CN116111678A - Energy storage battery dynamic grading charge and discharge control method based on maximum service life - Google Patents

Energy storage battery dynamic grading charge and discharge control method based on maximum service life Download PDF

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CN116111678A
CN116111678A CN202310045897.9A CN202310045897A CN116111678A CN 116111678 A CN116111678 A CN 116111678A CN 202310045897 A CN202310045897 A CN 202310045897A CN 116111678 A CN116111678 A CN 116111678A
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energy storage
storage battery
battery
charge
discharge
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李一波
尹继伟
李亚辉
杨毅
葛艳秋
解大
吴洋
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Anhui Zhichu New Energy Technology Development Co ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/0047—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries with monitoring or indicating devices or circuits
    • H02J7/005—Detection of state of health [SOH]
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/44—Methods for charging or discharging
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/007—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources
    • H02J3/0075—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources for providing alternative feeding paths between load and source according to economic or energy efficiency considerations, e.g. economic dispatch
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/00032—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries characterised by data exchange
    • H02J7/00036—Charger exchanging data with battery
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/0068—Battery or charger load switching, e.g. concurrent charging and load supply
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02E60/10—Energy storage using batteries

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Abstract

The invention discloses a method for controlling dynamic grading charge and discharge of an energy storage battery based on maximum service life, which comprises the following steps: step 1, dividing an energy storage battery into a plurality of stages according to SOH, wherein each stage is divided into a plurality of stages according to SOH; step 2, establishing a total cycle life model and a total battery profit model in the life cycle of the energy storage battery; step 3, solving a total cycle life model and a total battery profit model by taking the longest cycle life and the greatest battery profit as constraint conditions to obtain the cycle times of each stage in each stage of battery state of the energy storage battery; and 4, controlling the energy storage battery to complete the charge and discharge cycle of the cycle times obtained in the step 3 at each stage of each battery state of the energy storage battery. The invention can more accurately obtain the charge and discharge mode with the longest service life and highest benefit of the energy storage battery.

Description

Energy storage battery dynamic grading charge and discharge control method based on maximum service life
Technical Field
The invention relates to the field of battery charge and discharge control methods, in particular to a maximum-service-life-based energy storage battery dynamic grading charge and discharge control method.
Background
In the running process of the micro-grid, the service life of the energy storage battery is accelerated and attenuated due to the irregularity of charge and discharge, and the battery is often failed before the planned period of energy storage, so that the energy storage cost is increased. The battery has its own characteristics and cannot be charged or discharged without limit. Research on the charging time and the charging mode of an energy storage battery is attracting great attention.
In the current research stage, the energy storage battery is charged and discharged in the valley time and the peak-to-valley difference in the charge and discharge time of the energy storage battery in consideration of stage charge and discharge by using the time-sharing electricity price of the power grid, so that the energy storage battery is charged in the valley time and discharged in the peak time electricity price. In the charge-discharge mode of the energy storage battery, the influence of a plurality of factors on the service life of the energy storage battery is also considered, wherein the factors comprise discharge multiplying power, DOD, SOC, time, temperature and the like. How to extend the service life of the battery, improve the service efficiency of the battery and ensure the service safety of the battery is always an important content of research.
In the prior art, the peak-to-valley time-of-use electricity price is utilized to reduce the operation cost, the energy storage battery is preferably arranged to be charged in the valley time electricity price period through analysis of the peak-to-valley electricity price of the power grid, the energy storage battery is discharged in the peak time electricity price period, and a corresponding benefit analysis model is provided. However, the peak-valley period is not analyzed, and the specific charging mode of the energy storage is not analyzed according to the charging and discharging modes of the energy storage battery in the peak-valley period.
In the prior art, studies on battery life have generally been analyzed using equivalent cycle life. And calculating the charge and discharge depth and times according to the charge power curve and an equivalent cycle life calculation method to obtain an equivalent cycle life value. However, for different charge and discharge conditions, the remaining cycle number value of the battery has no corresponding calculation model, and the cycle number of the battery in different charge and discharge modes cannot be obtained.
Disclosure of Invention
The invention provides a method for controlling the dynamic grading charge and discharge of an energy storage battery based on the maximum service life, which aims to solve the problem that the charge and discharge control of the battery in the prior art cannot achieve both the service life and the maximization of benefits.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
the energy storage battery dynamic grading charge and discharge control method based on the maximum service life comprises the following steps:
step 1, selecting a plurality of SOH values as classification points according to the SOH of the battery state of health of the energy storage battery, and classifying the energy storage battery into a plurality of battery states according to the SOH; selecting a plurality of SOH values as phasing points in the SOH range corresponding to each stage of battery state of the energy storage battery, and dividing each stage of battery state into a plurality of stages according to SOH;
step 2, establishing a cycle life model and a battery profit model of each stage in each stage of battery state of the energy storage battery, thereby obtaining a total cycle life model and a total battery profit model in the whole life cycle of the energy storage battery;
and 3, solving the total cycle life model and the total battery profit model obtained in the step 2 by taking the maximum total cycle life and the maximum total battery profit of the energy storage battery as constraint conditions to obtain the cycle times of each stage in each battery state of the energy storage battery, wherein the accumulated cycle times of each stage are the service life of the battery.
