A method and system for evaluating the health of energy storage equipment based on vehicle-grid interaction

Abstract

The present invention relates to the technical field of energy storage equipment health management, and in particular to a method and system for evaluating the health of energy storage equipment based on vehicle-grid interaction. The method comprises: S1, collecting real-time operating data of multiple energy storage devices, and collecting charging and discharging data of single cells; S2, obtaining multiple incomplete charging and discharging process information of single cells, integrating them into a complete charging and discharging process information, and obtaining single cell SOH information; calculating the difference coefficient of each energy storage device; calculating the reliability of each energy storage device; calculating the fault alarm information of each energy storage device; S3, evaluating the health status of each energy storage device based on the single cell SOH information, the difference coefficient of the energy storage device, the reliability information and the fault alarm information; S4, comprehensively analyzing the health status of multiple energy storage devices and the operating status of the energy storage devices, and adjusting the control strategy for all energy storage devices. Reasonable regulation and management of energy storage facilities improves the stability and economic benefits of station operation.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage device health management, and in particular to a method and system for evaluating the health of energy storage devices based on vehicle-grid interaction. Background Art

[0002] In recent years, artificial intelligence technology has developed rapidly, and data-driven energy storage health status assessment methods have been promoted. By collecting a large amount of energy storage operation data, mainly current, voltage, temperature and other data during the charging and discharging process, after data processing and feature extraction, machine learning and deep learning models are used to evaluate the performance of energy storage equipment.

[0003] However, the energy storage operation data is based on the complete charging and discharging process. By observing the data changes during the charging and discharging process, the feature quantities that are obviously related to the health of the energy storage are extracted. The extraction of feature quantities varies from person to person, and the selection of feature quantities has a great impact on the accuracy of the model. Too many features may easily lead to overfitting problems. Too few features may not be able to fully describe the characteristics of the data, resulting in limited model performance.

[0004] In the vehicle-grid interaction mode, the operation of the energy storage equipment is based on the real-time operation status of the current station, and is coordinated and controlled by the energy control module in combination with parameters such as peak-valley utilization, photovoltaic smoothing, emergency power supply, and charging load. In the vehicle-grid interaction mode, the charging and discharging data of the energy storage equipment are random and incomplete, which may miss key operating information, affect the accuracy of the health assessment of the energy storage equipment, and reduce the reliability of the vehicle-grid interaction. Summary of the invention

[0005] In view of the above-mentioned deficiencies in the prior art, the present invention provides a method and system for evaluating the health of energy storage equipment based on vehicle-grid interaction to solve the above-mentioned technical problems.

[0006] In a first aspect, the present invention provides a method for evaluating the health of energy storage equipment based on vehicle-grid interaction, which adopts the following technical solution:

[0007] A method for evaluating the health of energy storage equipment based on vehicle-grid interaction includes the following steps:

[0008] S1, collects real-time operation data of multiple energy storage devices and collects charging and discharging data of single cells of each energy storage device;

[0009] S2, obtaining multiple incomplete charge and discharge process information of the single battery based on the operation data within a preset time, integrating the incomplete charge and discharge process information of the single battery into a complete charge and discharge process information, and obtaining the SOH information of the single battery based on the complete charge and discharge process information of the single battery;

[0010] Calculate the difference coefficient of each energy storage device based on the charge and discharge data of the single battery of the energy storage device;

[0011] Calculate the reliability of each energy storage device based on the usage of the energy storage device;

[0012] Calculate the fault alarm information of each energy storage device based on the single battery fault condition of the energy storage device;

[0013] S3, evaluates the health status of each energy storage device based on the single battery SOH information, the difference coefficient of the energy storage device, the reliability information and the fault alarm information;

[0014] S4, comprehensively considering the health status and operating status of multiple energy storage devices, and adjusting the control strategy for all energy storage devices.

[0015] In an optional embodiment, in step S2, multiple incomplete charge and discharge process information of the single battery is obtained based on the operation data within a preset time, and the incomplete charge and discharge process information of the single battery is integrated into a complete charge and discharge process information, specifically including:

[0016] Extracting a plurality of continuous sampling data points of each charging process of a single battery within a preset time, each sampling data point including a specific voltage and a charging capacity increment;

[0017] All the continuous sampling data points of each charging process constitute a capacity increment sequence;

[0018] Construct a cubic spline curve for fitting all capacity increment sequences;

[0019]

[0020]

[0021] Where t represents the voltage independent variable, k represents the index of the interval, represents the starting specific voltage of the kth interval, represents a cubic polynomial function on the kth interval, are the coefficients of the cubic polynomial, represents a cubic spline function;

[0022] Solve the cubic polynomial coefficients by minimizing the objective function;

[0023] The cubic polynomial coefficients are brought into the cubic spline curve for integration to obtain the complete capacity increment sequence as the complete charging and discharging process information.

