Adaptive adjustment and control method and system for photovoltaic storage coordination supporting network construction

Abstract

This invention discloses a photovoltaic-storage coordinated adaptive regulation and control method and system supported by grid-type energy storage, belonging to the field of photovoltaic-storage coordinated regulation technology. It includes: analyzing the mode amplification risk factors of each photovoltaic node, determining the regulation execution path of each photovoltaic node, adaptively regulating each device of each regulated photovoltaic node through reactive power regulation, analyzing the state-of-charge (SOC) parameters of the energy storage system, analyzing the first regulation execution path of the energy storage system, suppressing nonlinear notch waves through decoupling interleaved responses, and analyzing the second regulation execution path of the energy storage system. This invention can identify mode amplification risks and nonlinear notch wave phenomena in stages, and perform decoupling coordinated regulation between the photovoltaic system and the energy storage system, improving the voltage stability and power quality of photovoltaic output, enhancing the energy storage system's ability to suppress complex disturbances, reducing grid voltage fluctuations and frequency domain resonance risks, and improving grid stability.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic-storage coordinated regulation technology, and in particular to a photovoltaic-storage coordinated adaptive regulation and control method and system supported by grid-type energy storage. Background Technology

[0002] Distributed photovoltaic (PV) systems are primarily connected to the grid via inverters, outputting active power based on environmental parameters such as local irradiance and module temperature, and possessing a certain degree of reactive power regulation capability. Their operation is significantly affected by weather conditions, and power output exhibits dynamic variations over time. To improve the controllability and grid adaptability of PV power generation, energy storage systems are being gradually deployed. Common energy storage systems include electrochemical cells and energy management controllers, typically connected to the distribution network via power storage converters (PCS). Depending on their coordination with the grid, energy storage systems mainly fall into two operating modes: grid-connected and grid-connected.

[0003] In existing applications, grid-based energy storage systems possess the ability to autonomously construct target voltage waveforms and frequency references. Their inverters can operate independently or in a dominant mode based on strategies such as Virtual Synchronous Machine (VSG) control and droop control. In islanded, weak grid, or microgrid environments, grid-based energy storage can act as both a frequency and voltage source. These systems support collaborative operation with other grid-based or grid-connected devices, adapting to the coordinated control requirements of multi-source distributed systems.

[0004] For example, Chinese invention patent CN113364042B discloses a method and system for coordinated optimization configuration of photovoltaic and energy storage in a data center, which includes: obtaining typical parameters of the data center and the load power and grid electricity price of the data center during each time period of a typical day; inputting the typical parameters and the load power and grid electricity price of the data center during each time period of a typical day into a pre-established coordinated optimization configuration model of photovoltaic and energy storage to obtain the capacity of the energy storage battery and the photovoltaic installed capacity; wherein, the coordinated optimization configuration model of photovoltaic and energy storage is established based on the power supply reliability of the data center.

[0005] For example, Chinese invention patent CN114336703B discloses an automatic coordinated control method for large-scale wind-solar-storage power stations, which includes the following steps: Step 1: Smoothing the active power demand of energy storage fluctuating with wind and solar power; Step 2: Tracking the active power demand of energy storage according to the planned curve; Step 3: Smoothing the total active power demand of energy storage fluctuating with wind and solar power and tracking the planned curve.

[0006] The above-mentioned technology has at least the following technical problems:

[0007] Under specific feeder topologies and equivalent impedance structures, when multiple distributed photovoltaic systems simultaneously experience periodic power disturbances due to weather changes (such as cloud cover), the disturbance frequency couples with the voltage response mode frequency of the local power grid, forming a spatially fixed, time-periodic voltage amplification mode. To address this mode amplification, energy storage controllers or inverters employ dynamic reactive power support, droop control, or lag voltage compensation strategies to attempt to "suppress amplified fluctuations." However, if multiple energy storage / inverter devices simultaneously identify and respond to disturbances, reactive power is injected at voltage drops and absorbed at voltage rises. Due to a lack of communication and coordination, these devices exhibit "interleaved control" with inconsistent adjustment directions and misaligned rhythms in space. The phase misalignment and lag superposition result in a periodic "notch-surge" nonlinear characteristic in the voltage waveform. If the notch depth exceeds the device's voltage dead zone, it may trigger malfunctions, causing frequent "sink-surge" transients at local nodes, ultimately leading to frequent charging and discharging switching of energy storage and resulting in lifespan loss. Summary of the Invention

[0008] To address the aforementioned technical problems in existing technologies, embodiments of the present invention provide a photovoltaic-storage collaborative adaptive regulation and control method and system supported by grid-type energy storage. The technical solution is as follows:

[0009] On the one hand, a photovoltaic-storage collaborative adaptive regulation and control method supporting grid-type energy storage is provided, including:

[0010] Real-time monitoring of each photovoltaic node is conducted to analyze the modal amplification risk factors of each photovoltaic node and determine the control execution path of each photovoltaic node.

[0011] When the control execution path of the photovoltaic node is to perform mode amplification suppression regulation, the corresponding photovoltaic node is recorded as the control photovoltaic node. The reactive power regulation is used to adaptively regulate each device of each control photovoltaic node, and the change parameters of the state of charge of the energy storage system are analyzed after the regulation is completed.

[0012] Based on the parameter analysis of the change in the state of charge of the energy storage system, the first control execution path of the energy storage system is analyzed. When the first control execution path of the energy storage system is to perform nonlinear notch suppression regulation, nonlinear notch is suppressed by decoupling the interleaved response. After the regulation is completed, the second control execution path of the energy storage system is analyzed.

[0013] On the other hand, a photovoltaic-storage collaborative adaptive regulation and control system supporting grid-type energy storage is provided. The system includes: a regulation execution path determination module, a mode amplification suppression regulation module, and a nonlinear notch suppression regulation module.

[0014] The control execution path determination module is used to monitor each photovoltaic node in real time, analyze the modal amplification risk factors of each photovoltaic node, and determine the control execution path of each photovoltaic node.

[0015] The mode amplification suppression regulation module is used to record the corresponding photovoltaic node as the regulated photovoltaic node when the regulation execution path of the photovoltaic node is to perform mode amplification suppression regulation. It adaptively regulates each device of each regulated photovoltaic node through reactive power regulation, and analyzes the change parameters of the state of charge of the energy storage system after the regulation is completed.

[0016] The nonlinear notch suppression regulation module is used to analyze the first regulation execution path of the energy storage system based on the parameter of the change in the state of charge of the energy storage system. When the first regulation execution path of the energy storage system is to perform nonlinear notch suppression regulation, it suppresses the nonlinear notch by decoupling the interleaved response, and analyzes the second regulation execution path of the energy storage system after the regulation is completed.

