A method for coordinated control of energy storage voltage stabilization and VSG network construction in a light storage grid-connected system

Abstract

The application discloses a kind of energy storage voltage stabilization and VSG network configuration collaborative control methods of light storage grid-connected system, and relates to light storage operation control technical field, and its technical solution points include the following specific steps: according to the system operating parameter of monitoring unit acquisition, construct the parallel collaborative closed loop architecture of hybrid energy storage and grid-connected side VSG control;Based on the difference of energy storage side to photovoltaic output and load power power frequency, the power component of different frequency is obtained, and the power component of different frequency is distributed to each energy storage unit of hybrid energy storage;The distribution result of power component is balancedly modified in combination with the state of charge of each energy storage unit, and the modified power instruction is obtained, the method can dynamically adjust adaptive weight coefficient according to system working condition, improve current tracking accuracy, stabilize DC bus voltage, effectively avoid system power oscillation, circulating current and other faults, so as to significantly improve the safety of light storage system grid-connected operation.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic-storage grid-connected operation control technology, and more specifically, to a method for coordinated control of energy storage voltage stabilization and VSG grid construction in a photovoltaic-storage grid-connected system. Background Technology

[0002] As the global energy structure shifts towards cleaner and lower-carbon energy, new energy power generation technologies such as photovoltaics have been widely promoted and applied, becoming a core support for alleviating the energy crisis and reducing carbon emissions. However, photovoltaic power output has significant randomness, volatility, and intermittency. Its large-scale grid connection can severely impact the voltage and frequency stability of the power grid, leading to increased grid dispatching difficulties, decreased power supply reliability, and even safety hazards such as power oscillations and equipment damage, seriously restricting the absorption and grid connection quality of new energy.

[0003] However, in existing photovoltaic-storage grid-connected systems, the hybrid energy storage control and VSG grid-connection control operate completely independently and in isolation, with no data interaction or collaborative linkage mechanism between them. Photovoltaics, hybrid energy storage, and VSG each operate according to their own fixed control logic, failing to form a unified collaborative control architecture. The power distribution and SOC balancing control of hybrid energy storage are not combined with the grid-connection requirements of VSG, leading to severe voltage and frequency fluctuations in weak grid or off-grid conditions, easily causing power oscillations and circulating currents, seriously affecting grid-connection safety. Furthermore, the virtual inertia and damping adjustment of VSG are not adapted to the SOC state of hybrid energy storage, easily causing overcharging and over-discharging of energy storage units, shortening equipment lifespan and increasing operation and maintenance costs. Simultaneously, photovoltaics and hybrid energy storage are connected to the grid separately through converters, not only increasing equipment costs but also easily generating circulating current losses. Moreover, without any supporting collaborative control strategies, the respective advantages of hybrid energy storage and VSG cannot be fully utilized, resulting in extremely poor overall operational stability, robustness, and engineering adaptability, making it difficult to meet the engineering requirements of high stability, high robustness, and long equipment lifespan for new energy grid connection. Summary of the Invention

[0004] To address the shortcomings of existing technologies, the present invention aims to provide a method for coordinated control of energy storage voltage stabilization and VSG network construction in a photovoltaic-storage grid-connected system.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A method for coordinated control of energy storage voltage stabilization and VSG grid construction in a photovoltaic-storage grid-connected system, the method comprising the following specific steps:

[0007] Based on the system operating parameters collected by the monitoring unit, a parallel and collaborative closed-loop architecture for hybrid energy storage and grid-connected VSG control is constructed.

[0008] Based on the power frequency division of the difference between photovoltaic output and load power on the energy storage side, power components of different frequencies are obtained, and the power components of different frequencies are distributed to each energy storage unit of the hybrid energy storage.

[0009] The power component allocation results are balanced and corrected by combining the state of charge of each energy storage unit to obtain the corrected power command.

