CN114610591A - Lithium ion battery energy storage system evaluation method based on equipment health degree model - Google Patents

Lithium ion battery energy storage system evaluation method based on equipment health degree model Download PDF

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CN114610591A
CN114610591A CN202210237954.9A CN202210237954A CN114610591A CN 114610591 A CN114610591 A CN 114610591A CN 202210237954 A CN202210237954 A CN 202210237954A CN 114610591 A CN114610591 A CN 114610591A
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黄文瑞
田立亭
田文辉
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Beijing Huisi Huineng Technology Co ltd
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Abstract

The invention relates to a lithium ion battery energy storage system evaluation method based on an equipment health degree model, which is used for comprehensively evaluating a battery monomer health degree index, a battery module health degree index, an energy storage subsystem health degree index and an energy storage power station health degree index by adopting a weighted average method. The invention describes the health degree of the energy storage system and the main equipment thereof from multiple dimensions, carries out rapid online evaluation, can realize comprehensive evaluation from an equipment level to a system level, and has important effects on improving the operation reliability of the energy storage system and preventing the equipment failure of the energy storage system.

Description

Lithium ion battery energy storage system evaluation method based on equipment health degree model
Technical Field
The invention relates to a lithium ion battery energy storage system evaluation method based on an equipment health degree model. Belongs to the technical field of electric power and energy.
Background
The electrochemical energy storage technology realizes the storage, release or rapid power exchange of electric energy through various batteries, can stabilize the power generation fluctuation of new energy, improve the balance of power supply and demand, and improve the stability of a power system, is mainly applied to the fields of electric power, energy, traffic and the like, and is one of the key technologies for supporting the novel power system taking the new energy as a main body.
The lithium ion battery technology has the characteristics of high energy density, long cycle life, high conversion efficiency and the like, and is rapidly developed in recent years. At present, the scale of the lithium ion battery energy storage machine in China accounts for more than 80% of the whole scale of the electrochemical energy storage. Because the lithium ion battery involves complex electrochemical reaction, the performance can be rapidly declined under atypical working conditions or when the lithium ion battery is improperly used and operated, even thermal runaway occurs to cause safety accidents, and serious hidden dangers are brought to the safety of life and property of people. Therefore, the operation state of the equipment is mastered in time, and the operation and maintenance strategy is formulated in a targeted manner, which is particularly important for safe and stable operation of the lithium ion battery energy storage system.
At present, the operation and maintenance methods of the energy storage system of the lithium ion battery are mainly divided into two types: the method is an operation and maintenance method based on online evaluation of battery state. According to the method, the early decline of the performance of the battery can be timely found through online monitoring of the SOC (state of charge), the SOH (state of health) and the like of the battery, and the method has a certain effect on preventing the faults of a single battery or a module; however, the method has high requirements on the accuracy of battery model modeling and parameter identification, and lacks systematic evaluation on electrochemical energy storage. And the other is an operation and maintenance method based on fault diagnosis of the energy storage system. The method designs a fault diagnosis system by utilizing big data such as a fault tree, an expert system, machine learning and the like and an artificial intelligence technology, quickly identifies fault reasons and takes necessary protective measures after an energy storage system has faults; however, the method is mainly applied to fault post-processing, a large number of data samples in normal and fault states are needed, and the modeling period is long.
Disclosure of Invention
The invention aims to overcome the defects and provides a lithium ion battery energy storage system evaluation method based on an equipment health degree model.
The purpose of the invention is realized as follows:
a lithium ion battery energy storage system evaluation method based on an equipment health degree model is characterized in that: comprehensively evaluating the health indexes of the battery monomers, the health indexes of the battery modules, the health indexes of the energy storage subsystems and the health indexes of the energy storage power stations by adopting a weighted average method;
the method comprises the following steps:
s1, the indexes of the health degree of the battery monomer comprise: the method comprises the following steps of (1) obtaining battery cell voltage, battery cell temperature, battery cell SOC and battery cell SOH; the battery cell voltage, the battery cell temperature, the battery cell SOC and the battery cell SOH are all taken from a battery management system;
s2, the battery module health degree index comprises: the battery module comprises battery module voltage, battery module temperature, battery module insulation resistance, battery module charging current, battery module discharging current, battery module running time, battery module charging and discharging energy conversion efficiency, battery module cell voltage consistency, battery module temperature consistency and battery module cell failure rate;
battery module voltage, battery module temperature, battery module insulation resistance, battery module charging current, battery module discharging current, and battery module run time are taken from the battery management system; the voltage consistency of the battery monomer of the battery module, the temperature consistency of the battery module and the failure rate of the battery monomer of the battery module can be obtained by calculation;
s3, the health degree index of the energy storage subsystem comprises: the method comprises the following steps of (1) total voltage of a battery cluster, charging current of the battery cluster and discharging current of the battery cluster, voltage consistency of single batteries of the battery cluster, temperature consistency of single batteries of the battery cluster and failure rate of single batteries of the battery cluster, temperature of an energy storage converter of the battery cluster, insulation resistance of the battery cluster and conversion efficiency of the converter of the battery cluster;
the total voltage of the battery cluster, the charging current of the battery cluster and the discharging current of the battery cluster are taken from a battery management system, and the temperature of a battery cluster energy storage converter and the insulation resistance of the battery cluster are taken from a converter; the voltage consistency of the single batteries of the battery cluster, the temperature consistency of the single batteries of the battery cluster and the failure rate of the single batteries of the battery cluster can be obtained through calculation;
s4, the health degree indexes of the energy storage power station comprise: indoor temperature, relative humidity, system charge-discharge energy conversion efficiency, unplanned shutdown coefficient and relative failure times of a battery cluster;
the indoor temperature and relative humidity are taken from a battery management system; the charging and discharging energy conversion efficiency of the system, the unplanned shutdown coefficient and the relative failure times of the battery cluster can be obtained through calculation;
s5, scoring all indexes in real time according to the health degree index scoring standard table;
s6, comprehensively evaluating the health degree model of the battery monomer, the health degree model of the battery module, the health degree model of the energy storage subsystem and the health degree model of the energy storage power station by adopting a weighted average method;
and S7, comparing the health degree of the battery monomer, the health degree of the battery module, the health degree of the energy storage subsystem and the health degree of the energy storage power station in the S5 with a health degree rating and operation and maintenance suggestion table, and giving rating and operation and maintenance suggestions.