[0017] The beneficial effects of the technical solutions provided by the embodiments of the present invention include at least the following:

[0018] 1. The photovoltaic-storage collaborative adaptive regulation and control method provided by the present invention can identify the risk of modal amplification and nonlinear notch phenomenon in stages, and perform decoupled collaborative regulation between the photovoltaic system and the energy storage system, thereby improving the voltage stability and power quality of photovoltaic output, enhancing the energy storage system's ability to suppress complex disturbances, reducing the risk of grid voltage fluctuations and frequency domain resonance, and improving grid stability.

[0019] 2. By determining the control execution path for each photovoltaic node, this invention enables differentiated identification of voltage disturbance risks at different photovoltaic nodes. This ensures that the system only implements targeted reactive power regulation on nodes with modal amplification risks, avoiding resource waste and system disturbances caused by ineffective or excessive regulation. Simultaneously, it provides more accurate numerical data for subsequent photovoltaic-energy storage linkage, contributing to the construction of a highly efficient, precisely distributed, and orderly regional collaborative control system, thereby improving the dynamic stability and operational reliability of the overall photovoltaic-energy storage system.

[0020] 3. By analyzing the first regulation execution path of the energy storage system, this invention can identify the presence of nonlinear notch risk based on the state of charge change characteristics of the energy storage system after the photovoltaic node has completed the initial regulation. This allows for the determination of whether further intervention is needed to regulate the energy storage system, enabling early perception and warning triggering of abnormal dynamics. This ensures that the energy storage system can intervene precisely when it has the necessity and capability to regulate, thereby improving the overall system's response efficiency and regulation stability to complex disturbances and avoiding new voltage anomalies caused by improper timing or strategy of regulation. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a schematic diagram of the photovoltaic-storage collaborative adaptive regulation and control method provided in an embodiment of the present invention.

[0023] Figure 2 This is a structural diagram of the photovoltaic-storage collaborative adaptive regulation and control system provided in an embodiment of the present invention.

[0024] Figure 3 This is a flowchart illustrating the combined modal amplification identification and reactive power adaptive adjustment process involved in an embodiment of the present invention.

[0025] Figure 4 This is a flowchart illustrating the combined analysis of charge state change parameters and notch filtering strategy in an embodiment of the present invention. Detailed Implementation

[0026] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0027] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0028] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0029] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0030] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0031] This invention provides a photovoltaic-storage collaborative adaptive regulation and control method and system supported by grid-type energy storage. Grid-type energy storage refers to an energy storage system with "grid-building capability", that is, an energy storage system that can actively establish voltage, current, and frequency references in the absence of a main grid (or a weak grid). In this invention, when the voltage or frequency is unstable, it takes priority in participating in control and actively builds a stable operating reference.

[0032] Photovoltaic-storage synergy refers to the coordinated control of a photovoltaic power generation system and a battery energy storage system to smooth out fluctuations in photovoltaic output, utilize energy storage for frequency / voltage / peak regulation, improve photovoltaic grid integration, and alleviate curtailment issues. In this invention, the energy storage system dynamically responds to the fluctuating behavior of photovoltaic power generation and completes coordinated control through control logic.

[0033] like Figure 1 The schematic diagram shown illustrates the photovoltaic-storage collaborative adaptive regulation and control method for grid-type energy storage support, including:

[0034] Real-time monitoring of each photovoltaic node is conducted to analyze the modal amplification risk factors of each photovoltaic node and determine the control execution path of each photovoltaic node.

[0035] like Figure 3 The diagram shows a combined flowchart of modal amplification identification and reactive power adaptive adjustment involved in an embodiment of the present invention. First, the modal amplification risk factor of each photovoltaic node is analyzed, and it is determined whether it is greater than or equal to the modal amplification risk factor threshold. If the condition is met, the node is marked as a control photovoltaic node, its modal amplification risk deviation factor is calculated, and the corresponding reactive power adjustment benchmark value is matched. Then, the voltage fluctuation of the equipment is collected, and it is determined whether it exceeds the voltage fluctuation trigger threshold. If it is met, it is marked as a demand control device, and its reactive power adjustment value is further determined. Adaptive reactive power adjustment of the control photovoltaic node is completed in conjunction with the reactive power direction. If the control conditions are not met, it is set to continuous monitoring status.

[0036] Example 1: Analysis of the modal amplification risk factors for each photovoltaic node. The analysis process is as follows:

[0037] The modal amplification characterization parameters of each photovoltaic node are collected, including the rate of change of active power output, voltage fluctuation frequency, equivalent impedance, and voltage amplitude change of each photovoltaic node.

[0038] It should be noted that the rate of change of active power output refers to the rate of change of active power output by the photovoltaic node, reflecting the instantaneous fluctuation intensity of the photovoltaic system's output power. Its value is usually obtained by calculating the ratio of the active power difference to the time interval within a continuous time window, with the unit being kilowatts per minute. The aforementioned active power difference refers to the difference between the maximum and minimum active power values ​​within a continuous time window.

[0039] Voltage fluctuation frequency refers to the dominant frequency component of the voltage amplitude change over time at a photovoltaic node, representing the periodic characteristics of voltage fluctuation. It is determined by extracting the frequency component with the largest energy proportion after performing frequency domain transformation (such as fast Fourier transform) on the node voltage signal, and the unit is Hertz.

[0040] Equivalent impedance refers to the overall impedance experienced by a photovoltaic node when it injects disturbance current into the grid, in a topology structure where the photovoltaic node is connected to the grid. It includes equivalent resistance and equivalent reactance components, and reflects the sensitivity of the node to voltage response to disturbance current. The unit is ohms, and it can be obtained through PMU (Phasor Measurement Unit) technology.

[0041] Voltage amplitude change refers to the difference between the maximum and minimum values ​​of the photovoltaic node voltage, reflecting the transient fluctuation amplitude of the node voltage. It is used to measure the voltage deviation intensity caused by power disturbances, and the unit is volts. It is collected by a voltage sensor.

[0042] There is a significant dynamic coupling relationship between the rate of change of active power output, voltage fluctuation frequency, equivalent impedance, and voltage amplitude change. When the rate of change of active power output of a photovoltaic system increases, especially when rapid power increases or decreases occur in a short period of time, it will cause abrupt changes in node voltage, leading to an increase in voltage amplitude change. If this change is coupled with the equivalent impedance of the node, it is more likely to cause voltage response amplification in regions with higher impedance, causing the voltage fluctuation frequency to tend to concentrate and forming frequency domain disturbance characteristics. At the same time, the change in voltage fluctuation frequency will further affect the response rhythm of voltage control equipment, thereby affecting the system's ability to absorb and regulate active power disturbances, forming a positive feedback effect.

