An interconnected multi-micronet energy storage unit (soc) dynamic balancing speed control method and system

Abstract

The application relates to a kind of interconnection multi-micronet energy storage unit SOC dynamic equalization speed control method and system, according to the state characteristic quantity of multi-micronet energy storage unit, establish fuzzy rule control table, dynamically adjust the equalization factor of each energy storage unit, through dynamic equalization factor fuzzy control power function, update droop coefficient, based on droop control technology, adjust the output voltage of each energy storage unit, so that each energy storage unit SOC level tends to be equal, the state characteristic quantity of the multi-micronet energy storage unit includes power margin, equalization degree and battery temperature.Compared with prior art, the application further accelerates the equalization speed by using the higher power margin and bus voltage low fluctuation possessed by energy storage unit under light load.

Description

Technical Field

[0001] This invention belongs to the field of energy storage control technology for interconnected multi-microgrid systems, and in particular relates to a dynamic balancing speed control method and system for the SOC of interconnected multi-microgrid energy storage units. Background Technology

[0002] With the introduction of the "dual-carbon strategy" and the further maturation of new energy control technologies, traditional AC power grids are facing a surge in small-capacity, decentralized distributed photovoltaic (PV) grid integration. Microgrids are small-scale power generation and distribution systems composed of distributed power sources, energy storage devices, loads, distribution facilities, monitoring and protection devices, etc. Due to the randomness, intermittency, and volatility of renewable energy generation, these characteristics will cause serious power quality problems as the penetration rate of renewable energy generation continues to increase. Individual microgrids suffer from poor disturbance rejection capabilities, limited operating capacity, and lack of backup power; fluctuation mitigation and capacity compensation for a single microgrid still rely on the main grid. Multi-microgrids, as an extension and functional expansion of the single microgrid structure, can improve the renewable energy absorption capacity by operating multiple sub-microgrids in a cluster. Off-grid multi-microgrid operation is an effective way to improve the reliability of power supply at the end of distribution networks in remote mountainous areas, island regions, and even cities.

[0003] Currently, in multi-microgrid interconnected systems, each energy storage unit operates independently, making it difficult to effectively expand the system's backup capacity through clustering. In some interconnected scenarios, remote power supply can effectively increase the overall energy storage capacity. Multi-energy storage cluster power supply can utilize SOC (State of Charge) balancing control to prevent some energy storage units from overcharging or over-discharging and prematurely disconnecting. However, different energy storage units have different states of charge, and the SOC balancing speed among multiple energy storage units is set too conservatively due to the maximum fluctuation of the bus voltage. Chinese patent CN113097992B discloses a droop control method for DC microgrids, which adjusts the droop coefficient in real time based on the current state of charge of each energy storage unit, ultimately balancing the state of charge of each unit and avoiding overcharging, over-discharging, and imbalanced state of charge. While this method controls bus voltage fluctuations to a high level of stability, it requires a significant amount of time to reach equilibrium and is prone to convergence difficulties when the equilibrium is high. Chinese patent CN109687490B discloses a variable adjustment factor SOC droop control method for distributed energy storage systems. Although this method aims to maximize the equalization speed of energy storage units through variable equalization factor control, it ignores the problem caused by the continuous high power output of some energy storage units with high SOC deviation. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art by providing a dynamic balancing speed control method and system for interconnected multi-microgrid energy storage units (SOCs), which further accelerates the balancing speed by utilizing the higher power margin of the energy storage unit and the low fluctuation of the bus voltage under light load.

[0005] The objective of this invention can be achieved through the following technical solutions:

[0006] A dynamic balancing speed control method for the State of Charge (SOC) of interconnected multi-microgrid energy storage units is proposed. This method establishes a fuzzy rule control table based on the state characteristics of the multi-microgrid energy storage units, dynamically adjusts the balancing factor of each energy storage unit, updates the droop coefficient through a fuzzy control power function of the dynamic balancing factor, and adjusts the output voltage of each energy storage unit based on droop control technology to achieve a more balanced SOC level. The state characteristics of the multi-microgrid energy storage units include power margin, balancing degree, and battery temperature.

[0007] Furthermore, in the fuzzy rule control table, different state characteristic quantities of multi-microgrid energy storage units have a unique corresponding equilibrium factor.

