequency decrease process simulates the inertial response of a synchronous generator during a sudden load increase as the rotor releases kinetic energy. The frequency does not jump instantaneously, but rather follows a gradual decrease from... The determined gradual rate change provides the system with valuable buffer time. Meanwhile, as... The decrease, damping term Becoming negative, generating a prompt The restored positive torque suppresses further frequency decline. Then, with the rebalancing of active power (the inverter output power naturally increases through the droop characteristic after the frequency decline), Gradually approaching zero, the angular acceleration decreases to zero, and the angular velocity stabilizes at the new equilibrium point. During this transient process, the virtual rotor angular velocity and voltage phase reference values ​​are obtained in real time by continuously integrating the active-frequency rotor inertia equation. The magnitude of the virtual moment of inertia J determines the strength of the inertial support. The larger the value, the greater the inertia of frequency changes, and the better the buffering effect on power fluctuations, but the longer the frequency recovery time; damping coefficient The magnitude determines the oscillation suppression capability: The larger the value, the faster the frequency recovery and the smaller the overshoot, but the steady-state frequency deviation may increase. Finally, the active power frequency control sub-loop continuously performs the above calculations in each control cycle and outputs the frequency reference value in real time. and voltage phase reference value These reference values ​​are used, on the one hand, for the synchronous modulation of the grid-connected inverter (ensuring that the inverter output is synchronized with the grid), and on the other hand, as the phase input for the Park transformation in the sliding mode control sub-loop, so that the entire VSG-sliding mode cooperative control is established in a unified rotating coordinate system.

[0046] By simulating the rotor inertia and damping characteristics of a synchronous generator using the active-frequency rotor inertia equation, the photovoltaic inverter acquires frequency regulation capabilities similar to those of a synchronous generator. The virtual moment of inertia provides virtual inertia support for the microgrid, and by releasing or absorbing rotor kinetic energy (simulated value) during load abrupt changes, it buffers power imbalances, effectively suppressing frequency abrupt changes and oscillations, and achieving a significant improvement in the frequency stability of the microgrid.

[0047] In this embodiment, the third-order virtual synchronous machine mathematical model adds an excitation dynamic equation to the second-order model: The transient voltage output equation is: ;in, The time constant of the excitation winding is... For d-axis synchronous reactance, For d-axis transient reactance, For q-axis synchronous reactance, For q-axis transient reactance, and These are the d-axis and q-axis components of the inverter output voltage, respectively. This is the transient excitation electromotive force. The magnetizing electromotive force. , These are the d-axis and q-axis components of the inverter output voltage. , These are the d-axis equivalent resistance and the q-axis equivalent resistance, respectively.

[0048] In one possible implementation, firstly, the excitation dynamic equation is established: This equation describes the transient excitation electromotive force. (That is, the dynamic process of the state variable reflecting the energy of the internal magnetic field of the inverter during transient processes) changing with time. The left side of the equation... Represents the rate of change of transient potential, where The time constant of the excitation winding when the stator winding is open-circuited determines the transient potential. Response speed The larger, The slower the change, the longer the transient process lasts. The right side of the equation consists of three parts: The excitation electromotive force is the externally applied excitation control input, which serves as the output of the sliding mode control sub-loop in this invention. The transient excitation electromotive force itself, its existence makes It exhibits a self-decaying trend; The armature reaction term reflects the influence of the stator current on the excitation magnetic field, in which... The d-axis synchronous reactance (affects the distribution of reactive power in steady state). It is the d-axis transient reactance (reflecting the equivalent impedance of the d-axis during the transient process). The d-axis stator current is obtained by converting the three-phase current through the Park transformation, that is, converting the AC quantity in the three-phase stationary coordinate system into the DC quantity in the two-phase rotating coordinate system. Next, the transient voltage output equation is established: The transient voltage equation describes the relationship between the transient electromotive force inside the inverter and the terminal voltage. , These represent the d-axis and q-axis components of the inverter output voltage. Next, the role of the third-order model in the overall control is explained. A virtual rotor angular velocity has already been generated in the active frequency control sub-loop. and voltage phase reference value Based on this, Park transformation is performed on the acquired three-phase voltage and current using phase θ to obtain the d-axis and q-axis components, respectively. The excitation dynamic equation in the third-order model describes the excitation dynamics from the control input. To the controlled quantity The dynamic link (first-order inertial element) between them is described by the transient voltage equation. End-to-end voltage , The relationship between the two equations. Together, they constitute the "control input". -transient potential Terminal voltage , The complete dynamic model provides a precise controlled object for the sliding mode control sub-loop. Then, the advantages of the third-order model compared to the second-order model are analyzed. The second-order model simplifies the excitation process to... The algebraic relationship assumes that the transient potential can instantaneously follow the change in control input, which is relevant in the time constant. The approximation holds true in smaller cases, but under large disturbance conditions (where the change in E' during the transient process cannot be ignored), this simplification leads to model mismatch. The third-order model, by introducing the excitation dynamic equation, fully preserves the first-order inertial characteristics of the transient potential, allowing the controller design to fully consider the time delay effect of the excitation winding and improving the accuracy of voltage control under large disturbance conditions.