[0043] Extract the defined active power output change rate, defined equivalent impedance, and defined voltage amplitude change stored in the database.

[0044] Extract grid mode frequencies from the system program log.

[0045] The changes in active power output, equivalent impedance, and voltage amplitude are compared with their corresponding threshold values ​​to obtain the proportionality coefficients for the changes in active power output, equivalent impedance, and voltage amplitude.

[0046] It should be explained that the active power output change rate is divided by the defined active power output change rate to obtain the active power output change rate proportionality coefficient, the equivalent impedance is divided by the defined equivalent impedance to obtain the equivalent impedance proportionality coefficient, and the voltage amplitude change is divided by the defined voltage amplitude change to obtain the voltage amplitude change proportionality coefficient.

[0047] The voltage fluctuation frequency and the grid mode frequency are processed to remove the deviation, and the grid mode frequency is compared with the deviation processing result to obtain the voltage fluctuation frequency proportionality coefficient.

[0048] It should also be explained that the voltage fluctuation frequency proportionality coefficient is obtained by subtracting the grid mode frequency from the voltage fluctuation frequency to obtain the deviation frequency, and then dividing the grid mode frequency by the sum of the deviation frequency and a small positive number to obtain the voltage fluctuation frequency proportionality coefficient.

[0049] In this embodiment, a small positive number is introduced when performing the comparison calculation to ensure that the ratio is defined across the entire frequency band. The small positive number is a positive number that is close to zero but not zero and is preset in the database. It is usually much smaller than the actual measured value and is used to ensure that the denominator is always greater than zero.

[0050] It should be noted that when the voltage fluctuation frequency is exactly or approximately the power grid mode frequency, a modal resonance amplification phenomenon will occur.

[0051] Extract the pre-defined active power output change rate proportional coefficient feature allocation factor, voltage fluctuation frequency proportional coefficient feature allocation factor, equivalent impedance proportional coefficient feature allocation factor, and voltage amplitude change proportional coefficient feature allocation factor from the database.

[0052] In this embodiment, to achieve weighted coupling calculation of photovoltaic node modal amplification risk factors, a multi-dimensional feature factor configuration system is pre-established in the database to associate different proportional coefficients with their corresponding feature allocation factors. Specifically, the system defines the feature allocation factors corresponding to the active power output change rate proportional coefficient, voltage fluctuation frequency proportional coefficient, equivalent impedance proportional coefficient, and voltage amplitude change proportional coefficient through a configuration table. The configuration table is stored in the database in the form of a structured parameter mapping (such as a feature factor configuration table), which can support condition matching based on proportional coefficient ranges or levels. In actual operation, the system dynamically extracts the matching feature allocation factor values ​​from the configuration table according to the proportional coefficients of the current node, which are used for subsequent weighted modeling of modal amplification risk. The values ​​of all feature allocation factors are limited to between 0 and 1, and the sum of the four allocation factors is 1, in order to maintain the normalization property and mathematical consistency of the modal risk coupling model, and ensure that the contribution of each feature to the final risk indicator has a clear weight distribution structure.

[0053] By weighting and coupling the proportional coefficients of active power output change rate, voltage fluctuation frequency, equivalent impedance, and voltage amplitude change through characteristic allocation factors, the modal amplification risk factor is obtained.

[0054] In a specific embodiment, the modal amplification risk factor is represented as follows:

[0055] ,

[0056] Where A is the modal amplification risk factor, a is the active power output change rate proportional coefficient, b is the voltage fluctuation frequency proportional coefficient, c is the equivalent impedance proportional coefficient, d is the voltage amplitude change proportional coefficient, x1 is the active power output change rate proportional coefficient characteristic allocation factor, x2 is the voltage fluctuation frequency proportional coefficient characteristic allocation factor, x3 is the equivalent impedance proportional coefficient characteristic allocation factor, and x4 is the voltage amplitude change proportional coefficient characteristic allocation factor.

[0057] By iterating through each photovoltaic node, the modal amplification risk factor of each photovoltaic node is obtained.

[0058] Furthermore, the control execution path for each photovoltaic node is determined, and the analysis process is as follows:

[0059] If the modal amplification risk factor of a photovoltaic node is greater than or equal to the preset modal amplification risk factor threshold in the database, then the regulation execution path of that photovoltaic node is recorded as performing modal amplification suppression regulation.

[0060] In this embodiment, if the modal amplification risk factor of a photovoltaic node is greater than or equal to the preset modal amplification risk factor threshold in the database, it indicates that the node's current operating state has a high risk of modal resonance. This is manifested in its drastic fluctuations in active power output, voltage fluctuation frequencies close to the system modal frequencies, high equivalent impedance, and significant voltage amplitude disturbances, which can easily lead to amplification or instability in the local node voltage response. At this time, the photovoltaic node is no longer suitable for continuous observation and requires active intervention and control. Therefore, its control execution path is determined to be modal amplification suppression regulation, which suppresses the local modal response that may be induced by reactive power regulation and other means, thereby reducing the impact on the grid voltage stability.

[0061] If the modal amplification risk factor of a photovoltaic node is less than the modal amplification risk factor threshold, then the control execution path of that photovoltaic node is recorded as continuous monitoring.

[0062] If the modal amplification risk factor of a photovoltaic node is less than the modal amplification risk factor threshold, it indicates that the node is within a relatively stable or controllable range in the current cycle, and its operating state has not yet posed a significant modal resonance risk to the grid voltage. The node can continue to maintain its current operating state without immediate adjustment. Therefore, its control execution path is set to continuous monitoring to dynamically track changes in its operating state in future cycles.

[0063] By traversing each photovoltaic node, the control execution path for each photovoltaic node can be determined.

[0064] When the control execution path of the photovoltaic node is to perform mode amplification suppression regulation, the corresponding photovoltaic node is recorded as the control photovoltaic node. The reactive power regulation is used to adaptively regulate each device of each control photovoltaic node, and the change parameters of the state of charge of the energy storage system are analyzed after the regulation is completed.

[0065] Example 2: Adaptive control of each device at each photovoltaic node is achieved through reactive power regulation. The specific analysis process is as follows:

[0066] Modal amplification risk factors for each photovoltaic node are extracted based on the modal amplification risk factors of each photovoltaic node.

[0067] For a regulated photovoltaic node: the modal amplification risk factor threshold is subtracted from the modal amplification risk factor threshold of the regulated photovoltaic node to obtain the modal amplification risk deviation factor.

[0068] The reactive power benchmark adjustment value is matched based on the modal amplification risk deviation factor.

