Photovoltaic energy storage collaborative regulation method and system

Abstract

The application discloses a photovoltaic energy storage collaborative regulation method and system, applied to the photovoltaic energy storage regulation technical field, and the method comprises the steps of: when the absolute value of the light intensity change rate of a photovoltaic power generation device is greater than a preset threshold, determining a voltage tracking step length based on the light intensity change rate; based on the historical power-voltage relationship data of the photovoltaic power generation device and the voltage tracking step length, obtaining the maximum reference power of the photovoltaic power generation device; based on the load margin of the power consumption side, the state of charge of the hybrid energy storage device, the maximum reference power and the current output of the photovoltaic power generation device, and the current electricity price state, obtaining the current regulation parameter feasible region; based on a preset multi-objective, performing an optimization operation on the current regulation parameter feasible region to obtain a running parameter correction amount, so as to collaboratively regulate the photovoltaic power generation device and the hybrid energy storage device based on the running parameter correction amount. The application realizes the overall efficiency optimization of the photovoltaic energy storage system.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic energy storage regulation technology, and in particular to a photovoltaic energy storage coordinated regulation method and system. Background Technology

[0002] Existing photovoltaic (PV) energy storage coordinated regulation methods typically employ a hierarchical, independent control architecture. In Maximum Power Point Tracking (MPPT), existing methods often use fixed-step conductance increment methods or perturbation-observation methods, gradually approaching the maximum power point by perturbing the operating voltage of the PV power generation device with fixed voltage increments and observing the direction of power change. In energy storage management, existing schemes usually rely on simple State of Charge (SOC) thresholds for charge and discharge control; for example, forcing charging when the SOC is below the lower limit and stopping charging when it is above the upper limit. During the switching between grid-connected and off-grid modes, existing methods often directly switch control strategies, lacking pre-synchronous adjustment of phase and amplitude.

[0003] The aforementioned existing technologies suffer from the following problems: Fixed-step MPPT exhibits lag in response to sudden changes in illumination, making it difficult to quickly track the changed maximum power point, leading to energy loss; simple SOC threshold control does not consider time-of-use pricing and grid load conditions, and the charging and discharging strategy lacks economic optimization; inconsistencies in voltage, frequency, and phase during mode switching can easily generate inrush currents, affecting system stability. Furthermore, the control layers are independent of each other, lacking a collaborative optimization mechanism, making it difficult to achieve overall performance optimization of the photovoltaic energy storage system. Summary of the Invention

[0004] This invention provides a photovoltaic energy storage coordinated control method and system to solve the technical problem that existing photovoltaic energy storage systems are difficult to optimize overall performance.

[0005] To address the aforementioned technical problems, embodiments of the present invention provide a photovoltaic energy storage coordinated regulation method, comprising: When the absolute value of the rate of change of light intensity of the photovoltaic power generation device is greater than a preset threshold, the voltage tracking step size is determined based on the rate of change of light intensity. Based on the historical power-voltage relationship data of the photovoltaic power generation device and the voltage tracking step size, the maximum reference power of the photovoltaic power generation device is obtained. Based on the load margin on the electricity consumption side, the state of charge of the hybrid energy storage device, the maximum reference power and current output of the photovoltaic power generation device, and the current electricity price status, the feasible region of the current control parameters is obtained. Based on preset multi-objective optimization operations, the feasible domain of the current control parameters is optimized to obtain the operation parameter correction amount, and the photovoltaic power generation device and the hybrid energy storage device are coordinated and controlled based on the operation parameter correction amount.

[0006] As one preferred embodiment, determining the voltage tracking step size based on the rate of change of light intensity when the absolute value of the rate of change of light intensity of the photovoltaic power generation device is greater than a preset threshold includes: Acquire the light intensity of the first and second sampling points that are adjacent in time sequence of the photovoltaic power generation device; The light intensity change rate of the photovoltaic power generation device is obtained based on the light intensity of the first sampling point and the light intensity of the second sampling point. When the absolute value of the light intensity change rate is greater than a preset threshold, the voltage tracking step size of the second sampling point is obtained based on the absolute value.

[0007] As one preferred embodiment, obtaining the maximum reference power of the photovoltaic power generation device based on the historical power-voltage relationship data of the photovoltaic power generation device and the voltage tracking step size includes: Historical power-voltage relationship data of the photovoltaic power generation device are extracted to obtain the reference voltage, measured voltage, and measured power of all sampling points of the photovoltaic power generation device between the previous time and the current time. The reference voltage of the third sampling point is obtained based on the measured voltage, voltage tracking direction, and voltage tracking step size of the second sampling point. The voltage tracking direction of the second sampling point is obtained based on the measured voltage and measured power of the first sampling point, as well as the measured voltage and measured power of the second sampling point. The measured voltage of the third sampling point is measured under the influence of the reference voltage of the second sampling point. Based on the measured power of the photovoltaic power generation device at the last sampling point among all sampling points, the maximum reference power of the photovoltaic power generation device at the current moment is obtained.

[0008] As one preferred embodiment, the feasible domain for obtaining the current control parameters based on the load margin on the electricity consumption side, the state of charge of the hybrid energy storage device, the maximum reference power and current output of the photovoltaic power generation device, and the current electricity price status includes: The target power is obtained based on the load margin on the electricity consumption side, the state of charge of the hybrid energy storage device, and the maximum reference power of the photovoltaic power generation device. When the load margin determines that the electricity consumption side is under light load, the state of charge determines that the hybrid energy storage device is under full charge, the target power is less than the current output of the photovoltaic power generation device, and the current electricity price is at a low point, the current control operation is determined to include reducing the operating voltage of the photovoltaic power generation device; the feasible domain of the parameters of the current control operation is determined based on the target power and the current output. When the load margin determines that the electricity consumption side is under heavy load, the state of charge determines that the hybrid energy storage device is fully charged, the target power is greater than the current output of the photovoltaic power generation device, and the current electricity price is at its peak, the current control operation is determined to include increasing the output of the photovoltaic power generation device and discharging the hybrid energy storage device; the feasible domain of the parameters of the current control operation is determined based on the target power and the current output.

[0009] As one preferred embodiment, the hybrid energy storage device includes an electrochemical energy storage battery and an electrochemical energy storage capacitor; the step of obtaining the maximum reference power of the photovoltaic power generation device based on the historical power-voltage relationship data of the photovoltaic power generation device and the voltage tracking step size includes: When determining to perform a charge / discharge operation on the hybrid energy storage device, the charge / discharge power corresponding to the charge / discharge operation is obtained; Extract high-frequency fluctuation power components with a frequency greater than or equal to a preset frequency from the charging and discharging power, and extract low-frequency fluctuation power components with a frequency less than the preset frequency. The high-frequency fluctuation power component is stored in the electrochemical energy storage capacitor, or the electrochemical energy storage capacitor is controlled to release the power corresponding to the high-frequency fluctuation power component. The low-frequency fluctuation power component is stored in the electrochemical energy storage battery, or the electrochemical energy storage battery is controlled to release the power corresponding to the low-frequency fluctuation power component.