[0049] By introducing excitation dynamic equations into the mathematical model of a third-order virtual synchronous machine, the dynamic change process of transient excitation electromotive force is fully described, overcoming the deficiency of traditional second-order models that neglect transient effects of the excitation winding. A precise relationship between internal potential and terminal voltage is established through transient voltage output equations, providing an accurate controlled object model for the design of subsequent sliding mode control sub-loops and achieving a significant improvement in voltage control accuracy.

[0050] In this embodiment of the application, in step S3, the sliding mode control sub-loop adopts an integral sliding surface: ;in, For sliding surface, For voltage tracking error, This is the integral gain coefficient. , For the desired voltage, For reference voltage, The variable is the integral variable; the control law of the sliding mode control sub-loop adopts an equivalent control plus switching control structure: ;in, For sliding mode control law, For equivalent control quantity, To switch the control quantity; let the derivative of the sliding surface... Ignoring disturbances, the equivalent control quantity is solved using the aforementioned excitation dynamic equation: ;in for The first derivative, due to Since is a constant, its derivative is 0. Combining this with the third-order model, we get: ;in, for Substituting the first derivative into the sliding surface, we obtain the equivalent control quantity after simplification: The superspiral algorithm is adopted, and the switching control quantity is: ;in, To approximate the speed gain, a larger value results in stronger system disturbance rejection, but an excessively large value will exacerbate chattering. Let be the square root of the absolute value of the sliding surface, and let be the nonlinear term that causes the sliding variable to converge in a finite time. For symbolic functions, The integral suppression gain is used to reduce chattering and compensate for uncertainties, parameter variations, and external disturbances in the system. The variable is the integral variable; the final control law is: The final control law is substituted into the excitation dynamic equation as the excitation electromotive force to solve for the transient excitation electromotive force. This transient excitation electromotive force is then used as a voltage amplitude reference value to achieve dynamic control of the output voltage. The voltage phase reference value is calculated using the following formula: ;in, For the Laplace operator, This is the damping coefficient, used to suppress power oscillations. For power deviation, The final control law is substituted into the excitation dynamic equation as the excitation electromotive force to solve the transient excitation electromotive force. The transient excitation electromotive force is then used as the voltage amplitude reference value to achieve dynamic control of the output voltage.

[0051] In one possible implementation, firstly, an integral sliding surface is designed. The voltage tracking error is then defined. ,in This is the q-axis transient potential (as a given voltage command, i.e., the desired internal potential of the inverter). This is the reference value for the terminal voltage (i.e., the value of the actual sampled voltage after per-unit processing, representing the actual output voltage state). Constructing an integral sliding mode surface: ,in This is the integral gain coefficient. The variable is the integral variable. Next, the overall structure of the control law is designed. The control law for the sliding mode control sub-loop adopts the classic structure of equivalent control plus switching control: .in This is the sliding mode control law (i.e., the final output of the sliding mode controller). For equivalent control components, To switch control components, the equivalent control quantity is then derived. Let the derivative of the sliding surface... Ignoring external disturbances, and combining the excitation dynamic equations of the third-order model, we obtain... Substituting this equation into... In, that is Solve That is, the equivalent control quantity is obtained: The equivalent control quantity consists of three parts: This is the current value of the transient potential (feedforward compensation term). This is a compensation term for armature reaction. This is a feedback correction term based on voltage tracking error. Then, a switching control quantity is designed using a superspiral algorithm. The switching control quantity is designed as follows: .in To approximate the velocity gain, the system state is determined to tend towards the velocity of the sliding surface. The larger the value, the faster the approach and the stronger the anti-interference ability, but if it is too large, it will aggravate chattering; The square root of the absolute value of the sliding surface, this nonlinear term has the following effect: when When the value is large (the system state is far from the sliding surface). It is also relatively large, providing a faster approach speed; when When approaching zero (the system state is close to the sliding surface). As the variable approaches zero, the approach speed automatically decreases, achieving the effect of "rapid approach at a distance and smooth convergence at a close distance," ensuring that the sliding mode variable converges to zero within a finite time. For a sign function, when Take +1, Take -1 at time; The integral suppression gain is used to reduce chattering and compensate for uncertainties, parameter variations, and external disturbances in the system. Let be the integral variable. Finally, by combining the equivalent control and the switching control, the final excitation electromotive force control law is obtained: The final control law is used as the excitation electromotive force. Substituting the excitation dynamic equations into the third-order model The transient excitation electromotive force is solved by numerical integration methods (such as the Euler method or the Runge-Kutta method). The next instant value. The obtained transient excitation electromotive force E' is used as the voltage amplitude reference value and output to the subsequent voltage and current dual closed-loop control system to complete the transmission from the voltage stability control target to the inverter modulation signal.

