Rural distribution network energy storage battery charging optimization method based on battery soc state

Abstract

This invention relates to an optimized charging method for rural power grid energy storage batteries based on their State of Charge (SOC), belonging to the field of battery optimization. Before charging the rural power grid energy storage batteries, the SOC estimation result of the battery is detected, and a suitable charging scheme is selected according to different battery states. The charging scheme includes: when SOC ≤ 10%, constant current charging is performed based on the acceptable initial current rate of the battery; when 10% < SOC ≤ 75%, a constant charging current is maintained, and a negative pulse charging method is used, specifically: charging is stopped before the negative pulse, discharging occurs during the negative pulse, and charging is stopped after the negative pulse; when 75% < SOC ≤ 90%, a MAS-pulse charging method is used; when SOC > 90%, a constant voltage trickle charging method with adaptive current adjustment is used. This method ensures charging efficiency, improves safety, extends battery life, and reduces costs.

Description

Technical Field

[0001] This invention belongs to the field of battery optimization and relates to a method for optimizing the charging of rural power grid energy storage batteries based on battery SOC state. Background Technology

[0002] Currently, in remote rural areas, the distribution network suffers from problems such as low voltage and high losses due to rapid load growth and long lines, which seriously affect power quality. The existing power supply is mainly based on the terminal power supply method with distribution network transformers as the core. Since there are few households in remote rural areas and the households are prone to migration, the current traditional power supply method is prone to excessive redundancy in the capacity of distribution network transformers, resulting in excessively high construction costs for power grid companies. Developing new power supply methods is of great significance for the economic construction of rural distribution networks.

[0003] The new power supply solution for rural distribution networks based on large-capacity lithium iron phosphate energy storage batteries is a highly innovative and promising new solution. Through device regulation, this solution can achieve energy storage charging during off-peak hours and discharging during peak hours, realizing active and reactive power compensation functions at the end of rural distribution network lines. This is conducive to the interaction between source, grid, load, and storage, and reduces the energy consumption cost and equipment investment cost of the power grid system.

[0004] However, the state of charge (SOC) of a lithium iron phosphate (LFP) battery is a crucial parameter in the LFP battery management system, and its accuracy is fundamental to the monitoring and optimization of LFP battery charge and discharge. Because polarization reactions during LFP battery charging reduce the charging speed, and while traditional fast charging methods can improve the charging speed to some extent, they are more damaging to the LFP battery and can easily lead to safety hazards. Summary of the Invention

[0005] In view of this, the purpose of this invention is to provide a lithium iron phosphate battery charging optimization strategy based on the state of charge (SOC) of the lithium iron phosphate battery, so as to reduce the polarization reaction of the lithium iron phosphate battery during the charging process, effectively reduce the charging time, and improve the charging safety and reliability.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A method for optimizing the charging of rural power grid energy storage batteries based on battery state of charge (SOC) involves detecting the SOC estimation result of the battery before charging and selecting a suitable charging scheme according to different battery states. The charging scheme includes:

[0008] When SOC≤10%, the optimal initial current is determined based on the battery's acceptable starting current for constant current charging.

[0009] When 10% < SOC ≤ 75%, maintain a constant charging current and use a negative pulse charging method for charging. Specifically, charging is performed by stopping charging before the negative pulse, discharging during the negative pulse, and stopping charging after the negative pulse.

[0010] When 75% < SOC ≤ 90%, charging is performed using the MAS-pulse charging method;

[0011] When SOC > 90%, a constant voltage trickle charging method with adaptive current regulation is used for charging.

[0012] Furthermore, the rural power grid energy storage battery is a lithium iron phosphate battery.

[0013] Furthermore, the SOC estimation result of the tested battery specifically includes:

[0014] The first-order battery model equation for lithium iron phosphate energy storage batteries is as follows:

[0015] E = V b -I·Z (1)

[0016]

[0017] In the formula, E represents the terminal voltage of the lithium iron phosphate battery, V b Let Z represent an ideal voltage source, and let Z represent the internal resistance of a first-order battery model, which is composed of the battery's ohmic internal resistance R0 and the parallel resistance R that describes the battery's charging polarization process. p and parallel capacitor C p composition;

[0018] A state-of-charge (SOC) assessment model for lithium iron phosphate batteries is established based on a recurrent neural network. The inputs of the SOC assessment model are the current terminal voltage V, charging current I, and the sampled value of the current SOC of the energy storage battery. The output is the internal resistance Z of the first-order battery model. The predicted SOC sampled value is determined using the E-SOC curve of the lithium iron phosphate battery, thereby completing the dynamic assessment of the SOC of the lithium iron phosphate battery.