2. The lithium ion battery energy storage system evaluation method based on the equipment health degree model according to claim 1, characterized in that: the SOH of the energy storage system is represented by the ratio of the maximum dischargeable capacity of the battery monomer to the rated capacity, and the SOH of the power storage system is represented by the ratio of the internal resistance of the battery monomer to the rated internal resistance.
3. The lithium ion battery energy storage system evaluation method based on the equipment health degree model according to claim 1, characterized in that: in S4, in the standard table of health index score, fiminAnd fimaxThe lower limit value and the upper limit value of the ith index are respectively determined according to an equipment manual and a related standard; alpha is a coefficient of a lower limit value, and beta is a coefficient of an upper limit value; if the index sampling period is less than or equal to the evaluation period, taking the average value of the scores of the index in the evaluation period as the final score; and if the index sampling period is greater than the evaluation period, taking the latest score of the index as the final score.
4. The lithium ion battery energy storage system evaluation method based on the equipment health degree model according to claim 1, characterized in that: step S1-S4, 1 energy storage power station index matrix F can be calculatedstation1 energy storage subsystem index matrix FsystemM x M battery module index matrix F under same battery clustermoduleAnd a battery cell index matrix F under the same M × M × N modulescell：
Figure BDA0003543082110000041
Figure BDA0003543082110000042
Figure BDA0003543082110000043
Figure BDA0003543082110000044
Wherein, 1 energy storage power station divides the system by having M energy storage, and every energy storage divides the system to have M battery cluster, and every battery cluster has N battery module, and every battery module has N battery monomer.
5. The lithium ion battery energy storage system evaluation method based on the equipment health degree model according to claim 1, characterized in that: in S2, the charge-discharge energy conversion efficiency of the battery module is calculated by the following method:
recording the SOC of the battery module at the moment when the test is started, recording the total charging amount and the discharging amount of the battery module at the moment when the SOC of the battery module is equal to the SOC at the start of the test for the first time after a certain time interval, and taking the ratio of the total discharging amount to the total charging amount as a primary test result; continuously repeating the test for 3 times, and taking the average value of the test for 3 times as the charging and discharging energy conversion efficiency of the battery module;
Figure BDA0003543082110000051
in the formula:
Figure BDA0003543082110000052
charge-discharge energy conversion efficiency,%, for the battery module; e.g. of the typeCiAnd eDiRespectively testing the total discharge capacity and the total charge capacity of the battery module at the ith time, wherein the unit is kilowatt-hour (kW.h);
the cell voltage uniformity in a battery module can be calculated by the following formula:
Figure BDA0003543082110000053
in the formula:
Figure BDA0003543082110000054
the consistency of the voltage of the battery monomer in the battery module is percent; u shapeiAnd
Figure BDA0003543082110000055
the unit is the voltage (V) of the ith battery monomer and the average value of the voltage of the monomer in the battery module at a certain moment; n is the total number of the battery monomers in the battery module;
the uniformity of the temperature of the cell in the battery module can be calculated by the following formula:
Figure BDA0003543082110000056
in the formula:
Figure BDA0003543082110000057
the consistency of the temperature of the battery monomer in the battery module is percent;
Figure BDA0003543082110000058
and
Figure BDA0003543082110000059
respectively obtaining the average value of the temperature of the ith battery monomer and the temperature of the monomer in the battery module at a certain moment, wherein the unit is centigrade (DEG C); n is the total number of the battery monomers in the battery module;
the cell failure rate in a battery module can be calculated by the following formula:
Figure BDA0003543082110000061
in the formula:
Figure BDA0003543082110000062
the failure rate of a battery monomer in the battery module is percent; n isinvalidAnd n is the number of failed battery cells and the total number of battery cells in the battery module in one week, respectively.
6. The lithium ion battery energy storage system evaluation method based on the equipment health degree model according to claim 1, characterized in that: in S3, the cell voltage uniformity in the battery cluster can be calculated by the following formula:
Figure BDA0003543082110000063
in the formula:
Figure BDA0003543082110000064
the consistency of the voltage of the battery monomer in the battery cluster is percent; u shapeiAnd
Figure BDA0003543082110000065
the unit is volt (V) and the unit is the average value of the voltage of the ith battery monomer in the battery cluster at a certain moment; n is the total number of the single batteries in the battery cluster;
the temperature uniformity of the battery cells in the battery cluster can be calculated by the following formula:
Figure BDA0003543082110000066
in the formula:
Figure BDA0003543082110000067
the consistency of the temperature of the battery modules in the battery cluster is percent;
Figure BDA0003543082110000068
and
Figure BDA0003543082110000069
respectively the temperature of the ith battery module in the battery cluster at a certain momentDegree and module temperature averages in degrees Celsius (. degree. C.); n is the number of battery modules in the battery cluster;
the failure rate of the battery monomer in the battery cluster can be calculated by the following formula:
Figure BDA0003543082110000071
in the formula:
Figure BDA0003543082110000072
the failure rate of a single battery in the battery cluster is percent; sigma ninvalidAnd sigma n is the number of the failed single batteries in the battery cluster and the total number of the single batteries in the evaluation period respectively;
the conversion efficiency of the battery cluster converter can be calculated by the following formula:
Figure BDA0003543082110000073
in the formula:
Figure BDA0003543082110000074
conversion efficiency of the converter,%; pACAnd PDCThe unit is watt (W) for alternating current side power and direct current side power of the converter.
