CN111337846A - Method for estimating running state of user-side energy storage lithium battery - Google Patents

Method for estimating running state of user-side energy storage lithium battery Download PDF

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Publication number
CN111337846A
CN111337846A CN202010283027.1A CN202010283027A CN111337846A CN 111337846 A CN111337846 A CN 111337846A CN 202010283027 A CN202010283027 A CN 202010283027A CN 111337846 A CN111337846 A CN 111337846A
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energy storage
index
battery
lithium battery
string
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洪星
司静
杨帆
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Jiangsu Huizhi Energy Engineering Technology Innovation Research Institute Co ltd
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Jiangsu Huizhi Energy Engineering Technology Innovation Research Institute Co ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/392—Determining battery ageing or deterioration, e.g. state of health
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
    • G01R31/3835—Arrangements for monitoring battery or accumulator variables, e.g. SoC involving only voltage measurements

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  • General Physics & Mathematics (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)
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Abstract

The invention discloses a method for estimating the running state of a user-side energy storage lithium battery, which comprises the steps of firstly constructing a comprehensive estimation method system for the running state of a lithium battery energy storage unit, determining each index to be estimated, calculating and extracting each estimation index to be estimated according to actual running data of a power station, determining a threshold value of the lithium battery energy storage running state estimation index, determining an objective weight vector of the estimation index by adopting an entropy weight method, and calculating the comprehensive score of the lithium battery energy storage running state estimation.