[0069] In this embodiment, to achieve precise response in modal amplification control, the system pre-establishes a mapping relationship between modal amplification risk deviation factors and corresponding reactive power reference adjustment values ​​in the database. This mapping relationship is managed and accessed in the form of a structured configuration data table (e.g., a reactive power adjustment parameter configuration table). During the actual matching process, the system extracts the modal amplification risk deviation factor of the target photovoltaic node and uses it as an index parameter to retrieve the corresponding reactive power reference adjustment value set in the configuration table. This adjustment value set includes the basic reactive power compensation amount and its adaptive adjustment range, which can be flexibly amplified or contracted according to the node's risk level. By finding the reactive power reference value corresponding to the current deviation factor, the system can implement differentiated reactive power adjustment strategies for different modal risk levels, thereby effectively improving the control accuracy and stability of local voltage modal response.

[0070] It should be added that the larger the mode amplification risk deviation factor, the stronger the mode amplification trend of the target photovoltaic node and the higher the local accumulation risk of voltage disturbance. In order to enhance the reactive power support capability of such high-risk nodes and improve their suppression response strength to voltage mode changes, the corresponding reactive power reference adjustment value should also be larger.

[0071] It should also be noted that the reactive power reference adjustment value is a numerical value and has no positive or negative meaning.

[0072] The voltage fluctuation trigger thresholds and response weights of each device in the controlled photovoltaic node are extracted from the database.

[0073] Voltage fluctuations of each device in the controlled photovoltaic node are collected using voltage sensors.

[0074] Devices whose voltage fluctuations exceed the voltage fluctuation trigger threshold are classified as demand control devices.

[0075] It should be added that if the voltage fluctuation of a device does not exceed the voltage fluctuation trigger threshold, the device will not be regulated.

[0076] The response weights of each demand control device are extracted based on the response weights of each device.

[0077] The reactive power adjustment value of each demand control device is analyzed based on the response weight and reactive power benchmark adjustment value of each demand control device. That is, the product of the response weight and reactive power benchmark adjustment value of each demand control device is used as the numerical result of the reactive power adjustment value of each demand control device.

[0078] Collect the active power change rate of each demand control device of the photovoltaic node and analyze the reactive power direction of each demand control device.

[0079] It should be explained that the rate of change of active power is obtained by subtracting the active power at the start time from the active power at the end time within a preset sampling window, and then dividing by the sampling window duration.

[0080] It should be noted that reactive power direction includes both absorbing reactive power and injecting reactive power.

[0081] If the rate of change of active power of a demand control device is greater than zero, it absorbs reactive power; if the rate of change of active power of a demand control device is less than or equal to zero, it injects reactive power.

[0082] By injecting / absorbing reactive power, a suppression effect is achieved on the corresponding fluctuation phase (such as absorption in the rising segment and injection in the falling segment), thereby smoothing out the fluctuation curve.

[0083] It needs to be explained that when power increases, more active power is injected into the nodes, which often leads to a rise in voltage. To suppress excessively high voltage, reactive power needs to be absorbed, thereby reducing the node voltage. Conversely, when power decreases, the node voltage tends to decrease, and reactive power should be injected to support the voltage.

[0084] The adaptive control of the photovoltaic node is achieved based on the reactive power direction and the reactive power adjustment values ​​of each demand control device.

[0085] In one specific embodiment, if a demand control device needs to inject reactive power, then it needs to inject reactive power with its corresponding reactive power adjustment value.

[0086] By traversing each controlled photovoltaic node, adaptive control of each controlled photovoltaic node is achieved.

[0087] like Figure 4The diagram shows a combined flowchart of state-of-charge (POC) change parameter analysis and notch filter suppression strategy according to an embodiment of the present invention. First, it determines whether the POC change parameter is less than or equal to a first-order threshold. If the condition is met, the first stage is set to continuous monitoring; otherwise, the first deviation parameter of the POC change is calculated, a response delay benchmark is matched, and the response delay of each inverter is calculated, while simultaneously matching the controller response frequency reduction value. Next, it determines whether the POC change parameter is greater than or equal to a second-order threshold. If not, a notch filter suppression strategy combining delay and frequency limiting is executed; if so, the second deviation parameter of the POC change is calculated, a response amplitude reduction value is matched, and finally, a notch filter suppression strategy combining delay, frequency limiting, and amplitude limiting is executed to complete the complete notch filter suppression adjustment process.

[0088] Furthermore, after the regulation is completed, the parameters of the energy storage system's state of charge change are analyzed. The specific analysis process is as follows:

[0089] Within a preset time window, the energy storage system's state of charge parameters are collected, including voltage notch amplitude, voltage rise amplitude, adjustment trigger frequency, and adjustment frequency misalignment.

[0090] It should be added that voltage notch amplitude refers to the difference between the lowest point of the node voltage drop caused by disturbance or interleaved control response within a preset time window and the steady-state reference voltage. It reflects the degree of the "valley effect" formed by short-time negative feedback or inverter delay response and is an important indicator for measuring the instantaneous voltage support capability of the system under nonlinear fluctuations. The unit is volts.

[0091] Voltage surge amplitude refers to the maximum positive deviation of the actual voltage peak value relative to the steady-state reference voltage during short-term voltage regulation caused by factors such as excessively fast response or control coordination imbalance.

[0092] The adjustment trigger frequency refers to the dominant disturbance frequency of the voltage signal when the controller is triggered to start reactive power or other forms of adjustment behavior. It is determined by extracting significant frequency components of the node voltage signal through frequency domain analysis and is used to identify the frequency characteristics of voltage fluctuations when the controller starts. The unit is Hertz.

[0093] The frequency misalignment refers to the frequency offset between the target control frequency preset in the database used by the control response system and the main frequency of the actual voltage disturbance at the node. It is used to measure the degree of matching between the control strategy and the voltage disturbance, and to reflect the degree of coupling between the control response spectrum and the disturbance spectrum. The smaller the deviation, the more accurate the control response. The unit is Hertz.

[0094] When a system is disturbed or enters a regulation phase, the regulation trigger frequency, as the frequency domain starting point of the control system response, determines the frequency reference range for the controller to initiate regulation. If this trigger frequency deviates significantly from the dominant frequency of the actual voltage disturbance, i.e., the regulation frequency misalignment increases, the controller may be unable to suppress voltage fluctuations within the optimal frequency band, leading to an excessively slow or fast system response, thus causing obvious voltage anomalies. When the controller response is delayed or the amplitude is insufficient, the voltage is prone to dip, manifested as an increase in the voltage notch amplitude; conversely, if the controller response is excessive or there is interleaving regulation, the voltage may surge sharply in a short period, resulting in an amplified voltage jump amplitude. Therefore, the rationality of the regulation trigger frequency directly affects the response synchronization. The greater the frequency misalignment, the easier it is to form nonlinear disturbance characteristics of both notch and jump in voltage fluctuations. These four factors constitute a mutually causal and complex coupling relationship at both the time and frequency domain levels.