[0024] In an optional embodiment, the step of obtaining the SOH information of the single cell based on the complete charge and discharge process information of the single cell includes:

[0025] Obtain the complete capacity increment sequence of the single cell and the health test sequence of the single cell;

[0026] Calculate the Euclidean distance between each point in the complete capacity increment sequence and each point in the healthy experiment sequence, and form a distance matrix;

[0027] Based on the DTW algorithm, the cumulative distance on the optimal matching path between the complete capacity increment sequence and the healthy experiment sequence is calculated as the actual DTW distance;

[0028] A mapping relationship table between DTW distance and SOH value is established in advance, and the actual SOH value is obtained based on the actual DTW distance;

[0029] The SOH threshold range in which the actual SOH value is located is determined based on the preset multiple SOH threshold ranges, and the number of single cells in each SOH threshold range of the energy storage device is accumulated as the single cell SOH information of the energy storage device.

[0030] In an optional implementation, the difference coefficient of each energy storage device is calculated based on the charge and discharge data of the single battery of the energy storage device; the difference coefficient of the energy storage device includes a voltage difference coefficient and a temperature difference coefficient, and the specific acquisition steps include:

[0031] Obtain the voltage data curve and temperature data curve of each single battery in the same energy storage device in the same time series;

[0032] Calculate the difference between the voltage data curve of each single battery and the reference voltage data curve, and the difference between the temperature data curve and the reference temperature data curve;

[0033] The voltage difference coefficient of the energy storage device is obtained by weighted synthesis of the difference degrees of different voltage data curves, and the temperature difference coefficient of the energy storage device is obtained by weighted synthesis of the difference degrees of different temperature data curves.

[0034] In an optional embodiment, the reliability of each energy storage device is calculated based on the usage of the energy storage device;

[0035] Based on the actual usage time of each energy storage device within the preset usage time, obtaining the utilization coefficient of each energy storage device;

[0036] Based on the actual operation data of each energy storage device, obtain the availability factor of each energy storage device;

[0037] Based on the outage time of each energy storage device within the preset usage time, an outage coefficient of each energy storage device is obtained.

[0038] In an optional implementation, the fault alarm information of each energy storage device is calculated based on the single cell fault condition of the energy storage device, specifically including:

[0039] The charging and discharging data of a single battery can obtain voltage information, temperature information and SOC information;

[0040] Based on the voltage fault threshold, voltage information is judged to obtain the cumulative number of single cell overvoltage alarms and the cumulative number of single cell undervoltage alarms;

[0041] Based on the temperature fault threshold, the temperature information is judged to obtain the cumulative number of single cell over-temperature alarms and the cumulative number of single cell under-temperature alarms;

[0042] The SOC information is judged based on the SOC fault threshold, and the cumulative number of single-cell battery SOC too high alarms and the cumulative number of single-cell battery SOC too low alarms are obtained.

[0043] In an optional implementation, step S3 specifically includes:

[0044] Based on the AHP method, a judgment matrix is ​​constructed by integrating each item of single cell SOH information, energy storage device consistency, energy storage device reliability and energy storage device fault alarm;

[0045] Conduct consistency check on the judgment matrix and adjust the judgment matrix according to the consistency check result;

[0046] Get the weight of each item based on the final judgment matrix;

[0047] The health of the energy storage system is obtained by weighting each item in the comprehensive single cell SOH information, energy storage device consistency, energy storage device reliability and energy storage device fault alarm.

[0048] In an optional implementation, the operating state of the energy storage device includes the charging state of the energy storage device, and step S4 specifically includes:

[0049] The charging priority is obtained by weighting the health status of each energy storage device and the charging status of the energy storage device;

[0050] Sort the energy storage devices from high to low based on the charging priority to obtain the charging strategy of the energy storage devices;

[0051] The charging priority is obtained by weighting the health status of each energy storage device and the discharge status of the energy storage device;

[0052] The energy storage devices are sorted from high to low based on the discharge priority to obtain the discharge strategy of the energy storage devices.

[0053] In a second aspect, a system for evaluating the health of an energy storage device based on vehicle-grid interaction is provided. The system executes the above-mentioned method for evaluating the health of an energy storage device based on vehicle-grid interaction. The system includes:

[0054] The data acquisition module collects the real-time operation data of multiple energy storage devices and the charge and discharge data of the single battery of each energy storage device.

[0055] The data processing module obtains multiple incomplete charge and discharge process information of the single battery based on the operation data within a preset time, integrates the incomplete charge and discharge process information of the single battery into a complete charge and discharge process information, and obtains the single battery SOH information based on the complete charge and discharge process information of the single battery; calculates the difference coefficient of each energy storage device based on the charge and discharge data of the single battery of the energy storage device; calculates the reliability of each energy storage device based on the usage of the energy storage device; calculates the fault alarm information of each energy storage device based on the fault condition of the single battery of the energy storage device;

[0056] The health evaluation module evaluates the health status of each energy storage device based on the single battery SOH information, the difference coefficient of the energy storage device, the reliability information and the fault alarm information;

[0057] The energy control module comprehensively considers the health status of multiple energy storage devices and adjusts the control strategy for all energy storage devices.