[0010] The voltage deviation of the DC bus introduced by the voltage regulation control is processed to obtain the voltage compensation amount. Based on the voltage and current dual closed-loop control, the bidirectional DC / DC converter of the voltage compensation amount in the hybrid energy storage is driven to generate grid-connected control commands.

[0011] The grid-connected side VSG controller receives grid-connected control commands and adjusts the virtual inertia and damping coefficients according to the grid-connected control commands to obtain grid support and grid-connected / off-grid switching.

[0012] The execution status of the grid-connected side is fed back to the energy storage side, and the grid-connected control command is iteratively optimized to form a closed-loop control system with guidance from the energy storage side, execution from the VSG side, status feedback, and optimization guidance.

[0013] Preferably, the system operating parameters include photovoltaic output, load power, state of charge of each energy storage unit, DC bus voltage, grid voltage and frequency;

[0014] Hybrid energy storage includes batteries as energy-type energy storage units and supercapacitors as power-type energy storage units;

[0015] The grid-connected VSG control commands include total active power commands, reactive power commands, DC bus voltage reference values, and grid-connected / off-grid mode commands.

[0016] The total active power is formed by summarizing the corrected power commands.

[0017] Preferably, the power frequency division decomposes the total smoothing power into low-frequency components and high-frequency components according to the filtering algorithm, and the low-frequency components and high-frequency components are power components of different frequencies.

[0018] Distribute low-frequency components to the battery and high-frequency components to the supercapacitor;

[0019] The filtering algorithms are first-order low-pass filtering, wavelet packet decomposition, moving average filtering, or empirical mode decomposition.

[0020] Preferably, the equalization correction includes:

[0021] Calculate the average state of charge (SOC) of all energy storage units:

[0022] ;

[0023] in, To collect the real-time SOC of each energy storage unit for the i-th energy storage unit,

[0024] Based on the State of Charge (SOC) of each energy storage unit i With SOC ave The difference ΔSOC is used to dynamically adjust the droop coefficient of each energy storage unit through a nonlinear function, resulting in the adjusted droop coefficient. Simultaneously, based on the imbalance of the state of charge of all energy storage units, the calculation formula is as follows:

[0025] ;

[0026] The equalization factor ρ is adaptively adjusted, and the power component allocation result is corrected based on the adjusted droop coefficient and the adaptive equalization factor ρ to obtain the corrected power command.

[0027] The expression for the adaptive SOC equilibrium factor ρ is:

[0028] ;

[0029] in, Equilibrium factor The initial reference value; This is the adjustment coefficient, which takes a positive value and is used for regulation. The growth rate, and The smaller, The faster the growth rate.

[0030] Preferably, the nonlinear function is an exponential-hyperbolic tangent mixture function, and the adjusted droop coefficient R i The expression is:

[0031] ;

[0032] ;

[0033] in, Output current to the energy storage unit. It is in discharge state at the time. It is currently in charging mode. It is an acceleration factor used to widen the difference in droop coefficients and increase the balancing rate.

[0034] Preferably, the voltage compensation amount is calculated based on the deviation between the real-time DC bus voltage and the rated reference value, according to linear active disturbance rejection control, sliding mode control, nonlinear active disturbance rejection control, or control algorithm based on disturbance observer, and is used to offset the voltage deviation introduced by droop control and power fluctuation; the voltage compensation amount is superimposed on the voltage regulation control target and then input to the voltage and current dual closed-loop control.

[0035] Preferably, based on PI control or fuzzy PI control, the control target and voltage compensation amount of the outer loop voltage regulation in the voltage and current dual closed-loop control are received, and the current reference value is output.

[0036] Based on improved model predictive control, model predictive current control, or PI control, the current reference value of the inner current loop is received, and grid-connected control commands are generated by rapidly tracking the current using adaptive weighting coefficients.

[0037] Preferably, based on the three-step prediction strategy, the current tracking weight 'a' and the voltage stability weight 'β' are set to obtain the improved model predictive control.

[0038] The adaptive weighting coefficient is dynamically adjusted based on the system's operating status to optimize the tracking accuracy of the current reference value.