And 4, controlling the energy storage battery to finish the charge and discharge cycle times corresponding to the step 3 at each stage of the energy storage battery so as to achieve the maximum service life and benefit.
Further, the total cycle life model N in the whole life cycle of the energy storage battery obtained in the step 2 is as follows:
Figure SMS_1
wherein N is the total cycle life of the energy storage battery; n (N) 100 The cycle life of the energy storage battery is 100% of the charge-discharge depth; i is the i-th stage of the energy storage battery; o (i) is the cycle number of the ith stage of the energy storage battery; x (i) is a fitting coefficient of the ith stage of the energy storage battery; d (i) is the charge and discharge depth of the energy storage battery in the ith stage; b is a fixed value, and the energy storage batteries of different materials have corresponding values; r is R EOL An ohmic internal resistance value at which the actual capacity is 80% of the rated capacity; r is R now Is the ohmic internal resistance in the current state; r is R N The ohmic internal resistance value of the battery when leaving the factory; alpha 1 The values of the experimental parameters are between 0.95 and 0.98, and the experimental parameters are different according to the materials of the batteries.
Further, the total battery profit model W in the whole life cycle of the energy storage battery obtained in step 2 is as follows:
Figure SMS_2
wherein i is the i-th stage of the energy storage battery; q is the total number of stages of the whole life cycle of the energy storage battery; t is the discharge time of the energy storage battery, and the sampling interval is 1 hour; e (t) is a time-of-use electricity price; p (t) is the power absorbed by the energy storage battery from the power grid; x is a fitting coefficient; n (N) 100 The cycle life of the energy storage battery is 100% of the charge-discharge depth; d (D) i The depth of charge and discharge of the energy storage battery at the ith stage; b is a fixed value, and the energy storage batteries of different materials have corresponding values; n is the total cycle life of the energy storage battery in the whole life cycle; c (C) i Is the cost of the energy storage battery at the i-th stage.
Further, in the step 4, a peak clipping and valley filling model of the energy storage battery is established, and charging time and discharging time of each charging and discharging cycle are obtained based on the peak clipping and valley filling model, so that the energy storage battery is controlled to start charging at the obtained charging time and discharging at the obtained discharging time during each charging and discharging cycle, and the energy storage battery is charged in a valley period of time-sharing electricity price and discharged in a peak period of time-sharing electricity price.
Further, the charging time t 1 The method is characterized by comprising the following steps of:
Figure SMS_3
wherein e (t) is a time-of-use electricity price; d represents the depth of charge and discharge; n (N) 100 Representing the cycle life of the cell at 100% dod; o (O) r Representing the remaining cycle life of the battery; b is a fixed value, and the energy storage batteries made of different materials have corresponding values.
Further, discharge time t 2 The method is characterized by comprising the following steps of:
Figure SMS_4
wherein e (t) is a time-of-use electricity price; d represents the depth of charge and discharge; n (N) 100 Representing the cycle life of the cell at 100% dod; o (O) r Representing the remaining cycle life of the battery; b is a fixed value, and the energy storage batteries made of different materials have corresponding values.
According to the invention, the charge and discharge of the energy storage battery are carried out on the basis of the time-of-use electricity price, the charge and discharge modes of the energy storage battery are researched, the energy storage battery grading charge and discharge technology is adopted, and different charge and discharge modes are adopted according to batteries in different states. By dynamically classifying the energy storage battery, the cycle life and the residual cycle life of the energy storage battery in different states and modes can be obtained, and the charge and discharge modes in different stages are optimized on the basis of subdivision, so that the charge and discharge mode with the longest service life and the highest benefit of the energy storage battery can be obtained more accurately.
Drawings
FIG. 1 is a schematic block diagram of an embodiment of the present invention.
Fig. 2 is a graph showing the relationship between SOH and the cycle number of the energy storage battery according to the embodiment of the present invention.
Fig. 3 is a hierarchical model of an energy storage cell according to an embodiment of the present invention.
FIG. 4 is a graph showing the effect of depth of discharge on cycle life for an embodiment of the present invention.
Fig. 5 shows peak-valley time-of-use electricity prices in the example of the present invention.