[0058] In summary, the present invention has the following beneficial technical effects:

[0059] Based on the incomplete charging and discharging operation data, the complete charging and discharging process is fitted, and based on the curve data of the charging and discharging capacity increment, the health status of the single battery and the overall energy storage system is evaluated respectively through similarity calculation and artificial intelligence algorithm, and effective information is extracted from the curve as comprehensively as possible, which can accurately reflect the true characteristics of the curve. The health assessment results of the energy storage system are fed back to the energy control module, and the energy control module implements a balanced control strategy based on the health status of the energy storage system, providing protection for the safety of the station, and improving the stability and economic benefits of the station operation through the reasonable control and management of energy storage facilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0061] Figure 1 It is a flow chart of a method for health assessment of energy storage equipment based on vehicle-grid interaction according to an embodiment of the present invention.

[0062] Figure 2 It is a schematic diagram of the control process between the energy storage system and the power generation equipment and the load equipment in an embodiment of the present invention.

[0063] Figure 3 It is a structural schematic diagram of a system for evaluating the health of energy storage equipment based on vehicle-grid interaction according to an embodiment of the present invention. DETAILED DESCRIPTION

[0064] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0065] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0066] The energy storage device health assessment method based on vehicle-grid interaction provided in the embodiment of the present invention is executed by a computer device, and accordingly, the energy storage device health assessment system based on vehicle-grid interaction runs in the computer device.

[0067] Figure 1 is a schematic flow chart of a method according to an embodiment of the present invention. Figure 1 The execution subject may be a health assessment system for energy storage equipment based on vehicle-grid interaction. According to different requirements, the order of the steps in the flowchart may be changed, and some may be omitted.

[0068] like Figure 1 As shown, the method includes:

[0069] Step S1, collecting real-time operation data of multiple energy storage devices and collecting charging and discharging data of single cells of each energy storage device;

[0070] Step S2, obtaining multiple incomplete charge and discharge process information of the single battery based on the operation data within a preset time, integrating the incomplete charge and discharge process information of the single battery into a complete charge and discharge process information, and obtaining the single battery SOH information based on the complete charge and discharge process information of the single battery;

[0071] Step S3, evaluating the health status of each energy storage device based on the single cell SOH information, the difference coefficient of the energy storage device, the reliability information and the fault alarm information;

[0072] Step S4, comprehensively analyzing the health status of multiple energy storage devices and the operating status of the energy storage devices, and adjusting the control strategy for all energy storage devices.

[0073] In an optional implementation, as an embodiment of the present invention, in step S2, multiple incomplete charge and discharge process information of the single battery is obtained based on the operation data within a preset time, and the incomplete charge and discharge process information of the single battery is integrated into a complete charge and discharge process information, specifically including:

[0074] Extracting a plurality of continuous sampling data points of each charging process of a single battery within a preset time, each sampling data point including a specific voltage and a charging capacity increment;

[0075] All the continuous sampling data points of each charging process constitute a capacity increment sequence;

[0076] Construct a cubic spline curve for fitting all capacity increment sequences;

[0077]

[0078]

[0079] Where t represents the voltage independent variable, k represents the index of the interval, represents the starting specific voltage of the kth interval, represents a cubic polynomial function on the kth interval, are the coefficients of the cubic polynomial, represents a cubic spline function;

[0080] Solve the cubic polynomial coefficients by minimizing the objective function;

[0081]

[0082] Where L represents the value of the objective function, is a parameter with a value range of (0,1]. is the weight of the kth point, Indicated in The actual value corresponding to the

[0083] The cubic polynomial coefficients are brought into the cubic spline curve for integration to obtain the complete capacity increment sequence as the complete charging and discharging process information.

[0084] In an optional implementation, as an example of the present invention, we set the voltage range to 3.2V to 3.65V, and collect data at fine intervals of 0.01V. Within this range, the battery charging process is regarded as an incomplete continuous dynamic change process, and the battery capacity changes with the change of voltage. Therefore, we can extract each charging process as a capacity increment sequence consisting of multiple continuous sampling data points. The sequence point of each sequence is the corresponding charging capacity increment at a specific voltage. According to the above settings, we extract multiple capacity increment sequences within the past seven days, recorded as:

[0085] QV1 = ([V1,Q1], [V2,Q2], …[Vm,Qm]),

[0086] QV2 = ([V2,Q2], [V3,Q3], …,[Vn,Qn) ,

[0087] …,

[0088] QVs = ([Vs,Qs], [Vs+1,Qs+1], …,[Vs+t,Qs+t]).

