Method and device for evaluating health state of energy storage equipment

Abstract

The invention belongs to the technical field of electric energy storage, and particularly relates to a method and device for evaluating the health state of energy storage equipment. In order to solve the problems that in the prior art, when evaluation is carried out by calculating the dispersion degree of each index of the energy storage equipment operation information, the adopted calculation mode is tedious, and the accuracy is low, the method comprises the following steps: calculating the membership degree and the weight coefficient of each index of the energy storage equipment operation information; according to the method, the calculation is simple, the qualitative problem is quantified, so that the evaluation result is clearer, the systematicness is higher, the accuracy of the evaluation result is improved, the health state of the energy storage equipment can be evaluated online in real time, and the method is suitable for popularization and application. And stable operation of the energy storage system is ensured.

Description

Technical Field

[0001] The present invention belongs to the technical field of electric energy storage, and particularly relates to a method and device for evaluating the health state of an energy storage device. Background Art

[0002] With the development of electric energy storage technology, the scale of energy storage devices is getting larger and larger. Among them, the health status of energy storage devices affects the stable operation of energy storage systems. Therefore, the monitoring of the health status of energy storage devices is particularly important. At present, most traditional health assessment methods evaluate energy storage devices based on their operation information. For example, the Chinese patent application with the publication number CN113030761A discloses a method and system for evaluating the health state of batteries in an ultra-large-scale energy storage power station. By performing standard deviation analysis on the correlation relationship model between preset evaluation indicators and the health state of energy storage batteries, the overall standard deviation and the sample relative standard deviation are obtained, and the coefficient of variation is calculated based on the overall standard deviation and the sample relative standard deviation. The weight of the evaluation indicators is measured based on the principle of maximum membership degree, and then the dispersion degree of each evaluation indicator is obtained according to the comprehensive ratio set by the sample relative standard deviation, coefficient of variation and weight of each evaluation indicator. Finally, the health state of the battery is determined according to the dispersion degree. When calculating the dispersion degree of each index for evaluation in the last step, this method uses a relatively cumbersome calculation method and has low accuracy. Summary of the Invention

[0003] The purpose of the present invention is to provide a method and device for evaluating the health state of an energy storage device, so as to solve the problems that the existing technology uses a relatively cumbersome calculation method and has low accuracy when evaluating by calculating the dispersion degree of each index of the operation information of the energy storage device.

[0004] To solve the above technical problems, the present invention provides a method for evaluating the health state of an energy storage device, which obtains the data of each index of the operation information of the energy storage device, calculates the coefficient of variation of each index according to the data of each index, and calculates the proportion of the coefficient of variation of each index in the total sum of the coefficients of variation of all indexes to obtain the weight coefficient of each index; calculates the membership degree of each index according to the type of membership function to which each index belongs and the range of this type of membership function in which the data of each index is located; combines the weight coefficient and membership degree of each index of the operation information obtained by calculation, calculates the evaluation result of the energy storage device evaluated according to the operation information, and evaluates the health state of the energy storage device according to the evaluation result.

[0005] Its beneficial effects are as follows: To solve the problems that the calculation methods used in the prior art for evaluating by calculating the dispersion of each index of the operating information of energy storage devices are relatively cumbersome and have low accuracy, the present invention is an improved invention. By calculating the membership degree and weight coefficient of each index of the operating information of energy storage devices, combining the calculated membership degree and weight coefficient to evaluate the energy storage devices based on the operating information, and finally evaluating the health status of the energy storage power station according to the evaluation results of the operating information. The method of the present invention is simple in calculation, quantifies qualitative problems, makes the evaluation results clearer and more systematic, thereby improving the accuracy of the evaluation results. It can also evaluate the health status of energy storage devices in real time online to ensure the stable operation of the energy storage system.

[0006] Further, the means for evaluating the health status of energy storage devices are as follows: Calculate the evaluation results of energy storage devices based on alarm information, and perform weighted summation on the evaluation results of operating information and the evaluation results of alarm information to comprehensively evaluate the health status of energy storage devices; among them, the specific means for evaluating energy storage devices based on alarm information include:

[0007] Obtain the data of each index of the alarm information of the energy storage device, and perform weighted summation on the data of each index according to the set weight coefficient and scoring standard of each index to obtain the evaluation results of the energy storage device based on the alarm information.