[0095] Extract the reference voltage notch amplitude, reference voltage jump amplitude, reference adjustment trigger frequency, and reference adjustment frequency misalignment value stored in the database.

[0096] The voltage notch amplitude, voltage rise amplitude, and adjustment trigger frequency are compared with their corresponding reference values ​​to obtain the proportional values ​​of voltage notch amplitude, voltage rise amplitude, and adjustment trigger frequency.

[0097] It should be explained that dividing the voltage notch amplitude by the reference voltage notch amplitude yields the voltage notch amplitude ratio, dividing the voltage jump amplitude by the reference voltage jump amplitude yields the voltage jump amplitude ratio, and dividing the adjusted trigger frequency by the reference adjusted trigger frequency yields the adjusted trigger frequency ratio.

[0098] The reference frequency misalignment is compared with the frequency misalignment to obtain the frequency misalignment ratio.

[0099] It should also be explained that the ratio of the adjustment frequency misalignment is obtained by dividing the reference adjustment frequency misalignment by the sum of the adjustment frequency misalignment and a small positive number.

[0100] In this embodiment, to avoid the fraction being meaningless due to the zero frequency misalignment, a small positive number is introduced when performing the ratio calculation to ensure that the ratio is defined across the entire frequency band. The small positive number is a positive number that is close to zero but not zero and is preset in the database. It is usually much smaller than the actual measured value and is used to ensure that the denominator is always greater than zero.

[0101] Extract the preset characteristic measurement factors of voltage notch amplitude ratio, voltage rise amplitude ratio, adjustment trigger frequency ratio, and adjustment frequency misalignment ratio from the database.

[0102] In this embodiment, to achieve weighted coupled evaluation of the state of charge (SCC) change parameters of the energy storage system, the system pre-constructs a mapping relationship between multiple proportional values ​​and their corresponding characteristic measurement factors in the database. This mapping relationship is stored in the form of a structured configuration table (such as a "SCC measurement configuration table"), which explicitly records the value ranges of the characteristic measurement factors corresponding to the proportional values ​​of voltage notch amplitude, voltage rise amplitude, regulation trigger frequency, and regulation frequency misalignment. In practical applications, the system automatically extracts the corresponding set of characteristic measurement factors by searching for the corresponding entries in the configuration table based on the proportional values ​​collected in the current cycle through conditional matching. This set is used to characterize the influence intensity of each disturbance feature on the SCC change and serves as the input basis for subsequent weighted modeling. The values ​​of all characteristic measurement factors are limited to between 0 and 1 and satisfy the normalization constraint that the sum of the four factors is 1, thereby ensuring the consistency and comparability of the SCC change evaluation results in a physical sense and meeting the requirements for fine evaluation and regulation judgment under multiple disturbance features.

[0103] By weighting and coupling the voltage notch amplitude ratio, voltage rise amplitude ratio, adjustment trigger frequency ratio, and adjustment frequency misalignment ratio using characteristic metric factors, the parameters of the energy storage system's state of charge change are obtained.

[0104] In a specific embodiment, the parameter representing the change in the state of charge of the energy storage system is represented as follows:

[0105] ,

[0106] Wherein, B is the parameter for the change of the state of charge of the energy storage system, f is the voltage notch amplitude ratio, g is the voltage rise amplitude ratio, h is the adjustment trigger frequency ratio, j is the adjustment frequency misalignment ratio, y1 is the characteristic metric factor for the voltage notch amplitude ratio, y2 is the characteristic metric factor for the voltage rise amplitude ratio, y3 is the characteristic metric factor for the adjustment trigger frequency ratio, and y4 is the characteristic metric factor for the adjustment frequency misalignment ratio.

[0107] Based on the parameter analysis of the change in the state of charge of the energy storage system, the first control execution path of the energy storage system is analyzed. When the first control execution path of the energy storage system is to perform nonlinear notch suppression regulation, nonlinear notch is suppressed by decoupling the interleaved response. After the regulation is completed, the second control execution path of the energy storage system is analyzed.

[0108] Example 3: Based on the parameter analysis of the change in the state of charge of the energy storage system, the first control execution path of the energy storage system is analyzed. The analysis process is as follows:

[0109] Extract the preset first-order threshold and second-order threshold of the state of charge change parameter from the database.

[0110] It should be noted that the first-order threshold of the state of charge change parameter is less than the second-order threshold of the state of charge change parameter.

[0111] If the state of charge change parameter of the energy storage system is less than or equal to the first-order threshold of the state of charge change parameter, then the first control execution path of the energy storage system is recorded as continuous monitoring.

[0112] In this embodiment, if the state of charge (SCC) change parameter of the energy storage system is less than or equal to the first-order threshold of the SCC change parameter, it indicates that the current SCC fluctuation of the energy storage system is small, and the overall operation is within a stable or normal range, without showing obvious nonlinear notch risk or voltage anomaly characteristics. Therefore, the system does not need to immediately initiate active adjustment measures, but only needs to maintain continuous monitoring of the energy storage system in order to promptly detect any subsequent possible abnormal changes and ensure safe and stable operation.

[0113] If the state-of-charge (SOC) parameter of the energy storage system is greater than the first-order threshold of the SOC parameter, then the first regulation execution path of the energy storage system is denoted as nonlinear notch suppression regulation.

[0114] If the state-of-charge (POC) parameter of the energy storage system exceeds the first-order threshold, it indicates that the current POC fluctuation of the energy storage system is small, and the overall operation is within a stable or normal range, without showing obvious nonlinear notch risk or voltage anomaly characteristics. Therefore, the system does not need to immediately initiate active adjustment measures; it only needs to maintain continuous monitoring of the energy storage system to promptly detect any subsequent abnormal changes and ensure operational safety and stability.

[0115] Furthermore, nonlinear notch filtering is suppressed by decoupling the interleaved response. The specific analysis process is as follows:

[0116] The first deviation parameter of the state of charge change is obtained by subtracting the first threshold of the state of charge change parameter from the state of charge change parameter of the energy storage system.

[0117] The reference value for the first deviation parameter matching response delay based on the state of charge change and the reduction value for the controller response frequency limit.

[0118] In this embodiment, the system pre-establishes a mapping relationship in the database between the first deviation parameter of state of charge change and the corresponding response delay reference value and controller response frequency limit reduction value. This mapping relationship is maintained and accessed in the form of a structured parameter configuration table. During the matching process, the system uses the first deviation parameter of state of charge change calculated in real time as the search keyword to locate the corresponding set of response delay reference values ​​and frequency limit reduction values ​​in the configuration table. This set includes the standard duration of the response delay and the dynamic adjustment range of the controller frequency response. By matching parameters adapted to the deviation parameter, the system can dynamically adjust the controller's response rhythm and frequency limit, thereby effectively suppressing the nonlinear notch phenomenon of the energy storage system and improving the accuracy and stability of the regulation.