[0019] The state-of-charge assessment model for the lithium iron phosphate battery has 3 output layer nodes and 3 input layer nodes, corresponding to an internal resistance of R0 and a parallel resistance of R. p and parallel capacitor C p ;

[0020] Standard current charge-discharge experiments were conducted on lithium iron phosphate batteries, and their E-SOC curves were obtained by combining polynomial fitting. Then, based on pulse charging, constant current, and constant voltage charging tests, energy storage battery charge-discharge training samples were constructed, and a recurrent neural network was trained and its parameters were continuously updated. Finally, a state-of-charge assessment model for lithium iron phosphate batteries was established to accurately assess the SOC state of lithium iron phosphate energy storage batteries.

[0021] Furthermore, when SOC ≤ 10%, determining the optimal initial current for constant current charging based on the battery's acceptable starting current rate specifically includes:

[0022] First, determine the initial charging curve according to the MAS law. The formula for the MAS charging curve is:

[0023] I k =I1+I2+I3+... (3)

[0024] In the formula, I1, I2, and I3 are the acceptable charging currents accumulated at different times, and I k Let be the acceptable current at time k;

[0025] The acceptable starting current α of lithium iron phosphate batteries is calculated using formula (4), which is:

[0026]

[0027] In the formula, C f The discharge capacity of the lithium iron phosphate battery is given by α, where α is the acceptable current rate and I is the discharge capacity. s Initial charging current;

[0028] The C is directly determined based on the SOC of the lithium iron phosphate battery. f Based on the calculated initial current acceptable rate α, the initial charging current I is obtained by formula (4). s Use this current to charge the battery at a constant current until the state of charge (SOC) is greater than 10%.

[0029] Furthermore, the step of maintaining a constant charging current and using a negative pulse charging method when 10% < SOC ≤ 75% specifically includes:

[0030] The method to increase the current acceptance rate α of lithium iron phosphate batteries is to use a negative pulse charging method and set the positive pulse width t. F The charging and stopping times t1 and t2 before and after the charging and stopping, and the negative pulse width t R Charging stops before a negative pulse, discharging occurs during a negative pulse, and charging stops after a negative pulse.

[0031] Furthermore, the charging method using MAS-pulse charging when 75% < SOC ≤ 90% specifically includes:

[0032] According to the MAS law, the charging method is switched to MAS-pulse charging, where the positive and negative pulse stop times t1 and t2 and t... R The negative pulse width is consistent with the setting used when employing the negative pulse charging method. The positive pulse magnitude varies with the charging curve according to the MAS law. The formula for the positive pulse current is:

[0033] I F (t)=I F ·e -αt (5)

[0034] In the formula, I F (t) represents the positive pulse current;

[0035] According to MAS law, the gas evolution ΔG generated by the positive pulse during the time interval Δt is removed by an equal amount of negative pulse discharge, thus determining the magnitude I of the negative pulse current. R (t):

[0036]

[0037] Furthermore, when SOC > 90%, a constant voltage trickle charging method with adaptive current regulation is used for charging, and the charging current I is based on the set rated current I. * With adaptive adjustment, the charging current gradually decreases as the charging time increases, and the state of charge (SOC) of the lithium iron phosphate battery tends to stabilize.

[0038] The beneficial effects of this invention are as follows: When charging energy storage lithium iron phosphate batteries, four phased fast charging strategies are formulated according to different current states of lithium iron phosphate batteries: constant current charging, negative pulse charging, and constant voltage trickle charging with adaptive current adjustment. This phased charging method not only ensures charging time efficiency, but also achieves safe and lossless charging, extends the service life of lithium iron phosphate batteries, and reduces the cost of lithium iron phosphate batteries.

[0039] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0040] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein:

[0041] Figure 1 for Figure 1This is a flowchart of the rural power distribution network energy storage battery charging optimization method based on battery SOC state as described in this invention;

[0042] Figure 2 This is the SOC estimation strategy of the present invention;

[0043] Figure 3 This is a schematic diagram of a multi-stage charging scheme. Detailed Implementation

[0044] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0045] The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual pictures. They should not be construed as limiting the invention. To better illustrate the embodiments of the invention, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product dimensions. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0046] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," "front," and "rear" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present invention. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0047] Figure 1 The flowchart below illustrates the multi-stage fast charging process of the method described in this invention. In step one, the lithium iron phosphate battery is first detected at the start of charging to obtain an estimate of its state of charge (SOC). To effectively improve the estimation accuracy, this invention establishes a SOC assessment model for the lithium iron phosphate battery based on a recurrent neural network. Figure 2 This is the SOC estimation strategy of the present invention.