[0010] Another embodiment of the present invention provides a photovoltaic energy storage coordinated control system, comprising: The voltage tracking step size determination module is used to determine the voltage tracking step size based on the rate of change of light intensity when the absolute value of the rate of change of light intensity of the photovoltaic power generation device is greater than a preset threshold. The maximum reference power determination module is used to obtain the maximum reference power of the photovoltaic power generation device based on the historical power-voltage relationship data of the photovoltaic power generation device and the voltage tracking step size; The current control parameter feasible region determination module is used to obtain the current control parameter feasible region based on the load margin on the electricity consumption side, the state of charge of the hybrid energy storage device, the maximum reference power and current output of the photovoltaic power generation device, and the current electricity price status. The collaborative control module is used to perform optimization operations on the feasible domain of the current control parameters based on preset multi-objectives to obtain the operating parameter correction amount, and to perform collaborative control of the photovoltaic power generation device and the hybrid energy storage device based on the operating parameter correction amount.

[0011] As one preferred embodiment, the voltage tracking step size determination module includes: The light intensity acquisition unit is used to acquire the light intensity of the first sampling point and the second sampling point that are adjacent in time sequence of the photovoltaic power generation device. The light intensity change rate determination unit is used to obtain the light intensity change rate of the photovoltaic power generation device based on the light intensity of the first sampling point and the light intensity of the second sampling point; The voltage tracking step size determination unit is used to determine the voltage tracking step size of the second sampling point based on the absolute value of the light intensity change rate when the absolute value is greater than a preset threshold.

[0012] As one preferred embodiment, the maximum reference power determination module includes: The data extraction unit is used to extract historical power-voltage relationship data of the photovoltaic power generation device to obtain the reference voltage, measured voltage, and measured power of all sampling points of the photovoltaic power generation device between the previous time and the current time. The reference voltage of the third sampling point is obtained based on the measured voltage, voltage tracking direction, and voltage tracking step size of the second sampling point. The voltage tracking direction of the second sampling point is obtained based on the measured voltage and measured power of the first sampling point, as well as the measured voltage and measured power of the second sampling point. The measured voltage of the third sampling point is measured under the influence of the reference voltage of the second sampling point. The maximum reference power determination unit is used to obtain the maximum reference power of the photovoltaic power generation device at the current moment based on the measured power of the last sampling point among all sampling points.

[0013] As one preferred embodiment, the current control parameter feasible domain determination module includes: The target power determination unit is used to obtain the target power based on the load margin on the power consumption side, the state of charge of the hybrid energy storage device, and the maximum reference power of the photovoltaic power generation device. The first parameter feasible region determination unit is used to determine that the current control operation includes reducing the operating voltage of the photovoltaic power generation device when the power consumption side is determined to be in a light load state based on the load margin, the hybrid energy storage device is determined to be in a fully charged state based on the state of charge, the target power is less than the current output of the photovoltaic power generation device, and the current electricity price is in a low-price state; the parameter feasible region of the current control operation is determined based on the target power and the current output. The second parameter feasible region determination unit is used to determine that the current control operation includes increasing the output of the photovoltaic power generation device and discharging the hybrid energy storage device when the power consumption side is determined to be under heavy load based on the load margin, the hybrid energy storage device is determined to be under full charge based on the state of charge, the target power is greater than the current output of the photovoltaic power generation device, and the current electricity price is at its peak. The parameter feasible region of the current control operation is determined based on the target power and the current output.

[0014] As one preferred embodiment, the hybrid energy storage device includes an electrochemical energy storage battery and an electrochemical energy storage capacitor; the system further includes: The charge / discharge power determination module is used to obtain the charge / discharge power corresponding to the charge / discharge operation when it is determined that a charge / discharge operation will be performed on the hybrid energy storage device. The fluctuating power component extraction module is used to extract high-frequency fluctuating power components with a frequency greater than or equal to a preset frequency from the charging and discharging power, and to extract low-frequency fluctuating power components with a frequency less than the preset frequency. A capacitor charging and discharging module is used to store the high-frequency fluctuating power component into the electrochemical energy storage capacitor, or to control the electrochemical energy storage capacitor to release the power corresponding to the high-frequency fluctuating power component. The battery charging and discharging module is used to store the low-frequency fluctuation power component into the electrochemical energy storage battery, or to control the electrochemical energy storage battery to release the power corresponding to the low-frequency fluctuation power component.

[0015] This application determines the adaptive voltage tracking step size by utilizing the rate of change of light intensity of the photovoltaic (PV) power generation device. Based on historical power-voltage relationship data and this step size, the maximum reference power is iteratively calculated, enabling the PV energy storage system to respond quickly to sudden changes in illumination and track accurately when illumination is stable. This overcomes the problem of traditional fixed-step-size methods struggling to balance dynamic and steady-state performance. Furthermore, by integrating five dimensions of data—load margin on the electricity demand side, energy storage state of charge, PV maximum reference power, current output, and current electricity price—a feasible domain for control parameters is constructed. This unifies physical safety constraints and economic constraints within the same framework, avoiding control errors caused by single-dimensional decision-making. Based on this, multi-objective optimization is performed within the feasible domain, outputting operational parameter corrections to drive the PV power generation device and hybrid energy storage device to operate collaboratively, allowing the system to approach overall optimization while meeting safety boundaries. Overall, this scheme forms a complete control closed loop from environmental perception and state constraints to optimization decision-making, achieving coordinated optimal control of the PV energy storage system under multiple constraints. Attached Figure Description

[0016] Figure 1 This is one of the flowcharts of the photovoltaic energy storage coordinated control method provided by the present invention; Figure 2 This is the second schematic diagram of the photovoltaic energy storage coordinated regulation method provided by the present invention; Figure 3 This is a schematic diagram of the photovoltaic energy storage coordinated control system provided by the present invention.

[0017] Figure label: Among them, 301 is the voltage tracking step size determination module; 302 is the maximum reference power determination module; 303 is the current control parameter feasible domain determination module; and 304 is the collaborative control module. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0019] In the description of this application, the terms "first," "second," "third," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined with "first," "second," "third," etc., may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0020] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to the internal communication between two components. The terms "vertical," "horizontal," "left," "right," "upper," "lower," and similar expressions used herein are for illustrative purposes only and do not indicate or imply that the device or component referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as limiting the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0021] In the description of this application, it should be noted that, unless otherwise defined, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this specification is for the purpose of describing specific embodiments only and is not intended to limit the invention. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0022] See Figure 1 , Figure 1 This is a flowchart illustrating an embodiment of the photovoltaic energy storage coordinated control method provided by the present invention, as shown below. Figure 1 As shown, this embodiment includes steps 100 to 400, and the specific steps are as follows: Step 100: When the absolute value of the rate of change of light intensity of the photovoltaic power generation device is greater than a preset threshold, determine the voltage tracking step size based on the rate of change of light intensity; This embodiment provides an implementation method for adaptively determining the voltage tracking step size based on the rate of change of light intensity. A light intensity sensor is configured in the photovoltaic power generation device, which collects ambient light intensity data in real time at a preset sampling frequency (e.g., 50 times / second). Light intensity data from adjacent sampling points in time sequence are acquired, and the rate of change of light intensity is calculated. In this embodiment, the rate of change of light intensity refers to the amount of change in light intensity per unit time, used to characterize the drastic degree of change in lighting conditions.