[0089] Where QVi = ([Vm,Qm], [Vm+1,Qm+1], …,[Vn,Qn]) represents a capacity increment sequence starting from voltage m and ending at voltage n;

[0090] Finally, the integration forms a complete sequence QV = ([V1,Q1], [V2,Q2], …,[Vn,Qn]).

[0091] In an optional implementation, as an embodiment of the present invention, in step S2, the step of obtaining the SOH information of the single cell based on the complete charge and discharge process information of the single cell includes:

[0092] Obtain the complete capacity increment sequence of the single cell and the health test sequence of the single cell;

[0093] Calculate the Euclidean distance between each point in the complete capacity increment sequence and each point in the healthy experiment sequence, and form a distance matrix;

[0094] Based on the DTW algorithm, the cumulative distance on the optimal matching path between the complete capacity increment sequence and the healthy experiment sequence is calculated as the actual DTW distance; the DTW algorithm is an effective method to measure the similarity between sequences.

[0095] A mapping relationship table between DTW distance and SOH value is established in advance, and the actual SOH value is obtained based on the actual DTW distance;

[0096] The SOH threshold range in which the actual SOH value is located is determined based on the preset multiple SOH threshold ranges, and the number of single cells in each SOH threshold range of the energy storage device is accumulated as the single cell SOH information of the energy storage device.

[0097] In an optional implementation, as an embodiment of the present invention, the actual calculation of the single cell SOH information is: two capacity increment sequences Q1={q11,q12,…,q1m} and Q2={q21,q22,…,q2n}, where m and n represent the number of data in the sequence. The Euclidean distance between each two feature points is calculated as follows:

[0098]

[0099] Construct an m*n distance matrix, find an optimal path by solving the minimum distance, and calculate the cumulative distance matrix formula as follows:

[0100]

[0101] The last element D(m,n) of the cumulative distance matrix D is the DTW distance of the capacity increment sequence, as shown below:

[0102]

[0103] Finally, the SOH of each single cell is obtained, realizing the real-time monitoring of the health status of the single cell. On this basis, different thresholds are set to divide the level of the single cell SOH. The SOH is divided into 5 health levels. The level division is as follows:

[0104] Grade A: SOH range 0.95-1;

[0105] B grade: SOH range 0.9-0.95;

[0106] C grade: SOH range 0.85-0.9;

[0107] D grade: SOH range 0.8-0.85;

[0108] E grade: SOH range 0-0.8.

[0109] In an optional implementation, as an embodiment of the present invention, in step S2, the difference coefficient of the energy storage device includes a voltage difference coefficient and a temperature difference coefficient, and the specific acquisition steps include:

[0110] Obtain the voltage data curve and temperature data curve of each single battery in the same energy storage device in the same time series;

[0111] Calculate the difference between the voltage data curve of each single battery and the reference voltage data curve, and the difference between the temperature data curve and the reference temperature data curve;

[0112] The voltage difference coefficient of the energy storage device is obtained by weighted synthesis of the difference degrees of different voltage data curves, and the temperature difference coefficient of the energy storage device is obtained by weighted synthesis of the difference degrees of different temperature data curves.

[0113] In an optional implementation, as an example of the present invention, the specific calculation of the difference coefficient is: an energy storage system includes n single cells, and the charge and discharge data of each single cell are collected. The voltage data and temperature data are collected at intervals of 1 minute. For the first battery, its voltage data can be expressed as V1=(V11, V12,…, V1m), where V1m represents the voltage value of the first battery at the mth minute. Similarly, the data of the second battery and the third battery are V2=(V21, V22,…, V2m) and V3=(V31, V32,…, V3m), respectively, and so on, until the nth battery Vn=(Vn1, Vn2,…, Vnm). On the basis of the consistency of the time axis, the difference coefficient of n batteries is calculated, and the formula is as follows

[0114] On the basis of the consistency of the time axis, the total difference of multiple curves is calculated by formula algorithm. The calculation formula is:

[0115]

[0116] Where n represents the total number of observations. represents the i-th observation value of battery 1, and is the ith observation of the reference curve. By summing the squared deviations of each observation and dividing by the number of observations, the mean square error between each curve and the reference curve can be calculated to obtain the degree of difference between multiple curves.

[0117] However, when dealing with multiple curves, relying solely on a single difference metric may not fully reflect the relationship between the curves. Therefore, a weighted average method is introduced to comprehensively evaluate the differences in the various metrics of charging voltage, charging temperature, discharge voltage, and discharge temperature. Set the weight of each metric , then the total difference can be expressed as:

[0118]

[0119] Where m is the number of metrics, and MSEi is the mean square error of the i-th metric. By adjusting the weights, the influence of each metric can be adjusted according to actual needs, thereby obtaining a more accurate total difference assessment. The difference coefficient of each energy storage system is calculated, and the larger the value, the more obvious the difference.

[0120] The health status of single cells and the coefficient of variation of the energy storage system were evaluated, and a comprehensive health assessment of the energy storage system was conducted by combining the energy storage fault alarm information and reliability information.