Detailed Description
In order to make the technical solution of the present invention better understood by those skilled in the art, the following detailed description will be given with reference to the accompanying drawings and examples, by which the technical means are applied to solve the technical problem, and the implementation process for achieving the corresponding technical effects can be fully understood and implemented. The embodiment of the invention and the characteristics in the embodiment can be mutually combined on the premise of no conflict, and the formed technical scheme is within the protection scope of the invention.
It will be apparent that the described embodiments are merely some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It is noted that the terms "comprises" and "comprising," and any variations thereof, in the description and claims of the present invention and in the foregoing figures, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or apparatus.
As shown in fig. 1, this embodiment discloses a method for controlling dynamic grading charge and discharge of an energy storage battery based on maximum service life, which analyzes charge and discharge time of the energy storage battery according to time-of-use electricity price, then grades the energy storage battery according to SOH of the energy storage battery, combines parameters such as internal resistance and materials of the energy storage battery to obtain charge and discharge models of the energy storage battery in different stages, and finally achieves the purposes of prolonging cycle life of the energy storage battery and increasing economic benefit.
And carrying out data statistics and collection on the charge states, the cycle times and the charge and discharge analysis of the energy storage batteries of different base stations. Comprehensively considering the information system source, quality and data availability of the data, determining the data requirement and carrying out data extraction. According to the collected data, the service conditions, the cycle life and the corresponding economic analysis of batteries of different levels under different states are mined item by using a data analysis method and technology.
The embodiment comprises the following steps:
step 1, selecting a plurality of SOH values as classification points according to the SOH of the battery state of health of the energy storage battery, and classifying the energy storage battery into a plurality of battery states according to the SOH; and selecting a plurality of SOH values as phasing points in the SOH range corresponding to each stage of battery state of the energy storage battery, and dividing each stage of battery state into a plurality of phases according to the SOH.
In this embodiment, the classification of the energy storage battery is performed according to the battery state of health SOH of the energy storage battery. Since SOH decays with the use of the energy storage battery, the embodiment takes 80%, 50% and 20% as classification points, so that the energy storage battery with SOH of 100% -80% is classified into a class I energy storage battery state, the energy storage battery with SOH of 80% -50% is classified into a class II energy storage battery state, the energy storage battery with SOH of 50% -20% is classified into a class III energy storage battery state, and the energy storage battery with SOH lower than 20% is considered as a waste battery.
The embodiment then stages the states of the energy storage batteries at different levels to obtain charge and discharge modes at different stages. For the state of the I-stage energy storage battery, three phasing points of 95%, 90% and 85% of 100% -80% of SOH are selected in the embodiment, and the state of the I-stage energy storage battery is divided into four phases. For the state of the class II energy storage battery, five phasing points of 75%, 70%, 65%, 60% and 55% of 80% -50% of SOH are selected in the embodiment, and the state of the class II energy storage battery is divided into six phases. For the class III energy storage battery state, five phasing points of 45%, 40%, 35%, 30% and 25% of 50% -20% of SOH are selected in the embodiment, and the class III energy storage battery state is divided into six phases.
And 2, establishing a cycle life model and a battery profit model of each stage in each stage of battery state of the energy storage battery, thereby obtaining a total cycle life model and a total battery profit model in the whole life cycle of the energy storage battery.
According to the embodiment, a cycle life and economic benefit model of the energy storage battery are obtained according to different charge and discharge modes; and finally, taking the longest cycle life and the highest economic benefit as constraint conditions, solving fitting parameters in the model, and applying the fitting parameters to an actual power system to achieve the aim of maximum benefit. The process is as follows:
1. hierarchical charge-discharge model analysis of energy storage battery
Aiming at the difference of peak-valley electricity price time periods of the power grid, the low-carbon system can calculate the charging mode of the energy storage battery according to the technical parameters of time period length, the SOC of the energy storage battery, the charged and discharged times, SOH and the like, and finally the optimal energy storage charging mode is realized so as to obtain the maximum service life of the battery.
SOH has certain relation with the cycle number of battery, and along with the use of battery, the health condition of battery can attenuate gradually, has:
Figure SMS_5
wherein the standard definition of SOH is the capacity C of the battery discharged from the full state to the cut-off voltage at a certain rate t And nominal capacity C 0 The ratio between them is shown in fig. 2.
Because SOH of the battery can be attenuated along with the increase of the cycle times, and the energy storage battery is not fully charged and discharged every time, in order to achieve the maximum benefit, the battery is subjected to a grading charge and discharge mode, and the optimal solution is obtained to achieve the maximum benefit.