[0023] When the absolute value of the calculated rate of change of light intensity exceeds a preset threshold, it is determined that the current situation is a sudden change in illumination, and the voltage tracking step size needs to be increased to accelerate the tracking speed. Specifically, the voltage tracking step size is determined based on the magnitude of the absolute value of the rate of change of light intensity through a preset mapping relationship or function: the larger the absolute value of the rate of change of light intensity, the larger the voltage tracking step size; the smaller the absolute value of the rate of change of light intensity, the smaller the voltage tracking step size. For example, when the rate of change of light intensity is the first value, the voltage tracking step size is the first value; when the rate of change of light intensity is the second value, which is greater than the first value, the voltage tracking step size is the second value, which is greater than the first value. When the absolute value of the rate of change of light intensity is less than or equal to the preset threshold, it is determined that the illumination conditions are relatively stable, and a smaller voltage tracking step size is used to maintain tracking accuracy.

[0024] Through the above method, this embodiment achieves adaptive adjustment of the voltage tracking step size to changes in illumination, enabling rapid response during sudden changes in illumination and accurate tracking when illumination is stable.

[0025] The technical advantage of this embodiment is that by dynamically determining the voltage tracking step size based on the rate of change of light intensity, it overcomes the contradiction that the existing fixed step size method has a lag response when the light intensity changes suddenly and an aggravated oscillation when the light intensity is stable. It achieves an adaptive balance between tracking speed and tracking accuracy, and effectively improves the energy capture efficiency of photovoltaic power generation devices under dynamic lighting conditions.

[0026] Step 200: Based on the historical power-voltage relationship data of the photovoltaic power generation device and the voltage tracking step size, obtain the maximum reference power of the photovoltaic power generation device; This embodiment provides an implementation method for iteratively calculating the maximum reference power based on historical power-voltage relationship data of a photovoltaic power generation device and a voltage tracking step size. The historical power-voltage relationship data in this embodiment refers to the correspondence between output voltage and output power collected and recorded by the photovoltaic power generation device in one or more previous control cycles, including the measured voltage and measured power values ​​at each sampling point.

[0027] Obtain the measured voltage from the previous control cycle in the current control cycle. and measured power and the measured voltage of the current control cycle. and measured power Based on the power difference between the previous control cycle and the current control cycle. and voltage difference Calculate the power-voltage slope .like If the current operating point is determined to be to the left of the maximum power point, the voltage disturbance direction is positive (increasing voltage); if If the current operating point is determined to be to the right of the maximum power point, the voltage disturbance direction is negative (reducing voltage); if It is determined that the current operating point is close to the maximum power point.

[0028] The determined voltage disturbance direction is multiplied by the aforementioned voltage tracking step size, and then superimposed onto the measured voltage of the current control cycle to generate the reference voltage command for the next control cycle. The voltage is then output to the PWM modulator to update the operating voltage of the photovoltaic power generation device. In the next control cycle, the measured voltage of the photovoltaic power generation device under the reference voltage command is acquired. and measured current Calculate the measured power Repeat the above iterative process until the absolute value of the power change over multiple consecutive control cycles is less than the preset accuracy threshold (e.g., the power change rate is less than 0.5%). At this point, the power value corresponding to the current operating voltage is determined to be the maximum reference power of the photovoltaic power generation device under the current illumination conditions.

[0029] The technical advantage of this embodiment is that by using historical power-voltage relationship data to determine the direction of the maximum power point and combining iterative approximation with adaptive voltage tracking step size, the maximum reference power is tracked quickly and accurately.

[0030] Step 300: Based on the load margin on the power consumption side, the state of charge of the hybrid energy storage device, the maximum reference power and current output of the photovoltaic power generation device, and the current electricity price status, obtain the feasible domain of the current control parameters; This embodiment provides an implementation method for constructing a feasible domain of current control parameters based on the load margin on the electricity consumption side, the state of charge of the hybrid energy storage device, the maximum reference power and current output of the photovoltaic power generation device, and the current electricity price status.

[0031] In this embodiment, the load margin on the demand side refers to the remaining capacity of the photovoltaic energy storage system to supply or draw active power from the external power grid or local load under the current operating state, used to characterize the grid's capacity to absorb or receive power. The load margin can be obtained through instructions received from the grid dispatch center via the communication module, or it can be estimated in real time based on the voltage and frequency deviations at the grid connection point. In this embodiment, the state of charge (SOC) of the hybrid energy storage device refers to the percentage of the hybrid energy storage device's current remaining power relative to its rated capacity, used to characterize the charging and discharging capability of the energy storage device. In this embodiment, the current output of the photovoltaic power generation device refers to the actual active power output of the photovoltaic power generation device under the current operating voltage, calculated in real time by voltage and current sensors. In this embodiment, the current electricity price status refers to the electricity price category of the current time period determined according to the time-of-use pricing policy, including but not limited to peak electricity price periods, flat electricity price periods, and off-peak electricity price periods.

[0032] After acquiring the aforementioned five-dimensional data, a feasible region for the current control parameters is constructed based on preset constraint rules. This feasible region defines the types of control operations that the system can perform at the current moment (including increasing photovoltaic output, decreasing photovoltaic output, energy storage charging, energy storage discharging, and energy storage standby, etc.) and the adjustable range of parameters corresponding to each operation (e.g., voltage regulation amplitude, charging and discharging power limits, and SOC target values, etc.). The boundaries of the feasible region are jointly determined by the following constraints: the upper and lower limits of SOC (e.g., 5% to 95%) determine the physical feasibility of charging and discharging; the load margin determines the allowable upper limit of power output to or from the grid; the difference between the maximum reference power and the current output determines the adjustable margin on the photovoltaic side; and the current electricity price status determines the economic priority of charging and discharging (e.g., priority discharging during peak hours and priority charging during off-peak hours).

[0033] For example, when the SOC is in the normal range of 20% to 80%, the load margin is positive (light grid load), and the current electricity price is in a low period, the feasible domain includes "energy storage charging" operation, and the upper limit of charging power is determined by the load margin and the maximum charging power. When the SOC is close to the upper limit (e.g., above 80%), the load margin is negative (heavy grid load), and the current electricity price is in a high period, the feasible domain primarily includes "energy storage discharging" operation.