[0052] By eliminating the steady-state error of voltage control through an integral sliding surface, zero steady-state error of voltage tracking is achieved. The continuous control signal of the super-spiral approach law effectively weakens the chattering phenomenon of traditional sliding mode control, avoiding damage to inverter switching devices and impact on grid-connected power quality caused by discontinuous control signals. Through the synergy of equivalent control and switching control, accurate feedforward compensation is provided for the known part of the model, while the discontinuous characteristics of switching control are used to resist model uncertainty and external disturbances, achieving a balance between speed, accuracy and robustness of voltage control.

[0053] Example 2:

[0054] Reference Figure 8This application also provides a voltage stability control system for a photovoltaic-sliding mode microgrid based on virtual synchronous machine-sliding mode cooperative control, comprising: a photovoltaic array, a boost converter, a maximum power point tracking controller, a hybrid energy storage system, a grid-connected inverter, and a VSG-sliding mode cooperative controller; the output terminal of the photovoltaic array is connected to the input terminal of the boost converter, and the output terminal of the boost converter is connected to the DC bus; the input terminal of the maximum power point tracking controller collects the output voltage and output current of the photovoltaic array, and the output terminal of the maximum power point tracking controller is connected to the control terminal of the boost converter, for outputting a duty cycle control signal based on the perturbation-observation method; the hybrid energy storage system includes a battery, a first bidirectional DC / DC converter, a supercapacitor, and a second bidirectional DC / DC converter; the battery is connected to the DC bus through the first bidirectional DC / DC converter, and the supercapacitor... The stage capacitor is connected to the DC bus through the second bidirectional DC / DC converter; the DC side of the grid-connected inverter is connected to the DC bus, and the AC side is connected to the power grid; the signal input terminal of the VSG-sliding mode co-controller collects the output voltage, output current, and DC bus voltage of the grid-connected inverter, and the control output terminal of the VSG-sliding mode co-controller is connected to the control terminal of the grid-connected inverter; the VSG-sliding mode co-controller includes an active frequency control module and a sliding mode control module; the active frequency control module generates frequency and voltage phase reference values ​​based on the active-frequency rotor inertia equation; the sliding mode control module generates voltage amplitude reference values ​​based on the third-order virtual synchronous machine mathematical model, integral sliding surface, and superspiral reaching law, and replaces the reactive voltage link of the traditional virtual synchronous machine; the frequency and voltage phase reference values ​​and the voltage amplitude reference values ​​are synthesized and then used for voltage and current dual closed-loop control to generate the modulation voltage signal of the grid-connected inverter.