[0039] Preferably, adaptive adjustment of virtual inertia and damping coefficient includes:

[0040] Adjust the virtual inertia J and damping coefficient D based on the intensity of photovoltaic power fluctuations and / or the state of charge of hybrid energy storage to determine the power demand in the grid-connected control command;

[0041] When power fluctuations are large or the state of charge is in an extreme range, increase the virtual inertia J to improve system stability.

[0042] When power fluctuations are small or the state of charge is within a safe range, the virtual inertia J is reduced to improve the response speed.

[0043] Preferably, the on-grid / off-grid switching is performed based on the voltage frequency provided by the VSG control unit;

[0044] The grid-connected VSG control is obtained based on the grid-connected and off-grid mode instructions in the grid-connected control instructions and the DC bus voltage reference value. The switching between grid-connected and off-grid is obtained by adjusting the internal voltage phase based on the VSG control.

[0045] The execution status of VSG control on the grid-connected side includes the adjusted grid voltage, frequency, and actual output power. This execution status is fed back to the energy storage side for iterative optimization.

[0046] Compared with existing technologies, this invention has the following advantages: By constructing a parallel and collaborative closed-loop architecture for hybrid energy storage and grid-connected VSG control, a two-way data interaction channel is established between the energy storage side and the VSG side. This facilitates a closed-loop linkage mechanism of energy storage side guidance, VSG side execution, status feedback, and iterative optimization, enabling unified and coordinated control of photovoltaics, hybrid energy storage, and VSG. This fully leverages the respective technical advantages of hybrid energy storage in smoothing power fluctuations and VSG in providing grid support for analog synchronization, significantly improving the overall system stability and control robustness. Furthermore, by performing power frequency division on the power difference between photovoltaics and the load, high and low frequency power components are matched and distributed to the battery and supercapacitor respectively, while simultaneously considering the load of each energy storage unit... The electrical state is balanced and corrected. The balancing factor is adaptively adjusted according to the degree of imbalance, and the energy storage droop coefficient is dynamically adjusted to achieve balanced control of the state of charge of the energy storage units. This effectively extends the service life of the energy storage equipment and reduces the later operation and maintenance costs of the system. The voltage compensation is solved by multiple anti-disturbance control algorithms to offset the DC bus voltage deviation caused by power distribution correction and power fluctuation. Then, through the dual closed-loop control of voltage outer loop and current inner loop, the current inner loop adopts a three-step long prediction improved model predictive control. The adaptive weight coefficient is dynamically adjusted according to the system operating conditions to improve the current tracking accuracy, stabilize the DC bus voltage, effectively avoid system power oscillation, circulating current and other faults, and significantly improve the grid-connected operation safety of the photovoltaic and energy storage system. Attached Figure Description

[0047] Figure 1 This is a schematic diagram of a method for coordinated control of energy storage voltage regulation and VSG grid construction in a photovoltaic-storage grid-connected system, provided in an embodiment of the present invention. Detailed Implementation

[0048] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0049] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways than those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0050] Secondly, the term "an embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places throughout this specification does not necessarily refer to the same embodiment, nor is it a single embodiment or an embodiment selectively excluded from other embodiments.

[0051] Reference Figure 1 As shown.

[0052] The following examples further illustrate the collaborative control method for energy storage voltage stabilization and VSG network construction in a photovoltaic-storage grid-connected system proposed in this invention.

[0053] A method for coordinated control of energy storage voltage stabilization and VSG grid construction in a photovoltaic-storage grid-connected system, the method comprising the following specific steps:

[0054] Based on the system operating parameters collected by the monitoring unit, a parallel and collaborative closed-loop architecture for hybrid energy storage and grid-connected VSG control is constructed.

[0055] Based on the power frequency division of the difference between photovoltaic output and load power on the energy storage side, power components of different frequencies are obtained, and the power components of different frequencies are distributed to each energy storage unit of the hybrid energy storage.

[0056] The power component allocation results are balanced and corrected by combining the state of charge of each energy storage unit to obtain the corrected power command.