[0048] First, a first-order battery model is established based on lithium iron phosphate energy storage batteries, and its equation is as follows:

[0049] E = V b -I·Z (1)

[0050]

[0051] In the formula, E represents the terminal voltage of the lithium iron phosphate battery, V b Let Z represent an ideal voltage source, and let Z represent the internal resistance of a first-order battery model, which is composed of the battery's ohmic internal resistance R0 and the parallel resistance R that describes the battery's charging polarization process. p and parallel capacitor C p composition.

[0052] The neural network takes the current terminal voltage V, charging current I, and sampled value of the current state of charge (SOC) of the energy storage battery as input and outputs the internal resistance Z of the first-order battery model. The predicted SOC sampled value is determined using the E-SOC curve of the lithium iron phosphate battery, thereby completing the dynamic evaluation of the state of charge of the lithium iron phosphate battery.

[0053] The dynamic parameters that the neural network needs to identify mainly include the ohmic internal resistance R0 and the parallel resistance R p and parallel capacitor C p That is, the number of output layer nodes is 3 and the number of input layer nodes is also 3, thus determining the network architecture.

[0054] Standard current charge-discharge experiments were conducted on lithium iron phosphate batteries, and their E-SOC curves were obtained by combining polynomial fitting. Then, based on pulse charging, constant current, and constant voltage charging tests, energy storage battery charge-discharge training samples were constructed to train the neural model and continuously update the network parameters, ultimately achieving an accurate assessment of the SOC state of lithium iron phosphate energy storage batteries.

[0055] Figure 3 It is a multi-stage charging solution.

[0056] In step two, before starting charging, it is necessary to determine the initial MAS law charging curve. The MAS charging curve formula is:

[0057] I k =I1+I2+I3+... (3)

[0058] In the formula, I1, I2, and I3 are the acceptable charging currents accumulated at different times, and I k Let be the acceptable current at time k.

[0059] The acceptable starting current α of lithium iron phosphate batteries is calculated using formula (4), which is:

[0060]

[0061] In the formula, C f The discharge capacity of the lithium iron phosphate battery is given by α, where α is the acceptable current rate and I is the discharge capacity. s Initial charging current.

[0062] Among them, C can be directly determined based on the SOC of the lithium iron phosphate battery. f Based on the calculated initial current acceptable rate α, the initial charging current I is obtained by formula (4). s Use this current to charge the battery at a constant current until the state of charge (SOC) is greater than 10%.

[0063] In step three, to better mitigate the impact of polarization on the charging speed, the current acceptance rate α of the lithium iron phosphate battery can be increased, i.e., a negative pulse charging method can be used, setting t... F The pulse width is positive, t1 and t2 are the pre- and post-charge pause times, and t... R The negative pulse width refers to the charging process where charging stops before the negative pulse, discharging occurs during the negative pulse, and charging stops after the negative pulse. This brief pause in charging and discharging significantly reduces the polarization effect within the lithium iron phosphate battery, increasing charging speed and achieving fast charging. When the state of charge (SOC) is below 75%, the negative pulse charging method is used.

[0064] In step four, after the negative pulse charging reaches a SOC greater than 75%, in order to better suppress the impact of the internal polarization effect of the lithium iron phosphate battery on the charging speed, the charging mode is switched to MAS-pulse charging according to the MAS law. The positive and negative pulse charging stop times t1 and t2, and t... R The negative pulse width remains consistent with the negative pulse charging method described above, while the positive pulse magnitude varies with the charging curve according to MAS law. The formula for the positive pulse current is:

[0065] I F (t)=I F ·e -αt (5)

[0066] In the formula, I F (t) represents the positive pulse current.

[0067] According to MAS law, the gas evolution ΔG generated by the positive pulse during the time interval Δt is removed by an equal amount of negative pulse discharge. Therefore, the magnitude I of the negative pulse current can be determined. R (t), the formula for negative pulse current is:

[0068]

[0069] In step five, when the state of charge (SOC) of the lithium iron phosphate battery is greater than 90%, the pulse charging current has dropped to a very small value and cannot meet the charging requirements. Therefore, a constant voltage trickle charging method with adaptive current regulation is adopted, and the charging current I is based on the set rated current I. * Adaptive adjustment is used to avoid overcharging and damaging battery life. As the charging time increases, the charging current gradually decreases, and the state of charge (SOC) of the lithium iron phosphate battery tends to stabilize to reduce the heat generated by the lithium iron phosphate battery. This ensures stable changes in the internal chemical reaction of the lithium iron phosphate battery and guarantees charging safety.