[0008] Its beneficial effects are as follows: Combining the alarm information of energy storage devices for comprehensive evaluation, further improving the accuracy of the evaluation results, having guiding significance for early fault warning of power station equipment, and facilitating the maintenance of energy storage devices by operation and maintenance personnel to ensure the stable operation of the energy storage system.

[0009] Further, the types of membership functions include S-type membership functions and parabolic membership functions. The calculation formulas of the two types of membership functions are as follows:

[0010]

[0011] Among them, μ 1 (x) is a parabolic membership function; μ 2 (x) is an S-type membership function; x is the data of each index of the obtained operating information; x 1 is the lower limit value of the operating information index; x 2 is the lower limit value of the optimal numerical value of the operating information index; x 3 is the upper limit value of the optimal numerical value of the operating information index; x 4 is the upper limit value of the operating information index.

[0012] Its beneficial effects are as follows: it is conducive to quantifying each index, and the evaluation of each index after quantification is more in line with objective facts, which can not only improve the evaluation efficiency, but also make the evaluation of the health state of energy storage devices more accurate.

[0013] Furthermore, the calculation formula for the health evaluation result of the operation information of the energy storage device is as follows:

[0014] B = A × R T × 100%

[0015]

[0016] Wherein, B is the comprehensive scoring matrix of the health state quantification of the energy storage device; A is the membership degree matrix of each operation information index of all devices of the same type of energy storage device; R T is the transpose of the weight coefficient vector R; b m is the information score of the operation information index class of the m-th energy storage device; m is the number of energy storage devices; n is the number of evaluation indexes of the operation information of the energy storage device; μ mn is the membership degree of the n-th operation information index of the m-th energy storage device; r n is the weight coefficient of the n-th operation information index.

[0017] Its beneficial effects are as follows: it is conducive to making the evaluation of each operation information index more in line with the actual situation of the device, making the evaluation more accurate and efficient, so as to ensure the stable operation of the energy storage system.

[0018] Furthermore, each index of the operation information of the energy storage device includes current, SOC, and charge-discharge efficiency.

[0019] Its beneficial effects are as follows: taking the above-mentioned parameters as the indexes of the operation information of the energy storage device is conducive to reflecting the most real health state of the operation status of the energy storage device to prevent faults of the energy storage device.

[0020] Furthermore, each index of the alarm information of the energy storage device includes the number of fault alarms and the number of abnormal alarms.

[0021] Its beneficial effects are as follows: taking the above-mentioned parameters as the indexes of the alarm information of the energy storage device is conducive to reflecting the historical alarm status of the energy storage device, has guiding significance for early fault warning of power station equipment, and is convenient for maintenance personnel to repair the energy storage device.

[0022] To solve the above technical problems, the present invention also provides an evaluation device for the health state of an energy storage device, including a memory and a processor, and the processor is used to execute computer program instructions stored in the memory to implement an evaluation method for the health state of an energy storage device introduced above.

[0023] Its beneficial effects are as follows: The device ensures the effective and reliable execution of a method for evaluating the health status of an energy storage device.

[0024] Furthermore, the means for evaluating the health status of the energy storage device are as follows: Calculate the evaluation result of the energy storage device based on the alarm information, and perform a weighted sum of the evaluation results of the operation information and the evaluation result of the alarm information to comprehensively evaluate the health status of the energy storage device; among them, the specific means for the energy storage device to evaluate based on the alarm information include:

[0025] Obtain the data of each index of the alarm information of the energy storage device, and perform a weighted sum of the data of each index according to the set weight coefficients and scoring criteria of each index to obtain the evaluation result of the energy storage device based on the alarm information.

[0026] Its beneficial effects are as follows: Combining the alarm information of the energy storage device for comprehensive evaluation further improves the accuracy of the evaluation result, has guiding significance for early fault warning of power station equipment, and facilitates the maintenance of the energy storage device by operation and maintenance personnel, ensuring the stable operation of the energy storage system.

[0027] Furthermore, the membership function types include S-shaped membership function and parabolic membership function, and the calculation formulas of the two types of membership functions are as follows:

[0028]

[0029]

[0030] Among them, μ 1 (x) is the parabolic membership function; μ 2 (x) is the S-shaped membership function; x is the data of each index of the obtained operation information; x 1 is the lower limit value of the operation information index; x 2 is the lower limit value of the optimal numerical value of the operation information index; x 3 is the upper limit value of the optimal numerical value of the operation information index; x 4 is the upper limit value of the operation information index.