[0121] In an optional implementation manner, as an embodiment of the present invention, in step S2, the reliability of each energy storage device includes a utilization coefficient, an availability coefficient and an outage coefficient, and the specific acquisition steps include:

[0122] Based on the actual usage time of each energy storage device within the preset usage time, obtaining the utilization coefficient of each energy storage device;

[0123] Based on the actual operation data of each energy storage device, obtain the availability factor of each energy storage device;

[0124] Based on the outage time of each energy storage device within the preset usage time, an outage coefficient of each energy storage device is obtained.

[0125] In an optional implementation manner, as an embodiment of the present invention, in step S2, calculating the fault alarm information of each energy storage device specifically includes:

[0126] The charging and discharging data of a single battery can obtain voltage information, temperature information and SOC information;

[0127] Based on the voltage fault threshold, voltage information is judged to obtain the cumulative number of single cell overvoltage alarms and the cumulative number of single cell undervoltage alarms;

[0128] Based on the temperature fault threshold, the temperature information is judged to obtain the cumulative number of single cell over-temperature alarms and the cumulative number of single cell under-temperature alarms;

[0129] The SOC information is judged based on the SOC fault threshold, and the cumulative number of single-cell battery SOC too high alarms and the cumulative number of single-cell battery SOC too low alarms are obtained.

[0130] In an optional implementation, as an embodiment of the present invention, step S3 specifically includes:

[0131] Specifically include:

[0132] Based on the AHP method, a judgment matrix is ​​constructed by integrating each item of single cell SOH information, energy storage equipment consistency, energy storage equipment reliability and energy storage equipment fault alarm; according to the index scaling method, the importance of evaluation indicators is compared pairwise to construct the judgment matrix A:

[0133]

[0134] in, It is the scale value of the importance of the evaluation indicators i and j at the same level;

[0135] Perform consistency check on the judgment matrix and adjust the judgment matrix according to the consistency check result; specifically calculate the consistency index And the consistency ratio CR:

[0136]

[0137]

[0138] in, is the maximum eigenvalue of the judgment matrix A, and n is the order of the judgment matrix; is the average random consistency test index corresponding to the exponential scale;

[0139] Solve the weight coefficients of each indicator and obtain the weight of each item based on the final judgment matrix;

[0140] The health of the energy storage system is obtained by weighting each item in the comprehensive single cell SOH information, energy storage device consistency, energy storage device reliability and energy storage device fault alarm.

[0141] In an optional implementation manner, as an embodiment of the present invention, step S4 specifically includes:

[0142] Evaluating the health status of each energy storage system and feeding it back to the energy control module is a key factor in achieving the coordinated operation of multiple energy storage systems. In the case of multiple energy storage systems, frequent charging and discharging will accelerate their decay process. It is particularly important to comprehensively consider the status of each energy storage system and formulate a reasonable scheduling plan. Find energy storage systems with higher operating efficiency and assign more energy storage and release tasks to these energy storage systems, thereby improving the energy utilization efficiency of the overall system.

[0143] SOC refers to the current state of charge of the battery, usually expressed as the ratio of the current power of the battery to its maximum available power. Too high or too low SOC may cause damage to the battery. SOH refers to the current health state of the battery, usually expressed as the ratio of the current capacity to the designed capacity. The monitoring of SOH can provide us with the actual performance of the battery, thus providing a basis for charge and discharge scheduling. The larger the SOH value, the better the health state, and charging and discharging should be given priority, while energy storage systems with low SOH values ​​are used as auxiliary charging and discharging; the larger the SOC value, the more available power, and discharge should be given priority while charging should be reduced, while the lower the SOC value, the less available power, and charging should be given priority while discharging should be minimized.

[0144] Effectively combining SOC and SOH to establish a dynamic coordinated control strategy for the energy storage system, and adaptively adjusting the charging and discharging strategy can achieve more intelligent charging and discharging management to ensure that the battery operates in the best state. The dynamic coordinated control strategy requires the calculation of the charging and discharging priority of each energy storage system.

[0145] The charging priority is obtained by weighting the health status of each energy storage device and the charging status of the energy storage device. The charging priority calculation formula is as follows:

[0146]

[0147] The charging priority is obtained by weighting the health status of each energy storage device and the discharge status of the energy storage device. The discharge priority calculation formula is as follows:

[0148]

[0149] in, is the weight coefficient of SOH, yes The weight coefficient of .

[0150] According to charging priority and discharge priority The energy storage systems are ranked from high to low, and dynamically coordinated and controlled in sequence.