[0070] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for optimizing the charging of rural power distribution network energy storage batteries based on battery SOC (State of Charge), characterized in that: Before charging the energy storage batteries in rural power distribution networks, the SOC estimation results of the batteries are checked, and a suitable charging scheme is selected according to different battery states. The charging scheme includes: When SOC≤10%, the optimal initial current is determined based on the battery's acceptable starting current for constant current charging. When 10% < SOC ≤ 75%, maintain a constant charging current and use a negative pulse charging method for charging. Specifically, charging is performed by stopping charging before the negative pulse, discharging during the negative pulse, and stopping charging after the negative pulse. When 75% < SOC ≤ 90%, charging is performed using the MAS-pulse charging method; When SOC > 90%, a constant voltage trickle charging method with adaptive current regulation is used for charging; The SOC estimation results of the tested battery specifically include: The first-order battery model equation for lithium iron phosphate energy storage batteries is as follows: (1) (2) In the formula, E This indicates the terminal voltage of a lithium iron phosphate battery. V b Let Z represent the ideal voltage source, and Z represent the internal resistance of the first-order battery model, which is determined by the ohmic internal resistance of the battery. R 0 and the parallel resistance describing the battery charging polarization process R p and parallel capacitors C p composition; A state-of-charge (SOC) assessment model for lithium iron phosphate batteries is established based on a recurrent neural network. The inputs of the SOC assessment model are the current terminal voltage V, charging current I, and the sampled value of the current SOC of the energy storage battery. The output is the internal resistance Z of the first-order battery model. The predicted SOC sampled value is determined using the E-SOC curve of the lithium iron phosphate battery, thereby completing the dynamic assessment of the SOC of the lithium iron phosphate battery. The state-of-charge assessment model for the lithium iron phosphate battery has 3 output layer nodes and 3 input layer nodes, corresponding to an ohmic internal resistance. R 0, parallel resistance R p and parallel capacitors C p ; Standard current charge-discharge experiments were conducted on lithium iron phosphate batteries, and their E-SOC curves were obtained by combining polynomial fitting. Then, based on pulse charging, constant current, and constant voltage charging tests, energy storage battery charge-discharge training samples were constructed, and a recurrent neural network was trained and the network parameters were continuously updated. Finally, a state of charge assessment model for lithium iron phosphate batteries was established to accurately assess the SOC state of lithium iron phosphate energy storage batteries. When 75% < SOC ≤ 90%, the MAS-pulse charging method is used for charging, specifically including: Based on the MAS law, the charging method is switched to MAS-pulse charging, where the positive and negative pulse pause times are... and as well as The negative pulse width is consistent with the setting used when employing the negative pulse charging method. The positive pulse magnitude varies with the charging curve according to the MAS law. The formula for the positive pulse current is: (5) In the formula, It is a positive pulse current; According to MAS law, the gas evolution produced by the positive pulse within a certain time period The magnitude of the negative pulse current is determined by removing it using an equal amount of negative pulse discharge. : (6)。 2. The method for optimizing charging of rural power distribution network energy storage batteries based on battery SOC state according to claim 1, characterized in that: The energy storage battery for the rural power distribution network is a lithium iron phosphate battery.

3. The method for optimizing the charging of rural power distribution network energy storage batteries based on battery SOC state according to claim 1, characterized in that: When SOC ≤ 10%, the optimal initial current is determined based on the battery's acceptable starting current for constant current charging, specifically including: First, determine the initial charging curve according to the MAS law. The formula for the MAS charging curve is: (3) In the formula, , , The acceptable charging current accumulated at different times. for Acceptable current at any given moment; Acceptable starting current of lithium iron phosphate batteries The formula for the acceptable rate of the starting current, obtained from formula (4), is as follows: (4) In the formula, This refers to the discharge capacity of lithium iron phosphate batteries. For current acceptable rate, Initial charging current; Determined directly based on the SOC of the lithium iron phosphate battery. Based on the calculated initial current acceptable rate Then, the initial charging current is obtained from formula (4). Use this current to charge the battery at a constant current until the state of charge (SOC) is greater than 10%.

4. The method for optimizing the charging of rural power distribution network energy storage batteries based on battery SOC state according to claim 1, characterized in that: When 10% < SOC ≤ 75%, a constant charging current is maintained, and charging is performed using a negative pulse charging method, specifically including: By increasing the current acceptance rate of lithium iron phosphate batteries The method involves using a negative pulse charging method and setting the positive pulse width. Before and after charging stop time and negative pulse width Charging stops before a negative pulse, discharging occurs during a negative pulse, and charging stops after a negative pulse.

5. The method for optimizing the charging of rural power distribution network energy storage batteries based on battery SOC state according to claim 1, characterized in that: When SOC > 90%, a constant voltage trickle charging method with adaptive current regulation is used for charging, and its charging current... According to the set rated current With adaptive adjustment, the charging current gradually decreases as the charging time increases, and the state of charge (SOC) of the lithium iron phosphate battery tends to stabilize.

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