[0034] The technical advantage of this embodiment is that by constructing a feasible domain for control parameters using five dimensions of data, including the load margin on the electricity consumption side, the state of charge of energy storage, the maximum reference power of photovoltaics, the current output of photovoltaics, and the current electricity price, physical and economic constraints are uniformly incorporated into the control framework. This provides a clear and safe decision space for subsequent multi-objective optimization and avoids control misconduct caused by single-dimensional decision-making.

[0035] Step 400: Based on preset multi-objectives, perform optimization operation on the feasible domain of the current control parameters to obtain the operation parameter correction amount, and then coordinate the control of the photovoltaic power generation device and the hybrid energy storage device based on the operation parameter correction amount.

[0036] This embodiment provides an implementation method for optimizing the feasible region of current control parameters based on preset multi-objectives to obtain the adjustment amount of operating parameters. The preset multi-objectives in this embodiment include at least two of the following: maximizing economic benefits, minimizing battery life loss, and minimizing curtailment rate. The adjustment amount of operating parameters in this embodiment refers to the incremental value used to adjust the current operating parameters (including but not limited to photovoltaic operating voltage, energy storage charge / discharge power, and charge / discharge depth threshold) of the photovoltaic power generation device and / or hybrid energy storage device.

[0037] Within the feasible region of the determined control parameters, a multi-objective optimization algorithm is employed for optimization. Specifically, an objective function containing multiple optimization objectives is constructed, such as maximizing electricity sales revenue (discharging more during peak hours and charging more during off-peak hours to profit from price differences), minimizing battery life loss (reducing charge-discharge cycle depth and rate), and minimizing curtailment rate (consuming as much photovoltaic power as possible). These objectives are conflicting (e.g., deep charge-discharge increases revenue but accelerates battery aging), requiring a Pareto optimal or weighted optimal solution to be found within the feasible region.

[0038] Optimization can be performed using one of the following methods: Method 1: Based on preset weight coefficients, transform the multi-objective problem into a single-objective weighted function, and search within the feasible region for the optimal combination of operating parameters that optimizes the weighted function; Method 2: Use a multi-objective evolutionary algorithm (e.g., NSGA-II algorithm) to solve for the Pareto optimal frontier, and then select a solution from the optimal frontier as the execution plan based on the current priority. The optimization result is output as the operating parameter correction amount, for example, the photovoltaic operating voltage correction amount. Energy storage charging and discharging power correction amount and the adjustment amount of the SOC target value wait.

[0039] The function of the operating parameter correction amount in this embodiment is to feed back the multi-objective optimization results to the current control parameters in an incremental form, so as to realize the dynamic fine-tuning of the operating status of the photovoltaic power generation device and the hybrid energy storage device, and make the system approach the multi-objective comprehensive optimum under the premise of satisfying physical constraints.

[0040] The technical advantage of this embodiment is that by performing multi-objective optimization within the feasible domain, it overcomes the shortcomings of traditional single-objective regulation in complex operating conditions, which tends to overlook one aspect while addressing another. It achieves comprehensive optimization of economy, battery life and photovoltaic absorption rate, enabling the system to adaptively select the optimal regulation strategy under different electricity price periods and grid conditions.

[0041] This application determines the adaptive voltage tracking step size by utilizing the rate of change of light intensity of the photovoltaic (PV) power generation device. Based on historical power-voltage relationship data and this step size, the maximum reference power is iteratively calculated, enabling the PV energy storage system to respond quickly to sudden changes in illumination and track accurately when illumination is stable. This overcomes the problem of traditional fixed-step-size methods struggling to balance dynamic and steady-state performance. Furthermore, by integrating five dimensions of data—load margin on the electricity demand side, energy storage state of charge, PV maximum reference power, current output, and current electricity price—a feasible domain for control parameters is constructed. This unifies physical safety constraints and economic constraints within the same framework, avoiding control errors caused by single-dimensional decision-making. Based on this, multi-objective optimization is performed within the feasible domain, outputting operational parameter corrections to drive the PV power generation device and hybrid energy storage device to operate collaboratively, allowing the system to approach overall optimization while meeting safety boundaries. Overall, this scheme forms a complete control closed loop from environmental perception and state constraints to optimization decision-making, achieving coordinated optimal control of the PV energy storage system under multiple constraints.

[0042] In another embodiment of the photovoltaic energy storage coordinated control method provided by the present invention, step 100 specifically includes: Step 110: Obtain the light intensity of the first sampling point and the second sampling point that are adjacent in time sequence of the photovoltaic power generation device; Step 120: Based on the light intensity of the first sampling point and the light intensity of the second sampling point, obtain the light intensity change rate of the photovoltaic power generation device; Step 130: When the absolute value of the light intensity change rate is greater than a preset threshold, the voltage tracking step size of the second sampling point is obtained based on the absolute value.

[0043] The photovoltaic power generation device is equipped with a light intensity sensor that continuously collects ambient light intensity data at a preset sampling frequency, acquiring the light intensity value of the first adjacent sampling point in time sequence. Light intensity value at the second sampling point ,in, Later The time interval between adjacent sampling points is (For example, 0.02 seconds). In this embodiment, the rate of change of light intensity refers to the change in light intensity per unit time. .

[0044] After calculating the rate of change of light intensity, its absolute value is compared with a preset threshold. When the absolute value of the rate of change of light intensity is greater than the preset threshold, it is determined that a sudden change has occurred in the current illumination conditions, requiring an increase in the voltage tracking step size for a faster response. The voltage tracking step size for the second sampling point is determined based on the magnitude of the absolute value of the rate of change of light intensity. Specifically, the voltage tracking step size is positively correlated with the absolute value of the rate of change of light intensity; the larger the absolute value of the rate of change of light intensity, the larger the voltage tracking step size; conversely, the smaller the absolute value of the rate of change of light intensity, the smaller the voltage tracking step size. In one specific embodiment, the voltage tracking step size can be determined through a preset mapping table or functional relationship, for example, ,in, and These are preset coefficients.

[0045] When the absolute value of the rate of change of light intensity is less than or equal to a preset threshold, the illumination conditions are determined to be relatively stable. A smaller base voltage tracking step size is adopted or the current step size is not changed to maintain tracking accuracy and system stability.

[0046] The technical advantage of this embodiment is that by collecting light intensity data from adjacent sampling points and calculating the rate of change of light intensity, accurate identification of sudden light events is achieved; by dynamically determining the voltage tracking step size based on the magnitude of the absolute value of the rate of change of light intensity, MPPT can track quickly with a large step size when the light intensity changes rapidly, and lock accurately with a small step size when the light intensity is stable, thus overcoming the problem that traditional fixed step size methods cannot balance dynamic and steady-state performance.

