Energy storage power station SOC automatic calibration and inter-cluster dynamic balance cooperative control method

Abstract

The invention relates to an energy storage power station SOC automatic calibration and inter-cluster dynamic balance cooperative control method. The method comprises the following steps: acquiring charge state parameters of a sodium ion supercapacitor cluster group preset in an energy storage power station; calculating a corresponding charge change rate based on the charge state parameters to judge whether calibration is abnormal or not; when the calibration is abnormal, the working modes of the cluster group are divided according to the charge state parameters, and a calibration period is set for each working mode; a local equilibrium buffer is additionally arranged on a preset management end of the energy storage power station, a previous calibration value is allowed to be returned within a preset time period, and the returning frequency of the previous calibration value is recorded; and when the return frequency of the previous calibration value is greater than the preset frequency, sending a calibration refresh request to the management end of the energy storage power station, shortening the calibration period, forcibly obtaining the latest SOC value, filling the missing estimated value, optimizing the operation efficiency of the energy storage power station through an adaptive calibration algorithm and hierarchical equalization, reducing redundant operations, and improving the reliability of the energy storage power station. Missing data is compensated through historical data trends, and the safety and reliability of the system are improved.

Description

Technical Field

[0001] The present invention relates to the field of energy storage power station control technology, and in particular to a method for coordinated control of automatic SOC calibration and inter-cluster dynamic balancing of an energy storage power station. Background Art

[0002] In current energy storage systems, sodium-ion supercapacitors are an important energy storage technology. Due to their fast response and high power density, they have been widely used in power systems, electric vehicles, and other applications requiring rapid energy storage and release. However, in practical applications, the unstable state of charge (SOC) reading accuracy and balance of sodium-ion supercapacitor clusters lead to performance fluctuations and shortened lifespan of the energy storage system, which in turn affects the overall efficiency and reliability of the energy storage system.

[0003] To solve the above problems, a control method is needed that can accurately read and calibrate the SOC value of the sodium-ion supercapacitor cluster group and achieve dynamic balancing between clusters. Traditional calibration methods often rely on fixed calibration schedules or empirical indicators, which are difficult to cope with the complex operating conditions during power plant operation, resulting in difficulty in ensuring the accuracy and timeliness of calibration. Although the existing dynamic balancing mechanism can improve the problem of uneven SOC distribution to a certain extent, it still lacks an effective calibration mechanism to compensate for the errors that may occur during the balancing process. Moreover, too frequent or untimely balancing operations will increase the burden on the system and affect the stable operation of the system. Summary of the Invention

[0004] In view of this, the present invention proposes a method for coordinated control of SOC automatic calibration and dynamic balancing between clusters of energy storage power stations, which can solve the problem that existing SOC automatic balancing technology is difficult to deal with the inconsistency between multiple clusters of batteries.

[0005] The technical solution of the present invention is achieved as follows: A method for coordinated control of automatic SOC calibration and inter-cluster dynamic balancing of an energy storage power station includes the following steps: Step S1, collecting state-of-charge parameters of a preset sodium ion supercapacitor cluster group in an energy storage power station, wherein the state-of-charge parameters include SOC value, charge and discharge current, and temperature distribution; Step S2: Calculate the corresponding charge change rate based on the state of charge parameter, and determine whether there is a calibration abnormality based on the charge change rate; Step S3: When a calibration anomaly occurs, the operating modes of the sodium ion supercapacitor cluster group are divided according to the state of charge parameters, and a calibration period is set for each operating mode; Step S4: Add a local balancing buffer on the preset management terminal of the energy storage power station, allow the return to the last calibration value within a preset period of time, and record the number of returns to the last calibration value; Step S5: When the number of times the previous calibration value is returned exceeds a preset number, a calibration refresh request is sent to the management terminal of the energy storage power station; Step S6: shorten the calibration cycle based on the calibration refresh request, forcibly obtain the latest SOC value, compare the latest SOC value with the last calibration value, and fill in the latest SOC value after calculating the missing estimated value.

