CN113343443A - Power distribution method for lithium battery prefabricated cabins with different SOC (state of charge) - Google Patents

Power distribution method for lithium battery prefabricated cabins with different SOC (state of charge) Download PDF

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CN113343443A
CN113343443A CN202110563443.1A CN202110563443A CN113343443A CN 113343443 A CN113343443 A CN 113343443A CN 202110563443 A CN202110563443 A CN 202110563443A CN 113343443 A CN113343443 A CN 113343443A
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lithium battery
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clustering
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CN113343443B (en
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周喜超
王楠
赵鹏翔
李建林
李娜
谭宇良
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Beijing Lianzhi Huineng Technology Co ltd
State Grid Comprehensive Energy Service Group Co ltd
North China University of Technology
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State Grid Comprehensive Energy Service Group Co ltd
North China University of Technology
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    • 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]
    • G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
    • 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]
    • G01R31/385—Arrangements for measuring battery or accumulator variables
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    • G06F2119/02—Reliability analysis or reliability optimisation; Failure analysis, e.g. worst case scenario performance, failure mode and effects analysis [FMEA]

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Abstract

The invention discloses a power distribution method for lithium battery prefabricated cabins with different SOC. The method includes the steps of selecting SOC of a plurality of lithium battery prefabricated cabins and recording the SOC as an initial value, recording battery SOC parameters of different lithium battery prefabricated cabins at the same moment, generating a plurality of clustering centers according to different SOC of each lithium battery prefabricated cabin by using a K-means clustering algorithm, selecting a type of SOC closest to a middle position as a reference value, giving specific power requirements within a certain time interval according to the requirements of a power grid, and distributing the specific power requirements to lithium battery systems under various conditions. The invention can distribute power by combining the demand of the power grid and the state of the lithium battery, prolong the service life of the lithium battery, improve the utilization rate of the lithium battery and ensure that the performance utilization performance of the lithium battery reaches the optimum.

Description

Power distribution method for lithium battery prefabricated cabins with different SOC (state of charge)
The technical field is as follows:
the invention relates to the technical field of lithium battery energy storage, in particular to a power distribution method for lithium battery prefabricated cabins with different SOC.
Background art:
the lithium ion battery is an energy storage technology in which lithium ions are taken as active ions, and the lithium ions are deintercalated between a positive electrode and a negative electrode through an electrolyte during charging and discharging, and electric energy is stored in a compound electrode intercalated (or inserted) with lithium, and the lithium ion battery is a practical secondary battery with the highest energy density at present. Under the condition of normal charge and discharge, lithium ions are inserted and extracted between positive and negative electrode material layers which are both in a layered structure, the interlayer spacing is generally changed, the crystal structure is not damaged, and the chemical structure of the electrode material is basically unchanged in the charge and discharge process. Therefore, the lithium ion battery reaction is an ideal reversible reaction, thereby ensuring long cycle life and high energy conversion efficiency of the battery.
Lithium ion batteries are widely applied to each link of a power system, and comprise a power generation side for assisting the dynamic operation of a traditional unit and delaying the investment of a newly built unit; participating in an auxiliary service market, and providing frequency modulation, standby and other services; the upgrading of power transmission and distribution facilities is delayed at the power transmission and distribution side, and the power supply reliability and safety of the power transmission and distribution side are guaranteed; the method helps the user to realize demand electric charge management, peak-valley price difference arbitrage, power supply reliability and electric energy quality improvement and the like; in a large renewable energy power generation station, the method helps smooth new energy power generation output, tracking planned output and the like; providing peak shaving service in the form of an independent energy storage power station; and the power battery (or the retired battery) of the electric automobile can be used as an energy storage unit and applied to a power system. The lithium ion battery mainly comprises materials (a positive electrode and a negative electrode), a diaphragm, electrolyte, a shell and the like, and the materials are rich and diverse.