[0047] In another embodiment of the photovoltaic energy storage coordinated control method provided by the present invention, step 200 specifically includes: Step 210: Extract the historical power-voltage relationship data of the photovoltaic power generation device to obtain the reference voltage, measured voltage, and measured power of all sampling points of the photovoltaic power generation device between the previous time and the current time; wherein, the reference voltage of the third sampling point is obtained based on the measured voltage, voltage tracking direction, and voltage tracking step size of the second sampling point; the voltage tracking direction of the second sampling point is obtained based on the measured voltage and measured power of the first sampling point, as well as the measured voltage and measured power of the second sampling point; the measured voltage of the third sampling point is measured under the action of the reference voltage of the second sampling point; Step 220: Based on the measured power of the photovoltaic power generation device at the last sampling point among all sampling points, obtain the maximum reference power of the photovoltaic power generation device at the current moment.

[0048] In this embodiment, the historical power-voltage relationship data includes the reference voltage, measured voltage, and measured power of all sampling points of the photovoltaic power generation device between the previous and current times. The measured voltage and measured current of each sampling point are collected at a preset sampling frequency (e.g., 50 times / second), and the measured power is calculated.

[0049] In one specific implementation, let the second sampling point be the sampling point (time) of the current control cycle. The first sampling point is the sampling point of the previous control cycle (time). First, obtain the measured voltage at the first sampling point. and measured power and the measured voltage at the second sampling point and measured power Calculate the power-voltage slope based on the above data. .like If the current operating point is determined to be to the left of the maximum power point, the voltage tracking direction is positive; if The system determines that the current operating point is to the right of the maximum power point, and the voltage tracking direction is negative.

[0050] The voltage tracking direction is aligned with the voltage tracking step size determined above. Multiply and superimpose the measured voltage at the second sampling point. Above, generate the reference voltage command for the third sampling point. The reference voltage command is output to the PWM modulator, which adjusts the operating voltage of the photovoltaic power generation device to the voltage value indicated by the reference voltage command at the third sampling point (the next control cycle). At the arrival of the third sampling point, the measured voltage of the photovoltaic power generation device under the action of the reference voltage command is acquired. and measured current Calculate the measured power .

[0051] The process iterates continuously across multiple sampling points in the manner described above. The reference voltage at each sampling point is determined based on the measured voltage, voltage tracking direction, and voltage tracking step size of the previous sampling point. The measured voltage at each sampling point is obtained under the influence of the reference voltage at the previous sampling point, until the power change at multiple consecutive sampling points is less than a preset accuracy threshold. At this point, the measured power at the last sampling point is taken as the maximum reference power of the photovoltaic power generation device at the current moment.

[0052] The technical advantage of this embodiment is that it clarifies that the maximum reference power is obtained by approximation cycle by cycle, rather than by a one-time calculation, thus ensuring the feasibility and convergence of the MPPT algorithm.

[0053] In another embodiment of the photovoltaic energy storage coordinated control method provided by the present invention, step 300 specifically includes: Step 310: Based on the load margin on the power consumption side, the state of charge of the hybrid energy storage device, and the maximum reference power of the photovoltaic power generation device, the target power is obtained; Step 320: When it is determined that the electricity consumption side is in a light-load state based on the load margin, the hybrid energy storage device is in a fully charged state based on the state of charge, the target power is less than the current output of the photovoltaic power generation device, and the current electricity price is in a low-price state, the current control operation is determined to include reducing the operating voltage of the photovoltaic power generation device; the feasible domain of the parameters of the current control operation is determined based on the target power and the current output. Step 330: When it is determined that the power consumption side is under heavy load based on the load margin, the hybrid energy storage device is under full charge based on the state of charge, the target power is greater than the current output of the photovoltaic power generation device, and the current electricity price is at its peak, the current control operation is determined to include increasing the output of the photovoltaic power generation device and discharging the hybrid energy storage device; the feasible domain of the parameters of the current control operation is determined based on the target power and the current output.

[0054] This embodiment provides a detailed explanation of "obtaining the feasible domain of current control parameters based on the load margin on the electricity consumption side, the state of charge of the hybrid energy storage device, the maximum reference power and current output of the photovoltaic power generation device, and the current electricity price status," and gives the following two typical operating conditions for determining the feasible domain.

[0055] Operating Scenario 1 (Light Load, Full Charge, Off-Peak Scenario): Based on the load margin of the power consumption side, it is determined that the power consumption side is currently in a light load state (e.g., the load margin is positive and greater than a first preset threshold). Based on the state of charge (SOC) of the hybrid energy storage device, it is determined that the device is in a full charge state (e.g., the SOC is greater than a preset high threshold, such as greater than 80% or 85%). The target power is calculated based on the load margin, SOC, and maximum reference power. ,when Less than the current output of the photovoltaic power generation device When the current electricity price is at a low point, the current regulatory operation will include reducing the operating voltage of the photovoltaic power generation device (i.e., active power curtailment or curtailment).

[0056] The feasible region of the current control operation parameters is based on the target power. and current efforts Specifically, the lower limit of the voltage reduction is defined as the threshold that causes the photovoltaic output to drop to [a certain value]. The required voltage adjustment amount is capped at the preset maximum allowable voltage drop.

[0057] Operating Scenario 2 (Heavy Load, Full Charge, Peak Scenario): Based on the load margin, it is determined that the power consumption side is currently under heavy load (e.g., the load margin is negative or less than the second preset threshold), and based on the SOC, it is determined that the hybrid energy storage device is fully charged. Calculations are obtained. Greater than the current output of the photovoltaic power generation device When the current electricity price is at its peak, the current regulatory actions will include increasing the output of photovoltaic power generation devices (i.e., tracking the maximum reference power) and discharging hybrid energy storage devices (to compensate for the power consumption). and (Power deficit between).

[0058] The feasible domain of the current control operation parameters is based on and It is determined that the target value for increasing photovoltaic output is the maximum reference power. The target value for energy storage discharge power is The upper limit of discharge power is constrained by the state of charge (SOC), the maximum discharge current, and the temperature state.

[0059] Specifically, target power The calculation method is as follows: ,in, This is the power correction amount on the grid side determined based on the load margin on the electricity consumption side; This is the power correction amount for the energy storage side determined based on the state of charge of the hybrid energy storage device.

[0060] The determination method is based on the magnitude and direction of the load margin on the power consumption side. When the load margin indicates that the power consumption side is in a heavy load state (i.e., there is a power deficit on the power consumption side, requiring external power support), Take a positive value; its magnitude is positively correlated with the degree of overload. The greater the degree of overload, The larger the positive value, the more likely the load margin indicates that the power consumption side is in a light-load state (i.e., the power consumption side has sufficient power and does not require additional power injection). Taking negative values, their magnitude is positively correlated with the degree of light load; the greater the degree of light load, the higher the value. The larger the absolute value of the negative value; when the load margin indicator shows that the power consumption side is in a normal state. Take zero or a small value close to zero.