[0006] Preferably, the calculation formula of the SOC value is: ; Among them, t represents the upper limit of time, is the integral variable of parameter t in the integral formula, is the initial state of charge, is the rated capacity, For the The charge and discharge current at the moment, For the The charge and discharge efficiency at each moment, It is a dynamic calibration compensation item, which is corrected according to temperature distribution and historical data trends.

[0007] Preferably, the state of charge parameters collected in step S1 are transmitted to the management end via a communication protocol format, and the communication quality during the transmission process is detected by the operation log of the sodium ion supercapacitor cluster group, wherein the operation log includes the average online rate, the number of disconnections, and the disconnection time period. If at least one of the average online rate, the number of disconnections, or the disconnection time period does not reach a preset quality threshold, the corresponding sodium ion supercapacitor cluster group is identified as a high packet loss cluster group, and the state of charge parameter reporting interval of the high packet loss cluster group is adjusted.

[0008] Preferably, the calculation formula for the charge change rate is: ; in is the charge change rate, is the SOC value at the current moment, is the SOC value at the previous calibration moment, is the calibration interval, if , it is judged as calibration abnormality.

[0009] Preferably, the specific steps of step S3 are: Set the normalized score of the SOC value : The corresponding SOC normalized score when the SOC value range is 0-50%, 50%-80%, and 80%-100% 0, 0.5, and 1 respectively; Set the current normalization score for charge and discharge current :Charge and discharge current range is , 100A-300A, The corresponding current normalized score at 300A 0, 0.5, and 1 respectively; Set the temperature normalized score of the temperature distribution : Temperature normalized scores corresponding to temperature ranges of -20-25℃, 25-40℃, and 40-60℃ 0, 0.5, and 1 respectively; Construct the scoring calculation formula: ,in represents the weight coefficient; according to S Value partitioning working mode: S ≥0.8 is high load, 0.4≤ S <0.8 is medium load, S When <0.4, it is low load.

[0010] Preferably, before adding the local balancing buffer in step S4, a state of charge update mode of the sodium ion supercapacitor cluster group is obtained based on a data sampling period preset by the management end, and the state of charge update mode includes timed sampling, event triggering and on-demand request; Determine whether the state of charge update mode matches the management end; if not, construct a balancing buffer strategy for the sodium ion supercapacitor cluster group, dynamically adjust the effective time range of the balancing buffer strategy according to the frequency of the state of charge update, and limit the preset non-applicable cluster group for balancing buffering according to the balancing buffer strategy; wherein, the non-applicable cluster group includes a transient charge change cluster group and a high-frequency signal interference cluster group.

[0011] Preferably, different working modes need to match the balancing frequency. If there is a mismatch, the balancing mechanism is dynamically adjusted through a hierarchical balancing structure. The hierarchical balancing structure includes a local balancing layer, a distributed balancing layer, and a cloud balancing layer. The local balancing layer is responsible for processing transient charge change clusters, and the distributed balancing layer is optimized for high-frequency signal interference clusters. The balancing mechanism includes active balancing and passive balancing.

[0012] Preferably, the specific steps of step S5 of sending a calibration refresh request to the management end of the energy storage power station are: detecting the communication mode of the sodium ion supercapacitor cluster group based on the communication protocol format of the sodium ion supercapacitor cluster group, judging whether the communication mode needs to enable preset secure communication, and if so, constructing the corresponding calibration request content according to the communication address of the sodium ion supercapacitor cluster group, and dynamically adjusting the request interval period of the calibration request content according to the charge state parameter, wherein the communication address includes an IP address, a physical address and an authentication key, and the calibration request content includes specifying the target cluster group ID, setting the charging time range and increasing the request priority.

[0013] Preferably, in step S6, after comparing the latest SOC value with the last calibration value, a weighted moving average method is used to calculate the missing estimate value based on the pre-recorded historical data trend, and the calculation formula is: ; in is the time decay weight, α is the attenuation coefficient, n =5, is the SOC value of the i sampling points before the missing moment.

[0014] Compared with the prior art, the present invention has the following beneficial effects: (1) The present invention dynamically adjusts the calibration cycle through an adaptive calibration algorithm and combines it with a forced refresh mechanism to obtain the latest SOC value, thus solving the problems of calibration lag and deviation exceeding the threshold in traditional methods and ensuring the consistency and real-time response capability of the cluster group SOC value.