[0151] In an optional implementation manner, as an embodiment of the present invention, as Figure 2 As shown, in step S4, in the actual use of the energy storage device, the comprehensive step flow with the power generation equipment and the equipment using the load includes:

[0152] When Ppv > Pbe + Pec and the energy storage SOC has not reached the maximum SOC limit MAX_SOC, the energy storage health status and energy storage charge state are comprehensively considered, and each energy storage device is reasonably regulated for charging so that the remaining photovoltaic power generation is given priority to charging the energy storage. At this time, V2G charging piles are prohibited from discharging, and energy storage is prohibited from discharging; when the energy storage SOC reaches the required limit MAX_SOC, the excess photovoltaic power is adjusted to implement the light abandonment strategy by adjusting the photovoltaic power.

[0153] When Pbe < Ppv< Pbe + Pec, if there are vehicles that meet the V2G discharge conditions, the platform controls the V2G vehicle to discharge and supplement the charging power of the charging pile. In the emergency guarantee mode, according to the charging strategy, the charging power of the charging pile is adjusted to the minimum charging power in sequence. When Ppv + Pdc still cannot meet the charging demand, the charging of the charging pile is stopped in sequence according to the charging strategy. Then the energy storage system is regulated to discharge. When the energy storage SOC is not less than the minimum SOC energy storage limit MIN_SOC, the energy storage health status and energy storage charge state are comprehensively considered, and each energy storage device is reasonably regulated to discharge. When the energy storage SOC is less than the minimum SOC energy storage limit MIN_SOC, office equipment such as air conditioners are controlled.

[0154] When Ppv < Pbe, if there are vehicles that meet the V2G discharge conditions, the platform controls the V2G vehicle to discharge and supplement the charging needs of necessary equipment. Then the energy storage system is regulated to discharge. When the energy storage SOC is not less than the minimum SOC energy storage limit MIN_SOC, the energy storage health status and energy storage charge state are comprehensively considered, and each energy storage device is reasonably regulated to discharge. When the energy storage SOC is less than the minimum SOC energy storage limit MIN_SOC, office equipment such as air conditioners are controlled.

[0155] Among them, Ppv is the photovoltaic power generation power, Pbe is the load power of necessary equipment at the station, office load, Pec is the charging power of the charging pile, Pdc is the discharging power of the charging pile, and Pes is the energy storage power.

[0156] In some embodiments, the energy storage device health assessment system based on vehicle-grid interaction may include a plurality of functional modules composed of computer program segments. The computer programs of the various program segments in the energy storage device health assessment system based on vehicle-grid interaction may be stored in a memory of a computer device and executed by at least one processor to execute (see Figure 1 Description) Function of energy storage device health assessment based on vehicle-grid interaction.

[0157] In this embodiment, the energy storage device health assessment system based on vehicle-grid interaction can be divided into multiple functional modules according to the functions it performs, such as Figure 3 As shown. The functional modules of the system may include: a data acquisition module, a data processing module, a health assessment module and an energy control module. The module referred to in the present invention refers to a series of computer program segments that can be executed by at least one processor and can complete fixed functions, which are stored in a memory. In this embodiment, the functions of each module will be described in detail in subsequent embodiments.

[0158] In an optional implementation, as an embodiment of the present invention, the functions of each module of the system specifically include:

[0159] The data acquisition module collects real-time operating data of multiple energy storage devices and the charging and discharging data of the single battery of each energy storage device. It is the basis and guarantee for realizing the health evaluation of energy storage equipment. It is responsible for the acquisition and transmission of information, and is the basis for realizing data-driven decision-making. It is responsible for collecting and controlling the operation data of the voltage, current, power, temperature, power, status, etc. of some key points of the aggregation control resources.

[0160] The data processing module obtains multiple incomplete charging and discharging process information of the single battery based on the operation data within the preset time, integrates the incomplete charging and discharging process information of the single battery into a complete charging and discharging process information, and obtains the single battery SOH information based on the complete charging and discharging process information of the single battery; calculates the difference coefficient of each energy storage device based on the charging and discharging data of the single battery of the energy storage device; calculates the reliability of each energy storage device based on the usage of the energy storage device; calculates the fault alarm information of each energy storage device based on the single battery failure of the energy storage device; in view of the fact that the charging and discharging process of the energy storage device in the vehicle-grid interaction mode is affected by many factors, incomplete charging and discharging records often appear. These incomplete data may lead to deviations in the analysis results. These incomplete charging and discharging processes are integrated into a complete charging and discharging process through data modeling to accurately describe the dynamic characteristics of charging and discharging; the complete charging and discharging process data obtained by the data processing module, the single battery experimental data is used to analyze the patterns and trends in the battery aging process, especially the analysis of the capacity increment curve, and the single battery in the energy storage system is evaluated for health through machine learning and deep learning algorithms.

[0161] The health evaluation module evaluates the health status of each energy storage device based on the single cell SOH information, the difference coefficient of the energy storage device, the reliability information and the fault alarm information. It comprehensively evaluates the health status of the energy storage system from four aspects: single cell operating condition, battery consistency, regulation reliability and operating environment, and feeds back the health status to the energy regulation module to guide the operation control of the energy regulation strategy.