[0119] It should be added that the larger the first deviation parameter of the state of charge change, the stronger the residual dynamic fluctuations in the energy storage system after the previous stage of adjustment, and the more obvious nonlinear disturbance trend its voltage notch or jump characteristics. To enhance the stability and disturbance rejection of the system response, the corresponding matching response delay reference value should be larger to appropriately lengthen the adjustment response start-up time of each inverter and reduce the synchronization interleaving phenomenon between inverters; at the same time, the absolute value of the controller response frequency limit reduction value should also be larger to suppress the rapid transition of the frequency domain response in the sensitive frequency range and reduce the risk of system notch coupling.

[0120] The response weights of each inverter in the energy storage system are obtained from the database.

[0121] The response delay of each inverter in the energy storage system is obtained by multiplying the response delay benchmark value and the response weight of each inverter in the energy storage system. In other words, the product of the response delay benchmark value and the response weight of each inverter in the energy storage system is used as the numerical result of the response delay of each inverter in the energy storage system.

[0122] If the state of charge change parameter of the energy storage system is less than the second-order threshold of the state of charge change parameter, nonlinear notch filtering is suppressed based on the response delay of each inverter in the energy storage system and the reduction value of the controller response frequency limit. That is, the response delay of each inverter in the energy storage system is set based on the response delay of each inverter in the energy storage system, the current controller response frequency limit value is extracted from the system program log synchronously, and the sum of the current controller response frequency limit value and the controller response frequency limit reduction value is used as the execution controller response frequency limit value.

[0123] If the state of charge change parameter of the energy storage system is greater than or equal to the second-order threshold of the state of charge change parameter, the second deviation parameter of the state of charge change is obtained by subtracting the second-order threshold of the state of charge change parameter of the energy storage system.

[0124] The response amplitude reduction value is matched by the second deviation parameter of the change in state of charge.

[0125] In this embodiment, the system pre-constructs a mapping relationship between the second deviation parameter of state of charge change and the corresponding response amplitude reduction value in the database. This mapping relationship is managed in the form of a structured parameter configuration table. During the matching process, the system uses the real-time acquired second deviation parameter of state of charge change as a query condition to retrieve the corresponding response amplitude reduction value from the configuration table. This reduction value reflects the controller's dynamic adjustment range of the response amplitude, used to limit voltage fluctuations caused by over-response. By accurately matching the second deviation parameter with the corresponding amplitude reduction value, the system can adaptively adjust the controller output amplitude, effectively suppressing nonlinear notch filtering and improving the stability and reliability of the energy storage system's regulation.

[0126] It should be added that the larger the second deviation parameter of the state of charge change, the higher the level of nonlinear fluctuation in the system. In order to further suppress local voltage anomalies caused by controller overshoot or frequency coupling, the absolute value of the corresponding matched response amplitude reduction value should be larger, thereby enhancing the suppression of the output amplitude and limiting the dynamic response amplitude of the controller in the sensitive frequency band.

[0127] Nonlinear traps are suppressed based on the response delay of each inverter in the energy storage system, the controller response frequency limit reduction value, and the response amplitude reduction value. Specifically, the response delay of each inverter in the energy storage system is set based on the response delay of each inverter. The current controller response frequency limit value and the current response amplitude are extracted from the system program log synchronously. The sum of the current controller response frequency limit value and the controller response frequency limit reduction value is used as the execution controller response frequency limit value, and the sum of the current response amplitude and the response amplitude reduction value is used as the execution response amplitude.

[0128] Furthermore, after the adjustment is completed, the second control execution path of the energy storage system is analyzed. The specific analysis process is as follows:

[0129] The buffer delay time is matched by the first deviation parameter of the change in state of charge.

[0130] In this embodiment, the system pre-establishes a mapping relationship between the first deviation parameter of the state of charge change and the corresponding buffer delay duration in the database. This mapping relationship is stored and managed in the form of a structured configuration table. During the matching process, the system uses the first deviation parameter of the state of charge change calculated in real time as the search keyword to locate the corresponding buffer delay duration parameter in the configuration table. This buffer delay duration is used to set the waiting period that the system enters after adjustment, so as to ensure the stability of control actions and prevent excessively frequent adjustment operations. By accurately matching the deviation parameter and the buffer delay duration, the system can dynamically adjust the buffer time to achieve a smooth response and effective control to the state of charge change of the energy storage system.

[0131] It should be added that the larger the first deviation parameter of the state of charge change, the higher the degree of dynamic fluctuation and nonlinear disturbance of the energy storage system, and the more urgent and larger the need for suppression and regulation. In order to ensure that the system has enough time to complete a stable response to the above-mentioned large-scale regulation actions and to prevent control oscillations or response superposition caused by starting the next round of regulation too quickly, the system should be matched with a longer buffer delay time.

[0132] After the adjustment is completed, a buffer delay period is entered with a buffer delay duration. After the buffer delay period ends, the change parameters of the state of charge of the energy storage system are re-analyzed and recorded as the change parameters of the state of charge of the second energy storage system.

[0133] If the state of charge change parameter of the second energy storage system is less than or equal to the first-order threshold of the state of charge change parameter, then the second control execution path of the energy storage system is recorded as continuous monitoring.

[0134] In this embodiment, if the state of charge change parameter of the second energy storage system is less than or equal to the first-order threshold of the state of charge change parameter, it indicates that the energy storage system is relatively stable after the buffer delay period, and no new or aggravated charge fluctuations have occurred. The system operation remains within a safe range. Therefore, the control strategy continues to maintain continuous monitoring to dynamically observe subsequent changes and ensure the safe and stable operation of the energy storage system.

[0135] If the state-of-charge change parameter of the second energy storage system is greater than the first-order threshold of the state-of-charge change parameter, then the second regulation execution path of the energy storage system is recorded as executing the second suppression regulation.

[0136] If the state-of-charge (SOC) parameter of the second energy storage system exceeds the first-order threshold, it indicates that even after the buffer delay period, the energy storage system still faces significant risks of charge fluctuations or nonlinear disturbances, which may affect grid stability. Therefore, the system needs to activate the second suppression and regulation path to further enhance the suppression of nonlinear notch waves and ensure the coordinated stability of the energy storage system and the grid.

[0137] Furthermore, the second inhibitory regulation is executed, and the specific execution process is as follows:

[0138] The deviation parameter of the state of charge change of the second energy storage system is obtained by subtracting the first-order threshold of the state of charge change parameter from the state of charge change parameter of the second energy storage system.