[0061] In one specific implementation, the load margin can be quantified as a range of values. dimensionless coefficient Where +1 indicates that the power supply side urgently needs power support (heavy load limit); -1 indicates that the power supply side does not need power injection at all (light load limit); 0 indicates normal. ,in, This refers to the rated power of the photovoltaic energy storage system. For example, when the load margin corresponds to... =+2、 When =100W, =+20W means that the power consumption side needs the system to provide an additional 20W of power support.

[0062] Determination method: The controller determines the state of charge (SOC) of the hybrid energy storage device. When the SOC indicates that the energy storage device has low power (i.e., needs to be charged to replenish energy), A positive value encourages the system to generate more electricity or draw energy from the grid to charge energy storage. The lower the SOC, the better. The larger the positive value, the more likely the SOC (State of Charge) indicator is to be high (i.e., close to full charge, and not suitable for further charging). Taking a negative value inhibits the system from continuing to charge the energy storage; the higher the SOC, the better. The larger the absolute value of the negative value; when SOC is in the middle range Take zero or a small value close to zero.

[0063] In one specific implementation, SOC can be mapped to a value range of... dimensionless coefficient For example, when SOC ≤ 20%, =+1; when SOC≥90% =-1; when SOC is between 20% and 90% It decreases linearly between +1 and -1. ,in, A preset energy storage correction weighting coefficient (e.g., 0.3) is used to adjust the proportion of energy storage correction in the total correction. For example, when SOC = 85%, =-0.5、 =100W When =0.3, =-15W indicates that the target power is adjusted down by 15W because the energy storage is close to full charge, in order to suppress further charging.

[0064] Calculation example: The maximum reference power of a photovoltaic power generation device in a specific scenario. =100W, current output =90W. The power-side load margin indicator shows that the current condition is light load. =-0.1, =100W), then =-10W. Hybrid energy storage device SOC=88%, indicating near full charge ( =-0.6, =0.3), then =-18W. (This is the result.) =100W + (-10W) + (-18W) = 72W. Because, =72W is less than the current output of the photovoltaic system. =90W, the current control operation is determined to be to reduce the operating voltage of the photovoltaic power generation device, causing the photovoltaic output to drop from 90W to 72W. The excess 18W of power is reduced through active curtailment. At this time, the energy storage device is in standby mode, neither charging nor discharging.

[0065] In another specific scenario, the maximum reference power of the photovoltaic power generation device =100W, current output =90W. The power-side load margin indicator shows that the current condition is under heavy load. =+0.3, =100W), then =+30W. The hybrid energy storage device's SOC is 75%, which is in the middle range. =0), then =0W. (This is the result.) =100W + 30W + 0W = 130W. Because, =130W is greater than the current output of the photovoltaic system. =90W, and the maximum reference power of photovoltaic =100W is also less than The current control operation is determined to be to increase the output of the photovoltaic power generation device to the maximum reference power of 100W (MPPT), while simultaneously discharging the hybrid energy storage device with a discharge power of [missing information]. =130W - 100W = 30W (within the allowable discharge range of SOC and temperature). The system ultimately outputs a total power of 130W to the power consumer.

[0066] The technical effect of this embodiment is that by providing specific methods for determining the feasible region under two typical operating conditions—light load full-charge off-peak and heavy load full-charge peak—it clarifies how different combinations of five-dimensional data lead to different control operation types and parameter ranges, making the feasible region engineering feasible and providing a clear decision boundary for multi-objective optimization.

[0067] See Figure 2 , Figure 2 This is a flowchart illustrating another embodiment of the photovoltaic energy storage coordinated control method provided by the present invention, as shown below. Figure 2As shown, this embodiment follows step 200 above and includes steps 500 to 800, each of which is detailed below: Step 500: When it is determined that a charge / discharge operation is to be performed on the hybrid energy storage device, the charge / discharge power corresponding to the charge / discharge operation is obtained; Step 600: Extract high-frequency fluctuation power components with a frequency greater than or equal to a preset frequency from the charging and discharging power, and extract low-frequency fluctuation power components with a frequency less than the preset frequency. Step 700: Store the high-frequency fluctuation power component into the electrochemical energy storage capacitor, or control the electrochemical energy storage capacitor to release the power corresponding to the high-frequency fluctuation power component. Step 800: Store the low-frequency fluctuation power component into the electrochemical energy storage battery, or control the electrochemical energy storage battery to release the power corresponding to the low-frequency fluctuation power component.

[0068] This embodiment refines the frequency power allocation of the aforementioned hybrid energy storage device. The hybrid energy storage device includes an electrochemical energy storage battery (e.g., a lithium battery) and an electrochemical energy storage capacitor (e.g., a supercapacitor). When determining to perform a charge / discharge operation on the hybrid energy storage device, the charge / discharge power command (total power value) corresponding to the charge / discharge operation is first obtained.

[0069] The charging / discharging power command is frequency-decomposed using a second-order Butterworth low-pass filter. In this embodiment, the second-order Butterworth low-pass filter separates the input power signal into low-frequency and high-frequency components, with a cutoff frequency set to a preset value (e.g., 0.5Hz). The portion of the power signal with frequencies below the cutoff frequency is the low-frequency fluctuating power component, and the portion with frequencies above the cutoff frequency is the high-frequency fluctuating power component.

[0070] In discharge mode, the power value corresponding to the high-frequency power fluctuation component is used as the discharge command for the supercapacitor, controlling it to release that power; the power value corresponding to the low-frequency power fluctuation component is used as the discharge command for the lithium battery, controlling it to release that power. In charging mode, the power value corresponding to the high-frequency power fluctuation component is used as the charging command for the supercapacitor, controlling it to absorb that power; the power value corresponding to the low-frequency power fluctuation component is used as the charging command for the lithium battery, controlling it to absorb that power. The supercapacitor and lithium battery respond in parallel within the same control cycle, jointly synthesizing the total charge and discharge power command.

[0071] In one specific implementation, when the total energy storage power command is 20W and the command contains instantaneous fluctuations of ±2W, the lithium battery undertakes a smooth base power of approximately 18W to 19W, and the supercapacitor undertakes fluctuation compensation power of ±1W to 2W. The two are superimposed in real time to present a total power output of 20W to the outside world.

[0072] In this embodiment, the electrochemical energy storage battery serves to handle the low-frequency smoothing component of the power signal, providing continuous and stable energy throughput. The electrochemical energy storage capacitor, on the other hand, handles the high-frequency fluctuation component of the power signal, providing rapid and instantaneous power compensation. Working together, they leverage both the high energy density of lithium batteries and the high power density, fast response speed, and long cycle life of supercapacitors.

[0073] The technical advantage of this embodiment is that by decomposing the charging and discharging power command into high-frequency and low-frequency components, which are respectively handled by the supercapacitor and the lithium battery, the lithium battery is prevented from aging rapidly due to frequent responses to high-frequency power fluctuations, thus extending the service life of the lithium battery. At the same time, the millisecond-level response characteristics of the supercapacitor effectively suppress the impact of power fluctuations on the power grid, improving the quality and stability of the system's output power.