[0031] Its beneficial effects are as follows: It is beneficial to quantify each index, and the evaluation of each quantified index is more in line with objective facts, which can not only improve the evaluation efficiency, but also make the evaluation of the health status of the energy storage device more accurate.

[0032] Furthermore, the calculation formula for the health evaluation result of the operation information of the energy storage device is as follows:

[0033] B = A × R T × 100%

[0034]

[0035] Among them, B is the comprehensive scoring matrix for quantifying the health state of the energy storage device; A is the membership matrix of each operation information index of all devices of the same type of energy storage device; R T is the transpose of the weight coefficient vector R; b m is the information score of the operation information index class of the m-th energy storage device; m is the number of energy storage devices; n is the number of evaluation indexes of the operation information of the energy storage device; μ mn is the membership degree of the n-th operation information index of the m-th energy storage device; r n is the weight coefficient of the n-th operation information index.

[0036] Its beneficial effect is: it is beneficial to make the evaluation of each operation information index more in line with the actual situation of the device, make the evaluation more accurate and efficient, and thus ensure the stable operation of the energy storage system.

[0037] Furthermore, each index of the operation information of the energy storage device includes current, SOC, and charge and discharge efficiency.

[0038] Its beneficial effect is: taking the above and each parameter as the index of the operation information of the energy storage device is beneficial to reflecting the most real health state of the operation status of the energy storage device to prevent faults of the energy storage device.

[0039] Furthermore, each index of the alarm information of the energy storage device includes the number of fault alarms and the number of abnormal alarms.

[0040] Its beneficial effect is: taking the above and each parameter as the index of the alarm information of the energy storage device is beneficial to reflecting the historical alarm status of the energy storage device, has guiding significance for early fault warning of power station equipment, and is convenient for maintenance personnel to repair the energy storage device. Description of the Drawings

[0041] Figure 1 is the flow chart for evaluating the health state of the energy storage device in this embodiment. Detailed Implementation Manner

[0042] The basic concept of the present invention is: determining the evaluation indexes of the operation information of the energy storage device and obtaining the relevant data of each index, calculating the weights of each index of the operation information, and then evaluating according to the determined evaluation criteria to obtain the evaluation result of the energy storage device based on the operation information, and then evaluating the health state of the energy storage device according to this evaluation result. The principle of the present invention is: the operation information of the energy storage device uses the coefficient of variation to calculate the index weights of this type of information, and then calculates the membership degrees of each index of the operation information of the energy storage device, combines the calculated membership degrees and weight coefficients to evaluate the energy storage device based on the operation information, and finally evaluates the health state of the energy storage power station according to the evaluation result of the operation information. Based on this concept, an evaluation method for the health state of an energy storage device and an evaluation device for the health state of an energy storage device of the present invention can be realized.

[0043] The present invention will be described in detail below in conjunction with the accompanying drawings and method embodiments.

[0044] Method embodiments:

[0045] An evaluation method for the health state of an energy storage device according to the present invention has a flowchart as Figure 1 shown. In this embodiment, the energy storage device is a battery cluster. The steps for evaluating the operation information of the battery cluster include:

[0046] Step 1: Use the current, state of charge (SOC), and charge-discharge efficiency of the battery cluster as the operation information indicators of the battery cluster, and count the data of each indicator for each battery cluster. Among them, single-index factor evaluation and analysis can be performed on the battery cluster. By counting the distribution of each operation information indicator of the battery cluster, the consistency and health state of the battery can be obtained.

[0047] Step 2: Calculate the weight coefficients of each indicator for each battery cluster according to the data of each operation information indicator of the battery cluster. The specific calculation steps are as follows:

[0048] 1) Calculate the average value and standard deviation corresponding to the current, SOC, and charge-discharge efficiency respectively in the indicators of the operation information of the battery cluster, and then divide the standard deviation of each operation information indicator by its average value to obtain the coefficient of variation of this indicator. The calculation formula is as follows:

[0049]

[0050] Among them, V i is the coefficient of variation of the i-th operation information indicator; σ i is the standard deviation of the i-th operation information indicator; x i is the average value of the i-th operation information indicator;

[0051] 2) By calculating the proportion of the coefficient of variation of each operation information indicator of the battery cluster in the total sum of the coefficients of variation of all operation information indicators, obtain the weight coefficients of each operation information indicator. The specific calculation formula is as follows:

[0052]

[0053] Among them, r i is the weight coefficient of the i-th indicator;

[0054] 3) Combine the weight coefficients of each operation information indicator to obtain a weight coefficient vector R, R = [r 1 , r 2 , …… r n , where n is the total number of operation information indicators.