When power distribution is carried out on the lithium battery prefabricated cabin, due to the fact that charging and discharging performances of the lithium battery prefabricated cabins with different SOC are different, clustering and summarizing are carried out on the sample lithium battery prefabricated cabin according to different SOC, the SOC is low in priority, and the SOC is high in priority and discharging is carried out.
The invention content is as follows:
the invention provides a power distribution method for lithium battery prefabricated cabins based on different SOC. The specific technical scheme is as follows:
a power distribution method for lithium battery prefabricated cabins with different SOC comprises the following steps:
step 1: measuring and recording the initial SOC of the lithium battery prefabricated cabin, wherein the value of the SOC is [0, 1 ]; selecting m lithium battery prefabricated cabin samples, selecting a certain moment t as initial test time of sampling, measuring the sampled lithium battery prefabricated cabins, measuring the SOC of each battery at the moment t, recording the SOC as an initial value of the lithium battery prefabricated cabin SOC, and recording the SOC as SOC (t) (t is 1, 2, 3, …, m);
step 2: collecting the charge and discharge condition and the SOC value of a prefabricated cabin of a lithium battery; selecting the sampling time of the lithium battery prefabricated cabin as delta T, selecting a period of time as interval time T, sampling the charging and discharging conditions of the lithium battery prefabricated cabin every delta T, measuring and recording the SOC of the lithium battery prefabricated cabin every T, wherein T is delta T;
and step 3: calculating clustering centers and classifying based on K-means algorithm
Carrying out cluster analysis on SOC (state of charge) and (t) of the m lithium battery prefabricated cabins measured in the step 1 by adopting a K-means clustering algorithm, and selecting z clustering centers (z is 1, 2 and 3), wherein the clustering centers are marked as zj(j＝1，2，3)，
When the clustering center z is 1, 3 cases of x1, x2 and x3 are divided,
case x 1: the cluster center is located between [0, 0.5],
case x 2: the cluster center is located above 0.5,
case x 3: the cluster center is located between [0.5, 1 ];
when the cluster center z is 2, 3 cases of y1, y2 and y3 are divided,
case y 1: the cluster centers are all located between 0-0.5,
case y 2: the cluster centers are all located between 0.5 and 1,
case y 3: the clustering centers are respectively positioned between [0-0.5] and [0.5-1],
when the clustering center z is 3, 3 cases of w1, w2 and w3 are divided,
w1 th case: two cluster centers are respectively positioned at 0-0.5 and 0.5-1, the other is positioned at 0.5,
w2 th case: two cluster centers are all located on 0-0.5, the other on 0.5,
w3 th case: two cluster centers are all located on 0.5-1, the other is located on 0.5,
in each case, the distance from the SOC of the prefabricated cabin of the rest lithium battery to each clustering center is respectively calculated and recorded as D (SOC (a)),
D(SOC(a))＝|SOC(a)-zj|2，
if D (soc (a)) min { D (soc (a), z)j) Fourthly, the lithium battery prefabricated cabin belongs to the clustering center, and the steps are repeated until all the lithium battery prefabricated cabins are classified completely;
and 4, step 4: selecting a reference cluster center and calculating a power requirement,
the distance between all the cluster centers and 0.5 is calculated for each case and is denoted as dj，
dj＝|SOC(t)-0.5|，
In each case take min [ d ]j]The corresponding clustering center is used as a reference clustering center;
the power demand of the power grid in the T time is related to the power generation condition and the load demand of the new energy, and the power demand of the power grid is set to be PNetThe power generated by the new energy is PNewThe load demand is PNegative poleTherefore, the power demand expression of the grid is: pNet＝PNegative pole-PNew