[0074] The photovoltaic energy storage coordinated control system provided by the present invention is described below. The photovoltaic energy storage coordinated control system described below can be referred to in correspondence with the photovoltaic energy storage coordinated control method described above.

[0075] Please refer to Figure 3 The present invention also provides a photovoltaic energy storage coordinated control system, comprising: The voltage tracking step size determination module 301 is used to determine the voltage tracking step size based on the rate of change of light intensity when the absolute value of the rate of change of light intensity of the photovoltaic power generation device is greater than a preset threshold. The maximum reference power determination module 302 is used to obtain the maximum reference power of the photovoltaic power generation device based on the historical power-voltage relationship data of the photovoltaic power generation device and the voltage tracking step size; The current control parameter feasible region determination module 303 is used to obtain the current control parameter feasible region based on the load margin on the power consumption side, the state of charge of the hybrid energy storage device, the maximum reference power and current output of the photovoltaic power generation device, and the current electricity price status. The collaborative control module 304 is used to perform optimization operations on the feasible domain of the current control parameters based on preset multi-objectives to obtain the operation parameter correction amount, and to perform collaborative control of the photovoltaic power generation device and the hybrid energy storage device based on the operation parameter correction amount.

[0076] Optionally, the voltage tracking step size determination module includes: The light intensity acquisition unit is used to acquire the light intensity of the first sampling point and the second sampling point that are adjacent in time sequence of the photovoltaic power generation device. The light intensity change rate determination unit is used to obtain the light intensity change rate of the photovoltaic power generation device based on the light intensity of the first sampling point and the light intensity of the second sampling point; The voltage tracking step size determination unit is used to determine the voltage tracking step size of the second sampling point based on the absolute value of the light intensity change rate when the absolute value is greater than a preset threshold.

[0077] Optionally, the maximum reference power determination module includes: The data extraction unit is used to extract historical power-voltage relationship data of the photovoltaic power generation device to obtain the reference voltage, measured voltage, and measured power of all sampling points of the photovoltaic power generation device between the previous time and the current time. The reference voltage of the third sampling point is obtained based on the measured voltage, voltage tracking direction, and voltage tracking step size of the second sampling point. The voltage tracking direction of the second sampling point is obtained based on the measured voltage and measured power of the first sampling point, as well as the measured voltage and measured power of the second sampling point. The measured voltage of the third sampling point is measured under the influence of the reference voltage of the second sampling point. The maximum reference power determination unit is used to obtain the maximum reference power of the photovoltaic power generation device at the current moment based on the measured power of the last sampling point among all sampling points.

[0078] Optionally, the current control parameter feasible domain determination module includes: The target power determination unit is used to obtain the target power based on the load margin on the power consumption side, the state of charge of the hybrid energy storage device, and the maximum reference power of the photovoltaic power generation device. The first parameter feasible region determination unit is used to determine that the current control operation includes reducing the operating voltage of the photovoltaic power generation device when the power consumption side is determined to be in a light load state based on the load margin, the hybrid energy storage device is determined to be in a fully charged state based on the state of charge, the target power is less than the current output of the photovoltaic power generation device, and the current electricity price is in a low-price state; the parameter feasible region of the current control operation is determined based on the target power and the current output. The second parameter feasible region determination unit is used to determine that the current control operation includes increasing the output of the photovoltaic power generation device and discharging the hybrid energy storage device when the power consumption side is determined to be under heavy load based on the load margin, the hybrid energy storage device is determined to be under full charge based on the state of charge, the target power is greater than the current output of the photovoltaic power generation device, and the current electricity price is at its peak. The parameter feasible region of the current control operation is determined based on the target power and the current output.

[0079] Optionally, the system further includes: The charge / discharge power determination module is used to obtain the charge / discharge power corresponding to the charge / discharge operation when it is determined that a charge / discharge operation will be performed on the hybrid energy storage device. The fluctuating power component extraction module is used to extract high-frequency fluctuating power components with a frequency greater than or equal to a preset frequency from the charging and discharging power, and to extract low-frequency fluctuating power components with a frequency less than the preset frequency. A capacitor charging and discharging module is used to store the high-frequency fluctuating power component into the electrochemical energy storage capacitor, or to control the electrochemical energy storage capacitor to release the power corresponding to the high-frequency fluctuating power component. The battery charging and discharging module is used to store the low-frequency fluctuation power component into the electrochemical energy storage battery, or to control the electrochemical energy storage battery to release the power corresponding to the low-frequency fluctuation power component.

[0080] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the appended claims.

Claims

1. A method for coordinated regulation of photovoltaic energy storage, characterized in that the method... include: When the absolute value of the rate of change of light intensity of the photovoltaic power generation device is greater than a preset threshold, the voltage tracking step size is determined based on the rate of change of light intensity. Based on the historical power-voltage relationship data of the photovoltaic power generation device and the voltage tracking step size, the maximum reference power of the photovoltaic power generation device is obtained. Based on the load margin on the electricity consumption side, the state of charge of the hybrid energy storage device, the maximum reference power and current output of the photovoltaic power generation device, and the current electricity price status, the feasible region of the current control parameters is obtained. Based on preset multi-objective optimization operations, the feasible domain of the current control parameters is optimized to obtain the operation parameter correction amount, and the photovoltaic power generation device and the hybrid energy storage device are coordinated and controlled based on the operation parameter correction amount.

2. The photovoltaic energy storage coordinated regulation method as described in claim 1, characterized in that, When the absolute value of the rate of change of light intensity of the photovoltaic power generation device is greater than a preset threshold, determining the voltage tracking step size based on the rate of change of light intensity includes: Acquire the light intensity of the first and second sampling points that are adjacent in time sequence of the photovoltaic power generation device; The light intensity change rate of the photovoltaic power generation device is obtained based on the light intensity of the first sampling point and the light intensity of the second sampling point. When the absolute value of the light intensity change rate is greater than a preset threshold, the voltage tracking step size of the second sampling point is obtained based on the absolute value.

3. The photovoltaic energy storage coordinated regulation method as described in claim 2, characterized in that, The process of obtaining the maximum reference power of the photovoltaic power generation device based on its historical power-voltage relationship data and the voltage tracking step size includes: Historical power-voltage relationship data of the photovoltaic power generation device are extracted to obtain the reference voltage, measured voltage, and measured power of all sampling points of the photovoltaic power generation device between the previous time and the current time. The reference voltage of the third sampling point is obtained based on the measured voltage, voltage tracking direction, and voltage tracking step size of the second sampling point. The voltage tracking direction of the second sampling point is obtained based on the measured voltage and measured power of the first sampling point, as well as the measured voltage and measured power of the second sampling point. The measured voltage of the third sampling point is measured under the influence of the reference voltage of the second sampling point. Based on the measured power of the photovoltaic power generation device at the last sampling point among all sampling points, the maximum reference power of the photovoltaic power generation device at the current moment is obtained.