According to the difference of the state of health (SOH), the energy storage batteries are divided into I-level, II-level, III-level batteries and scrapped batteries, and aiming at the energy storage batteries of different types, a charging and discharging configuration scheme of the batteries is adopted in a grading way, and a corresponding model is built so as to enable the energy storage batteries to achieve the longest service life and finally achieve the aim of optimal economic benefit. Wherein, the SOH is 100-80% of the I-class battery, the SOH is 80-50% of the II-class battery, the SOH is 50-20% of the III-class battery, and the battery with SOH less than 20% is disassembled and recycled. As shown in fig. 3.
In order to optimize the charge and discharge model, the energy storage battery reaches the optimal solution, the battery is continuously segmented, and the multi-segment is divided in the I, II and III-level batteries to carry out detailed analysis on the charge and discharge modes of the energy storage battery.
The factors influencing the service life of the energy storage battery mainly comprise the energy storage battery material, the charge and discharge depth (shown in fig. 4) of the energy storage battery, the charge and discharge current, the internal resistance of the energy storage battery, the capacity and the charge state of the energy storage battery and the like. 1) Material analysis of energy storage battery: the types of energy storage batteries are numerous and broadly classified into lead acid batteries, nickel hydrogen batteries, lithium batteries, sodium sulfur batteries, vanadium redox flow batteries, and the like. Batteries of different materials have different characteristics, energy efficiency, cost and cycle life. 2) Depth of charge and discharge of energy storage battery: wherein depth of discharge versus battery cycle life is shown. Wherein the deeper the depth of discharge, the lower the cycle life; high discharge rates may lead to low conductivity of the cell and an increase in electrode corrosion rate.
And (3) charge-discharge current analysis: in the working process of the lithium iron phosphate energy storage battery, if the charging and discharging currents are not in accordance with the requirements, when the charging and discharging currents exceed the limit, a large amount of heat is generated by accumulating the internal resistance of the battery along with time, so that potential safety hazards are caused, the service life of the battery is prolonged, and the safety performance is also affected and reduced.
Internal resistance and SOH of the energy storage battery: the internal resistance of a battery is an important characterization parameter of the state of health of the battery, and refers to the resistance experienced by current flowing through the interior of the battery, including polarization resistance and ohmic resistance. The phenomenon in which the electrode potential deviates from the equilibrium electrode potential when current is passed through the electrode is called polarization of the electrode. Polarization resistance refers to the internal resistance caused by polarization of the positive and negative electrodes of a battery when undergoing electrochemical reactions. The ohmic internal resistance mainly consists of electrode materials, electrolyte, diaphragm resistance and contact resistance of parts, and is related to the size, structure, assembly and the like of the battery, and the ohmic internal resistance mainly comprises the following components:
Figure SMS_6
wherein R is EOL An ohmic internal resistance value at which the actual capacity is 80% of the rated capacity; r is R N Is the ohmic internal resistance value R of the battery when leaving the factory now The ohmic internal resistance in the current state can be measured by a pulse charging method.
Capacity analysis of the energy storage battery: the capacity of the energy storage battery refers to the electric energy released by the energy storage battery, and the energy storage batteries of different types have different battery capacities. Mainly comprises rated capacity, actual capacity and theoretical capacity.
And (3) analyzing the charge state of the energy storage battery:
Figure SMS_7
wherein, SOC represents the charge state of the battery; q (Q) rem Representing the amount of remaining charge of the battery; q (Q) max Indicating the rated charge capacity of the battery.
2. Life analysis of energy storage battery
The factors influencing the service life of the energy storage battery are many, and the energy storage charging and discharging rate, DOD (depth of charge and discharge), the energy storage charge state and SOH all have nonlinear influences on the operation efficiency and service life attenuation of the energy storage. The one-time charge and discharge process of one energy storage battery is circulated once, and under a certain ideal charge and discharge mode, the residual use times of the battery are the difference value between the total use times and the used times.
Assuming that the number of cycles at full charge of the energy storage cell, i.e. 100% DOD, is N 100 The number of cycles in case of non-full drop, i.e. DDOD, is N D The cycle life of the energy storage battery at this time can be expressed as:
N(D)＝kN 100 D -b
wherein N (D) represents the battery cycle life when the depth of charge and discharge of the energy storage battery is D; n (N) 100 The cycle life of the energy storage battery is represented when the charge and discharge depth of the energy storage battery is 100%; d is the depth of charge and discharge of the energy storage battery; k is a proportionality coefficient; b is a fixed value, and the value of b is different for different batteries, and for example, a lithium battery is taken as b to be 0.8.
