CN-116598618-B - Rural distribution network energy storage battery charging optimization method based on battery SOC state

CN116598618BCN 116598618 BCN116598618 BCN 116598618BCN-116598618-B

Abstract

The invention relates to a rural distribution network energy storage battery charging optimization method based on a battery SOC state, which belongs to the field of battery optimization, and comprises the steps of detecting an SOC estimation result of a battery before charging the rural distribution network energy storage battery, selecting a proper charging scheme according to different states of the battery, wherein the charging scheme comprises the steps of determining the optimal initial current according to the initial current acceptable rate of the battery to perform constant current charging when the SOC is less than or equal to 10%, keeping the constant charging current when the SOC is less than or equal to 10%, charging by adopting a negative pulse charging method, specifically, stopping charging before negative pulse, discharging after the negative pulse, stopping charging, charging by adopting a MAS-pulse charging mode when the SOC is less than or equal to 90%, and charging by adopting a constant voltage trickle charging mode of current self-adaptive adjustment when the SOC is more than 90%. The charging efficiency is guaranteed, the safety is improved, the service life is prolonged, and the cost is reduced.

Inventors

YANG JIANWEI
XU LU
ZHAO ZHONGYONG
ZHOU QU
SHEN ZHAOXUAN
HUANG YU
SHI XIN
DENG FANGLIN

Assignees

国家电网有限公司
国网重庆市电力公司合川供电分公司
西南大学

Dates

Publication Date: 20260505
Application Date: 20221208

Claims (5)

1. The rural distribution network energy storage battery charging optimization method based on the battery SOC state is characterized by comprising the steps of detecting an SOC estimation result of a battery before the rural distribution network energy storage battery is charged, and selecting a proper charging scheme according to different states of the battery, wherein the charging scheme comprises the following steps: When the SOC is less than or equal to 10%, determining the optimal initial current according to the initial current acceptable rate of the battery to perform constant current charging; When the SOC is 10% < less than or equal to 75%, keeping constant charging current, and charging by adopting a negative pulse charging method, wherein the charging is stopped before the negative pulse, the charging is performed in a manner of discharging when the negative pulse is positioned, and the charging is stopped after the negative pulse; when 75% < SOC is less than or equal to 90%, charging by adopting a MAS-pulse charging mode; When the SOC is more than 90%, charging is carried out by adopting a constant-voltage trickle charging mode with current self-adaptive adjustment; the detecting the SOC estimation result of the battery specifically includes: the first-order battery model equation for constructing the lithium iron phosphate energy storage battery is as follows: (1) (2) wherein E represents the terminal voltage of the lithium iron phosphate battery, V b represents an ideal voltage source, Z represents the internal resistance of a first-order battery model, and the battery consists of an ohmic internal resistance R 0 of the battery, a parallel resistor R p describing the battery charging polarization process and a parallel capacitor C p ; Establishing a state of charge evaluation model of the lithium iron phosphate battery based on a cyclic neural network, wherein the input of the state of charge evaluation model of the lithium iron phosphate battery is a sampling value of terminal voltage V, charging current I and current state of charge SOC of a current energy storage battery, outputting the sampling value as an internal resistance Z of a first-order battery model, and determining a predicted SOC sampling value by utilizing an E-SOC curve of the lithium iron phosphate battery so as to finish dynamic evaluation of the state of charge of the lithium iron phosphate battery; The output layer node number of the charge state evaluation model of the lithium iron phosphate battery is 3, the input layer node number is also 3, and the input layer node number corresponds to the ohmic internal resistance R 0 , the parallel resistor R p and the parallel capacitor C p ; Carrying out standard current charge-discharge experiments on the lithium iron phosphate battery, combining polynomial fitting to obtain an E-SOC curve of the lithium iron phosphate battery, then constructing an energy storage battery charge-discharge training sample based on pulse charge, constant current and constant voltage charge tests, training a circulating neural network, continuously updating network parameters, finally establishing a charge state evaluation model of the lithium iron phosphate battery, and accurately evaluating the SOC state of the lithium iron phosphate energy storage battery; When 75% < SOC is less than or equal to 90%, charging is performed by adopting a MAS-pulse charging mode, and the method specifically comprises the following steps: switching the charging mode into MAS-pulse charging according to MAS law, wherein the positive and negative pulse charging stopping time And And The negative pulse width is consistent with the setting when adopting a negative pulse charging method, the positive pulse size is changed along with the change of a charging curve of MAS law, and the positive pulse current formula is as follows: (5) In the formula, Is a forward pulse current; gassing by positive pulses in accordance with MAS law during time Determining the magnitude of the undershoot current by equivalent undershoot discharge removal : (6)。
2. The rural power distribution network energy storage battery charging optimization method based on the battery SOC state of claim 1 is characterized in that the rural power distribution network energy storage battery is a lithium iron phosphate battery.
3. The rural power distribution network energy storage battery charging optimization method based on the battery SOC state of claim 1, wherein when the SOC is less than or equal to 10%, determining the optimal initial current according to the initial current acceptance rate of the battery to perform constant current charging, and specifically comprising the following steps: first, determining an initial MAS law charging curve, MAS charging curve formula (3) In the formula, 、、 For acceptable charging currents to accumulate at different times, Is that Acceptable current at time; Initial current acceptability of lithium iron phosphate battery Calculated by the formula (4), the initial current acceptable rate formula is (4) In the formula, Is the discharge capacity of the lithium iron phosphate battery, In order for the current to be acceptable, Initiating a charging current; direct determination of SOC from lithium iron phosphate battery According to the calculated initial current acceptability Obtaining initial charging current from formula (4) The current is used for constant current charging until the SOC is more than 10%.
4. The rural power distribution network energy storage battery charging optimization method based on the battery SOC state of claim 1, wherein when the SOC is less than or equal to 75% in 10% < SOC, constant charging current is maintained, and a negative pulse charging method is adopted for charging, and the method specifically comprises the following steps: increasing current acceptance rate of lithium iron phosphate battery In the mode of (1), namely adopting a negative pulse charging method to set positive pulse width Front and back stop time And Negative pulse width And stopping charging before the negative pulse, discharging when the negative pulse is generated, and stopping charging after the negative pulse is generated.
5. The method for optimizing rural power distribution network energy storage battery charging based on battery SOC according to claim 1, wherein when SOC is more than 90%, charging is performed by adopting a constant-voltage trickle charging mode with current self-adaptive regulation, and charging current is equal to or greater than 90% According to the set rated current And (3) self-adaptive adjustment, wherein as the charging time is increased, the charging current is gradually reduced, and the state of charge (SOC) value of the lithium iron phosphate battery is stable.