[0015] (2) The present invention uses a hierarchical balancing structure to perform balancing operations, reducing redundant energy consumption. At the same time, it dynamically switches between active and passive balancing mechanisms to improve balancing efficiency under complex working conditions, reducing ineffective balancing operations by approximately 40% compared to existing technologies.

[0016] (3) This invention allows for temporary return to historical calibration values ​​through local balancing buffering and fills in missing data by combining trend analysis of historical data from the past 30 days, effectively addressing communication anomalies or data loss scenarios. The design of communication quality monitoring and dynamically adjusting reporting intervals further ensures stable system operation under extreme operating conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only preferred embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1This is a flow chart of a method for coordinated control of automatic SOC calibration and dynamic balancing between clusters in an energy storage power station according to the present invention. DETAILED DESCRIPTION

[0019] In order to better understand the technical content of the present invention, a specific embodiment is provided below, and the present invention is further described in conjunction with the accompanying drawings.

[0020] See also Figure 1 The present invention provides a method for coordinated control of SOC automatic calibration and inter-cluster dynamic balancing of an energy storage power station, comprising the following steps: Step S1, collecting state-of-charge parameters of a preset sodium ion supercapacitor cluster group in an energy storage power station, wherein the state-of-charge parameters include SOC value, charge and discharge current, and temperature distribution; The calculation formula of SOC value is: ; Among them, t represents the upper limit of time, is the integral variable of parameter t in the integral formula, is the initial state of charge, is the rated capacity, For the The charge and discharge current at the moment, For the The charge and discharge efficiency at each moment, It is a dynamic calibration compensation item, which is corrected according to temperature distribution and historical data trends.

[0021] In actual operation, a sensor network connects to a sodium-ion supercapacitor cluster and collects state-of-charge (SOC) parameters in real time. These parameters include SOC value, charge and discharge current (ranging from -500A to 500A), and temperature distribution (ranging from -20°C to 60°C). These SOC parameters are transmitted to the management client via communication protocols such as Modbus, CAN bus, and TCP / IP. The communication quality during SOC parameter transmission is monitored by an operation log, which records the average online rate (preset quality threshold of 95%), the number of disconnections (no more than 5 times per month), and the duration of disconnections (no more than 10 minutes per time). If communication quality falls below the preset quality threshold, such as the average online rate falling below 90% or the number of disconnections reaching 8 times per month, the management client identifies clusters with high packet loss and dynamically adjusts the SOC reporting interval from 10 seconds to 30 seconds to reduce transmission frequency.

[0022] Step S2: Calculate the corresponding charge change rate based on the state of charge parameter, and determine whether there is a calibration abnormality based on the charge change rate. Calibration abnormalities include SOC deviation exceeding a threshold (±5%) and inter-cluster consistency decreasing (standard deviation > 3%). During the judgment process, the charge change rate is identified based on the preset charge state update interval (5 minutes / time) of the sodium ion supercapacitor cluster group. The calculation formula is: ; in is the charge change rate, is the SOC value at the current moment, is the SOC value at the previous calibration moment, is the calibration interval, if If the calibration is abnormal, the system will further check the data integrity, which includes the data value and format. If there is an abnormal cluster, such as three consecutive data out-of-range values, the management terminal will send batch charge resampling requests, sending three groups of requests at a time to ensure data accuracy.

[0023] Step S3: When there is a calibration anomaly, the working mode of the sodium ion supercapacitor cluster group is divided according to the state of charge parameter, and a calibration cycle is set for each working mode. The specific steps are as follows: Set the normalized score of the SOC value : The corresponding SOC normalized score when the SOC value range is 0-50%, 50%-80%, and 80%-100% 0, 0.5, and 1 respectively; Set the current normalization score for charge and discharge current :Charge and discharge current range is , 100A-300A, The corresponding current normalized score at 300A 0, 0.5, and 1 respectively; Set the temperature normalized score of the temperature distribution : Temperature normalized scores corresponding to temperature ranges of -20-25℃, 25-40℃, and 40-60℃ 0, 0.5, and 1 respectively; Construct the scoring calculation formula: ,in represents the weight coefficient. In this embodiment, =0.5, =0.3, =0.2; according to S Value partitioning working mode: ≥0.8 is high load, 0.4≤ <0.8 is medium load, When <0.4, it is low load.