[0055] In one possible embodiment, firstly, the output of the photovoltaic array is connected to the input of the Boost converter circuit. The photovoltaic array consists of multiple photovoltaic modules connected in series and parallel, and its output DC voltage varies with light intensity and temperature. The output of the Boost converter circuit is connected to the DC bus, boosting the lower DC voltage output by the photovoltaic array to the voltage level required by the DC bus. The Boost circuit also acts as the actuator of the maximum power point tracking (MPPT) stage, indirectly controlling the operating voltage of the photovoltaic array by adjusting the duty cycle of its switching transistors. Secondly, the input of the MPPT controller collects the output voltage and current of the photovoltaic array through voltage and current sensors, and its output is connected to the control terminal (i.e., the PWM drive port) of the Boost converter circuit. The MPPT controller, based on the perturbation observation method, outputs a duty cycle control signal according to the changing trends of power and voltage, adjusting the conduction ratio of the Boost converter's switching transistors to ensure that the photovoltaic array always operates at the maximum power point under the current environmental conditions. Next, the hybrid energy storage system includes four sub-components: a battery, a first bidirectional DC / DC converter, a supercapacitor, and a second bidirectional DC / DC converter. The battery is connected to the DC bus via a first bidirectional DC / DC converter, and the supercapacitor is connected to the same DC bus via a second bidirectional DC / DC converter. Two energy storage branches are connected in parallel on the DC bus. The battery branch is responsible for smoothing low-frequency, slowly changing power fluctuations (such as gradual changes in light intensity or load variation), while the supercapacitor branch is responsible for smoothing high-frequency, instantaneous power surges (such as sudden load shedding or fault events). The DC side of the grid-connected inverter is then connected to the DC bus, and the AC side is connected to the grid via an LC filter. The signal input of the VSG-sliding mode co-controller collects the output voltage (three-phase AC voltage), output current (three-phase AC current), and DC bus voltage of the grid-connected inverter through voltage transformers, current transformers, and voltage sensors. The control output of the VSG-sliding mode co-controller is connected to the PWM drive port of the grid-connected inverter, outputting a modulation signal to control the turn-on timing of the inverter's switching transistors. The VSG-sliding mode co-controller comprises two core functional modules: an active power frequency control module, which calculates the virtual rotor angular velocity and voltage phase reference values ​​based on the active power-frequency rotor inertia equation and the detected output power and a set active power reference value; and a sliding mode control module, which calculates the voltage amplitude reference value based on a third-order virtual synchronous machine mathematical model, an integral sliding surface, and a superspiral reaching law, completely replacing the reactive power-voltage link in a traditional virtual synchronous machine. The frequency and phase reference values ​​output from the active power frequency control module are combined with the voltage amplitude reference value output from the sliding mode control module, and then used to generate a PWM modulation signal via voltage and current dual closed-loop control to drive the grid-connected inverter.Finally, the entire system's workflow is as follows: the MPPT controller continuously adjusts the photovoltaic array to operate at its maximum power point - the hybrid energy storage system gradually smooths out power fluctuations to maintain DC bus voltage stability - the VSG-sliding mode co-controller calculates frequency, phase, and voltage amplitude reference values ​​in real time - the dual closed-loop control generates modulation signals to drive the inverter - the grid-connected output voltage and current reach a high-quality stable state.

[0056] The above system architecture achieves an organic integration of photovoltaic grid-connected power generation, hybrid energy storage, and VSG-sliding mode collaborative control. Each functional module has a clear division of labor and interconnections: the MPPT controller is responsible for maximizing photovoltaic energy harvesting, the hybrid energy storage system is responsible for graded smoothing of power fluctuations, and the VSG-sliding mode collaborative controller is responsible for stable voltage and frequency control. The sliding mode control module replaces the reactive power-voltage link of the traditional VSG, directly generating voltage amplitude reference values ​​based on a third-order model, improving the accuracy and robustness of transient voltage control, and realizing modular and high-reliability voltage stability control of the microgrid.

[0057] In this embodiment, both the first bidirectional DC / DC converter and the second bidirectional DC / DC converter are half-bridge bidirectional Buck-Boost converters; the control signal for the first bidirectional DC / DC converter is taken from the battery output power. With expected active power The difference is generated after PI regulation and PWM modulation; the control signal of the second bidirectional DC / DC converter is taken from the DC bus voltage deviation and generated after PI regulation and PWM modulation; the first bidirectional DC / DC converter charges the battery when it operates in Buck mode and discharges the battery when it operates in Boost mode; the second bidirectional DC / DC converter charges the supercapacitor when it operates in Buck mode and discharges the supercapacitor when it operates in Boost mode.