7. The lithium ion battery energy storage system evaluation method based on the equipment health degree model according to claim 1, characterized in that: in S4, the system charge-discharge energy conversion efficiency can be calculated by the following method:
recording the SOC of the energy storage system at the moment when the test is started, recording the total charge quantity and the discharge quantity of the energy storage system at the moment when the SOC of the energy storage system is equal to the SOC at the start of the test for the first time after a certain time interval, and taking the ratio of the total discharge quantity to the total charge quantity as a primary test result; continuously repeating the test for 3 times, and taking the average value of the test for 3 times as the charge-discharge energy conversion efficiency of the energy storage system;
Figure BDA0003543082110000075
in the formula:
Figure BDA0003543082110000076
the charge-discharge energy conversion efficiency of the energy storage system is percent; eCiAnd EDiThe total discharge capacity and the total charge capacity of the energy storage system in the ith test are respectively expressed in kilowatt-hour (kWh & h);
the unplanned outage factor may be calculated by the following equation:
Figure BDA0003543082110000077
in the formula:
Figure BDA0003543082110000078
the coefficient of unplanned shutdown of the energy storage power station,%; t is a unit ofUOAnd T is the unplanned outage time and the statistical time of the energy storage power station in the evaluation period respectively, and the unit is hour (h);
the relative failure times of the battery clusters can be calculated by the following formula:
Figure BDA0003543082110000081
in the formula:
Figure BDA0003543082110000082
the relative failure times of the battery clusters are counted; m isfaultAnd m is the failure times of the battery clusters and the number of the battery clusters in the energy storage power station in the evaluation period respectively.
8. The lithium ion battery energy storage system evaluation method based on the equipment health degree model according to claim 1, characterized in that: in S5, the health degree of the battery monomer, the health degree of the battery module, the health degree of the energy storage subsystem and the health degree of the energy storage power station are as follows:
Figure BDA0003543082110000083
Figure BDA0003543082110000084
Figure BDA0003543082110000085
Figure BDA0003543082110000086
in the formula, Hcell、Hmodule、HsystemAnd HstationRespectively is a battery monomer health degree, a battery module health degree, an energy storage subsystem health degree and an energy storage power station health degree, wiIs the weight coefficient of the corresponding index.
9. The lithium ion battery energy storage system evaluation method based on the equipment health degree model according to claim 8, characterized in that: the weight coefficient can be determined by an entropy weight method, and the calculation method is as follows:
assuming that S is a normalized matrix composed of m indexes and n groups of data, then
S＝(sij)m×n
In the formula, sijThe score of the ith index and the jth data is obtained; if the information entropy of the ith index is EiThen, then
Figure BDA0003543082110000091
In the formula, pijThe score of the jth data and the ith index accounts for the proportion of the total score of the index; if the weighting coefficient of the ith index is wiThen, then
Figure BDA0003543082110000092
Compared with the prior art, the invention has the beneficial effects that:
according to the lithium ion battery energy storage system evaluation method based on the equipment health degree model, the health degree of the energy storage system and the main equipment thereof is described from multiple dimensions, and rapid online evaluation is performed, so that comprehensive evaluation from an equipment level to a system level can be realized, and the method plays an important role in improving the operation reliability of the energy storage system and preventing equipment faults of the energy storage system.
Detailed Description
The following further describes embodiments of the present invention with reference to examples. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
The invention relates to a lithium ion battery energy storage system evaluation method based on an equipment health degree model.
The invention provides a lithium ion battery energy storage system evaluation method based on a health degree model, which is used for comprehensively evaluating a health degree index of a battery monomer, a health degree index of a battery module, a health degree index of an energy storage subsystem and a health degree index of an energy storage power station by adopting a weighted average method.
The indexes of the health degree of the battery monomer comprise: cell voltage, cell temperature, cell SOC, and cell SOH.
The voltage, the temperature, the SOC and the SOH of each battery are taken from a battery management system; the SOH of the energy type energy storage system is represented by the ratio of the maximum dischargeable capacity of the single battery to the rated capacity, and the SOH of the power type energy storage system is represented by the ratio of the internal resistance of the single battery to the rated internal resistance.
The battery module health indicator includes: the method comprises the following steps of (1) obtaining battery module voltage, battery module temperature, battery module insulation resistance, battery module charging current, battery module discharging current, battery module running time, battery module charging and discharging energy conversion efficiency, battery module single cell voltage consistency, battery module temperature consistency and battery module single cell failure rate; wherein the battery module voltage, temperature, insulation resistance, charging current, discharging current, and run time are taken from the battery management system.
The charge-discharge energy conversion efficiency of the battery module can be calculated by the following method:
recording the SOC of the battery module at the moment when the test is started, recording the total charging quantity and the discharging quantity of the battery module at the moment when the SOC of the battery module is equal to the SOC at the test start for the first time after a certain time interval, and taking the ratio of the total discharging quantity to the total charging quantity as a primary test result. And continuously repeating the test for 3 times, and taking the average value of the test for 3 times as the charging and discharging energy conversion efficiency of the battery module.
Figure BDA0003543082110000101
In the formula:
Figure BDA0003543082110000102
charge-discharge energy conversion efficiency,%, for the battery module; e.g. of the typeCiAnd eDiThe total discharge capacity and the total charge capacity of the battery module tested at the ith time are respectively expressed in kilowatt-hour (kW.h).