[0008] Furthermore, the dynamic equilibrium factor fuzzy control power function The expression is:

[0009]

[0010] Where, N i i is the equilibrium factor. h For the energy storage unit output current, SOC avg Let k be the average SOC of all energy storage units. i This indicates the battery energy storage switching state.

[0011] Furthermore, the droop coefficient is R. i Its update formula is:

[0012]

[0013] Where R 0i C is the initial droop coefficient. sum For the overall capacity of all energy storage units, C i Let i be the capacity of energy storage unit i. It is a fuzzy control power function for dynamic equilibrium factors.

[0014] Furthermore, the expression for the droop control is:

[0015] u hi =-R i i hi +V ref +ΔV li +ΔVi ,

[0016] Where u hi R is the output voltage of energy storage unit i. i V is the droop coefficient. ref The rated voltage of the common DC bus, ΔV li The line resistance compensation voltage is ΔV. i This is the secondary compensation amount for the bus voltage.

[0017] Furthermore, the line resistance compensation voltage ΔV li The calculation formula is as follows:

[0018]

[0019] Among them, K P1 and K I1 Where S is the PI control constant, and i is the transfer function factor. hi ′ represents the ideal output current of energy storage unit i, i hi is the actual current of energy storage unit i.

[0020] Furthermore, the secondary compensation amount ΔV of the bus voltage i The calculation formula is as follows:

[0021]

[0022] Among them, K P2 and K I2 This is the PI control constant.

[0023] Furthermore, the power margin is P. s The calculation formula is:

[0024]

[0025] Where P cmax and P dmax These are the maximum charge and discharge smoothing power, P sum This is the net load power.

[0026] Furthermore, the balance degree is denoted as D, and the SOC standard deviation of each microgrid energy storage unit is used to describe the balance effect. The calculation formula is as follows:

[0027]

[0028] Where k i This refers to the battery energy storage switching state, SOC. avg The SOC is the average value of all microgrid energy storage units. i Let be the SOC value of energy storage unit i.

[0029] The present invention also provides a dynamic balancing speed control system for interconnected multi-microgrid energy storage unit (SOC), including a communication control subsystem and multiple interconnected microgrids;

[0030] The communication control subsystem is used to obtain the state characteristics of multiple microgrid energy storage units from the interconnected microgrid, establish a fuzzy rule control table based on the state characteristics of the multiple microgrid energy storage units, dynamically adjust the balance factor of each energy storage unit, update the droop coefficient in the interconnected microgrid through the fuzzy control power function of the dynamic balance factor, and adjust the output voltage of each energy storage unit so that the SOC level of each energy storage unit tends to be balanced. The state characteristics of the multiple microgrid energy storage units include power margin, balance degree and battery temperature.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] 1. This invention, based on traditional SOC equalization control of interconnected multi-microgrid energy storage units, introduces state characteristic quantities of multi-microgrid energy storage units, including power margin, equalization degree, and battery temperature. A fuzzy rule control table is established based on these state characteristic quantities to dynamically adjust the equalization factor of each energy storage unit. The droop coefficient is updated using a fuzzy control power function based on the dynamic equalization factor. Based on droop control technology, the output voltage of each energy storage unit is adjusted to make the SOC level of each energy storage unit tend towards equalization. This invention utilizes the power margin under light load to further accelerate the SOC equalization speed, greatly improving the SOC equalization degree of each microgrid energy storage unit. It can effectively avoid overcharging and over-discharging of energy storage units and the resulting premature shutdown of energy storage batteries, leading to a reduction in the overall system smoothing power. This effectively extends battery life, enhances the smoothing capability of the interconnected system, and maintains the safe and stable operation of the multi-microgrid interconnected system.

[0033] 2. This invention incorporates line resistance compensation control and secondary voltage bus compensation control into the droop control, which can effectively offset the influence of line resistance in each microgrid and maintain the bus voltage stable at the rated voltage. Based on the droop control, this invention adds SOC equalization control, which enables energy storage units with high SOC average deviation to output more power and energy storage units with low deviation to output less power, so that the SOC of energy storage units in each microgrid is consistent.