[0024] Different operating modes correspond to different SOC calibration cycles, which are calculated using a unified time base. For example, in high-load mode, the calibration cycle is 5 minutes, while in low-load mode, the calibration cycle is 30 minutes.

[0025] Before adding a local balancing buffer, a state of charge update mode of the sodium ion supercapacitor cluster group is obtained based on a data sampling period preset by the management end, wherein the state of charge update mode includes timed sampling, event triggering, and on-demand request; Determine whether the state of charge update mode matches the management end; if not, construct a balancing buffer strategy for the sodium ion supercapacitor cluster group, dynamically adjust the effective time range of the balancing buffer strategy according to the frequency of the state of charge update, and limit the preset non-applicable cluster group for balancing buffering according to the balancing buffer strategy; wherein, the non-applicable cluster group includes a transient charge change cluster group and a high-frequency signal interference cluster group.

[0026] Different working modes require matching balancing frequencies, among which high load needs to match 50Hz, medium load 30Hz, and low load 10Hz. If there is a mismatch, the balancing mechanism is dynamically adjusted through a hierarchical balancing structure. The balancing mechanism includes active balancing and passive balancing. The hierarchical balancing structure includes a local balancing layer, a distributed balancing layer, and a cloud balancing layer. The local balancing layer is responsible for processing transient charge change clusters with a change range of within ±10%. The distributed balancing layer is optimized for high-frequency signal interference clusters (interference above 1kHz), and the cloud balancing layer is mainly used for global data analysis and long-term trend prediction, among which the sampling period is 24 hours.

[0027] Active and passive balancing mechanisms dynamically switch in different scenarios. For example, when inter-cluster consistency decreases, the active balancing mechanism is activated first. The differential balancing detection module only balances the data with differences, that is, clusters with differences greater than 2%, to reduce redundant operations. The inter-cluster difference is calculated using the following formula: Difference = 100% in, For the i The real-time SOC value of each cluster group, is the average SOC value of all clusters. Active balancing is triggered when the difference exceeds 2%. The differential balancing detection module analyzes the SOC differences between clusters and identifies specific targets for balancing, thereby improving balancing efficiency.

[0028] Step S4: Add a local balancing buffer on the preset management terminal of the energy storage power station, allow the return to the last calibration value within a preset period, and record the number of returns to the last calibration value to cope with temporary data loss or abnormal situations; Based on the status monitoring preset by the management end, the operating status of the cluster group is identified; whether the operating status is offline is determined; if not, the timeout information of the cluster group is collected, and the data loss rate when the charge state is updated is obtained according to the timeout information, and the data loss rate is compared with the data reception timestamp preset by the management end to detect the corresponding delay and lost data.

[0029] Step S5: When the number of times the previous calibration value is returned exceeds a preset number, a calibration refresh request is sent to the management terminal of the energy storage power station; The specific steps of sending a calibration refresh request to the management end of the energy storage power station are as follows: detecting the communication mode of the sodium ion supercapacitor cluster group based on the communication protocol format of the sodium ion supercapacitor cluster group, wherein the communication protocol format includes Modbus, CAN bus, and TCP / IP, and judging whether the communication mode needs to enable the preset secure communication. If so, constructing the corresponding calibration request content according to the communication address of the sodium ion supercapacitor cluster group, and dynamically adjusting the request interval period of the calibration request content according to the charge state parameter, wherein the communication address includes the IP address, physical address and authentication key, and the calibration request content includes specifying the target cluster group ID, setting the charging time range and increasing the request priority.

[0030] Step S6: Based on the calibration refresh request, shorten the calibration cycle, force the acquisition of the latest SOC value, compare the latest SOC value with the previous calibration value, and calculate the missing estimate value using the weighted moving average method based on the pre-recorded historical data trend (data for the past 30 days). The calculation formula is: ; in is the time decay weight, α is the attenuation coefficient, with a value of 0.1. The more recent the data, the higher the weight. n =5 (take the last 5 valid data points), is the SOC value of the i sampling points before the missing moment.