[0057] The voltage deviation of the DC bus introduced by the voltage regulation control is processed to obtain the voltage compensation amount. Based on the voltage and current dual closed-loop control, the bidirectional DC / DC converter of the voltage compensation amount in the hybrid energy storage is driven to generate grid-connected control commands.

[0058] The grid-connected side VSG controller receives grid-connected control commands and adjusts the virtual inertia and damping coefficients according to the grid-connected control commands to obtain grid support and grid-connected / off-grid switching.

[0059] The execution status of the grid-connected side is fed back to the energy storage side, and the grid-connected control command is iteratively optimized to form a closed-loop control system with guidance from the energy storage side, execution from the VSG side, status feedback, and optimization guidance.

[0060] System operating parameters include photovoltaic output, load power, state of charge of each energy storage unit, DC bus voltage, grid voltage and frequency;

[0061] Hybrid energy storage includes batteries as energy-type energy storage units and supercapacitors as power-type energy storage units;

[0062] The grid-connected VSG control commands include total active power commands, reactive power commands, DC bus voltage reference values, and grid-connected / off-grid mode commands.

[0063] The total active power is formed by summarizing the corrected power commands.

[0064] Complete system operating parameters are collected according to the monitoring unit, wherein the collected parameters include photovoltaic output, load power, state of charge of each energy storage unit, DC bus voltage, grid voltage and frequency. A closed-loop architecture for parallel coordination of hybrid energy storage and grid-side VSG control is constructed based on all collected parameters. The hybrid energy storage is divided into two types of energy storage units: a storage battery is used as an energy-type energy storage unit, and a super capacitor is used as a power-type energy storage unit. The system completes power frequency division operation according to the difference between the photovoltaic output and the load power, splits to obtain power components of different frequencies, and then matches and distributes each power component to the corresponding energy storage units of the storage battery and the super capacitor.

[0065] After the distribution is completed, the system performs equilibrium correction operation on the power component distribution result in combination with the respective state of charge of the two types of energy storage units to obtain corrected power commands, and all corrected power commands are aggregated to form the total active power command required for grid-side VSG control. The equilibrium correction operation will cause DC bus voltage deviation. The system processes the voltage deviation by means of voltage stabilization control, solves and obtains a voltage compensation amount, drives the bidirectional DC / DC converter matched with the hybrid energy storage according to voltage and current double closed-loop control, and finally generates a complete set of grid-connected control commands required for grid-side VSG control. In addition to the aggregated total active power command, the complete set of grid-connected control commands also includes a reactive power command, a DC bus voltage reference value and a grid-connected / off-grid mode command.

[0066] After the grid-side VSG controller receives the complete grid-connected control command, it adjusts the virtual inertia and damping coefficient according to the content of the command, so as to realize AC side grid-forming support and smooth switching of system grid-connected / off-grid working conditions. The system continuously collects the actual execution status of grid-side equipment, and transmits the status data back to the front-end hybrid energy storage voltage stabilization control link, and iteratively optimizes the grid-connected control command output in the next cycle based on the feedback status data, so as to circularly complete the complete process of issuing collaborative control commands by the energy storage side, executing grid-forming regulation by the grid-side VSG, reversely feeding back the grid-connected operation status, and updating and optimizing control commands by the energy storage side, forming a collaborative closed-loop control system with mutual cooperation between energy storage voltage stabilization and VSG grid-forming and continuous self-correction.

[0067] The power frequency division is to decompose the total smoothing power into a low-frequency component and a high-frequency component according to a filtering algorithm, wherein the low-frequency component and the high-frequency component are power components of different frequencies;

[0068] distributing the low-frequency component to the storage battery, and distributing the high-frequency component to the super capacitor;

[0069] the filtering algorithm is first-order low-pass filtering, wavelet packet decomposition, moving average filtering or empirical mode decomposition.