The present embodiment will be described with reference to the class I battery state as an example. The class I battery corresponds to 100% -80% of SOH, and the class I battery with 100% of SOH of the energy storage battery adopts a charge and discharge depth of D 1 DOD is charged and discharged until the I-level battery drops from SOH of 100% to s 1 At this time, the number of cycles is O 1 During this period, the energy storage battery cycle life is:
N(D 1 )＝k 1 N 100 D 1 -b
wherein N (D) 1 ) Indicating the depth of charge and discharge of the energy storage battery as D 1 The cycle life of the battery; n (N) 100 The cycle life of the energy storage battery is represented when the charge and discharge depth of the energy storage battery is 100%; k (k) 1 Fitting coefficients; b is a fixed value, and the values of different batteries b are different.
The remaining cycle number of the energy storage battery when the mode is used for charging and discharging is as follows:
L(D 1 )＝k 1 N 100 D 1 -b -r
wherein L (D) 1 ) Indicating the remaining cycle life of the energy storage battery; n (N) 100 The cycle life of the energy storage battery is represented when the charge and discharge depth of the energy storage battery is 100%; d (D) 1 The depth of charge and discharge of the energy storage battery is set; k (k) 1 Fitting coefficients; b is a fixed value, and the values of different batteries b are different; r is the number of cycles the battery has been cycled.
In D 1 DOD is charged and discharged, and the cycle number is O 1 In the case of the class I battery of (2), SOH is S 1 . Adopts the depth of charge and discharge as D 2 DOD is charged and discharged until SOH of the battery is reduced to s 2 At this time, the number of cycles is O 2 At SOH by S 1 Down to s 2 During this period, the cycle life of the energy storage battery is:
N(D 2 )＝k 2 N 100 D 2 -b
wherein N (D) 2 ) Indicating the depth of charge and discharge of the energy storage battery as D 2 The cycle life of the battery; n (N) 100 The cycle life of the energy storage battery is represented when the charge and discharge depth of the energy storage battery is 100%; k (k) 2 Fitting coefficients; b is a constant value, pairDifferent cells b take different values.
And if the charge and discharge are carried out continuously in the mode, the remaining cycle times of the energy storage battery are as follows:
L(D 2 )＝k 2 N 100 D 2 -b -r
wherein L (D) 2 ) Indicating the remaining cycle life of the energy storage battery; n (N) 100 The cycle life of the energy storage battery is represented when the charge and discharge depth of the energy storage battery is 100%; d (D) 2 The depth of charge and discharge of the energy storage battery is set; k (k) 2 Fitting coefficients; b is a fixed value, and the values of different batteries b are different; r is the number of cycles the battery has been cycled.
In D 2 DOD is charged and discharged, and the cycle number is O 2 From SOH to s for class I cells 2 Down to s 3 At this time, the depth of charge and discharge is changed to d 3 DOD, pushing in this way until the SOH of the energy storage battery is reduced to 80%, and the grade I battery is reduced to the grade II battery and finally reduced to the grade III battery until the grade III battery is scrapped.
The battery is classified by the SOH, and then is dynamically adjusted in stages according to the charge and discharge of each stage of battery state, so that the longest service life of the battery and the biggest benefit are finally realized, and the related research is carried out on the basis of the longest service life of the battery.
3. Grading charge-discharge model for realizing maximum service life of energy storage
The charging and discharging time of the battery is combined with the time-sharing electricity price, so that the charging cost of the energy storage battery can be obtained. And obtaining the cycle life of the battery by considering the charge and discharge depth of the energy storage battery, and carrying out benefit analysis. Due to the different states of the battery, the charging cost of the battery can be optimized by dynamically grading the battery, so that the battery can obtain the maximum service life, and the maximum benefit is realized.
The conventional method for analyzing the cost benefit of the energy storage battery unifies the charge and discharge modes of the battery, and the actual cost and the generated benefit of the energy storage battery cannot be dynamically and accurately analyzed. The energy storage battery is dynamic uncertainty in actual operation, the battery state can be monitored, and the most applicable charge and discharge modes in the state are analyzed to obtain the optimal benefit.
The cost of the energy storage battery is related to the time-of-use electricity price, the power absorbed by the energy storage battery from the power grid, the charge and discharge depth and the service life of the energy storage battery, and the cost function of the energy storage battery is obtained as follows:
Figure SMS_8
wherein e (t) is the time-of-use electricity price, and the sampling interval is 1 hour; p (t) is the power absorbed by the energy storage battery system from the power grid; x is a fitting coefficient; d is the depth of charge and discharge of the energy storage battery; b is a fixed value; the values of the different types of batteries b are different.
The present embodiment will be described with reference to the class I battery state as an example. The cost of the I-level battery in the 1 st stage is C I1 ：
Figure SMS_9
Energy storage battery benefit M I1 ：
M I1 ＝∫ 1 24 te(t)P(t)dt
Wherein t is the discharge time of the energy storage battery, e (t) is the time-sharing electricity price, and the sampling interval is 1 hour; p (t) is the power absorbed by the energy storage battery system from the grid.