And 5: problem of power distribution in different situations
When z is 1:
clustering center as shown in the x1 case, the batteries are all in low SOC state, all the prefabricated lithium battery cabin are only suitable for charging,
the clustering center is as shown in the x2 case, all the batteries are in the state of SOC being 0.5, all the prefabricated cabins of lithium batteries are in the state of being chargeable and dischargeable,
the clustering center is shown as the x3 situation, all the batteries are in a high SOC state, and all the prefabricated cabins of the lithium batteries are only suitable for discharging;
when z is 2:
as shown in the case of the y1, the clustering center is that part of the batteries are in a high SOC state, part of the batteries are in a state of SOC equal to 0.5, when the batteries need to be charged, the lithium battery prefabricated cabin with SOC equal to 0.5 is charged preferentially, and when the batteries need to be discharged, the lithium battery prefabricated cabin with high SOC is discharged preferentially;
as shown in the case of the y2, the clustering center is that part of the batteries are in a low SOC state, and part of the batteries are in a state of SOC equal to 0.5, when the batteries need to be charged, the prefabricated lithium battery compartment in the low SOC state is charged preferentially, and when the batteries need to be discharged, the prefabricated lithium battery compartment in the SOC equal to 0.5 is discharged preferentially;
as shown in the y3 case, the clustering center is characterized in that part of the battery is in a low SOC state, part of the battery is in a high SOC state, when the battery needs to be charged, the lithium battery prefabricated cabin in the low SOC state is charged preferentially, and when the battery needs to be discharged, the lithium battery prefabricated cabin in the high SOC is discharged preferentially;
when z is 3:
the clustering centers are as shown in the w1 cases, two clustering centers of the similar battery are respectively positioned at [0-0.5] and [0.5-1], and the other clustering center is positioned at 0.5; when the battery needs to be charged, the lithium battery prefabricated cabin in a low SOC state and with the SOC being 0.5 is charged preferentially; when the battery is required to discharge, the lithium battery prefabricated cabin in a high SOC state and with the SOC being 0.5 is discharged preferentially;
clustering centers as shown in the w2 cases, two clustering centers of the similar battery are all located at [0-0.5], and the other is located at 0.5; when the battery is required to be charged, the lithium battery prefabricated cabin with the SOC being 0.5 is charged preferentially; when the battery is required to be discharged, the two types of lithium battery prefabricated cabins in the high SOC state are discharged preferentially, and the higher the SOC is, the higher the discharging priority is;
clustering centers As shown in the w3 th case, two clustering centers are all located at [0.5-1], and the other is located at 0.5; when the battery is required to be charged, the lithium battery prefabricated cabin in the low SOC state is charged preferentially, and the lower the SOC is, the higher the charging priority is; when the battery is required to be discharged, the lithium battery prefabricated cabin with the SOC being 0.5 is preferentially discharged.
Compared with the prior art, the invention has the advantages that: the service efficiency of the prefabricated cabin of lithium cell is improved, the prefabricated cabin life of lithium cell is prolonged.
Description of the drawings:
fig. 1 is a schematic diagram of the x1 th case.
Fig. 2 is a schematic diagram of the case x 2.
Fig. 3 is a schematic diagram of the case x 3.
Fig. 4 is a schematic diagram of the case y 1.
Fig. 5 is a schematic diagram of the case y 2.
Fig. 6 is a schematic diagram of the case y 3.
Fig. 7 is a schematic diagram of the situation w 1.
Fig. 8 is a schematic diagram of the case w 2.
Fig. 9 is a schematic diagram of the case w 3.