[0162] The energy control module integrates the health status of multiple energy storage devices and adjusts the control strategy for all energy storage devices. The control center of the energy storage device health status assessment and control system based on the vehicle-grid interaction mode realizes unified dispatch management, multi-energy complementary optimization and coordinated operation control within the station with its effective energy management strategy. Aggregate control resources include photovoltaic, energy storage, charging piles, air conditioning, lighting and other equipment.

[0163] The energy storage equipment health status assessment and control system based on the vehicle-grid interaction mode first issues collection tasks regularly through the energy control module according to the actual operation status of the equipment, historical data and environmental factors. The data collection task is completed by the data collection module, and the data processing module performs data cleaning, conversion, merging and other processing on the collected data to improve the reliability of the data. The health assessment module uses the data processed by the data processing module and adopts data analysis technologies such as machine learning to build a health assessment model for energy storage equipment to evaluate the health status of the current energy storage equipment. Based on the evaluation results, the control system will implement corresponding control strategies, which include adjusting operating parameters, optimizing charging and discharging strategies, etc. The various module processes of the energy storage equipment health status assessment and control system complement each other. Through effective health status assessment and intelligent control, not only the safety and reliability of energy storage equipment are improved, but also the interaction and coordination between vehicles and networks are promoted.

[0164] Therefore, the present invention provides a method and system for evaluating the health of energy storage equipment based on vehicle-grid interaction. The technical effects that can be achieved by this embodiment can be found in the description above and will not be repeated here.

[0165] Those skilled in the art can clearly understand that the technology in the embodiments of the present invention can be implemented by means of software plus a necessary general hardware platform. Based on this understanding, the technical solution in the embodiments of the present invention, in essence or in other words, the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, and other media that can store program codes, including several instructions for enabling a computer terminal (which can be a personal computer, a server, or a second terminal, a network terminal, etc.) to execute all or part of the steps of the methods described in each embodiment of the present invention.

[0166] In this specification, the same or similar parts between the various embodiments can be referred to each other. In particular, for the terminal embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the description in the method embodiment.

[0167] In the several embodiments provided by the present invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of systems or modules, which can be electrical, mechanical or other forms.

[0168] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0169] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0170] Although the present invention has been described in detail with reference to the accompanying drawings and in combination with the preferred embodiments, the present invention is not limited thereto. Without departing from the spirit and essence of the present invention, a person of ordinary skill in the art may make various equivalent modifications or substitutions to the embodiments of the present invention, and these modifications or substitutions shall be within the scope of the present invention. Any person of ordinary skill in the art may easily think of changes or substitutions within the technical scope disclosed by the present invention, and these shall be within the scope of protection of the present invention.

Claims

1. A method for evaluating the health of energy storage equipment based on vehicle-grid interaction, characterized in that: The following steps are involved: S1, collects real-time operation data of multiple energy storage devices and collects charging and discharging data of single cells of each energy storage device; S2, obtaining multiple incomplete charge and discharge process information of the single battery based on the operation data within a preset time, integrating the incomplete charge and discharge process information of the single battery into a complete charge and discharge process information, and obtaining the SOH information of the single battery based on the complete charge and discharge process information of the single battery; Calculate the difference coefficient of each energy storage device based on the charge and discharge data of the single battery of the energy storage device; Calculate the reliability of each energy storage device based on the usage of the energy storage device; Calculate the fault alarm information of each energy storage device based on the single battery fault condition of the energy storage device; In step S2, a plurality of incomplete charge and discharge process information of the single battery is obtained based on the operation data within a preset time, and the incomplete charge and discharge process information of the single battery is integrated into a complete charge and discharge process information, which specifically includes: Extracting a plurality of continuous sampling data points of each charging process of a single battery within a preset time, each sampling data point including a specific voltage and a charging capacity increment; All the continuous sampling data points of each charging process constitute a capacity increment sequence; Construct a cubic spline curve for fitting all capacity increment sequences; Where t represents the voltage independent variable, k represents the index of the interval, represents the starting specific voltage of the kth interval, represents a cubic polynomial function on the kth interval, are the coefficients of the cubic polynomial, represents a cubic spline function; Solve the cubic polynomial coefficients by minimizing the objective function; The cubic polynomial coefficients are brought into the cubic spline curve for integration to obtain a complete capacity increment sequence as the complete charge and discharge process information; S3, evaluates the health status of each energy storage device based on the single battery SOH information, the difference coefficient of the energy storage device, the reliability information and the fault alarm information; Step S3 specifically includes: Based on the AHP method, a judgment matrix is ​​constructed by integrating each item of single cell SOH information, energy storage device consistency, energy storage device reliability and energy storage device fault alarm; Conduct consistency check on the judgment matrix and adjust the judgment matrix according to the consistency check result; Get the weight of each item based on the final judgment matrix; The health of the energy storage system is obtained by weighting each item in the comprehensive single cell SOH information, energy storage device consistency, energy storage device reliability and energy storage device fault alarm; S4, comprehensively considering the health status and operating status of multiple energy storage devices, and adjusting the control strategy for all energy storage devices.