[0070] The system decomposes the total power smoothing power using a filtering algorithm. This decomposition separates the total power smoothing power into two different frequency components: low-frequency and high-frequency components. Selectable filtering algorithms include first-order low-pass filtering, wavelet packet decomposition, moving average filtering, and empirical mode decomposition. After frequency-division decomposition of the total power smoothing power, the system allocates the low-frequency power components to batteries (energy storage units) and the high-frequency power components to supercapacitors (power storage units), thus matching and transmitting power components of different frequencies to their corresponding energy storage units.

[0071] The equilibrium correction includes:

[0072] Calculate the average state of charge (SOC) of all energy storage units:

[0073] ;

[0074] in, To collect the real-time SOC of each energy storage unit for the i-th energy storage unit,

[0075] Based on the State of Charge (SOC) of each energy storage unit i With SOC ave The difference ΔSOC is used to dynamically adjust the droop coefficient of each energy storage unit through a nonlinear function, resulting in the adjusted droop coefficient. Simultaneously, based on the imbalance of the state of charge of all energy storage units, the calculation formula is as follows:

[0076] ;

[0077] The equalization factor ρ is adaptively adjusted, and the power component allocation result is corrected based on the adjusted droop coefficient and the adaptive equalization factor ρ to obtain the corrected power command.

[0078] The expression for the adaptive SOC equilibrium factor ρ is:

[0079] ;

[0080] in, Equilibrium factor The initial baseline value; This is the adjustment coefficient, which takes a positive value and is used for regulation. The growth rate, and The smaller, The faster the growth rate.

[0081] Preferably, the nonlinear function is an exponential-hyperbolic tangent mixture function, and the adjusted droop coefficient R i The expression is:

[0082] ;

[0083] ;

[0084] in, Output current to the energy storage unit. It is in discharge state at the time. It is currently in charging mode. It is an acceleration factor used to widen the difference in droop coefficients and increase the balancing rate.

[0085] The average state of charge (SOC) of all energy storage units is calculated using the formula: the sum of the SOC values ​​of all energy storage units divided by the total number of energy storage units. The variables in the formula are defined as follows: SOC... i Let be the state of charge (SOC) acquired in real time for the i-th energy storage unit. After calculating the average SOC, the difference ΔSOC between the SOC of each energy storage unit and the average is calculated. Based on this difference, the droop coefficient of each energy storage unit is dynamically adjusted using a nonlinear function to obtain the adjusted droop coefficient. At the same time, the imbalance of the SOC of all energy storage units is calculated. The calculation formula is the sum of the absolute values ​​of the differences between the SOC of all energy storage units and the average, divided by the total number of energy storage units. The adaptive adjustment of the equalization factor ρ is performed based on the obtained imbalance degree. The adaptive SOC equalization factor ρ is set with a piecewise expression. When the sum of the imbalance degree and the adjustment coefficient is less than or equal to 1, the equalization factor ρ is equal to the initial reference equalization factor ρ0 multiplied by the negative logarithm and the result added to a fixed value. When the sum of the imbalance degree and the adjustment coefficient is greater than 1, the equalization factor ρ directly takes the initial reference value ρ0, where ρ0 represents the initial reference value of the equalization factor ρ, and ω is a positive adjustment coefficient that can regulate the growth rate of the equalization factor ρ. The smaller the value of the adjustment coefficient ω, the faster the growth rate of the equalization factor ρ. After obtaining the adjusted droop coefficient and the adaptively adjusted equalization factor ρ, the power component distribution result is corrected by combining the two sets of parameters, and finally the power command after the equalization correction is generated.

[0086] The voltage compensation amount is calculated based on the deviation between the real-time DC bus voltage and the rated reference value, using linear active disturbance rejection control, sliding mode control, nonlinear active disturbance rejection control, or disturbance observer-based control algorithms. This compensation amount is used to offset the voltage deviation introduced by droop control and power fluctuations. The voltage compensation amount is then superimposed on the voltage regulation control target and input to the voltage and current dual closed-loop control.