The specific implementation mode is as follows:
a power distribution method for lithium battery prefabricated cabins with different SOC comprises the following steps:
step 1: measuring and recording the initial SOC of the lithium battery prefabricated cabin, wherein the value of the SOC is [0, 1 ]; selecting m lithium battery prefabricated cabin samples, selecting a certain moment t as initial test time of sampling, measuring the sampled lithium battery prefabricated cabins, measuring the SOC of each battery at the moment t, recording the SOC as an initial value of the lithium battery prefabricated cabin SOC, and recording the SOC as SOC (t) (t is 1, 2, 3, …, m);
step 2: collecting the charge and discharge condition and the SOC value of a prefabricated cabin of a lithium battery; selecting the sampling time of the lithium battery prefabricated cabin as delta T, selecting a period of time as interval time T, sampling the charging and discharging conditions of the lithium battery prefabricated cabin every delta T, measuring and recording the SOC of the lithium battery prefabricated cabin every T, wherein T is delta T;
and step 3: calculating a clustering center based on a K-means algorithm and classifying;
carrying out cluster analysis on SOC (state of charge) and (t) of the m lithium battery prefabricated cabins measured in the step 1 by adopting a K-means clustering algorithm, and selecting z clustering centers (z is 1, 2 and 3), wherein the clustering centers are marked as zj(j＝1，2，3)，
When the clustering center z is 1, 3 cases of x1, x2 and x3 are divided,
case x 1: the cluster centers are located between [0, 0.5], as shown in FIG. 1;
case x 2: cluster centers are located above 0.5, as shown in fig. 2;
case x 3: the cluster center is located between [0.5, 1], as shown in FIG. 1;
when the cluster center z is 2, 3 cases of y1, y2 and y3 are divided,
case y 1: the cluster centers are all located between [0-0.5], as shown in FIG. 4;
case y 2: the cluster centers are all located between [0.5-1], as shown in FIG. 5;
case y 3: the clustering centers are respectively located between [0-0.5] and [0.5-1], as shown in FIG. 6;
when the clustering center z is 3, 3 cases of w1, w2 and w3 are divided,
w1 th case: two cluster centers are respectively located at [0-0.5] and [0.5-1], and the other is located at 0.5, as shown in FIG. 7;
w2 th case: both cluster centers are located at [0-0.5] and the other at 0.5, as shown in FIG. 8;
w3 th case: two cluster centers are all located at [0.5-1], and the other is located at 0.5, as shown in FIG. 9;
in each case, the distance from the SOC of the prefabricated cabin of the rest lithium battery to each clustering center is respectively calculated and recorded as D (SOC (a)),
D(SOC(a))＝|SOC(a)-zj|2，
if D (soc (a)) min { D (soc (a), z)j) Fourthly, the lithium battery prefabricated cabin belongs to the clustering center, and the steps are repeated until all the lithium battery prefabricated cabins are classified completely;
and 4, step 4: selecting a reference cluster center and calculating a power requirement,
the distance between all the cluster centers and 0.5 is calculated for each case and is denoted as dj，
dj＝|SOC(t)-0.5|
In each case take min [ d ]j]The corresponding clustering center is used as a reference clustering center;
the power demand of the power grid in the T time is related to the power generation condition and the load demand of the new energy, and the power demand of the power grid is set to be PNetThe power generated by the new energy is PNewThe load demand is PNegative poleTherefore, the power demand expression of the grid is: pNet＝PNegative pole-PNew
And 5: problem of power distribution in different situations
When z is 1:
clustering center as shown in the x1 case, the batteries are all in low SOC state, all the prefabricated lithium battery cabin are only suitable for charging,
the clustering center is as shown in the x2 case, all the batteries are in the state of SOC being 0.5, all the prefabricated cabins of lithium batteries are in the state of being chargeable and dischargeable,
the clustering center is shown as the x3 situation, all the batteries are in a high SOC state, and all the prefabricated cabins of the lithium batteries are only suitable for discharging;
when z is 2:
as shown in the case of the y1, the clustering center is that part of the batteries are in a high SOC state, part of the batteries are in a state of SOC equal to 0.5, when the batteries need to be charged, the lithium battery prefabricated cabin with SOC equal to 0.5 is charged preferentially, and when the batteries need to be discharged, the lithium battery prefabricated cabin with high SOC is discharged preferentially;