The cell voltage uniformity in a battery module can be calculated by the following formula:
Figure BDA0003543082110000111
in the formula:
Figure BDA0003543082110000112
the consistency of the voltage of the battery monomer in the battery module is percent; u shapeiAnd
Figure BDA0003543082110000113
the unit is the voltage (V) of the ith battery monomer and the average value of the voltage of the monomer in the battery module at a certain moment; and b is the total number of the battery cells in the battery module.
The uniformity of the temperature of the cell in the battery module can be calculated by the following formula:
Figure BDA0003543082110000114
in the formula:
Figure BDA0003543082110000115
the consistency of the temperature of the battery monomer in the battery module is percent;
Figure BDA0003543082110000116
and
Figure BDA0003543082110000117
respectively obtaining the average value of the temperature of the ith battery monomer and the temperature of the monomer in the battery module at a certain moment, wherein the unit is centigrade (DEG C); and n is the total number of the battery cells in the battery module.
The cell failure rate in a battery module can be calculated by the following formula:
Figure BDA0003543082110000118
in the formula:
Figure BDA0003543082110000119
the failure rate of a battery monomer in the battery module is percent; binvalidAnd n is the number of failed battery cells and the total number of battery cells in the battery module in one week, respectively.
The health degree index of the energy storage subsystem comprises the following indexes: the system comprises a battery cluster, a battery cluster energy storage converter, a battery cluster charging current, a battery cluster discharging current, battery cluster single-cell voltage consistency, battery cluster single-cell temperature consistency, battery cluster single-cell failure rate, a battery cluster energy storage converter temperature, a battery cluster insulation resistance and a battery cluster converter conversion efficiency.
The total voltage of the battery cluster, the charging current of the battery cluster and the discharging current of the battery cluster are taken from a battery management system, and the temperature of the energy storage converter of the battery cluster and the insulation resistance of the battery cluster are taken from the converter.
The cell voltage uniformity in a battery cluster can be calculated by the following formula:
Figure BDA0003543082110000121
in the formula:
Figure BDA0003543082110000122
the consistency of the voltage of the single batteries in the battery cluster is percent; u shapeiAnd
Figure BDA0003543082110000123
the unit is volt (V) and the unit is the average value of the voltage of the ith battery monomer in the battery cluster at a certain moment; and n is the total number of the battery cells in the battery cluster.
The temperature uniformity of the battery cells in the battery cluster can be calculated by the following formula:
Figure BDA0003543082110000124
in the formula:
Figure BDA0003543082110000125
the consistency of the temperature of the battery modules in the battery cluster is percent;
Figure BDA0003543082110000126
and
Figure BDA0003543082110000127
respectively obtaining the average value of the temperature of the ith battery module in the battery cluster at a certain moment and the module temperature, wherein the unit is centigrade (DEG C); and N is the number of the battery modules in the battery cluster.
The failure rate of a single battery in the battery cluster can be calculated by the following formula:
Figure BDA0003543082110000128
in the formula:
Figure BDA0003543082110000129
the failure rate of a single battery in the battery cluster is percent; sigma ninvalidAnd Σ n are the number of failed cells and the total number of cells in the battery cluster in the evaluation period, respectively.
The conversion efficiency of the battery cluster converter can be calculated by the following formula:
Figure BDA00035430821100001210
in the formula:
Figure BDA00035430821100001211
converting efficiency of a battery cluster converter,%; pACAnd PDCThe unit is watt (W) for alternating current side power and direct current side power of the converter.
The health degree indexes of the energy storage power station comprise: indoor temperature, relative humidity, system charge-discharge energy conversion efficiency, unplanned shutdown coefficient and relative failure times of the battery cluster.
The indoor temperature, relative humidity are taken from the battery management system.
The system charge-discharge energy conversion efficiency can be calculated by the following method:
and recording the SOC of the energy storage system at the moment when the test is started, recording the total charging amount and the total discharging amount of the energy storage system during a certain time interval when the SOC of the energy storage system is equal to the SOC at the start of the test for the first time after a certain time interval, and taking the ratio of the total discharging amount to the total charging amount as a test result. And continuously repeating the test for 3 times, and taking the average value of the test for 3 times as the charging and discharging energy conversion efficiency of the energy storage system.
Figure BDA0003543082110000131
In the formula:
Figure BDA0003543082110000132
the charge-discharge energy conversion efficiency of the energy storage system is percent; eCiAnd EDiThe total discharge capacity and the total charge capacity of the energy storage system in the ith test are respectively expressed in kilowatt-hour (kW.h).
The unplanned outage factor may be calculated by the following equation:
Figure BDA0003543082110000133
in the formula:
Figure BDA0003543082110000134
the coefficient of unplanned shutdown of the energy storage power station,%; t isUOAnd T is the unplanned outage time and the statistical time of the energy storage power station in the evaluation period respectively, and the unit is hour (h).
The relative failure times of the battery clusters can be calculated by the following formula:
Figure BDA0003543082110000135
in the formula:
Figure BDA0003543082110000136
the relative failure times of the battery clusters are times/clusters; m isfaultAnd m is the failure times of the battery clusters in the energy storage power station and the number of the battery clusters in the evaluation period respectively.
The invention provides a health degree model of a lithium ion battery energy storage system, which comprises the following components: the evaluation period can be set as day, week, month, year and the like.
The invention provides a grading standard for health indexes of a lithium ion battery energy storage system, and the grading standard is determined according to whether each index value deviates from a rated value or an average value or not or the deviation degree.
The scoring criteria are shown in the following table:
health index scoring standard
Figure BDA0003543082110000141
Figure BDA0003543082110000151
Figure BDA0003543082110000161
Figure BDA0003543082110000171
Figure BDA0003543082110000172
And
Figure BDA0003543082110000173
the scores of the ith indexes of the battery monomer, the battery module, the energy storage subsystem and the energy storage power station are respectively obtained; f. ofiminAnd fimaxThe lower limit value and the upper limit value of the ith index are respectively determined according to an equipment manual and a related standard; alpha is a coefficient of a lower limit value, and is generally 0.8-1; beta is a coefficient of an upper limit value, and is generally 1 to 1.2.