[0087] The calculation is performed using linear active disturbance rejection control, sliding mode control, nonlinear active disturbance rejection control, or a control algorithm based on a disturbance observer. During the calculation, the real-time DC bus voltage is compared with the rated reference value of the DC bus voltage to obtain the voltage deviation between the two. Based on the selected control algorithm and this voltage deviation, the corresponding voltage compensation amount is calculated. The purpose of this voltage compensation amount is to offset the DC bus voltage deviation introduced by the droop control operation and system power fluctuations. After solving for the voltage compensation amount, the voltage compensation amount is superimposed on the voltage regulation control target value. The voltage regulation control target value after superposition is sent to the voltage and current dual closed-loop control loop as the input of the dual closed-loop control for subsequent regulation.

[0088] Based on PI control or fuzzy PI control, receive the control target and voltage compensation amount of the voltage outer loop stabilization in the voltage and current dual closed-loop control, and output the current reference value.

[0089] Based on improved model predictive control, model predictive current control, or PI control, the current reference value of the inner current loop is received, and grid-connected control commands are generated by rapidly tracking the current using adaptive weighting coefficients.

[0090] The voltage and current dual closed-loop control consists of two levels: an outer voltage loop and an inner current loop. The outer loop operates sequentially from the outer to the inner loop. The outer voltage loop uses PI control or fuzzy PI control as its calculation method. It receives the voltage regulation control target after superimposing voltage compensation, performs calculations using the corresponding control algorithm, and outputs a current reference value, which is then transmitted to the inner current loop. The inner current loop can use improved model predictive control, model predictive current control, or PI control for calculations. It receives the current reference value output from the outer voltage loop and, during the calculation process, incorporates adaptive weighting coefficients to achieve rapid current tracking. Based on the aforementioned control logic, the final grid-connected control command is generated after the calculations are completed.

[0091] Based on the three-step prediction strategy, an improved model predictive control is obtained by setting the current tracking weight 'a' and the voltage stability weight 'β'.

[0092] The adaptive weighting coefficient is dynamically adjusted based on the system's operating status to optimize the tracking accuracy of the current reference value.

[0093] An improved model predictive control is built based on a three-step prediction strategy. During the construction process, a current tracking weight 'a' and a voltage stability weight 'β' are set respectively. The two sets of weights together constitute the control parameters of the improved model predictive control. During the control operation phase of the current inner loop, the system will collect its own operating status information in real time and dynamically adjust the adaptive weight coefficients according to the current system operating status. The dynamically adjusted adaptive weight coefficients can optimize the tracking accuracy of the current reference value and improve the following effect of the current inner loop on the target current reference value.

[0094] Adaptive adjustment of virtual inertia and damping coefficient, including:

[0095] Adjust the virtual inertia J and damping coefficient D based on the intensity of photovoltaic power fluctuations and / or the state of charge of hybrid energy storage to determine the power demand in the grid-connected control command;

[0096] When power fluctuations are large or the state of charge is in an extreme range, increase the virtual inertia J to improve system stability.

[0097] When power fluctuations are small or the state of charge is within a safe range, the virtual inertia J is reduced to improve the response speed.

[0098] The system adaptively adjusts the virtual inertia and damping coefficient. The complete adjustment logic consists of multiple execution steps. First, the system reads two types of operating parameters: the intensity of photovoltaic power fluctuations and the state of charge of the hybrid energy storage. Simultaneously, it identifies the power demand contained in the grid-connected control command. Based on multi-dimensional information, the system synchronously completes the adaptive adjustment of the virtual inertia J and the damping coefficient D. When the system determines that the current photovoltaic power fluctuation is large, or the state of charge of the hybrid energy storage unit falls within an extreme range, the system increases the value of the virtual inertia J to enhance the system's operational stability. When the system determines that the current photovoltaic power fluctuation is small, or the state of charge of the hybrid energy storage unit is within a safe range, the system decreases the value of the virtual inertia J to accelerate the overall system response speed. The system dynamically adapts the virtual parameters based on real-time operating conditions throughout the entire process.