2. The method for evaluating the health of energy storage equipment based on vehicle-grid interaction according to claim 1 is characterized in that: The steps of obtaining the SOH information of a single cell based on the complete charge and discharge process information of the single cell include: Obtain the complete capacity increment sequence of the single cell and the health test sequence of the single cell; Calculate the Euclidean distance between each point in the complete capacity increment sequence and each point in the healthy experiment sequence, and form a distance matrix; Based on the DTW algorithm, the cumulative distance on the optimal matching path between the complete capacity increment sequence and the healthy experiment sequence is calculated as the actual DTW distance; A mapping relationship table between DTW distance and SOH value is established in advance, and the actual SOH value is obtained based on the actual DTW distance; The SOH threshold range in which the actual SOH value is located is determined based on the preset multiple SOH threshold ranges, and the number of single cells in each SOH threshold range of the energy storage device is accumulated as the single cell SOH information of the energy storage device.

3. The method for evaluating the health of energy storage equipment based on vehicle-grid interaction according to claim 2 is characterized in that: Calculate the difference coefficient of each energy storage device based on the charge and discharge data of the single battery of the energy storage device; The difference coefficient of the energy storage device includes the voltage difference coefficient and the temperature difference coefficient. The specific acquisition steps include: Obtain the voltage data curve and temperature data curve of each single battery in the same energy storage device in the same time series; Calculate the difference between the voltage data curve of each single battery and the reference voltage data curve, and the difference between the temperature data curve and the reference temperature data curve; The voltage difference coefficient of the energy storage device is obtained by weighted synthesis of the difference degrees of different voltage data curves, and the temperature difference coefficient of the energy storage device is obtained by weighted synthesis of the difference degrees of different temperature data curves.

4. The method for evaluating the health of energy storage equipment based on vehicle-grid interaction according to claim 3 is characterized in that: Calculate the reliability of each energy storage device based on the usage of the energy storage device; Specifically include: Based on the actual usage time of each energy storage device within the preset usage time, obtaining the utilization coefficient of each energy storage device; Based on the actual operation data of each energy storage device, obtain the availability factor of each energy storage device; Based on the outage time of each energy storage device within the preset usage time, an outage coefficient of each energy storage device is obtained.

5. The method for evaluating the health of energy storage equipment based on vehicle-grid interaction according to claim 4 is characterized in that: The fault alarm information of each energy storage device is calculated based on the single battery fault condition of the energy storage device, including: The charging and discharging data of a single battery can obtain voltage information, temperature information and SOC information; Based on the voltage fault threshold, voltage information is judged to obtain the cumulative number of single cell overvoltage alarms and the cumulative number of single cell undervoltage alarms; Based on the temperature fault threshold, the temperature information is judged to obtain the cumulative number of single cell over-temperature alarms and the cumulative number of single cell under-temperature alarms; The SOC information is judged based on the SOC fault threshold, and the cumulative number of single-cell battery SOC too high alarms and the cumulative number of single-cell battery SOC too low alarms are obtained.

6. The method for evaluating the health of energy storage equipment based on vehicle-grid interaction according to claim 5 is characterized in that: The operating state of the energy storage device includes the charging state of the energy storage device. Step S4 specifically includes: The charging priority is obtained by weighting the health status of each energy storage device and the charging status of the energy storage device; Sort the energy storage devices from high to low based on the charging priority to obtain the charging strategy of the energy storage devices; The charging priority is obtained by weighting the health status of each energy storage device and the discharge status of the energy storage device; The energy storage devices are sorted from high to low based on the discharge priority to obtain the discharge strategy of the energy storage devices.

7. A health assessment system for energy storage equipment based on vehicle-grid interaction, characterized in that: The system executes the energy storage device health assessment method based on vehicle-grid interaction as described in any one of claims 1 to 6, and the system includes: The data acquisition module collects the real-time operation data of multiple energy storage devices and the charge and discharge data of the single battery of each energy storage device; The data processing module obtains multiple incomplete charge and discharge process information of the single battery based on the operation data within a preset time, integrates the incomplete charge and discharge process information of the single battery into a complete charge and discharge process information, and obtains the single battery SOH information based on the complete charge and discharge process information of the single battery; calculates the difference coefficient of each energy storage device based on the charge and discharge data of the single battery of the energy storage device; calculates the reliability of each energy storage device based on the usage of the energy storage device; calculates the fault alarm information of each energy storage device based on the fault condition of the single battery of the energy storage device; The health evaluation module evaluates the health status of each energy storage device based on the single battery SOH information, the difference coefficient of the energy storage device, the reliability information and the fault alarm information; The energy control module comprehensively considers the health status of multiple energy storage devices and adjusts the control strategy for all energy storage devices.

Images