[0034] 3. When the central control fails, i.e. there is no communication between microgrids, the SOC dynamic balancing speed control fails, and the multi-microgrid system automatically reverts to the original droop control. The basic droop control does not require communication between the multi-microgrids to maintain system stability and can still maintain the original bus voltage balance. Therefore, in the event of communication link failure or maintenance, the control method of this invention can still maintain the normal interconnection and operation of the multi-microgrid system, without affecting bus voltage fluctuations and power smoothing. It only stops the SOC dynamic balancing of the energy storage units. Overcharged and over-discharged energy storage units can still be switched on and off through the microgrid local energy storage unit detection unit and DC reclosing. Attached Figure Description

[0035] Figure 1 This is a schematic diagram of the communication and circuit topology of the control system of the present invention;

[0036] Figure 2 This is a schematic diagram of the converter control structure and equivalent model.

[0037] Where R li Indicates the resistance of the interconnection line and node between the energy storage unit and the DC bus, u hi and i hi P represents the output voltage and current of the energy storage unit. sum V is the equivalent net load power. ref R is the rated voltage of the DC bus. load i is the net load equivalent resistance. pv The current is the equivalent input bus current on the generator side;

[0038] Figure 3 This is a schematic diagram of the control method of the present invention.

[0039] Among them, P s Where D is the power margin, T is the battery balance, and C is the battery temperature. i V represents the capacity of energy storage unit i. ref Rated voltage of common DC bus, SOC i Let u be the SOC value of energy storage unit i. hi and i hi These represent the output voltage and current of the energy storage unit, respectively, R i ΔV is the droop coefficient. li The line resistance compensation voltage is ΔV. i N is the secondary compensation amount for bus voltage. i As a dynamic equilibrium factor;

[0040] Figure 4 This is a schematic diagram of a fuzzy rule control function;

[0041] Figure 5 This is a schematic diagram verifying the convergence effect of multiple microgrid energy storage units, where P sum Net load power;

[0042] Figure 6 A comparison chart of SOC changes in step experiments with light and heavy loads;

[0043] Figure 7 This is a comparison chart of the power and equalization of high-temperature energy storage units.

[0044] Where P bat1 P bat2 P bat3 P bat4 and P bat5These represent the power of energy storage units 1, 2, 3, 4, and 5, respectively. Detailed Implementation

[0045] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. These embodiments are based on the technical solution of the present invention and provide detailed implementation methods and specific operating procedures. However, the scope of protection of the present invention is not limited to the following embodiments.

[0046] This embodiment provides a method for dynamic balancing speed control of the SOC of interconnected multi-microgrid energy storage units, such as... Figure 1 As shown, each microgrid energy storage unit is connected to a common DC bus via a droop-controlled bidirectional DC-DC converter to mitigate bus voltage fluctuations caused by uneven source-load distribution among multiple microgrids. Based on traditional droop control, line resistance compensation control and secondary voltage bus compensation control are added, ΔV li and ΔV i These are the line resistance compensation voltage and the secondary compensation amount for the bus voltage, respectively; simultaneously, SOC equalization control is added by identifying the state characteristics of multiple microgrid energy storage units, including the power margin P. s The balance factor N in the SOC balance control is dynamically adjusted using fuzzy control, taking into account the balance degree D and the battery temperature T. i This allows for adjustment of the droop coefficient R. i This enables control of the output voltage of each energy storage unit.

[0047] The specific process is as follows:

[0048] Traditional droop control works by changing the virtual resistance R. i To achieve the goal of changing the output voltage of the energy storage unit, its droop expression is as follows:

[0049] u hi =-R i i hi +V ref (1)

[0050] Where u hi and i hi These are the output voltage and current of the energy storage unit, V. ref R is the rated voltage of the DC bus. i The droop coefficient is determined by changing the droop coefficient R. i Change the output voltage of the energy storage unit.

[0051] To ensure the stability and accuracy of the bus voltage, this invention incorporates line resistance compensation control and secondary voltage bus compensation control. To achieve the line resistance compensation, a line resistance compensation current i is introduced. hi The line resistance compensation current is given based on empirical values ​​for multi-microgrid interconnection to offset the line resistance on the power connection lines. This is achieved through a reference voltage ΔV. liThe compensation offsets the line resistance R. li The effect on the denominator, the line resistance compensation voltage ΔV li for:

[0052]

[0053] Among them, K P1 and K I1 Where S is the PI control constant, and i is the transfer function factor. hi ′ represents the ideal output current of each unit, i hi i represents the actual current of each unit. hi ′-i hi The deviation value between the ideal output current and the actual current of each unit is the control value, and the ideal output current i of each unit is... hi 'for:

[0054]

[0055] Line resistance compensation causes the energy storage unit to output current i hi According to the droop control coefficient R i The inverse proportional output effectively offsets the influence of the line resistance of each microgrid. However, the addition of the line resistance compensation voltage causes the bus voltage to deviate from the reference value in actual control. Therefore, a secondary compensation amount ΔV for the bus voltage is introduced. i :

[0056]

[0057] Among them, K P2 and K I2 This is the PI control constant.