[0058] In one possible embodiment, both the first and second bidirectional DC / DC converters employ a half-bridge bidirectional Buck-Boost converter topology. The half-bridge bidirectional Buck-Boost converter is a basic bidirectional DC / DC converter topology, comprising two switching transistors (IGBTs or MOSFETs) with anti-parallel diodes, forming the upper and lower arms of the half-bridge structure, respectively. An energy storage element is connected between the midpoint of the half-bridge and one side of the DC bus. By controlling the complementary conduction of the two switching transistors, bidirectional energy flow can be achieved: when the upper transistor is on and the lower transistor is off, current flows from the DC bus through the upper transistor to the energy storage element; this is Buck mode (boost charging); when the lower transistor is on and the upper transistor is off, current flows from the energy storage element through the lower transistor to the DC bus; this is Boost mode (boost discharging). Compared to the traditional two independent unidirectional converter scheme, the half-bridge bidirectional topology only requires one set of bridge arms to achieve bidirectional energy flow, reducing the number of switching devices and the complexity of the drive circuit. Secondly, the control signal generation process of the first bidirectional DC / DC converter involves: acquiring the voltage and current of the battery branch and calculating the battery output power. .Will With expected active power The power deviation is obtained by subtracting the expected output power of the battery set by the system based on power balance requirements. The power deviation is input to a PI controller for proportional-integral (PI) calculation, and the PI controller outputs a normalized control quantity. This control quantity is then modulated using PWM (with a triangular wave as the carrier wave) to generate the duty cycle signal for the first bidirectional DC / DC converter. When When the battery output power is too high, the power deviation is positive, the PI regulator shifts the duty cycle towards Buck mode, and the battery absorbs energy from the bus to charge; when When the battery output power is insufficient, the power deviation is negative. The PI regulator shifts the duty cycle towards Boost mode, and the battery discharges energy to the bus. Next, the control signal generation process for the second bidirectional DC / DC converter: unlike the battery branch which uses power control, the supercapacitor branch uses a voltage control strategy. The DC bus voltage is acquired, and the bus voltage deviation is calculated. (That is, the difference between the actual bus voltage and the rated bus voltage). The voltage deviation is input to the PI regulator, which outputs a normalized control quantity, which is then modulated by PWM to generate the duty cycle signal of the second bidirectional DC / DC converter. When When the bus voltage is low and the system power is insufficient, the voltage deviation is negative. The PI regulator shifts the duty cycle towards Boost mode, and the supercapacitor discharges to the bus to replenish energy and support the bus voltage. When the bus voltage is high and the system power is excessive, the voltage deviation is positive, the duty cycle is biased towards Buck mode, and the supercapacitor absorbs excess energy from the bus to suppress the rise in bus voltage. Then, the automatic switching mechanism of the charging and discharging modes of the two branches is described. When the first bidirectional DC / DC converter operates in Buck mode, the battery absorbs energy from the DC bus to charge (occurring when photovoltaic power generation is excessive and load demand is low); when operating in Boost mode, the battery releases energy to the DC bus to discharge (occurring when photovoltaic power generation is insufficient and load demand is high). When the second bidirectional DC / DC converter operates in Buck mode, the supercapacitor absorbs energy from the DC bus to charge; when operating in Boost mode, the supercapacitor releases energy to the DC bus to discharge. The switching between the two modes is automatically determined by the output of their respective PI regulators, requiring no additional mode judgment logic or mode switching device, resulting in a simple and reliable control structure. Finally, the differentiated control strategies of the two branches reflect the functional division of labor in a hybrid energy storage system: the battery branch employs power point tracking (PTC) control (tracking the expected active power value), responsible for the overall power balance of the system and the smoothing of low-frequency slow-changing disturbances; the supercapacitor branch employs voltage stabilization control (maintaining the DC bus voltage near its rated value), responsible for rapid compensation of high-frequency instantaneous power disturbances and precise maintenance of the bus voltage. Each control strategy fulfills its specific function, avoiding control conflicts between the two branches.

[0059] By employing a half-bridge bidirectional Buck-Boost converter topology, only one bridge arm is needed to achieve bidirectional energy flow to the energy storage components. Compared to the traditional two independent unidirectional converter schemes, this reduces the number of switching devices and the complexity of the drive circuit, thereby lowering system cost and size. Through differentiated control strategies—power deviation PI control (battery branch) and voltage deviation PI control (supercapacitor branch)—the two energy storage branches each perform their respective functions: the battery branch handles power smoothing (tracking the power reference), while the supercapacitor branch handles voltage stabilization (maintaining the bus voltage). This avoids control conflicts and achieves efficient and coordinated management of the hybrid energy storage system.