[0031] After obtaining the missing estimated value, the latest SOC value can be filled in to ensure the integrity and consistency of the state of charge data.

[0032] In a real-world application scenario, suppose a cluster experiences an abnormal SOC update due to high-frequency signal interference. At this point, the acquisition module detects a decrease in communication quality, and the management end identifies the cluster as non-suitable and restricts its balancing cache. Simultaneously, the distributed balancing layer within the hierarchical balancing structure activates a passive balancing mechanism, using the differential balancing detection module to balance only the affected data. If the anomaly persists (e.g., for more than 10 minutes) and the last calibration value has been returned more than a preset number of times (five), the calibration refresh request module shortens the calibration interval and forces the acquisition of the latest SOC value. The historical data trend analysis module calculates missing estimates based on historical data trends to fill in the data gaps caused by the anomaly. Furthermore, the operational requirements of the management end determine the collection and adjustment strategy for the balancing frequency. For example, in medium load mode, if the balancing frequency does not match the SOC requirement, the balancing mechanism is dynamically adjusted through a hierarchical balancing structure. Active and passive balancing mechanisms switch based on the actual operating status of the cluster group (e.g., switching to passive balancing when the difference is less than 3%), ensuring efficient and targeted balancing operations. Furthermore, the data sampling period preset by the management end (1 second / time under high load, 5 seconds / time under medium load, and 10 seconds / time under low load) determines the cluster group's SOC update mode, which includes scheduled sampling, event triggering, and on-demand requests. If the SOC update mode does not match the management end's requirements, such as a 10-second sampling period in medium load mode, a balancing cache strategy is established to dynamically adjust the effective time range of the balancing cache. Through the above-mentioned implementation, the present invention achieves the goal of automatic SOC calibration and dynamic balanced coordinated control between clusters of sodium ion supercapacitor energy storage power stations, solves the shortcomings of the existing technology, and improves the operating efficiency, consistency and safety of energy storage power stations.

[0033] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for coordinated control of automatic SOC calibration and dynamic balancing between clusters in an energy storage power station, characterized in that: The following steps are involved: Step S1, collecting state-of-charge parameters of a preset sodium ion supercapacitor cluster group in an energy storage power station, wherein the state-of-charge parameters include SOC value, charge and discharge current, and temperature distribution; Step S2: Calculate the corresponding charge change rate based on the state of charge parameter, and determine whether there is a calibration abnormality based on the charge change rate; Step S3: When a calibration anomaly occurs, the operating modes of the sodium ion supercapacitor cluster group are divided according to the state of charge parameters, and a calibration period is set for each operating mode; Step S4: Add a local balancing buffer on the preset management terminal of the energy storage power station, allow the return to the last calibration value within a preset period of time, and record the number of returns to the last calibration value; Step S5: When the number of times the previous calibration value is returned exceeds a preset number, a calibration refresh request is sent to the management terminal of the energy storage power station; Step S6: shorten the calibration cycle based on the calibration refresh request, forcibly obtain the latest SOC value, compare the latest SOC value with the last calibration value, and fill in the latest SOC value after calculating the missing estimated value.

2. The method for coordinated control of SOC automatic calibration and inter-cluster dynamic balancing of an energy storage power station according to claim 1, characterized in that: The calculation formula of the SOC value is: ； Among them, t represents the upper limit of time, is the integral variable of parameter t in the integral formula, is the initial state of charge, is the rated capacity, For the The charge and discharge current at the moment, For the The charge and discharge efficiency at each moment, It is a dynamic calibration compensation item, which is corrected according to temperature distribution and historical data trends.

3. The method for coordinated control of SOC automatic calibration and inter-cluster dynamic balancing of an energy storage power station according to claim 1, characterized in that: The state of charge parameters collected in step S1 are transmitted to the management end through a communication protocol format. The communication quality during the transmission process is detected by the operation log of the sodium ion supercapacitor cluster group. The operation log includes the average online rate, the number of disconnections, and the disconnection time period. If at least one of the average online rate, the number of disconnections, or the disconnection time period does not reach a preset quality threshold, the corresponding sodium ion supercapacitor cluster group is identified as a high packet loss cluster group, and the state of charge parameter reporting interval of the high packet loss cluster group is adjusted.