In the table, each index is scored in real time according to the respective sampling period. If the index sampling period is less than or equal to the evaluation period, taking the average value of the scores of the index in the evaluation period as the final score of the evaluation period; and if the index sampling period is greater than the evaluation period, taking the latest score of the index as the final score of the evaluation period.
And comprehensively evaluating the health degree model of the battery monomer, the health degree model of the battery module, the health degree model of the energy storage subsystem and the health degree model of the energy storage power station by adopting a weighted average method.
Figure BDA0003543082110000181
Figure BDA0003543082110000182
Figure BDA0003543082110000183
Figure BDA0003543082110000184
In the formula, Hcell、Hmodule、HsystemAnd HstationRespectively is a battery monomer health degree, a battery module health degree, an energy storage subsystem health degree and an energy storage power station health degree, wiIs the weight coefficient of the corresponding index.
The weight coefficient can be determined by an entropy weight method, and the calculation method is as follows:
assuming that S is a normalized matrix composed of m indexes and n groups of data, then
S＝(sij)m×n
In the formula, sijThe score of the ith index and the jth data is shown. If the information entropy of the ith index is EiThen, then
Figure BDA0003543082110000185
In the formula, pijThe score of the ith index in the jth data is expressed as the proportion of the total score of the index. If the weighting coefficient of the ith index is wiThen, then
Figure BDA0003543082110000191
And giving a rating and operation and maintenance suggestion according to the health degree of the single battery, the health degree of the battery module, the health degree of the energy storage subsystem and the health degree of the energy storage power station as follows:
health degree rating and operation and maintenance suggestion
Degree of health Rating Operation and maintenance suggestion
H≥0.8 Health care Is free of
0.6≥H>0.8 Sub-health Periodic maintenance
0.4≥H>0.6 Fault of Preventive maintenance
H<0.4 Replacement of Preventive replacement
The specific embodiment is as follows:
1 energy storage power station by there being M energy storage subsystem, every energy storage subsystem has M battery cluster, and every battery cluster has N battery module, and every battery module has N battery monomer. The method for evaluating the energy storage system based on the equipment health degree model is used for evaluating the operating condition of the energy storage power station for one week.
The data collected by the energy storage power station through the battery management system, the inverter and the monitoring system are assumed to comprise: the system comprises battery cell voltage, temperature, SOC and SOH, battery module voltage, temperature, insulation resistance, SOC, charging amount, discharging amount, charging current, discharging current, running time and the number of failed battery cells in the module, total voltage, charging current and discharging current of a battery cluster, temperature and insulation resistance of an energy storage converter, the number of faults of the battery cluster in an energy storage subsystem, indoor temperature, relative humidity, SOC, charging amount, discharging amount and unplanned shutdown time of an energy storage power station.
The health degree evaluation indexes comprise cell voltage, temperature, SOC (system on chip) and SOH (state of health), cell module voltage, temperature, insulation resistance, charging current, discharging current, running time and module charging and discharging energy conversion efficiency, cell voltage consistency, temperature consistency and failure rate in the module, total voltage, charging current and discharging current of a cell cluster, cell voltage consistency, temperature consistency and failure rate in the cell cluster, temperature, insulation resistance and conversion efficiency of an energy storage converter, indoor temperature, relative humidity, system charging and discharging energy conversion efficiency, unplanned shutdown coefficients and relative failure times of the cell cluster.
The module charge-discharge energy conversion efficiency can be calculated by the following method:
recording the SOC of the battery module at the moment when the test is started, recording the total charging quantity and the discharging quantity of the battery module at the moment when the SOC of the battery module is equal to the SOC at the test start for the first time after a certain time interval, and taking the ratio of the total discharging quantity to the total charging quantity as a primary test result. And continuously repeating the test for 3 times, and taking the average value of the test for 3 times as the charging and discharging energy conversion efficiency of the battery module.
Figure BDA0003543082110000201
In the formula:
Figure BDA0003543082110000202
is electricityThe battery module has charge-discharge energy conversion efficiency,%; e.g. of the typeCiAnd eDiThe total discharge capacity and the total charge capacity of the battery module tested at the ith time are respectively expressed in kilowatt-hour (kW.h).
The cell voltage uniformity in a battery module can be calculated by the following formula:
Figure BDA0003543082110000203
in the formula:
Figure BDA0003543082110000204
the consistency of the voltage of the battery monomer in the battery module is percent; u shapeiAnd
Figure BDA0003543082110000205
the unit is the voltage (V) of the ith battery monomer and the average value of the voltage of the monomer in the battery module at a certain moment; and n is the total number of the battery cells in the battery module.
The cell temperature uniformity in the battery module can be calculated by the following formula:
Figure BDA0003543082110000206
in the formula:
Figure BDA0003543082110000207
the consistency of the temperature of the battery monomer in the battery module is percent;
Figure BDA0003543082110000208
and
Figure BDA0003543082110000209
respectively obtaining the average value of the temperature of the ith battery monomer and the temperature of the monomer in the battery module at a certain moment, wherein the unit is centigrade (DEG C); and n is the total number of the battery cells in the battery module.
The cell failure rate in a battery module can be calculated by the following formula:
Figure BDA0003543082110000211
in the formula:
Figure BDA0003543082110000212
the failure rate of a battery monomer in the battery module is percent; n isinvalidAnd n is the number of failed battery cells and the total number of battery cells in the battery module in one week, respectively.