[0060] In this embodiment, the sliding mode control module includes a sliding mode surface calculation unit, an equivalent control calculation unit, a super-helical switching control calculation unit, and an excitation electromotive force solution unit; the sliding mode surface calculation unit calculates the sliding mode surface based on the voltage tracking error and the integral gain coefficient, and its expression is: ;in, For sliding surface, For voltage tracking error, This is the integral gain coefficient. , For the desired voltage, For reference voltage, For time; the equivalent calculation unit calculates the equivalent control quantity based on the excitation dynamic equation parameters, and its expression is: ;in, For equivalent control quantity, The time constant of the excitation winding is... The transient excitation electromotive force is used; the super-spiral switching control calculation unit calculates the switching control quantity based on the approach velocity gain and integral suppression gain, and its expression is: ;in, To switch control quantities, To approximate the speed gain, a larger value results in stronger system disturbance rejection, but an excessively large value will exacerbate chattering. Let be the square root of the absolute value of the sliding surface, and let be the nonlinear term that causes the sliding variable to converge in a finite time. For symbolic functions, The integral suppression gain is used to reduce chattering and compensate for uncertainties, parameter variations, and external disturbances in the system. The integral variable is used; the excitation electromotive force solving unit takes the sum of the equivalent control quantity and the switching control quantity as the excitation electromotive force, and substitutes it into the excitation dynamic equation to solve the transient excitation electromotive force, which is output as a voltage amplitude reference value.

[0061] The optional embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the embodiments of the present invention are not limited to the specific details in the above embodiments. Within the scope of the technical concept of the embodiments of the present invention, various simple modifications can be made to the technical solutions of the embodiments of the present invention, and these simple modifications all fall within the protection scope of the embodiments of the present invention.

[0062] It should also be noted that the various specific technical features described in the above embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the embodiments of the present invention will not describe the various possible combinations separately.

[0063] Furthermore, various different implementations of the present invention can be combined arbitrarily, as long as they do not violate the spirit of the present invention, they should also be regarded as the content disclosed in the present invention.

Claims

1. A voltage stability control method for a photovoltaic-storage microgrid based on virtual synchronous machine-sliding mode cooperative control, characterized in that, include: S1. The output of the photovoltaic array is boosted by the Boost circuit, and the duty cycle is adjusted by the maximum power point tracking stage based on the perturbation observation method to make the photovoltaic array work at the maximum power point. The output terminals of the S2 and Boost circuits are connected to a hybrid energy storage system consisting of a battery and a supercapacitor. The battery is connected to the DC bus via the first bidirectional DC / DC converter to smooth out low-frequency slow-changing disturbances. The supercapacitor is connected to the DC bus via the second bidirectional DC / DC converter to smooth out high-frequency instantaneous disturbances. S3. DC bus power is converted into AC power by grid-connected inverter and connected to the grid. The grid-connected inverter is controlled by a virtual synchronous machine and sliding mode control link. The active frequency control sub-link of this link generates frequency and phase reference values ​​based on the rotor inertia equation. The sliding mode control sub-link generates voltage amplitude reference values ​​based on the third-order virtual synchronous machine model, integral sliding surface and super-helical approach law, replacing the traditional reactive voltage link. S4. Combine the frequency phase reference value and the voltage amplitude reference value into an inverter voltage command, and generate a modulation signal through a voltage and current dual closed loop to drive the grid-connected inverter.

2. The voltage stability control method for photovoltaic-storage microgrids based on virtual synchronous machine-sliding mode cooperative control according to claim 1, characterized in that, In S1, the perturbation observation method includes: Real-time detection of photovoltaic array output voltage and output current And calculate the real-time output power of the photovoltaic array. ; Output power at the current sampling time Output power at the previous sampling time Compare the output voltage at the current sampling time. Output voltage at the previous sampling time Based on the comparison, adjust the duty cycle according to the following logic: when and At that time, if Then the duty cycle increases positively: ;like Then the duty cycle decreases in the opposite direction: ; when and At that time, if Then the duty cycle decreases in the opposite direction: ;like Then the duty cycle increases positively: ; when At this time, the duty cycle remains unchanged: ; in, Let be the output voltage of the photovoltaic array at the k-th sampling time. Let be the output current of the photovoltaic array at the k-th sampling time. Let be the output power of the photovoltaic array at the k-th sampling time. The output voltage of the photovoltaic array at the (k-1)th sampling time is... Let be the output power of the photovoltaic array at the (k-1)th sampling time. The reference voltage at the k-th sampling time. Let be the reference voltage at the (k-1)th sampling time. The voltage is varied in fixed steps.