[0055] Step 3: Calculate the membership degrees of each operation information index and combine them into an evaluation matrix. The specific calculation steps are as follows:

[0056] ① Set the operation information indexes that meet the following conditions as S-type membership functions: positively or negatively correlated with the battery state within a certain range, and having little impact on the battery state beyond this range; set the operation information indexes that meet the following conditions as parabolic membership functions: most beneficial to the battery state within a certain range, and it is not conducive to battery health to increase or decrease deviating from this range.

[0057] Among them, the calculation formula of the parabolic membership function is as follows:

[0058]

[0059] Among them, μ 1 (x) is the parabolic membership function; x is the data of each index of the operation information obtained; x 1 is the lower limit value of the operation information index; x 2 is the lower limit value of the optimal value of the operation information index; x 3 is the upper limit value of the optimal value of the operation information index; x 4 is the upper limit value of the operation information index; the battery cluster current and SOC in the operation information index both belong to the parabolic membership function, and the membership function is calculated according to the standard deviation of the two indexes.

[0060] The calculation formula of the S-type membership function is as follows:

[0061]

[0062] Among them, μ 2 (x) is the S-type membership function; the battery cluster charge and discharge efficiency in the operation information index of this embodiment belongs to the S-type membership function.

[0063] ② Combine the membership degrees of each calculated operation information index to obtain an evaluation matrix:

[0064]

[0065] Among them, A is; m is the number of battery clusters; n is the number of battery evaluation indexes; μ mn is the membership degree of the nth operation information index of the mth battery cluster.

[0066] Step 4: Adopt the fuzzy comprehensive evaluation algorithm and combine the weight coefficients of each index and the membership degrees of each index to quantitatively comprehensively evaluate the operation information indexes of the battery cluster. The formula is as follows:

[0067] B = A × R T × 100%

[0068]

[0069] Among them, B is the comprehensive scoring matrix for quantifying the health status of the battery cluster; b m is the information score of the operation information index class of the m-th battery cluster; R T is the transpose of the weight coefficient vector R.

[0070] The steps for evaluating the battery cluster alarm information include:

[0071] (1) Select the number of battery cluster fault alarms and the number of battery cluster abnormal alarms as the indicators of the battery cluster alarm information, set the weights of each indicator according to the on-site empirical data and put them into the expert library, and the expert library supports the resetting of the weight coefficients; the weights of the indicators of the alarm information in this embodiment are shown in Table 1 below:

[0072] Table 1

[0073] Indicator ID Device Type Indicator Classification ID Indicator Name Weight Data Type Data Retrieval Period 1 1 2 Number of Battery Cluster Fault Alarms 0.75 1 0 2 1 2 Number of Battery Cluster Abnormal Alarms 0.15 1 0

[0074] (2) As shown in Table 2 below, formulate the scoring criteria for each indicator of the battery cluster alarm information, put the scoring criteria into the expert library, and the expert library supports the modification of the scoring criteria; for example, if the number of alarms of a certain alarm information indicator is within 0 - 5 times (including 5), then the score of this alarm indicator is 100.

[0075] Table 2

[0076] Scoring Standard ID Indicator ID Lower Limit of Indicator Value Upper Limit of Indicator Value Score Scoring Grade 1 1 0 5 100 1 2 1 5 10 90 2 3 1 10 20 80 3 4 1 20 30 70 4 5 1 30 40 60 5 6 2 0 5 100 1 7 2 5 10 90 2 8 2 10 20 80 3 9 2 20 30 70 4 10 2 30 40 60 5

[0077] According to the scoring criteria in the above table, obtain the scores of each indicator, and then perform weighted summation on each indicator of the battery cluster alarm information according to the weight coefficients of each indicator to obtain a quantitative comprehensive evaluation of the operation information indicators of the battery cluster.