Thereby obtaining the profit W of the energy storage battery at each stage i
Figure SMS_10
In which W is i Profit for the energy storage battery at the i-th stage; m is M i The benefits of the energy storage battery in the ith stage; c (C) i Cost of the energy storage battery at the ith stage; o (O) i The cycle number of the energy storage battery in the ith stage; t is the discharge time of the energy storage battery, e (t) is the time-sharing electricity price, and the sampling interval is 1 hour; p (t) is the power absorbed by the energy storage battery system from the grid.
Total profit W generated by the energy storage battery over the full life cycle:
Figure SMS_11
wherein i is the current i-th stage mode of the energy storage battery; q is the total number of stages of the whole life cycle of the energy storage battery; o (O) i The cycle number of the energy storage battery in the ith stage; t is the discharge time of the energy storage battery, e (t) is the time-sharing electricity price, and the sampling interval is 1 hour; p (t) is the power absorbed by the energy storage battery system from the grid.
4. Conclusion(s)
And the optimal model coefficient is obtained through hierarchical analysis by taking the longest cycle life of the energy storage battery and the highest economic benefit of the energy storage battery as constraint conditions. The analysis from the latest use stage to the scrapping stage of one energy storage battery is expanded to the fact that the energy storage batteries in the power system at the same moment have different SOH coefficients. And sending instructions through the monitoring system, and carrying out different charge and discharge modes on the energy storage batteries in different states so as to achieve the optimal charge and discharge model of all the energy storage batteries of the power station.
The cycle life of the energy storage battery is as follows:
Figure SMS_12
wherein N is the total cycle life of the energy storage battery; n (N) 100 The cycle life of the energy storage battery is 100% of the charge-discharge depth; i is the i-th stage of the energy storage battery; o (i) is the cycle number of the ith stage of the energy storage battery; x (i) is a fitting coefficient of the ith stage of the energy storage battery; d (i) is the charge and discharge depth of the energy storage battery in the ith stage; b is a fixed value, and the energy storage batteries of different materials have corresponding values; r is R EOL An ohmic internal resistance value at which the actual capacity is 80% of the rated capacity; r is R now Is the ohmic internal resistance in the current state; r is R N The ohmic internal resistance value of the battery when leaving the factory; alpha 1 The values of the experimental parameters are between 0.95 and 0.98, and the experimental parameters are different according to the materials of the batteries.
By carrying out grading treatment on the energy storage battery, different charge and discharge modes are adopted at different stages, so that the cycle life of the energy storage battery is prolonged.
Profit W of energy storage battery at each stage i ：
Figure SMS_13
In which W is i Profit for the energy storage battery at the i-th stage; m is M i The benefits of the energy storage battery in the ith stage; c (C) i Cost of the energy storage battery at the ith stage; o (O) i The cycle number of the energy storage battery in the ith stage; t is the discharge time of the energy storage battery, e (t) is the time-sharing electricity price, and the sampling interval is 1 hour; p (t) is the power absorbed by the energy storage battery system from the grid.
Total profit W generated by the energy storage battery over the full life cycle:
Figure SMS_14
wherein i is the current i-th stage mode of the energy storage battery; q is the total number of stages of the whole life cycle of the energy storage battery; o (O) i The cycle number of the energy storage battery in the ith stage; t is the discharge time of the energy storage battery, e (t) is the time-sharing electricity price, and the sampling interval is 1 hour; p (t) is the power absorbed by the energy storage battery system from the grid.
And 3, solving the total cycle life model and the total battery profit model obtained in the step 2 by taking the maximum total cycle life and the maximum total battery profit of the energy storage battery as constraint conditions to obtain the cycle times of each stage in each stage of battery state of the energy storage battery, wherein the accumulated cycle times of each stage are the service life of the battery, and the service life of the battery is the target variable of the patent.
And 4, controlling the energy storage battery to finish the charge and discharge cycle times corresponding to the step 3 at each stage of the energy storage battery so as to achieve the maximum service life and benefit.
The load in the power grid has large peak-valley drop, and can cause adverse effect on the system. To ameliorate this adverse effect, energy storage batteries are added to the power grid. The battery is charged in the valley period, the electricity price is cheaper, the effect of filling the valley is achieved, the energy storage battery is discharged in the peak period, the power consumption of the power grid is reduced, and the effect of peak clipping is achieved. In order to achieve better effect, firstly, the smallest variance value of the load curve after peak clipping and valley filling is selected as an objective function.