[0139] If the energy storage system does not perform response amplitude reduction, the response amplitude reduction value is matched based on the second energy storage system state of charge change deviation parameter, thereby completing the second suppression regulation.

[0140] It should be added that the larger the deviation parameter of the state of charge change of the second energy storage system, the more significant the dynamic fluctuations and overresponse risk still exist in the system after the first adjustment, and the nonlinear notch phenomenon has not been sufficiently suppressed. In order to further limit the output amplitude of the controller and prevent voltage overshoot and oscillation caused by the adjustment action, the absolute value of the corresponding response amplitude reduction value should be larger. By increasing the reduction of the response amplitude, the system can effectively suppress residual disturbances and improve the regulation stability of the energy storage system and the safety and reliability of grid operation.

[0141] In this embodiment, the system pre-establishes a mapping relationship between the deviation parameter of the second energy storage system's state of charge (SBC) and the corresponding response amplitude reduction value in the database. This mapping relationship is stored and managed in the form of a structured configuration table. During matching, the system uses the real-time calculated deviation parameter of the second SBC as the query key to find the corresponding response amplitude reduction value in the configuration table. This reduction value is used to dynamically adjust the response amplitude of the controller output to limit voltage fluctuations caused by over-regulation. By accurately matching the deviation parameter and the amplitude reduction value, the system achieves adaptive amplitude control of the energy storage system, effectively suppressing nonlinear notch waves and improving the stability and reliability of system regulation.

[0142] If the energy storage system does not implement response amplitude reduction, it indicates that the current energy storage system has not taken amplitude limiting measures during the previous regulation process, and the system still has sufficient regulation margin. At this time, based on the deviation parameter of the state of charge change of the second energy storage system, the system can match the corresponding response amplitude reduction value and implement the second suppression regulation, thereby effectively mitigating the risk of nonlinear notch filtering and improving the targeting and accuracy of regulation.

[0143] If the energy storage system has already implemented a response reduction, an early warning message will be generated.

[0144] If the energy storage system has already implemented response amplitude reduction, it indicates that the system has previously initiated amplitude limiting measures to suppress voltage fluctuations. However, the current deviation in state of charge (SOC) has not been significantly improved, and there is a persistent risk of nonlinear notch waves. In this case, the system will generate an early warning message, prompting maintenance personnel or the upper-level control system to take further auxiliary measures or conduct manual intervention to ensure the safe and stable operation of the energy storage system and the power grid.

[0145] like Figure 2 The diagram shown illustrates the structure of a photovoltaic-storage collaborative adaptive regulation and control system for grid-type energy storage. This system provides a photovoltaic-storage collaborative adaptive regulation and control system for grid-type energy storage, which includes: a regulation execution path determination module, a modal amplification and suppression regulation module, and a nonlinear notch filter suppression regulation module.

[0146] The control execution path determination module is used to monitor each photovoltaic node in real time, analyze the modal amplification risk factors of each photovoltaic node, and determine the control execution path of each photovoltaic node.

[0147] The mode amplification suppression regulation module is used to record the corresponding photovoltaic node as the regulated photovoltaic node when the regulation execution path of the photovoltaic node is to perform mode amplification suppression regulation. It adaptively regulates each device of each regulated photovoltaic node through reactive power regulation, and analyzes the change parameters of the state of charge of the energy storage system after the regulation is completed.

[0148] The nonlinear notch suppression regulation module is used to analyze the first regulation execution path of the energy storage system based on the parameter of the change in the state of charge of the energy storage system. When the first regulation execution path of the energy storage system is to perform nonlinear notch suppression regulation, it suppresses the nonlinear notch by decoupling the interleaved response, and analyzes the second regulation execution path of the energy storage system after the regulation is completed.

[0149] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the flow or function according to the embodiments of the present invention is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. A computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. Available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. Semiconductor media can be solid-state drives.

[0150] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0151] In this invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be a single item or multiple items.

[0152] It should be understood that, in various embodiments of the present invention, the order of the above-mentioned process numbers does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0153] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0154] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0155] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0156] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0157] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A photovoltaic-storage collaborative adaptive regulation and control method supported by grid-type energy storage, characterized in that, Includes the following steps: Real-time monitoring of each photovoltaic node, analysis of the modal amplification risk factors of each photovoltaic node, and determination of the control execution path of each photovoltaic node; When the control execution path of the photovoltaic node is to perform mode amplification suppression regulation, the corresponding photovoltaic node is recorded as the control photovoltaic node. The reactive power regulation is used to adaptively regulate each device of each control photovoltaic node, and the change parameters of the state of charge of the energy storage system are analyzed after the regulation is completed. Based on the parameter analysis of the change of the state of charge of the energy storage system, the first control execution path of the energy storage system is analyzed. When the first control execution path of the energy storage system is to perform nonlinear notch suppression regulation, nonlinear notch is suppressed by decoupling the staggered response. After the regulation is completed, the second control execution path of the energy storage system is analyzed. The analysis of the modal amplification risk factors for each photovoltaic node is as follows: The modal amplification characterization parameters of each photovoltaic node are collected, including the rate of change of active power output, voltage fluctuation frequency, equivalent impedance and voltage amplitude change of each photovoltaic node. The changes in active power output, equivalent impedance, and voltage amplitude are compared with their corresponding threshold values ​​to obtain the proportionality coefficients for the changes in active power output, equivalent impedance, and voltage amplitude. The voltage fluctuation frequency and the grid mode frequency are processed to remove the deviation, and the grid mode frequency is compared with the deviation processing result to obtain the voltage fluctuation frequency proportionality coefficient. The modal amplification risk factor is obtained by weighting and coupling the active power output change rate proportional coefficient, voltage fluctuation frequency proportional coefficient, equivalent impedance proportional coefficient, and voltage amplitude change proportional coefficient through the characteristic allocation factor. By traversing each photovoltaic node, the modal amplification risk factor of each photovoltaic node is obtained; The specific analysis process for suppressing nonlinear notch filtering by decoupling interleaved responses is as follows: Subtracting the first-order threshold of the state of charge change parameter from the state of charge change parameter of the energy storage system yields the first deviation parameter of the state of charge change. Based on the first deviation parameter matching response delay reference value and the controller response frequency limit reduction value based on the change of state of charge; Obtain the response weights of each inverter in the energy storage system from the database; The response delay of each inverter in the energy storage system is obtained based on the response delay baseline value and the response weight of each inverter in the energy storage system. If the state of charge change parameter of the energy storage system is less than the second-order threshold of the state of charge change parameter, nonlinear notch filtering is suppressed based on the reduction value of the response delay of each inverter and the response frequency limit of the controller in the energy storage system. If the state of charge change parameter of the energy storage system is greater than or equal to the second-order threshold of the state of charge change parameter, the second deviation parameter of the state of charge change is obtained by subtracting the second-order threshold of the state of charge change parameter of the energy storage system from the state of charge change parameter. The response amplitude reduction value is matched by the second deviation parameter of the change in state of charge. Nonlinear notch filtering is suppressed based on the response delay of each inverter in the energy storage system, the reduction value of the controller response frequency limit, and the reduction value of the response amplitude.