Description

Method for estimating running state of user-side energy storage lithium battery
Technical Field
The invention relates to a comprehensive estimation method for the running state of a user-side energy storage lithium battery, and belongs to the technical field of electric power.
Background
Along with the increase of the number of the battery energy storage power stations and the extension of the operation time, the operation condition of the energy storage power stations is more and more emphasized by the operation units, and the energy storage units are used as important operation equipment of the energy storage power stations, so that the estimation of the operation state of the energy storage units has important significance for mastering the operation condition of the energy storage power stations and improving the operation reliability of the energy storage equipment.
The standard of the foreign energy storage system is mainly IEC standard and IEEE standard, the IEEE standard specifies the overall performance estimation indexes such as charging and discharging multiplying power, efficiency, service life, self-discharging rate and the like for the emergency back-up power supply energy storage system, but the adopted standard is also a test method, and the purpose is to estimate the applicability of different energy storage forms such as electrochemistry, machinery, electromagnetism, heat and the like in the application field of the back-up power supply, but not to estimate the running state of the energy storage equipment. In addition, the National Institute of Standards and Technology (NIST) and the JESC have also conducted some work to develop energy storage standards.
The technical research on the operation state estimation of the lithium battery energy storage unit in China is based on operation data, theoretical analysis is combined, the lithium battery energy storage operation state estimation indexes such as battery voltage range, battery voltage standard deviation coefficient, battery temperature range, SOE range, power-SOE correlation, operation charge and discharge efficiency and the like are researched, and the estimation index system is comprehensively estimated according to the internal relation among the indexes. However, at present, the lithium battery energy storage unit operation state estimation technology research is based on operation data, and theoretical analysis is combined to determine the lithium battery energy storage operation state estimation indexes, but in the comprehensive estimation method for each index, an analytic hierarchy process is mainly adopted to determine the weight of each index, the determination of the weight is greatly influenced by subjective human factors, and the accuracy of the estimation result still has a further space for improvement.
Disclosure of Invention
The purpose of the invention is as follows: in order to overcome the defects in the prior art, the invention provides a method for estimating the running state of a user-side energy storage lithium battery.
The technical scheme is as follows: in order to achieve the purpose, the invention adopts the technical scheme that:
a method for estimating the running state of a user side energy storage lithium battery comprises the following steps:
step 1, collecting relevant parameters of the energy storage lithium battery, and determining battery voltage range, battery voltage standard deviation coefficient, battery temperature range, SOC range, string operation charge-discharge efficiency and energy storage unit charge-discharge efficiency as estimation indexes according to the relevant parameters.
And 2, calculating various estimation indexes according to the actual operation related parameter data of the power station.
Step 21) battery voltage range: difference between maximum cell voltage and minimum cell voltage in the same battery string:
ΔU＝Umax-Umin
wherein, UmaxIs the maximum battery voltage, U, in the battery stringminIs the minimum cell voltage in the battery string.
Step 22) battery voltage standard deviation coefficient: standard deviation coefficient of battery string voltage:
Figure BDA0002447413360000021
wherein u isδIs the cell voltage standard deviation coefficient, deltauIs the standard deviation of the voltage of the battery,
Figure BDA0002447413360000024
is the average value of the cell voltage, uiIs the ith cell voltage, and n is the number of cells in the battery pack string.
Step 23) battery temperature range: difference between maximum and minimum battery temperatures in the same battery string:
ΔT＝Tmax-Tmin
wherein, TmaxIs the maximum battery temperature, T, in the battery stringminIs the minimum cell temperature in the string of battery packs.
Step 24) SOC extreme difference: the difference between the maximum SOC and the minimum SOC of the battery pack strings in the same energy storage unit is as follows:
ΔSOC＝SOCmax-SOCmin
therein, SOCmaxIs the maximum SOC, SOCminIs the minimum SOC.
Step 25), the charge-discharge efficiency of the group of strings is as follows: percentage of discharge energy to charge energy of the battery string during operation:
Figure BDA0002447413360000022
wherein E iscdisDischarging energy for the battery string, EcchCharging the battery string with energy.
Step 26) charging and discharging efficiency of the energy storage unit: the percentage of discharge energy to charge energy of the energy storage unit in the operation process is as follows:
Figure BDA0002447413360000023
wherein E isDC-disDischarging energy for the DC side of the energy storage unit, EDC-chAnd charging energy for the direct current side of the energy storage unit. .
And 3, dividing the operation states of the energy storage lithium battery into healthy, sub-healthy, serious and severe states, and calculating the threshold value of each operation state according to the interval of each estimation index statistical result by adopting a linear interpolation method.
And 4, determining the running state given in the step 3 according to each estimation index obtained in the step 2, and scoring each index.
And 5, determining the weight of each index by an entropy weight method according to each estimation index obtained in the step 2 and each index score obtained in the step 4.
Step 51), for n samples, m indexes, xijThe value of the j index of the ith sample,
i＝1,…n；j＝1,…,m)。