[0099] The on-grid and off-grid switching is performed based on the voltage frequency provided by the VSG control unit;

[0100] The grid-connected VSG control is obtained based on the grid-connected and off-grid mode instructions in the grid-connected control instructions and the DC bus voltage reference value. The switching between grid-connected and off-grid is obtained by adjusting the internal voltage phase based on the VSG control.

[0101] The execution status of VSG control on the grid-connected side includes the adjusted grid voltage, frequency, and actual output power. This execution status is fed back to the energy storage side for iterative optimization.

[0102] The system completes grid-connected / off-grid switching operations based on the voltage and frequency regulation capabilities of the VSG control unit. During operation, it reads the grid-connected / off-grid mode command and DC bus voltage reference value carried in the grid-connected control command, and generates the corresponding VSG control strategy for the grid-connected side by combining the two types of parameters. The system then adjusts the internal voltage phase according to the generated VSG control strategy, and completes the switching between grid-connected and off-grid conditions by adjusting the voltage phase. After the grid-connected VSG control executes the operation, it generates corresponding execution status data, which includes the adjusted grid voltage, grid frequency, and actual VSG output power. The system transmits all execution status data back to the energy storage side control link. After receiving the feedback status data, the energy storage side iteratively optimizes the grid-connected control command output in the next cycle.

[0103] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0104] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for coordinated control of energy storage voltage stabilization and VSG grid construction in a photovoltaic-storage grid-connected system, characterized in that, The method includes the following specific steps: Based on the system operating parameters collected by the monitoring unit, a parallel and collaborative closed-loop architecture for hybrid energy storage and grid-connected VSG control is constructed. On the energy storage side, the difference between photovoltaic output and load power is processed by power frequency division to obtain power components of different frequencies, and each power component is allocated to the corresponding energy storage unit of the hybrid energy storage. The power component allocation results are balanced and corrected by combining the state of charge of each energy storage unit to obtain the corrected power command. Voltage compensation is obtained by processing the DC bus voltage deviation introduced by droop control and power fluctuation through voltage regulation control; the bidirectional DC / DC converter on the hybrid energy storage side is driven by voltage and current dual closed-loop control to generate grid-connected control commands. The grid-connected VSG control unit receives grid-connected control commands and adjusts the virtual inertia and damping coefficients according to the grid-connected control commands to realize grid support and grid-connected / off-grid switching. The execution status of the grid-connected side is fed back to the energy storage side, and the grid-connected control command is iteratively optimized to form a closed-loop control system with guidance from the energy storage side, execution from the VSG side, status feedback, and optimization guidance.

2. The method for coordinated control of energy storage voltage stabilization and VSG grid construction in a photovoltaic-storage grid-connected system according to claim 1, characterized in that, System operating parameters include photovoltaic output, load power, state of charge of each energy storage unit, DC bus voltage, grid voltage and frequency; Hybrid energy storage includes batteries as energy-type energy storage units and supercapacitors as power-type energy storage units; The grid-connected VSG control commands include total active power commands, reactive power commands, DC bus voltage reference values, and grid-connected / off-grid mode commands. The total active power is formed by summarizing the corrected power commands.

3. The method for coordinated control of energy storage voltage stabilization and VSG grid construction in a photovoltaic-storage grid-connected system according to claim 2, characterized in that, The power frequency division decomposes the total smoothing power into low-frequency components and high-frequency components according to the filtering algorithm. The low-frequency components and high-frequency components are power components of different frequencies. Distribute low-frequency components to the battery and high-frequency components to the supercapacitor; The filtering algorithms are first-order low-pass filtering, wavelet packet decomposition, moving average filtering, or empirical mode decomposition.