3. The voltage stability control method for photovoltaic-storage microgrids based on virtual synchronous machine-sliding mode cooperative control according to claim 1, characterized in that, In step S2, the power balance relationship of the hybrid energy storage system is as follows: ； in, For the output power of the photovoltaic array, For the output power of the storage battery, This refers to the output power of the supercapacitor. Power loss is caused by line resistance and parasitic resistance. This refers to the inverter's output power. The total power that the hybrid energy storage system needs to mitigate is: ； in, Power to be mitigated in hybrid energy storage systems; The battery branch acquires the DC bus voltage and current values, and uses the voltage and current conversion of the first bidirectional DC / DC converter to obtain the battery branch voltage and current values, thereby calculating the battery output power. and will Compared with the preset expected active power value The difference is calculated and input into the PI controller, and then the modulation signal of the first bidirectional DC / DC converter is obtained through PWM calculation, so as to suppress low-frequency, slow-changing disturbances. The supercapacitor branch collects the DC bus voltage and current values, and calculates the voltage and current values ​​of the supercapacitor branch through the voltage and current conversion of the second bidirectional DC / DC converter. The DC bus voltage deviation is used as the control target, and the modulation signal of the second bidirectional DC / DC converter is calculated by the PI controller and PWM to achieve the smoothing of high-frequency, instantaneous power disturbances. The first bidirectional DC / DC converter and the second bidirectional DC / DC converter operate in Buck mode and Boost mode, respectively: in Buck mode, energy flows from the DC bus to the energy storage element, and in Boost mode, energy flows from the energy storage element to the DC bus.

4. The voltage stability control method for photovoltaic-storage microgrids based on virtual synchronous machine-sliding mode cooperative control according to claim 1, characterized in that, In step S3, the active frequency control sub-loop is based on the active-frequency rotor inertia equation: ； in, For virtual rotational inertia, The damping coefficient is... For virtual rotor angular velocity, This is the preset active power reference value. To output electromagnetic power to the inverter, The angular velocity of the power grid; The angular velocity was calculated using the active-frequency rotor inertia equation. and voltage phase reference value The virtual moment of inertia The photovoltaic inverter simulates the rotor inertial response of a synchronous generator, wherein the damping coefficient Provides damping support to the system to suppress power oscillations.

5. The voltage stability control method for photovoltaic-storage microgrids based on virtual synchronous machine-sliding mode cooperative control according to claim 1, characterized in that, In step S3, the third-order virtual synchronous machine mathematical model adds excitation dynamic equations to the second-order model: ； The transient voltage output equation is: ； in, The time constant of the excitation winding is... For d-axis synchronous reactance, For d-axis transient reactance, For q-axis synchronous reactance, For q-axis transient reactance, and These are the d-axis and q-axis components of the inverter output voltage, respectively. This is the transient excitation electromotive force. The magnetizing electromotive force. , These are the d-axis and q-axis components of the inverter output voltage. , These are the d-axis equivalent resistance and the q-axis equivalent resistance, respectively.

6. The voltage stability control method for photovoltaic-storage microgrids based on virtual synchronous machine-sliding mode cooperative control according to claim 5, characterized in that, In step S3, the sliding mode control sub-loop adopts an integral sliding surface: ； in, For sliding surface, For voltage tracking error, This is the integral gain coefficient. , For the desired voltage, For reference voltage, For time; The control law of the sliding mode control sub-module adopts an equivalent control plus switching control structure: ； in, For sliding mode control law, For equivalent control quantity, To switch control quantities; Let the derivative of the sliding surface Ignoring disturbances, the equivalent control quantity is solved using the aforementioned excitation dynamic equation: ;in for The first derivative, due to Since is a constant, its derivative is 0. Combining this with the third-order model, we get: ;in, for The first derivative, Substituting the sliding surface, the simplified equivalent control quantity is obtained: ； Using the superspiral algorithm, the switching control quantity is: ； in, To approximate the speed gain, a larger value results in stronger system disturbance rejection, but an excessively large value will exacerbate chattering. Let be the square root of the absolute value of the sliding surface, and let be the nonlinear term that causes the sliding variable to converge in a finite time. For symbolic functions, The integral suppression gain is used to reduce chattering and compensate for uncertainties, parameter variations, and external disturbances in the system. For integration variables; The final control law is: ;in, The voltage phase reference value is calculated using the following formula: ;in, For the Laplace operator, This is the damping coefficient, used to suppress power oscillations. For power deviation, ; The final control law is substituted into the excitation dynamic equation as the excitation electromotive force to solve the transient excitation electromotive force. The transient excitation electromotive force is then used as the voltage amplitude reference value to achieve dynamic control of the output voltage.