The cell voltage uniformity in a battery cluster can be calculated by the following formula:
Figure BDA0003543082110000213
in the formula:
Figure BDA0003543082110000214
the consistency of the voltage of the single batteries in the battery cluster is percent; u shapeiAnd
Figure BDA0003543082110000215
the unit is volt (V) and the unit is the average value of the voltage of the ith battery monomer in the battery cluster at a certain moment; and n is the total number of the battery cells in the battery cluster.
The temperature uniformity of the battery cells in the battery cluster can be calculated by the following formula:
Figure BDA0003543082110000216
in the formula:
Figure BDA0003543082110000217
the consistency of the temperature of the battery modules in the battery cluster is percent;
Figure BDA0003543082110000218
and
Figure BDA0003543082110000219
respectively obtaining the average value of the temperature of the ith battery module in the battery cluster at a certain moment and the module temperature, wherein the unit is centigrade (DEG C); and N is the number of the battery modules in the battery cluster.
The failure rate of the battery monomer in the battery cluster can be calculated by the following formula:
Figure BDA00035430821100002110
in the formula:
Figure BDA00035430821100002111
the failure rate of a single battery in the battery cluster is percent; sigma ninvalidAnd Σ n is the number of failed cells and the total number of cells in the battery cluster in one week, respectively.
The conversion efficiency of the battery cluster converter can be calculated by the following formula:
Figure BDA0003543082110000221
in the formula:
Figure BDA0003543082110000222
conversion efficiency of the converter,%; pACAnd PDCThe unit is watt (W) for alternating current side power and direct current side power of the converter.
The system charge-discharge energy conversion efficiency can be calculated by the following method:
recording the SOC of the energy storage system at the moment when the test is started, recording the total charge quantity and the discharge quantity of the energy storage system at the moment when the SOC of the energy storage system is equal to the SOC at the start of the test for the first time after a certain time interval, and taking the ratio of the total discharge quantity to the total charge quantity as a primary test result. And continuously repeating the test for 3 times, and taking the average value of the test for 3 times as the charge-discharge energy conversion efficiency of the energy storage system.
Figure BDA0003543082110000223
In the formula:
Figure BDA0003543082110000224
the charge-discharge energy conversion efficiency of the energy storage system is percent; eCiAnd EDiThe total discharge capacity and the total charge capacity of the energy storage system in the ith test are respectively expressed in kilowatt-hour (kW.h).
The unplanned outage factor may be calculated by the following equation:
Figure BDA0003543082110000225
in the formula:
Figure BDA0003543082110000226
the coefficient of unplanned shutdown of the energy storage power station,%; t isUOAnd T is the unplanned outage time and the statistical time of the energy storage power station in the evaluation period respectively, and the unit is hour (h).
The relative failure times of the battery clusters can be calculated by the following formula:
Figure BDA0003543082110000227
in the formula:
Figure BDA0003543082110000228
the relative failure times of the battery clusters are times/clusters; m isfaultAnd m is the failure times of the battery clusters in the energy storage power station and the number of the battery clusters in the evaluation period respectively.
1 energy storage power station index matrix F can be calculatedstation1 energy storage subsystem index matrix FsystemM x M battery module index matrix F under same battery clustermoduleAnd a battery cell index matrix F under the same M x M x n modulescell：
Figure BDA0003543082110000231
Figure BDA0003543082110000232
Figure BDA0003543082110000233
Figure BDA0003543082110000234
All the indexes were scored in real time according to the scoring criteria shown in the following table.
Health index scoring standard
Figure BDA0003543082110000235
Figure BDA0003543082110000241
Figure BDA0003543082110000251
Figure BDA0003543082110000261
Figure BDA0003543082110000271
Wherein f isiminAnd fimaxThe lower limit value and the upper limit value of the ith index are respectively determined according to an equipment manual and a related standard; alpha is a coefficient of a lower limit value, and 0.8 is taken; β is a coefficient of the upper limit value, and is 1.2. Such as a fingerIf the standard sampling period is less than or equal to one week, taking the average value of the scores of the index in one week as the final score; and if the index sampling period is more than one week, taking the score of the last week of the index as the final score.
1 index scoring matrix S of the energy storage power station can be obtainedstation1 energy storage subsystem index scoring matrix SsystemM x M battery module index scoring matrix S under same battery clustermoduleAnd a battery monomer index scoring matrix S under the same M multiplied by M multiplied by N modulescell：
Figure BDA0003543082110000272
Figure BDA0003543082110000273
Figure BDA0003543082110000281
Figure BDA0003543082110000282
And for each scoring matrix, performing comprehensive evaluation by adopting a weighted average method. The weight coefficient is determined by an entropy weight method, and the calculation method is as follows:
for each normalized matrix S consisting of k indexes and l groups of data, then
S＝(sij)k×l
Figure BDA0003543082110000283
Figure BDA0003543082110000284
Figure BDA0003543082110000285
Hj＝∑sij×wi
In the formula, sijThe score of the ith index and the jth data is obtained; p is a radical ofijThe score of the jth data and the ith index accounts for the proportion of the total score of the index; eiInformation entropy of the ith index; w is aiA weight coefficient of the ith index; hjThe health score was assigned to the jth group of data.
Energy storage power station health degree score H can be calculatedstation1 energy storage subsystem health degree scoring vector HsystemM multiplied by M battery module health degree score vectors H under same battery clustermoduleAnd M × M × N scoring vectors of the health degree of the battery cells under the same modulecell：
Figure BDA0003543082110000291
Figure BDA0003543082110000292
Figure BDA0003543082110000293
And according to the health degree rating and operation and maintenance suggestions shown in the following table, displaying the health state and performing preventive operation and maintenance on each battery monomer, each battery module, each energy storage subsystem and each energy storage power station.