(1) Peak-valley time-of-use electricity price model
And (5) considering an optimization model for peak clipping and valley filling. And the cost and the income of the energy storage battery are analyzed in detail to obtain an optimal scheme, and the peak-valley time-of-use electricity price is shown in figure 5.
As shown in fig. 5, 24 hours throughout the day were equally divided into 24 time periods. For example, in different time periods, electricity prices are divided into low electricity prices of 0.22 yuan/kWh; peak electricity price 0.99 yuan/kWh; and a flat price of 0.58 yuan/kWh. The energy storage battery is charged during the valley electricity price period, so that the charging cost of the energy storage battery can be reduced; during peak-time electricity price, the energy storage battery discharges, and the electric quantity in the energy storage battery is utilized, so that electricity consumption cost can be reduced. Therefore, the energy storage battery is reasonably charged and discharged, and the effects of reducing electricity cost and increasing economic benefit can be achieved. As shown in fig. 4, the peak load shifting effect of the energy storage battery reduces the power generation amount of the power grid in the peak time period, and increases the income.
(2) Peak clipping and valley filling model of energy storage battery
The energy storage battery charges the battery in the valley period, the electricity price is cheaper, the effect of filling the valley is achieved, the energy storage battery discharges in the peak period, and the power consumption of a power grid is reduced, so that the effect of peak clipping is achieved. In order to achieve a better effect.
Charging and discharging time of energy storage battery
Charging time t 1 ：
Figure SMS_15
Wherein e (t) is a time-of-use electricity price; d represents the depth of charge and discharge; n (N) 100 Representing the cycle life of the cell at 100% dod; o (O) r Representing the remaining cycle life of the battery; b is a fixed value, and the energy storage batteries made of different materials have corresponding values.
Discharge time t 2 ：
Figure SMS_16
/>
Wherein e (t) is a time-of-use electricity price; d represents the depth of charge and discharge; n (N) 100 Representing the cycle life of the cell at 100% dod; o (O) r Representing the remaining cycle life of the battery; b is a fixed value, and the energy storage batteries made of different materials have corresponding values.
Thus, each charge-discharge cycle is controlled to start charging at the obtained charging time and to start discharging at the obtained discharging time, so that the energy storage battery is charged in the valley period of the time-sharing electricity price and discharged in the peak period of the time-sharing electricity price.
By carrying out grading treatment on the energy storage battery, different charge and discharge modes are adopted at different stages, so that the profit of the energy storage battery is increased.
Taking lithium iron phosphate as an example, according to a grading charge-discharge formula, the grading charge-discharge mode of the battery brought into energy storage is shown in table 1, the cycle life is longer than 10000 times, and the purposes of longest cycle life and optimal economic benefit are achieved.
The optimal charge and discharge mode is obtained through calculation in order to achieve the maximum service life and economic benefit of the battery. As shown in table 1, to achieve the longest battery life and the greatest benefit, different charge and discharge depths are used at different stages of the energy storage battery to calculate the corresponding cycle times.
After theoretical calculation, for batteries with different materials, the battery charge and discharge modes and the circulation times similar to those of the battery in table 1 can be obtained, and in actual operation, the service life of the battery can be prolonged to the maximum benefit by setting the charge and discharge depth and the circulation times.
TABLE 1 hierarchical charge and discharge modes for energy storage batteries
Figure SMS_17
Figure SMS_18
The preferred embodiments of the present invention have been described in detail above with reference to the accompanying drawings, and the examples described herein are merely illustrative of the preferred embodiments of the present invention and are not intended to limit the spirit and scope of the present invention. The individual technical features described in the above-described embodiments may be combined in any suitable manner without contradiction, and such combination should also be regarded as the disclosure of the present disclosure as long as it does not deviate from the idea of the present invention. The various possible combinations of the invention are not described in detail in order to avoid unnecessary repetition.
The present invention is not limited to the specific details of the above embodiments, and various modifications and improvements made by those skilled in the art to the technical solution of the present invention should fall within the protection scope of the present invention without departing from the scope of the technical concept of the present invention, and the technical content of the present invention is fully described in the claims.

Claims (6)

1. The energy storage battery dynamic grading charge and discharge control method based on the maximum service life is characterized by comprising the following steps of:
step 1, selecting a plurality of SOH values as classification points according to the SOH of the battery state of health of the energy storage battery, and classifying the energy storage battery into a plurality of battery states according to the SOH; selecting a plurality of SOH values as phasing points in the SOH range corresponding to each stage of battery state of the energy storage battery, and dividing each stage of battery state into a plurality of stages according to SOH;
step 2, establishing a cycle life model and a battery profit model of each stage in each stage of battery state of the energy storage battery, thereby obtaining a total cycle life model and a total battery profit model in the whole life cycle of the energy storage battery;
and 3, solving the total cycle life model and the total battery profit model obtained in the step 2 by taking the maximum total cycle life and the maximum total battery profit of the energy storage battery as constraint conditions to obtain the cycle times of each stage in each battery state of the energy storage battery, wherein the accumulated cycle times of each stage are the service life of the battery.