4. The method for coordinated control of SOC automatic calibration and inter-cluster dynamic balancing of an energy storage power station according to claim 1, characterized in that: The calculation formula of the charge change rate is: ； in is the charge change rate, is the SOC value at the current moment, is the SOC value at the previous calibration moment, is the calibration interval, if , it is judged as calibration abnormality.

5. The method for coordinated control of SOC automatic calibration and inter-cluster dynamic balancing of an energy storage power station according to claim 1, characterized in that: The specific steps of step S3 are: Set the normalized score of the SOC value : The corresponding SOC normalized score when the SOC value range is 0-50%, 50%-80%, and 80%-100% 0, 0.5, and 1 respectively; Set the current normalization score for charge and discharge current :Charge and discharge current range is , 100A-300A, The corresponding current normalized score at 300A 0, 0.5, and 1 respectively; Set the temperature normalized score of the temperature distribution : Temperature normalized scores corresponding to temperature ranges of -20-25℃, 25-40℃, and 40-60℃ 0, 0.5, and 1 respectively; Construct the scoring calculation formula: ,in represents the weight coefficient; according to S Value partitioning working mode: S ≥0.8 is high load, 0.4≤ S <0.8 is medium load, S When <0.4, it is low load.

6. The method for coordinated control of SOC automatic calibration and inter-cluster dynamic balancing of an energy storage power station according to claim 5, characterized in that: Before adding the local balancing buffer in step S4, a state of charge update mode of the sodium ion supercapacitor cluster group is obtained based on a data sampling period preset by the management end, and the state of charge update mode includes timed sampling, event triggering, and on-demand request; Determine whether the state of charge update mode matches the management end; if not, construct a balancing buffer strategy for the sodium ion supercapacitor cluster group, dynamically adjust the effective time range of the balancing buffer strategy according to the frequency of the state of charge update, and limit the preset non-applicable cluster group for balancing buffering according to the balancing buffer strategy; wherein, the non-applicable cluster group includes a transient charge change cluster group and a high-frequency signal interference cluster group.

7. The method for coordinated control of SOC automatic calibration and inter-cluster dynamic balancing of an energy storage power station according to claim 6, characterized in that: Different working modes require matching balancing frequencies. If there is a mismatch, the balancing mechanism is dynamically adjusted through a hierarchical balancing structure. The hierarchical balancing structure includes a local balancing layer, a distributed balancing layer, and a cloud balancing layer. The local balancing layer is responsible for processing transient charge change clusters, and the distributed balancing layer is optimized for high-frequency signal interference clusters. The balancing mechanism includes active balancing and passive balancing.

8. The method for coordinated control of SOC automatic calibration and inter-cluster dynamic balancing of an energy storage power station according to claim 1, characterized in that: The specific steps of step S5 of sending a calibration refresh request to the management end of the energy storage power station are as follows: detecting the communication mode of the sodium ion supercapacitor cluster group based on the communication protocol format of the sodium ion supercapacitor cluster group, determining whether the communication mode requires the use of preset secure communication, and if so, constructing the corresponding calibration request content according to the communication address of the sodium ion supercapacitor cluster group, and dynamically adjusting the request interval of the calibration request content according to the state of charge parameter, wherein the communication address includes an IP address, a physical address, and an authentication key, and the calibration request content includes specifying a target cluster group ID, setting a charging time range, and increasing the request priority.

9. The method for coordinated control of SOC automatic calibration and inter-cluster dynamic balancing of an energy storage power station according to claim 1, characterized in that: In step S6, after comparing the latest SOC value with the previous calibration value, the missing estimate value is calculated using the weighted moving average method based on the pre-recorded historical data trend. The calculation formula is: ； in is the time decay weight, α is the attenuation coefficient, n =5, is the SOC value of the i sampling points before the missing moment.

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