[0058] After compensation by formula (2), the droop control expression for the interconnected multi-microgrid energy storage system is:

[0059] u hi =-R i i hi +V ref +ΔV li +ΔV i (3)

[0060] With the above-mentioned improved control, while maintaining the bus voltage stable at the rated voltage, each energy storage unit can be controlled by the droop coefficient R. i Ideal current i hi ′。 Compensated droop coefficient R i The SOC (State of Charge) value of energy storage unit i i rate of change The relationship is:

[0061]

[0062] Based on this, a dynamic equilibrium factor fuzzy control power function is introduced. Its expression is:

[0063]

[0064] Where, N i i is the dynamic equilibrium factor. h For converter output current, SOC avg Let k be the average SOC of multiple energy storage units. i This indicates the battery energy storage switching state; a value of 0 indicates the energy storage unit is switched off, and a value of 1 indicates it is switched on.

[0065]

[0066] Update the droop coefficient R using the above formula. i Its expression is:

[0067]

[0068] Where C sum For the overall energy storage capacity of the interconnected multi-microgrid energy storage system, C i Let i be the capacity of energy storage unit i, and the ratio of the two. R is used to homogenize the capacity of each energy storage unit. 0i Let S be the initial droop coefficient. From equations (5) and (7), it can be seen that during discharge, if the SOC value of energy storage unit i is SOC... i Higher than the average SOC of multiple energy storage units avg If the energy storage unit discharges more to reduce the SOC value, then the SOC value of energy storage unit i is... i Lower than the average SOC of multiple energy storage units avg If the energy storage unit discharges less, the opposite will happen during charging. Through the control loop of equations (5)-(7), as charging and discharging proceed, the SOC value of each microgrid energy storage unit gradually approaches the average value, and finally achieves balance.

[0069] Since the aforementioned SOC balancing control cannot increase or decrease the balancing speed based on load conditions, variable factor balancing control is introduced to address this issue by adjusting the balancing factor N. i The value is used to increase or decrease the SOC resolution of each microgrid, and to increase or decrease the droop coefficient difference, thereby accelerating or slowing down the balancing speed of multiple energy storage units. To describe load and energy storage state variables, state characteristic variables of multiple microgrid energy storage units are introduced, including power margin P. s Balance D and battery temperature T:

[0070]

[0071]

[0072] Where P cmax P dmax These represent the maximum charge / discharge smoothing power, P sum The net load power is used, and the balance degree D uses the standard deviation of the SOC of each microgrid energy storage unit to describe the balance effect.

[0073] Based on the above three indicators, a fuzzy rule control table is established as shown in Table 1, which is used to select a reasonable equilibrium factor N. i The corresponding fuzzy rule control function is as follows: Figure 4 As shown, it should be noted that the fuzzy rules in the table only refer to the relationship of change, and different parameters should be set for actual application in different systems.

[0074] Table 1 Fuzzy Rule Control Table

[0075]

[0076] Based on the above analysis, simulation experiments were set up. The variable-factor SOC equalization control based on fuzzy control of this invention was used as the experimental group, and the constant equalization factor control was used as the control group. The results of the multi-microgrid energy storage unit convergence performance verification experiment are as follows: Figure 5 As shown, the artificially set net load power P sum Used to simulate the load changes of multiple microgrids under large-scale power fluctuations, it is easy to see from the image that the present invention has a high convergence speed. In particular, it is worth noting that the present invention specifically improves the balancing efficiency under light load, that is, the slope (absolute value) of the curve is higher under light load.