step 52), index normalization:
the forward direction index is as follows:
Figure BDA0002447413360000031
negative direction index:
Figure BDA0002447413360000032
step 53), calculating the specific gravity of the j index of the ith sample
Figure BDA0002447413360000033
Step 54), calculating the entropy value of the j index
Figure BDA0002447413360000034
Wherein k is 1/ln (n) > 0
Step 55) calculating the weight of each index
Figure BDA0002447413360000035
Wherein, wjRepresenting the weight of each index.
And 6, scoring according to the weight of each index obtained in the step 5 and each index obtained in the step 4 to obtain the comprehensive score of the energy storage lithium battery:
the composite score is ∑ each index score weight.
Preferably: in the step 4, the scores of healthy, sub-healthy, serious and severe running states of all indexes are respectively 2,4,8 and 10.
Compared with the prior art, the invention has the following beneficial effects:
the invention adopts the entropy weight method to determine the weight of each index objectively and fairly, has no subjective influence, improves the accuracy of the estimation result, has clear index score, is easy to understand, has simple and convenient comprehensive score calculation and easy result comparison, and simultaneously has effective estimation index and simple and convenient calculation.
Detailed Description
The invention is further illustrated by the following examples in connection with specific embodiments thereof, it is to be understood that these examples are intended in an illustrative rather than in a limiting sense and that various equivalent modifications of the invention as described herein will occur to those skilled in the art upon reading the present disclosure and are intended to be covered by the appended claims.
A method for estimating the running state of a user side energy storage lithium battery comprises the following steps:
step 1, collecting relevant parameters of the energy storage lithium battery, and determining battery voltage range, battery voltage standard deviation coefficient, battery temperature range, SOC range, string operation charge-discharge efficiency and energy storage unit charge-discharge efficiency as estimation indexes according to the relevant parameters.
And 2, calculating various estimation indexes according to the actual operation related parameter data of the power station.
Step 21) battery voltage range: difference between maximum cell voltage and minimum cell voltage in the same battery string:
ΔU＝Umax-Umin
wherein, UmaxIs the maximum battery voltage, U, in the battery stringminIs the minimum cell voltage in the battery string.
Step 22) battery voltage standard deviation coefficient: standard deviation coefficient of battery string voltage:
Figure BDA0002447413360000041
wherein u isδIs the cell voltage standard deviation coefficient, deltauIs the standard deviation of the voltage of the battery,
Figure BDA0002447413360000042
is the average value of the cell voltage, uiIs the ith cell voltage, and n is the number of cells in the battery pack string.
Step 23) battery temperature range: difference between maximum and minimum battery temperatures in the same battery string:
ΔT＝Tmax-Tmin
wherein, TmaxIs the maximum battery temperature, T, in the battery stringminIs the minimum cell temperature in the string of battery packs.
Step 24) SOC extreme difference: the difference between the maximum SOC and the minimum SOC of the battery pack strings in the same energy storage unit is as follows:
ΔSOC＝SOCmax-SOCmin
therein, SOCmaxIs the maximum SOC, SOCminIs the minimum SOC.
Step 25), the charge-discharge efficiency of the group of strings is as follows: percentage of discharge energy to charge energy of the battery string during operation:
Figure BDA0002447413360000043
wherein E iscdisDischarging energy for the battery string, EcchCharging the battery string with energy.
Step 26) charging and discharging efficiency of the energy storage unit: the percentage of discharge energy to charge energy of the energy storage unit in the operation process is as follows:
Figure BDA0002447413360000051
wherein E isDC-disDischarging energy for the DC side of the energy storage unit, EDC-chAnd charging energy for the direct current side of the energy storage unit. .
And 3, dividing the operation states of the energy storage lithium battery into healthy, sub-healthy, serious and severe states, and calculating the threshold value of each operation state according to the interval of each estimation index statistical result by adopting a linear interpolation method.
And 4, determining the running state given in the step 3 according to each estimation index obtained in the step 2, scoring each index, wherein the scores of the running state health, sub-health, serious and severe of each index are respectively 2,4,8 and 10, namely, when the running state of the index is in a healthy state, scoring 2. And when the index running state is in a sub-health state, marking 4 points. And 8 points are given when the index running state is in a serious state. And when the index running state is in a severe state, 10 points are given.
And 5, determining the weight of each index by an entropy weight method according to each estimation index obtained in the step 2 and each index score obtained in the step 4.
Step 51), for n samples, m indexes, xijThe value of the j index of the ith sample,
i＝1,…n；j＝1,…,m)。
step 52), index normalization:
forward directionIndexes are as follows:
Figure BDA0002447413360000052
negative direction index:
Figure BDA0002447413360000053
step 53), calculating the specific gravity of the j index of the ith sample
Figure BDA0002447413360000054
Step 54), calculating the entropy value of the j index
Figure BDA0002447413360000055
Wherein k is 1/ln (n) > 0
Step 55) calculating the weight of each index
Figure BDA0002447413360000056
Wherein, wjRepresenting the weight of each index.
And 6, scoring according to the weight of each index obtained in the step 5 and each index obtained in the step 4 to obtain the comprehensive score of the energy storage lithium battery:
the composite score is ∑ each index score weight.
The above description is only of the preferred embodiments of the present invention, and it should be noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the invention and these are intended to be within the scope of the invention.