7. A voltage stability control system for a photovoltaic-storage microgrid based on virtual synchronous machine-sliding mode cooperative control, characterized in that, The method for voltage stability control of a photovoltaic-storage microgrid based on virtual synchronous machine-sliding mode cooperative control as described in any one of claims 1 to 6 includes: Photovoltaic arrays, boost converters, maximum power point tracking controllers, hybrid energy storage systems, grid-connected inverters, and VSG-sliding mode co-controllers; The output terminal of the photovoltaic array is connected to the input terminal of the Boost circuit, and the output terminal of the Boost circuit is connected to the DC bus; the input terminal of the maximum power point tracking controller collects the output voltage and output current of the photovoltaic array, and the output terminal of the maximum power point tracking controller is connected to the control terminal of the Boost circuit, for outputting a duty cycle control signal based on the perturbation observation method; The hybrid energy storage system includes a battery, a first bidirectional DC / DC converter, a supercapacitor, and a second bidirectional DC / DC converter; the battery is connected to a DC bus through the first bidirectional DC / DC converter, and the supercapacitor is connected to the DC bus through the second bidirectional DC / DC converter. The DC side of the grid-connected inverter is connected to the DC bus, and the AC side is connected to the power grid; the signal input terminal of the VSG-sliding mode co-controller collects the output voltage, output current and DC bus voltage of the grid-connected inverter, and the control output terminal of the VSG-sliding mode co-controller is connected to the control terminal of the grid-connected inverter; The VSG-sliding mode co-controller includes an active frequency control module and a sliding mode control module. The active frequency control module generates frequency and voltage phase reference values ​​based on the active-frequency rotor inertia equation. The sliding mode control module generates voltage amplitude reference values ​​based on a third-order virtual synchronous machine mathematical model, an integral sliding surface, and a super-spiral reaching law, replacing the reactive voltage link of the traditional virtual synchronous machine. The frequency and voltage phase reference values ​​are combined with the voltage amplitude reference values ​​and then used for voltage and current dual closed-loop control to generate the modulation voltage signal for the grid-connected inverter.

8. The photovoltaic-storage microgrid voltage stability control system based on virtual synchronous machine-sliding mode cooperative control according to claim 7, characterized in that, Both the first and second bidirectional DC / DC converters are half-bridge bidirectional Buck-Boost converters; the control signal for the first bidirectional DC / DC converter is taken from the battery output power. With expected active power The difference is generated after PI regulation and PWM modulation; the control signal of the second bidirectional DC / DC converter is taken from the DC bus voltage deviation and generated after PI regulation and PWM modulation; the first bidirectional DC / DC converter charges the battery when it operates in Buck mode and discharges the battery when it operates in Boost mode; the second bidirectional DC / DC converter charges the supercapacitor when it operates in Buck mode and discharges the supercapacitor when it operates in Boost mode.

9. The photovoltaic-storage microgrid voltage stability control system based on virtual synchronous machine-sliding mode cooperative control according to claim 7, characterized in that, The sliding mode control module includes a sliding mode surface calculation unit, an equivalent control calculation unit, a super-helical switching control calculation unit, and an excitation electromotive force solution unit. The sliding surface calculation unit calculates the sliding surface based on the voltage tracking error and the integral gain coefficient, and its expression is as follows: ;in, For sliding surface, For voltage tracking error, This is the integral gain coefficient. , For the desired voltage, For reference voltage, For time; The equivalent calculation unit calculates the equivalent control quantity based on the parameters of the excitation dynamic equation, and its expression is: ;in, For equivalent control quantity, The time constant of the excitation winding is... This is the transient excitation electromotive force; The superspiral switching control calculation unit calculates the switching control quantity based on the approach velocity gain and integral suppression gain, and its expression is as follows: ;in, To switch control quantities, To approximate the speed gain, a larger value results in stronger system disturbance rejection, but an excessively large value will exacerbate chattering. Let be the square root of the absolute value of the sliding surface, and let be the nonlinear term that causes the sliding variable to converge in a finite time. For symbolic functions, The integral suppression gain is used to reduce chattering and compensate for uncertainties, parameter variations, and external disturbances in the system. For integration variables; The excitation electromotive force (EMF) solving unit takes the sum of the equivalent control quantity and the switching control quantity as the excitation EMF, and substitutes it into the excitation dynamic equation to solve the transient excitation EMF. The transient excitation EMF is output as a voltage amplitude reference value.

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