[0078] Based on the expert library, perform weighted summation on the evaluation results of the battery cluster operation information and the evaluation results of the battery cluster alarm information, and finally obtain the comprehensive evaluation result of the battery cluster health status. When it is greater than or equal to the level included in the evaluation conclusion, push out the result; the weights of the operation information and the alarm information in this embodiment during the comprehensive evaluation are shown in Table 3 below:

[0079] Table 3

[0080] Indicator Classification ID Device ID Indicator Type Name Evaluation Conclusion Includes Grade Automatic Evaluation Interval (days) Weight 1 1 Operating Indicator 4 1 0.5 2 1 Alarm Indicator 4 1 0.5

[0081] The method of the present invention is simple to calculate, quantifies qualitative problems, makes the evaluation results clearer and more systematic, thereby improving the accuracy of the evaluation results, has guiding significance for early fault warning of power station equipment, and is convenient for maintenance personnel to repair energy storage equipment, ensuring the stable operation of the energy storage system.

[0082] Device embodiment:

[0083] An evaluation device for the health state of an energy storage device according to the present invention includes a memory and a processor. The processor is configured to execute computer program instructions stored in the memory to implement an evaluation method for the health state of an energy storage device introduced in the method embodiment of the present invention. Among them, the processor can be a processing device such as a programmable logic device FPGA. The memory can be various memories that store information in the form of electric energy, such as RAM, ROM, etc., and can also be memories in other forms.

Claims

1. A method for evaluating the health state of an energy storage device, characterized in that, obtain the data of each index of the operation information of the energy storage device, calculate the coefficient of variation of each index according to the data of each index, and calculate the proportion of the coefficient of variation of each index in the total sum of the coefficients of variation of all indexes to obtain the weight coefficient of each index; calculate the membership degree of each index according to the type of membership function to which each index belongs and the range of this type of membership function where the data of each index is located; combine the weight coefficient and membership degree of each index of the operation information obtained by calculation, calculate the evaluation result of the energy storage device based on the operation information, and evaluate the health state of the energy storage device according to this evaluation result.

2. The method for evaluating the health state of an energy storage device according to claim 1, characterized in that, the means for evaluating the health state of the energy storage device is: calculate the evaluation result of the energy storage device based on the alarm information, and perform weighted summation on the evaluation result of the operation information and the evaluation result of the alarm information to comprehensively evaluate the health state of the energy storage device; wherein, the specific means for the energy storage device to evaluate based on the alarm information includes: obtain the data of each index of the alarm information of the energy storage device, and perform weighted summation on the data of each index according to the set weight coefficient of each index and the scoring standard to obtain the evaluation result of the energy storage device based on the alarm information.

3. The method for evaluating the health state of an energy storage device according to claim 1, characterized in that, the types of membership functions include S-type membership functions and parabolic membership functions, and the calculation formulas of the two types of membership functions are as follows: Among them, μ 1 (x) is a parabolic membership function; μ 2 (x) is an S-shaped membership function; x is the data of each index of the obtained operation information; x 1 is the lower limit value of the operation information index; x 2 is the lower limit value of the optimal numerical value of the operation information index; x 3 is the upper limit value of the optimal numerical value of the operation information index; x 4 is the upper limit value of the operation information index.

4. The method for evaluating the health state of an energy storage device according to claim 1, characterized in that, the calculation formula of the health evaluation result of the operation information of the energy storage device is as follows: B = A × R T × 100% Among them, B is the comprehensive scoring matrix for quantifying the health state of the energy storage device; A is the membership degree matrix of each operation information index of all devices of the same type of energy storage device; R T is the transpose of the weight coefficient vector R; b m is the information score of the operation information index class of the m-th energy storage device; m is the number of energy storage devices; n is the number of evaluation indexes of the operation information of the energy storage device; μ mn is the membership degree of the n-th operation information index of the m-th energy storage device; r n is the weight coefficient of the n-th operation information index.

5. The method for evaluating the health state of an energy storage device according to claim 1, characterized in that, each index of the operation information of the energy storage device includes current, SOC and charge-discharge efficiency.

6. The method for evaluating the health state of an energy storage device according to claim 2, characterized in that, each index of the alarm information of the energy storage device includes the number of fault alarms and the number of abnormal alarms.

7. An evaluation device for the health state of an energy storage device, characterized in that, comprises a memory and a processor, and the processor is used to execute the computer program instructions stored in the memory to implement the method for evaluating the health state of an energy storage device according to any one of claims 1-6.

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