Claims (8)

1. A method for estimating the running state of a user side energy storage lithium battery is characterized by comprising the following steps:
step 1, collecting relevant parameters of the energy storage lithium battery, and determining battery voltage range, battery voltage standard deviation coefficient, battery temperature range, SOC range, string operation charge-discharge efficiency and energy storage unit charge-discharge efficiency as estimation indexes according to the relevant parameters.
Step 2, calculating various estimation indexes according to the actual operation related parameter data of the power station;
step 3, dividing the operation states of the energy storage lithium battery into healthy, sub-healthy, serious and severe states, and calculating the threshold value of each operation state according to the interval of each estimation index statistical result by adopting a linear interpolation method;
step 4, determining the running state given in the step 3 according to each estimation index obtained in the step 2, and scoring each index;
step 5, determining the weight of each index by an entropy weight method according to each estimation index obtained in the step 2 and each index score obtained in the step 4;
step 51), for n samples, m indexes, xijThe j index value of the ith sample, i is 1, … n; j ═ 1, …, m);
step 52), index normalization:
the forward direction index is as follows:
Figure FDA0002447413350000011
negative direction index:
Figure FDA0002447413350000012
step 53), calculating the specific gravity of the j index of the ith sample
Figure FDA0002447413350000013
Step 54), calculating the entropy value of the j index
Figure FDA0002447413350000014
Wherein k is 1/ln (n) > 0
Step 55) calculating the weight of each index
Figure FDA0002447413350000015
Wherein, wjRepresenting the weight of each index;
and 6, scoring according to the weight of each index obtained in the step 5 and each index obtained in the step 4 to obtain the comprehensive score of the energy storage lithium battery:
the composite score is ∑ each index score weight.
2. The method for estimating the operating state of the user-side energy storage lithium battery according to claim 1, characterized in that: the battery voltage range in step 2 is calculated by the following formula:
ΔU＝Umax-Umin
wherein, UmaxIs the maximum battery voltage, U, in the battery stringminIs the minimum cell voltage in the battery string.
3. The method for estimating the operating state of the user-side energy storage lithium battery according to claim 1, characterized in that: the battery voltage standard deviation coefficient in step 2 is calculated by the following formula:
Figure FDA0002447413350000021
wherein u isδIs the cell voltage standard deviation coefficient, deltauIs the standard deviation of the voltage of the battery,
Figure FDA0002447413350000022
is the average value of the cell voltage, uiIs the ith cell voltage, and n is the number of cells in the battery pack string.
4. The method for estimating the operating state of the user-side energy storage lithium battery according to claim 1, characterized in that: the battery temperature range in step 2 is calculated by the following formula:
ΔT＝Tmax-Tmin
wherein, TmaxIs the maximum battery temperature, T, in the battery stringminIs the minimum cell temperature in the string of battery packs.
5. The method for estimating the operating state of the user-side energy storage lithium battery according to claim 1, characterized in that: the SOC pole difference in step 2 is calculated by the following formula:
ΔSOC＝SOCmax-SOCmin
therein, SOCmaxIs the maximum SOC, SOCminIs the minimum SOC.
6. The method for estimating the operating state of the user-side energy storage lithium battery according to claim 1, characterized in that: the charge-discharge efficiency of the string operation in the step 2 is calculated by the following formula:
Figure FDA0002447413350000023
wherein E iscdisDischarging energy for the battery string, EcchCharging the battery string with energy.
7. The method for estimating the operating state of the user-side energy storage lithium battery according to claim 1, characterized in that: in the step 2, the charge-discharge efficiency of the energy storage unit is calculated by the following formula:
Figure FDA0002447413350000031
wherein E isDC-disDischarging energy for the DC side of the energy storage unit, EDC-chAnd charging energy for the direct current side of the energy storage unit.
8. The method for estimating the operating state of the user-side energy storage lithium battery as recited in claim 2, wherein: in the step 4, the scores of healthy, sub-healthy, serious and severe running states of all indexes are respectively 2,4,8 and 10.
CN202010283027.1A 2020-04-13 2020-04-13 Method for estimating running state of user-side energy storage lithium battery Pending CN111337846A (en)

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CN112904201A (en) * 2021-01-05 2021-06-04 浙江工业大学 Real-time online evaluation system and method for charging and discharging processes of energy storage battery
CN113030761A (en) * 2021-04-08 2021-06-25 中国电力科学研究院有限公司 Method and system for evaluating health state of battery of super-large-scale energy storage power station
CN114295999A (en) * 2021-12-30 2022-04-08 国网浙江省电力有限公司电力科学研究院 Lithium ion battery SOH prediction method and system based on indirect health index

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Application publication date: 20200626