And 4, controlling the energy storage battery to finish the charge and discharge cycle times corresponding to the step 3 at each stage of the energy storage battery so as to achieve the maximum service life and benefit.
2. The method for controlling the dynamic grading charge and discharge of the energy storage battery based on the maximum service life according to claim 1, wherein the total cycle life model N in the whole life cycle of the energy storage battery obtained in the step 2 is as follows:
Figure FDA0004055406560000011
wherein N is the total cycle life of the energy storage battery; n (N) 100 The cycle life of the energy storage battery is 100% of the charge-discharge depth; i is the i-th stage of the energy storage battery; o (i) is the cycle number of the ith stage of the energy storage battery; x (i) is a fitting coefficient of the ith stage of the energy storage battery; d (i) is the charge and discharge depth of the energy storage battery in the ith stage; b is a fixed value, and the energy storage batteries of different materials have corresponding values; r is R EOL An ohmic internal resistance value at which the actual capacity is 80% of the rated capacity; r is R now Is the ohmic internal resistance in the current state; r is R N The ohmic internal resistance value of the battery when leaving the factory; alpha 1 The values of the experimental parameters are between 0.95 and 0.98, and the experimental parameters are different according to the materials of the batteries.
3. The method for controlling the dynamic grading charge and discharge of the energy storage battery based on the maximum service life according to claim 1, wherein the total battery profit model W in the whole life cycle of the energy storage battery obtained in the step 2 is as follows:
Figure FDA0004055406560000021
wherein i is the i-th stage of the energy storage battery; q is the total number of stages of the whole life cycle of the energy storage battery; t is tThe discharge time of the energy storage battery is 1 hour at sampling intervals; e (t) is a time-of-use electricity price; p (t) is the power absorbed by the energy storage battery from the power grid; x is a fitting coefficient; n (N) 100 The cycle life of the energy storage battery is 100% of the charge-discharge depth; d (D) i The depth of charge and discharge of the energy storage battery at the ith stage; b is a fixed value, and the energy storage batteries of different materials have corresponding values; n is the total cycle life of the energy storage battery in the whole life cycle; c (C) i Is the cost of the energy storage battery at the i-th stage.
4. The method for controlling the dynamic grading charge and discharge of the energy storage battery based on the maximum service life according to claim 1, wherein in the step 4, a peak clipping and valley filling model of the energy storage battery is established, and the charge time and the discharge time of each charge and discharge cycle are obtained based on the peak clipping and valley filling model, so that the energy storage battery is controlled to start to charge at the obtained charge time and to start to discharge at the obtained discharge time during each charge and discharge at the peak time of the time-sharing electricity price, and the energy storage battery is charged at the valley time of the time-sharing electricity price is realized.
5. The method for dynamically classifying charge and discharge control of an energy storage battery based on maximum lifetime as recited in claim 4, wherein the charge time t 1 The method is characterized by comprising the following steps of:
Figure FDA0004055406560000022
wherein e (t) is a time-of-use electricity price; d represents the depth of charge and discharge; n (N) 100 Representing the cycle life of the cell at 100% dod; o (O) r Representing the remaining cycle life of the battery; b is a fixed value, and the energy storage batteries made of different materials have corresponding values.
6. The method for dynamically classifying charge and discharge control of an energy storage battery based on maximum lifetime as recited in claim 4, wherein the discharge time t 2 The method is characterized by comprising the following steps of:
Figure FDA0004055406560000023
wherein e (t) is a time-of-use electricity price; d represents the depth of charge and discharge; n (N) 100 Representing the cycle life of the cell at 100% dod; o (O) r Representing the remaining cycle life of the battery; b is a fixed value, and the energy storage batteries made of different materials have corresponding values.
CN202310045897.9A 2023-01-30 2023-01-30 Energy storage battery dynamic grading charge and discharge control method based on maximum service life Pending CN116111678A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116799899A (en) * 2023-05-29 2023-09-22 芜湖鑫锐信息科技有限公司 Battery safety management method, device, equipment and storage medium

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116799899A (en) * 2023-05-29 2023-09-22 芜湖鑫锐信息科技有限公司 Battery safety management method, device, equipment and storage medium
CN116799899B (en) * 2023-05-29 2024-02-27 深圳市泰量电子有限公司 Battery safety management method, device, equipment and storage medium

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