4. The method for coordinated control of energy storage voltage stabilization and VSG grid construction in a photovoltaic-storage grid-connected system according to claim 3, characterized in that, The equilibrium correction includes: Calculate the average state of charge (SOC) of all energy storage units: ； in, To collect the real-time SOC of each energy storage unit for the i-th energy storage unit, Based on the State of Charge (SOC) of each energy storage unit i With SOC ave The difference ΔSOC is used to dynamically adjust the droop coefficient of each energy storage unit through a nonlinear function, resulting in the adjusted droop coefficient. Simultaneously, the imbalance of the state of charge of all energy storage units is calculated using the following formula: ； The equalization factor ρ is adaptively adjusted, and the power component allocation result is corrected based on the adjusted droop coefficient and the adaptive equalization factor ρ to obtain the corrected power command. The expression for the adaptive SOC equilibrium factor ρ is: ； in, Equilibrium factor The initial reference value; This is the adjustment coefficient, which takes a positive value and is used for regulation. The growth rate, and The smaller, The faster the growth rate.

5. The method for coordinated control of energy storage voltage stabilization and VSG grid construction in a photovoltaic-storage grid-connected system according to claim 4, characterized in that, The nonlinear function is a mixture of exponential and hyperbolic tangent functions, with the adjusted droop coefficient R. i The expression is: ； ； in, Output current to the energy storage unit. It is in the discharge state at the time. It is currently in charging mode. It is an acceleration factor used to widen the difference in droop coefficients and increase the balancing rate.

6. The method for coordinated control of energy storage voltage stabilization and VSG grid construction in a photovoltaic-storage grid-connected system according to claim 5, characterized in that, The voltage compensation is calculated by using linear active disturbance rejection control, sliding mode control, nonlinear active disturbance rejection control, or a control algorithm based on disturbance observer, combined with the deviation between the real-time DC bus voltage and the rated reference value. This compensation is used to offset the voltage deviation introduced by droop control and power fluctuations. The voltage compensation is then superimposed on the voltage regulation control target and input to the voltage and current dual closed-loop control.

7. The method for coordinated control of energy storage voltage stabilization and VSG grid construction in a photovoltaic-storage grid-connected system according to claim 6, characterized in that, Voltage outer loop PI control or fuzzy PI control, receives the control target and voltage compensation amount of voltage outer loop stabilization in voltage and current dual closed loop control, and outputs current reference value; The current inner loop improves model predictive control, model predictive current control, or PI control, receives the current reference value from the current inner loop, and generates grid-connected control commands by combining adaptive weighting coefficients to quickly track the current.

8. The method for coordinated control of energy storage voltage stabilization and VSG grid construction in a photovoltaic-storage grid-connected system according to claim 7, characterized in that, Based on a three-step prediction strategy, an improved model predictive control algorithm is constructed by setting current tracking weight 'a' and voltage stability weight 'β'. The adaptive weighting coefficient is dynamically adjusted based on the system's operating status to optimize the tracking accuracy of the current reference value.

9. The method for coordinated control of energy storage voltage stabilization and VSG grid construction in a photovoltaic-storage grid-connected system according to claim 8, characterized in that, Adaptive adjustment of virtual inertia and damping coefficient, including: Adjust the virtual inertia J and damping coefficient D based on the intensity of photovoltaic power fluctuations and / or the state of charge of hybrid energy storage to determine the power demand in the grid-connected control command; When power fluctuations are large or the state of charge is in an extreme range, increase the virtual inertia J to improve system stability. When power fluctuations are small or the state of charge is within a safe range, the virtual inertia J is reduced to improve the response speed.

10. The method for coordinated control of energy storage voltage stabilization and VSG grid construction in a photovoltaic-storage grid-connected system according to claim 9, characterized in that, The system relies on the voltage and frequency of the VSG control unit to perform on-grid and off-grid switching. The grid-connected VSG control is obtained based on the grid-connected and off-grid mode instructions in the grid-connected control instructions and the DC bus voltage reference value. The switching between grid-connected and off-grid is obtained by adjusting the internal voltage phase based on the VSG control. The execution status of VSG control on the grid-connected side includes the adjusted grid voltage, frequency, and actual output power. This execution status is fed back to the energy storage side for iterative optimization of grid-connected control commands.

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