as shown in the case of the y2, the clustering center is that part of the batteries are in a low SOC state, and part of the batteries are in a state of SOC equal to 0.5, when the batteries need to be charged, the prefabricated lithium battery compartment in the low SOC state is charged preferentially, and when the batteries need to be discharged, the prefabricated lithium battery compartment in the SOC equal to 0.5 is discharged preferentially;
as shown in the y3 case, the clustering center is characterized in that part of the battery is in a low SOC state, part of the battery is in a high SOC state, when the battery needs to be charged, the lithium battery prefabricated cabin in the low SOC state is charged preferentially, and when the battery needs to be discharged, the lithium battery prefabricated cabin in the high SOC is discharged preferentially;
when z is 3:
the clustering centers are as shown in the w1 cases, two clustering centers of the similar battery are respectively positioned at [0-0.5] and [0.5-1], and the other clustering center is positioned at 0.5; when the battery needs to be charged, the lithium battery prefabricated cabin in a low SOC state and with the SOC being 0.5 is charged preferentially; when the battery is required to discharge, the lithium battery prefabricated cabin in a high SOC state and with the SOC being 0.5 is discharged preferentially;
clustering centers as shown in the w2 cases, two clustering centers of the similar battery are all located at [0-0.5], and the other is located at 0.5; when the battery is required to be charged, the lithium battery prefabricated cabin with the SOC being 0.5 is charged preferentially; when the battery is required to be discharged, the two types of lithium battery prefabricated cabins in the high SOC state are discharged preferentially, and the higher the SOC is, the higher the discharging priority is;
clustering centers As shown in the w3 th case, two clustering centers are all located at [0.5-1], and the other is located at 0.5; when the battery is required to be charged, the lithium battery prefabricated cabin in the low SOC state is charged preferentially, and the lower the SOC is, the higher the charging priority is; when the battery is required to be discharged, the lithium battery prefabricated cabin with the SOC being 0.5 is preferentially discharged.

Claims (1)

1. A power distribution method for lithium battery prefabricated cabins with different SOC is characterized by comprising the following steps:
step 1: measuring and recording the initial SOC of the lithium battery prefabricated cabin, wherein the value of the SOC is [0, 1 ]; selecting m lithium battery prefabricated cabin samples, selecting a certain moment t as initial test time of sampling, measuring the sampled lithium battery prefabricated cabins, measuring the SOC of each battery at the moment t, recording the SOC as an initial value of the lithium battery prefabricated cabin SOC, and recording the SOC as SOC (t) (t is 1, 2, 3, …, m);
step 2: collecting the charge and discharge condition and the SOC value of a prefabricated cabin of a lithium battery; selecting the sampling time of the lithium battery prefabricated cabin as delta T, selecting a period of time as interval time T, wherein the charging and discharging conditions of the lithium battery prefabricated cabin are sampled every delta T, the SOC of the lithium battery prefabricated cabin is measured and recorded every T, and T is delta T;
and step 3: calculating clustering centers and classifying based on K-means algorithm
Carrying out cluster analysis on SOC (state of charge) and (t) of the m lithium battery prefabricated cabins measured in the step 1 by adopting a K-means clustering algorithm, and selecting z clustering centers (z is 1, 2 and 3), wherein the clustering centers are marked as zj(j＝1，2，3)，
When the clustering center z is 1, 3 cases of x1, x2 and x3 are divided,
case x 1: the cluster center is located between [0, 0.5],
case x 2: the cluster center is located above 0.5,
case x 3: the cluster center is located between [0.5, 1 ];
when the cluster center z is 2, 3 cases of y1, y2 and y3 are divided,
case y 1: the cluster centers are all located between 0-0.5,
case y 2: the cluster centers are all located between 0.5 and 1,
case y 3: the clustering centers are respectively positioned between [0-0.5] and [0.5-1],
when the clustering center z is 3, 3 cases of w1, w2 and w3 are divided,
w1 th case: two cluster centers are respectively positioned at 0-0.5 and 0.5-1, the other is positioned at 0.5,
w2 th case: two cluster centers are all located on 0-0.5, the other on 0.5,
w3 th case: two cluster centers are all located on 0.5-1, the other is located on 0.5,