Health rating and operation and maintenance suggestion
Degree of health Rating Operation and maintenance suggestion
H≥0.8 Health care Is free of
0.6≥H>0.8 Sub-health Periodic maintenance
0.4≥H>0.6 Fault of Preventive maintenance
H<0.4 Replacement of Preventive replacement
In the above embodiments, the present invention is described only by way of example, but those skilled in the art, after reading the present patent application, may make various modifications to the present invention without departing from the spirit and scope of the present invention.

Claims (9)

1. A lithium ion battery energy storage system evaluation method based on an equipment health degree model is characterized in that: comprehensively evaluating the health indexes of the battery monomers, the health indexes of the battery modules, the health indexes of the energy storage subsystems and the health indexes of the energy storage power stations by adopting a weighted average method;
the method comprises the following steps:
s1, the indexes of the health degree of the single battery comprise: the method comprises the following steps of (1) obtaining battery cell voltage, battery cell temperature, battery cell SOC and battery cell SOH; the battery cell voltage, the battery cell temperature, the battery cell SOC and the battery cell SOH are all taken from a battery management system;
s2, the battery module health degree index comprises: the battery module comprises battery module voltage, battery module temperature, battery module insulation resistance, battery module charging current, battery module discharging current, battery module running time, battery module charging and discharging energy conversion efficiency, battery module cell voltage consistency, battery module temperature consistency and battery module cell failure rate;
battery module voltage, battery module temperature, battery module insulation resistance, battery module charging current, battery module discharging current, and battery module run time are taken from the battery management system; the voltage consistency of the battery monomer of the battery module, the temperature consistency of the battery module and the failure rate of the battery monomer of the battery module can be obtained by calculation;
s3, the health degree index of the energy storage subsystem comprises: the method comprises the following steps of (1) total voltage of a battery cluster, charging current of the battery cluster and discharging current of the battery cluster, voltage consistency of single batteries of the battery cluster, temperature consistency of single batteries of the battery cluster and failure rate of single batteries of the battery cluster, temperature of an energy storage converter of the battery cluster, insulation resistance of the battery cluster and conversion efficiency of the converter of the battery cluster;
the total voltage of the battery cluster, the charging current of the battery cluster and the discharging current of the battery cluster are taken from a battery management system, and the temperature of the energy storage converter of the battery cluster and the insulation resistance of the battery cluster are taken from a converter; the voltage consistency of the single batteries of the battery cluster, the temperature consistency of the single batteries of the battery cluster and the failure rate of the single batteries of the battery cluster can be obtained through calculation;
s4, the health degree indexes of the energy storage power station comprise: indoor temperature, relative humidity, system charge-discharge energy conversion efficiency, unplanned shutdown coefficient and relative failure times of a battery cluster;
the indoor temperature and relative humidity are taken from a battery management system; the charging and discharging energy conversion efficiency of the system, the unplanned shutdown coefficient and the relative failure times of the battery cluster can be obtained through calculation;
s5, scoring all indexes in real time according to the health degree index scoring standard table;
s6, comprehensively evaluating the health degree model of the battery monomer, the health degree model of the battery module, the health degree model of the energy storage subsystem and the health degree model of the energy storage power station by adopting a weighted average method;
and S7, comparing the health degree of the battery monomer, the health degree of the battery module, the health degree of the energy storage subsystem and the health degree of the energy storage power station in the S5 with a health degree rating and operation and maintenance suggestion table, and giving rating and operation and maintenance suggestions.
2. The lithium ion battery energy storage system evaluation method based on the equipment health degree model according to claim 1, characterized in that: the SOH of the energy storage system is represented by the ratio of the maximum dischargeable capacity of the battery monomer to the rated capacity, and the SOH of the power storage system is represented by the ratio of the internal resistance of the battery monomer to the rated internal resistance.
3. The lithium ion battery energy storage system evaluation method based on the equipment health degree model according to claim 1, characterized in that: in S4, in the standard table of health index score, fiminAnd fimaxThe lower limit value and the upper limit value of the ith index are respectively determined according to an equipment manual and a related standard; alpha is a coefficient of a lower limit value, and beta is a coefficient of an upper limit value; if the index sampling period is less than or equal to the evaluation period, taking the average value of the scores of the index in the evaluation period as the final score; and if the index sampling period is greater than the evaluation period, taking the latest score of the index as the final score.
4. The lithium ion battery energy storage system evaluation method based on the equipment health degree model according to claim 1, characterized in that: step S1-S4, 1 energy storage power station index matrix F can be calculatedstation1 energy storage subsystem index matrix FsystemM x M battery module index matrix F under same battery clustermoduleAnd a battery cell index matrix F under the same M × M × N modulescell：
Figure FDA0003543082100000031
Figure FDA0003543082100000032
Figure FDA0003543082100000033
Figure FDA0003543082100000034
Wherein, 1 energy storage power station by there being M energy storage subsystem, every energy storage subsystem has M battery cluster, and every battery cluster has N battery module, and every battery module has N battery monomer.