2. The network construction type energy storage supported photo- storage cooperative adaptive regulation control method according to claim 1, characterized in that, The process of determining the control execution path for each photovoltaic node is as follows: If the modal amplification risk factor of a photovoltaic node is greater than or equal to the preset modal amplification risk factor threshold in the database, then the regulation execution path of the photovoltaic node is recorded as executing modal amplification suppression regulation. If the modal amplification risk factor of a photovoltaic node is less than the modal amplification risk factor threshold, then the control execution path of that photovoltaic node is recorded as continuous monitoring. By traversing each photovoltaic node, the control execution path for each photovoltaic node can be determined.

3. The photovoltaic-storage collaborative adaptive regulation and control method for grid-type energy storage support according to claim 1, characterized in that, The adaptive control of each device at each photovoltaic node through reactive power regulation is analyzed in the following process: Modal amplification risk factors for each photovoltaic node are extracted based on the modal amplification risk factors of each photovoltaic node. For a regulated photovoltaic node: the modal amplification risk factor threshold is subtracted from the modal amplification risk factor of the regulated photovoltaic node to obtain the modal amplification risk deviation factor; Based on the modal amplification risk deviation factor, the reactive power benchmark adjustment value is matched; Extract the voltage fluctuation trigger threshold and response weight of each device in the controlled photovoltaic node; Collect the voltage fluctuations of each device in the controlled photovoltaic node; Devices whose voltage fluctuations exceed the voltage fluctuation trigger threshold are classified as demand control devices. The response weights of each demand control device are extracted based on the response weights of each device. The reactive power adjustment values ​​of each demand control device are analyzed based on the response weights and reactive power benchmark adjustment values ​​of each demand control device. Collect the active power change rate of each demand control device of the photovoltaic node and analyze the reactive power direction of each demand control device; The adaptive control of the photovoltaic node is completed based on the reactive power direction and the reactive power adjustment value of each demand control device. By traversing each controlled photovoltaic node, adaptive control of each controlled photovoltaic node is achieved.

4. The network-constructed energy storage supported photovoltaic storage coordinated adaptive regulation and control method of claim 1, wherein, The analysis of the change in the state of charge of the energy storage system after regulation is completed is specifically as follows: Within a preset time window, the energy storage system's state of charge parameters are collected, including voltage notch amplitude, voltage rise amplitude, adjustment trigger frequency, and adjustment frequency misalignment. The voltage notch amplitude, voltage rise amplitude, and adjustment trigger frequency are compared with their corresponding reference values ​​to obtain the voltage notch amplitude ratio, voltage rise amplitude ratio, and adjustment trigger frequency ratio. The reference frequency misalignment is compared with the frequency misalignment to obtain the frequency misalignment ratio. By weighting and coupling the voltage notch amplitude ratio, voltage rise amplitude ratio, adjustment trigger frequency ratio, and adjustment frequency misalignment ratio using characteristic metric factors, the parameters of the energy storage system's state of charge change are obtained.

5. The photovoltaic-storage collaborative adaptive adjustment and control method for grid-type energy storage support according to claim 4, characterized in that, The analysis process for the first control execution path of the energy storage system based on the parameter analysis of the change in the state of charge of the energy storage system is as follows: Extract the preset first-order threshold and second-order threshold of the state of charge change parameter from the database. If the state of charge change parameter of the energy storage system is less than or equal to the first-order threshold of the state of charge change parameter, then the first control execution path of the energy storage system is recorded as continuous monitoring. If the state-of-charge (SOC) parameter of the energy storage system is greater than the first-order threshold of the SOC parameter, then the first regulation execution path of the energy storage system is denoted as nonlinear notch suppression regulation.

6. The photovoltaic-storage collaborative adaptive regulation and control method for grid-type energy storage support according to claim 1, characterized in that, The second control execution path of the energy storage system is analyzed after the adjustment is completed. The specific analysis process is as follows: The buffer delay time is matched by the first deviation parameter of the change in state of charge. After the adjustment is completed, a buffer delay period is entered with a buffer delay duration. After the buffer delay period ends, the change parameters of the state of charge of the energy storage system are re-analyzed and recorded as the change parameters of the state of charge of the second energy storage system. If the state of charge change parameter of the second energy storage system is less than or equal to the first-order threshold of the state of charge change parameter, then the second control execution path of the energy storage system is recorded as continuous monitoring. If the state-of-charge change parameter of the second energy storage system is greater than the first-order threshold of the state-of-charge change parameter, then the second regulation execution path of the energy storage system is recorded as executing the second suppression regulation.

7. The network-constructed energy storage supported photovoltaic storage cooperative adaptive regulation control method according to claim 6, characterized in that, The execution of the second inhibition regulation is as follows: Subtracting the first-order threshold of the state of charge change parameter from the state of charge change parameter of the second energy storage system yields the state of charge change deviation parameter of the second energy storage system. If the energy storage system does not perform response amplitude reduction, the response amplitude reduction value is matched based on the second energy storage system state of charge change deviation parameter, thereby completing the second suppression regulation; If the energy storage system has already implemented a response reduction, an early warning message will be generated.

8. A photovoltaic-storage collaborative adaptive regulation and control system for grid-type energy storage support, employing the photovoltaic-storage collaborative adaptive regulation and control method for grid-type energy storage support as described in any one of claims 1-7, characterized in that, The system includes: a control execution path determination module, a modal amplification suppression adjustment module, and a nonlinear notch suppression adjustment module; Among them, the control execution path determination module is used to monitor each photovoltaic node in real time, analyze the modal amplification risk factors of each photovoltaic node, and determine the control execution path of each photovoltaic node. The mode amplification suppression regulation module is used to record the corresponding photovoltaic node as the regulated photovoltaic node when the regulation execution path of the photovoltaic node is to perform mode amplification suppression regulation. It adaptively regulates each device of each regulated photovoltaic node through reactive power regulation, and analyzes the change parameters of the state of charge of the energy storage system after the regulation is completed. The nonlinear notch suppression regulation module is used to analyze the first regulation execution path of the energy storage system based on the parameter of the change in the state of charge of the energy storage system. When the first regulation execution path of the energy storage system is to perform nonlinear notch suppression regulation, it suppresses the nonlinear notch by decoupling the interleaved response, and analyzes the second regulation execution path of the energy storage system after the regulation is completed.

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