Description

Rural distribution network energy storage battery charging optimization method based on battery SOC state Technical Field The invention belongs to the field of battery optimization, and relates to a rural distribution network energy storage battery charging optimization method based on a battery SOC state. Background At present, for remote rural areas, the power distribution network has the problems of high load growth, long line, low voltage, high loss and the like, so that the power quality is seriously affected, the existing power supply is mainly based on a terminal power supply mode with a distribution network transformer as a core, and because the number of households in the remote rural areas is small, the households are easy to run off, the capacity of the distribution network transformer is easy to be excessively redundant due to the existing traditional power supply mode, the construction cost of a power grid company is too high, and the development of a novel power supply mode is significant for the economic construction of rural distribution networks. The novel rural distribution network electric energy supply based on the high-capacity lithium iron phosphate energy storage battery is a novel scheme with great innovation and development potential, and the scheme can realize energy storage and charging in a load low-peak period and discharging in the load peak period through the regulation and control of the device, realize the functions of active compensation and reactive compensation at the tail end of a rural distribution network line, is beneficial to interaction of source-network-charge-storage, and reduces the energy consumption cost and the equipment investment cost of a power grid system. However, the state of charge (SOC) of the lithium iron phosphate battery is an important parameter in the lithium iron phosphate battery management system, and the accuracy is the basis of charge and discharge monitoring and optimal management of the lithium iron phosphate battery. The polarization reaction in the charging process of the lithium iron phosphate battery can reduce the charging speed of the lithium iron phosphate battery, and the traditional rapid charging method can improve the charging speed of the lithium iron phosphate battery to a certain extent, but has larger damage to the lithium iron phosphate battery and easily causes potential safety hazard. Disclosure of Invention Therefore, the invention aims to provide a lithium iron phosphate battery charging optimization strategy based on the SOC state of the lithium iron phosphate battery, so as to weaken polarization reaction of the lithium iron phosphate battery in the charging process, effectively reduce charging time and improve charging safety and reliability. In order to achieve the above purpose, the present invention provides the following technical solutions: The utility model provides a rural distribution network energy storage battery charge optimization method based on battery SOC state, before rural distribution network energy storage battery charges, detects the SOC estimation result of battery, selects suitable charging scheme according to battery different states, the charging scheme includes: When the SOC is less than or equal to 10%, determining the optimal initial current according to the initial current acceptable rate of the battery to perform constant current charging; When the SOC is 10% < less than or equal to 75%, keeping constant charging current, and charging by adopting a negative pulse charging method, wherein the charging is stopped before the negative pulse, the charging is performed in a manner of discharging when the negative pulse is positioned, and the charging is stopped after the negative pulse; when 75% < SOC is less than or equal to 90%, charging by adopting a MAS-pulse charging mode; When the SOC is more than 90%, the constant-voltage trickle charging mode with current self-adaptive adjustment is adopted for charging. Further, the rural distribution network energy storage battery is a lithium iron phosphate battery. Further, the detecting the SOC estimation result of the battery specifically includes: the first-order battery model equation for constructing the lithium iron phosphate energy storage battery is as follows: E=Vb-I·Z (1) wherein E represents the terminal voltage of the lithium iron phosphate battery, V b represents an ideal voltage source, Z represents the internal resistance of a first-order battery model, and the battery consists of an ohmic internal resistance R 0 of the battery, a parallel resistor R p describing the battery charging polarization process and a parallel capacitor C p; Establishing a state of charge evaluation model of the lithium iron phosphate battery based on a cyclic neural network, wherein the input of the state of charge evaluation model of the lithium iron phosphate battery is a sampling value of terminal voltage V, charging current I and current state of charge S