in each case, the distance from the SOC of the prefabricated cabin of the rest lithium battery to each clustering center is respectively calculated and recorded as D (SOC (a)),
D(SOC(a))＝|SOC(a)-zj|2，
if D (soc (a)) min { D (soc (a), z)j) Fourthly, the lithium battery prefabricated cabin belongs to the clustering center, and the steps are repeated until all the lithium battery prefabricated cabins are classified completely;
and 4, step 4: selecting a reference cluster center and calculating a power requirement,
the distance between all the cluster centers and 0.5 is calculated for each case and is denoted as dj，
dj＝|SOC(t)-0.5|，
In each case take min [ d ]j]The corresponding clustering center is used as a reference clustering center;
the power demand of the power grid in the T time is related to the power generation condition and the load demand of the new energy, and the power demand of the power grid is set to be PNetThe power generated by the new energy is PNewThe load demand is PNegative poleTherefore, the power demand expression of the grid is: pNet＝PNegative pole-PNew
And 5: problem of power distribution in different situations
When z is 1:
clustering center as shown in the x1 case, the batteries are all in low SOC state, all the prefabricated lithium battery cabin are only suitable for charging,
the clustering center is as shown in the x2 case, all the batteries are in the state of SOC being 0.5, all the prefabricated cabins of lithium batteries are in the state of being chargeable and dischargeable,
the clustering center is shown as the x3 situation, all the batteries are in a high SOC state, and all the prefabricated cabins of the lithium batteries are only suitable for discharging;
when z is 2:
as shown in the case of the y1, the clustering center is that part of the batteries are in a high SOC state, part of the batteries are in a state of SOC equal to 0.5, when the batteries need to be charged, the lithium battery prefabricated cabin with SOC equal to 0.5 is charged preferentially, and when the batteries need to be discharged, the lithium battery prefabricated cabin with high SOC is discharged preferentially;
as shown in the case of the y2, the clustering center is that part of the batteries are in a low SOC state, and part of the batteries are in a state of SOC equal to 0.5, when the batteries need to be charged, the prefabricated lithium battery compartment in the low SOC state is charged preferentially, and when the batteries need to be discharged, the prefabricated lithium battery compartment in the SOC equal to 0.5 is discharged preferentially;
as shown in the y3 case, the clustering center is characterized in that part of the battery is in a low SOC state, part of the battery is in a high SOC state, when the battery needs to be charged, the lithium battery prefabricated cabin in the low SOC state is charged preferentially, and when the battery needs to be discharged, the lithium battery prefabricated cabin in the high SOC is discharged preferentially;
when z is 3:
the clustering centers are as shown in the w1 cases, two clustering centers of the similar battery are respectively positioned at [0-0.5] and [0.5-1], and the other clustering center is positioned at 0.5; when the battery needs to be charged, the lithium battery prefabricated cabin in a low SOC state and with the SOC being 0.5 is charged preferentially; when the battery is required to discharge, the lithium battery prefabricated cabin in a high SOC state and with the SOC being 0.5 is discharged preferentially;
clustering centers as shown in the w2 cases, two clustering centers of the similar battery are all located at [0-0.5], and the other is located at 0.5; when the battery is required to be charged, the lithium battery prefabricated cabin with the SOC being 0.5 is charged preferentially; when the battery is required to be discharged, the two types of lithium battery prefabricated cabins in the high SOC state are discharged preferentially, and the higher the SOC is, the higher the discharging priority is;
clustering centers As shown in the w3 th case, two clustering centers are all located at [0.5-1], and the other is located at 0.5; when the battery is required to be charged, the lithium battery prefabricated cabin in the low SOC state is charged preferentially, and the lower the SOC is, the higher the charging priority is; when the battery is required to be discharged, the lithium battery prefabricated cabin with the SOC being 0.5 is preferentially discharged.
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140316728A1 (en) * 2013-06-20 2014-10-23 University Of Electronic Science And Technology Of China System and method for soc estimation of a battery
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