5. The lithium ion battery energy storage system evaluation method based on the equipment health degree model according to claim 1, characterized in that: in S2, the charge-discharge energy conversion efficiency of the battery module is calculated by the following method:
recording the SOC of the battery module at the moment when the test is started, recording the total charging amount and the discharging amount of the battery module at the moment when the SOC of the battery module is equal to the SOC at the start of the test for the first time after a certain time interval, and taking the ratio of the total discharging amount to the total charging amount as a primary test result; continuously repeating the test for 3 times, and taking the average value of the test for 3 times as the charging and discharging energy conversion efficiency of the battery module;
Figure FDA0003543082100000041
in the formula:
Figure FDA0003543082100000042
charge-discharge energy conversion efficiency,%, for the battery module; e.g. of the typeCiAnd eDiRespectively testing the total discharge capacity and the total charge capacity of the battery module at the ith time, wherein the unit is kilowatt-hour (kW.h);
the cell voltage uniformity in a battery module can be calculated by the following formula:
Figure FDA0003543082100000043
in the formula:
Figure FDA0003543082100000044
the consistency of the voltage of the battery monomer in the battery module is percent; u shapeiAnd
Figure FDA0003543082100000045
the unit is the voltage (V) of the ith battery monomer and the average value of the voltage of the monomer in the battery module at a certain moment; n is the total number of the battery monomers in the battery module;
the cell temperature uniformity in the battery module can be calculated by the following formula:
Figure FDA0003543082100000046
in the formula:
Figure FDA0003543082100000047
the consistency of the temperature of the battery monomer in the battery module is percent;
Figure FDA0003543082100000048
and
Figure FDA0003543082100000049
respectively obtaining the average value of the temperature of the ith battery monomer and the temperature of the monomer in the battery module at a certain moment, wherein the unit is centigrade (DEG C); n is the total number of the battery monomers in the battery module;
the cell failure rate in a battery module can be calculated by the following formula:
Figure FDA00035430821000000410
in the formula:
Figure FDA00035430821000000411
the failure rate of a battery monomer in the battery module is percent; n isinvalidAnd n is the number of failed battery cells and the total number of battery cells in the battery module in one week, respectively.
6. The lithium ion battery energy storage system evaluation method based on the equipment health degree model according to claim 1, characterized in that: in S3, the cell voltage uniformity in the battery cluster can be calculated by the following formula:
Figure FDA0003543082100000051
in the formula:
Figure FDA0003543082100000052
the consistency of the voltage of the battery monomer in the battery cluster is percent; u shapeiAnd
Figure FDA0003543082100000053
the unit is volt (V) and the unit is the average value of the voltage of the ith battery monomer in the battery cluster at a certain moment; n is the total number of the single batteries in the battery cluster;
the temperature uniformity of the battery cells in the battery cluster can be calculated by the following formula:
Figure FDA0003543082100000054
in the formula:
Figure FDA0003543082100000055
the consistency of the temperature of the battery modules in the battery cluster is percent;
Figure FDA0003543082100000056
and
Figure FDA0003543082100000057
respectively obtaining the average value of the temperature of the ith battery module in the battery cluster at a certain moment and the module temperature, wherein the unit is centigrade (DEG C); n is the number of battery modules in the battery cluster;
the failure rate of the battery monomer in the battery cluster can be calculated by the following formula:
Figure FDA0003543082100000058
in the formula:
Figure FDA0003543082100000059
the failure rate of a single battery in the battery cluster is percent; sigma ninvalidAnd sigma n is the number of the failed single batteries in the battery cluster and the total number of the single batteries in the evaluation period respectively;
the conversion efficiency of the battery cluster converter can be calculated by the following formula:
Figure FDA00035430821000000510
in the formula:
Figure FDA00035430821000000511
conversion efficiency of the converter,%; pACAnd PDCThe unit is watt (W) for alternating current side power and direct current side power of the converter.
7. The lithium ion battery energy storage system evaluation method based on the equipment health degree model according to claim 1, characterized in that: in S4, the system charge-discharge energy conversion efficiency can be calculated by the following method:
recording the SOC of the energy storage system at the moment when the test is started, recording the total charge quantity and the discharge quantity of the energy storage system at the moment when the SOC of the energy storage system is equal to the SOC at the start of the test for the first time after a certain time interval, and taking the ratio of the total discharge quantity to the total charge quantity as a primary test result; continuously repeating the test for 3 times, and taking the average value of the test for 3 times as the charge-discharge energy conversion efficiency of the energy storage system;
Figure FDA0003543082100000061
in the formula:
Figure FDA0003543082100000062
the charge-discharge energy conversion efficiency of the energy storage system is percent; eCiAnd EDiThe total discharge capacity and the total charge capacity of the energy storage system in the ith test are respectively expressed in kilowatt-hour (kWh & h);
the unplanned outage factor may be calculated by the following equation:
Figure FDA0003543082100000063
in the formula:
Figure FDA0003543082100000064
the coefficient of unplanned shutdown of the energy storage power station,%; t is a unit ofUOAnd T is the unplanned outage time and the statistical time of the energy storage power station in the evaluation period respectively, and the unit is hour (h);
the relative failure times of the battery clusters can be calculated by the following formula:
Figure FDA0003543082100000065
in the formula:
Figure FDA0003543082100000066
the relative failure times of the battery clusters are times/clusters; m isfaultAnd m is the failure times of the battery clusters in the energy storage power station and the number of the battery clusters in the evaluation period respectively.
8. The lithium ion battery energy storage system evaluation method based on the equipment health degree model according to claim 1, characterized in that: in S5, the health degree of the battery monomer, the health degree of the battery module, the health degree of the energy storage subsystem and the health degree of the energy storage power station are as follows:
Figure FDA0003543082100000071
Figure FDA0003543082100000072
Figure FDA0003543082100000073
Figure FDA0003543082100000074
in the formula, Hcell、Hmodule、HsystemAnd HstationRespectively is a battery monomer health degree, a battery module health degree, an energy storage subsystem health degree and an energy storage power station health degree, wiIs the weight coefficient of the corresponding index.
9. The lithium ion battery energy storage system evaluation method based on the equipment health degree model according to claim 8, characterized in that: the weight coefficient can be determined by an entropy weight method, and the calculation method is as follows:
assuming that S is a normalized matrix composed of m indexes and n groups of data, then
S＝(sij)m×n
In the formula, sijThe score of the ith index and the jth data is obtained; if the information entropy of the ith index is EiThen, then
Figure FDA0003543082100000075
In the formula, pijThe score of the jth data and ith index accounts for the total score of the index; if the weighting coefficient of the ith index is wiThen, then
Figure FDA0003543082100000076
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