4. The photovoltaic energy storage coordinated regulation method as described in claim 1, characterized in that, The feasible domain for obtaining the current control parameters based on the load margin on the electricity consumption side, the state of charge of the hybrid energy storage device, the maximum reference power and current output of the photovoltaic power generation device, and the current electricity price status includes: The target power is obtained based on the load margin on the electricity consumption side, the state of charge of the hybrid energy storage device, and the maximum reference power of the photovoltaic power generation device. When the load margin determines that the electricity consumption side is under light load, the state of charge determines that the hybrid energy storage device is under full charge, the target power is less than the current output of the photovoltaic power generation device, and the current electricity price is at a low point, the current control operation is determined to include reducing the operating voltage of the photovoltaic power generation device; the feasible domain of the parameters of the current control operation is determined based on the target power and the current output. When the load margin determines that the electricity consumption side is under heavy load, the state of charge determines that the hybrid energy storage device is fully charged, the target power is greater than the current output of the photovoltaic power generation device, and the current electricity price is at its peak, the current control operation is determined to include increasing the output of the photovoltaic power generation device and discharging the hybrid energy storage device; the feasible domain of the parameters of the current control operation is determined based on the target power and the current output.

5. The photovoltaic energy storage coordinated regulation method as described in claim 4, characterized in that, The hybrid energy storage device includes an electrochemical energy storage battery and an electrochemical energy storage capacitor; after obtaining the maximum reference power of the photovoltaic power generation device based on the historical power-voltage relationship data of the photovoltaic power generation device and the voltage tracking step size, the process includes: When determining to perform a charge / discharge operation on the hybrid energy storage device, the charge / discharge power corresponding to the charge / discharge operation is obtained; Extract high-frequency fluctuation power components with a frequency greater than or equal to a preset frequency from the charging and discharging power, and extract low-frequency fluctuation power components with a frequency less than the preset frequency. The high-frequency fluctuation power component is stored in the electrochemical energy storage capacitor, or the electrochemical energy storage capacitor is controlled to release the power corresponding to the high-frequency fluctuation power component. The low-frequency fluctuation power component is stored in the electrochemical energy storage battery, or the electrochemical energy storage battery is controlled to release the power corresponding to the low-frequency fluctuation power component.

6. A photovoltaic energy storage coordinated control system, characterized in that, include: The voltage tracking step size determination module is used to determine the voltage tracking step size based on the rate of change of light intensity when the absolute value of the rate of change of light intensity of the photovoltaic power generation device is greater than a preset threshold. The maximum reference power determination module is used to obtain the maximum reference power of the photovoltaic power generation device based on the historical power-voltage relationship data of the photovoltaic power generation device and the voltage tracking step size; The current control parameter feasible region determination module is used to obtain the current control parameter feasible region based on the load margin on the electricity consumption side, the state of charge of the hybrid energy storage device, the maximum reference power and current output of the photovoltaic power generation device, and the current electricity price status. The collaborative control module is used to perform optimization operations on the feasible domain of the current control parameters based on preset multi-objectives to obtain the operating parameter correction amount, and to perform collaborative control of the photovoltaic power generation device and the hybrid energy storage device based on the operating parameter correction amount.

7. The photovoltaic energy storage coordinated control system as described in claim 6, characterized in that, The voltage tracking step size determination module includes: The light intensity acquisition unit is used to acquire the light intensity of the first sampling point and the second sampling point that are adjacent in time sequence of the photovoltaic power generation device. The light intensity change rate determination unit is used to obtain the light intensity change rate of the photovoltaic power generation device based on the light intensity of the first sampling point and the light intensity of the second sampling point; The voltage tracking step size determination unit is used to determine the voltage tracking step size of the second sampling point based on the absolute value of the light intensity change rate when the absolute value is greater than a preset threshold.

8. The photovoltaic energy storage coordinated control system as described in claim 7, characterized in that, The maximum reference power determination module includes: The data extraction unit is used to extract historical power-voltage relationship data of the photovoltaic power generation device to obtain the reference voltage, measured voltage, and measured power of all sampling points of the photovoltaic power generation device between the previous time and the current time. The reference voltage of the third sampling point is obtained based on the measured voltage, voltage tracking direction, and voltage tracking step size of the second sampling point. The voltage tracking direction of the second sampling point is obtained based on the measured voltage and measured power of the first sampling point, as well as the measured voltage and measured power of the second sampling point. The measured voltage of the third sampling point is measured under the influence of the reference voltage of the second sampling point. The maximum reference power determination unit is used to obtain the maximum reference power of the photovoltaic power generation device at the current moment based on the measured power of the last sampling point among all sampling points.

9. The photovoltaic energy storage coordinated control system as described in claim 6, characterized in that, The current control parameter feasible region determination module includes: The target power determination unit is used to obtain the target power based on the load margin on the power consumption side, the state of charge of the hybrid energy storage device, and the maximum reference power of the photovoltaic power generation device. The first parameter feasible region determination unit is used to determine that the current control operation includes reducing the operating voltage of the photovoltaic power generation device when the power consumption side is determined to be in a light load state based on the load margin, the hybrid energy storage device is determined to be in a fully charged state based on the state of charge, the target power is less than the current output of the photovoltaic power generation device, and the current electricity price is in a low-price state; the parameter feasible region of the current control operation is determined based on the target power and the current output. The second parameter feasible region determination unit is used to determine that the current control operation includes increasing the output of the photovoltaic power generation device and discharging the hybrid energy storage device when the power consumption side is determined to be under heavy load based on the load margin, the hybrid energy storage device is determined to be under full charge based on the state of charge, the target power is greater than the current output of the photovoltaic power generation device, and the current electricity price is at its peak. The parameter feasible region of the current control operation is determined based on the target power and the current output.

10. The photovoltaic energy storage coordinated control system as described in claim 9, characterized in that, The hybrid energy storage device includes an electrochemical energy storage battery and an electrochemical energy storage capacitor; the system also includes: The charge / discharge power determination module is used to obtain the charge / discharge power corresponding to the charge / discharge operation when it is determined that a charge / discharge operation will be performed on the hybrid energy storage device. The fluctuating power component extraction module is used to extract high-frequency fluctuating power components with a frequency greater than or equal to a preset frequency from the charging and discharging power, and to extract low-frequency fluctuating power components with a frequency less than the preset frequency. A capacitor charging and discharging module is used to store the high-frequency fluctuating power component into the electrochemical energy storage capacitor, or to control the electrochemical energy storage capacitor to release the power corresponding to the high-frequency fluctuating power component. The battery charging and discharging module is used to store the low-frequency fluctuation power component into the electrochemical energy storage battery, or to control the electrochemical energy storage battery to release the power corresponding to the low-frequency fluctuation power component.

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