[0077] The comparison graph of SOC changes in step experiments with light and heavy loads is shown below. Figure 6 As shown, the experimental group, i.e., the present invention, exhibits faster and better convergence. Furthermore, the inclusion of a temperature measurement module in this invention effectively prevents overheating issues in some high-power batteries, increasing the practicality of the SOC module. Figure 7 As shown, the energy storage unit 1 reaches a high temperature at 2200s. The experimental group uses high-temperature control for energy storage, while the control group does not use high-temperature control. It can be observed that the power of the energy storage unit 1 that reaches a high temperature is effectively reduced after the control described in this invention. As a result, the equalization degree is also reduced. That is, the equalization speed is effectively reduced by the control described in this invention.

[0078] In another embodiment, a dynamic balancing speed control system for interconnected multi-microgrid energy storage unit (SOC) is also provided, such as... Figure 1 As shown, it includes a communication control system and multiple interconnected microgrids. Each interconnected microgrid contains at least one energy storage unit and is connected to a common DC bus via a bidirectional DC-DC converter, enabling droop control including SOC equalization control.

[0079] The communication control subsystem is used to obtain the state characteristics of multiple microgrid energy storage units from the interconnected microgrid, establish a fuzzy rule control table based on the state characteristics of the multiple microgrid energy storage units, dynamically adjust the balance factor of each energy storage unit, update the droop coefficient in the interconnected microgrid through the fuzzy control power function of the dynamic balance factor, and adjust the output voltage of each energy storage unit so that the SOC level of each energy storage unit tends to be balanced. The state characteristics of the multiple microgrid energy storage units include power margin, balance degree and battery temperature.

[0080] Furthermore, each microgrid includes at least one power generation unit, such as a wind turbine system or a photovoltaic panel system (including MPPT). Each microgrid also has a certain amount of DC-AC load energy storage units, which are connected to the common DC bus through a bidirectional DC-DC converter with a certain voltage boosting function under PWM control and can transmit power bidirectionally. The common DC bus uses the voltage and current detection module in the communication control system to analyze the bus voltage fluctuation under the influence of power of each microgrid in real time. The communication control system also has temperature monitoring and circuit breakers to prevent overheating, overcharging and over-discharging.

[0081] To reduce computational load, it can be done through Figure 2 The simplified model shown illustrates the setup for the bidirectional DC-DC converter. Where R... li Indicates the resistance of the interconnection line and node between the energy storage unit and the DC bus, u hi and i hi P represents the output node voltage and current of the bidirectional DC-DC converter. sum V is the equivalent net load power. ref R is the rated voltage of the DC bus. load i is the net load equivalent resistance. pv This represents the current at the equivalent input bus on the generation side. In the simplified model, it is represented by the equivalent net load power R. sum Instead of the sum of power transmitted from each microgrid to the DC bus, this invention changes the net load equivalent resistance R. load and the current i of the equivalent input bus on the generator side pv To simulate the dynamic changes of multi-microgrid load and generator end.

[0082] Specifically, basic droop control maintains system stability without communication between microgrids, while variable factor SOC balancing control requires constant monitoring of the state characteristics of the energy storage units in the multi-microgrid system, including power margin, balance degree, and battery temperature, relying on the system's centralized control and communication transmission modules. When the centralized control fails, there is no communication between microgrids, so SOC balancing control fails, and the multi-microgrid system automatically reverts to the original droop control, still maintaining the original bus voltage balance. The control strategy can maintain normal interconnected operation of the multi-microgrid system even during communication link failures or maintenance, without affecting bus voltage fluctuations or power smoothing; it only stops the SOC balancing of the energy storage units. Overcharged or over-discharged energy storage units can still be switched on and off through the microgrid's local energy storage unit detection unit and DC reclosing.

[0083] Preferably, communication equipment and its power supply are installed, and signal links and interconnection system communication methods are set up. There are no restrictions on wireless or wired communication methods. In order to ensure the SOC balancing effect and bus voltage stability, communication speed and accuracy should be prioritized within the cost range.

[0084] Preferably, a bidirectional DC-DC converter with sufficient heat dissipation is installed. The circuit topology of the bidirectional DC-DC converter and whether it adopts the form of an isolation circuit depend on the voltage of each microgrid energy storage unit and the voltage of the common bus. The bidirectional DC-DC converter control system can be controlled by the method described in this invention.

[0085] The above description of the embodiments is provided to enable those skilled in the art to understand and use the invention. It will be apparent to those skilled in the art that various modifications can be made to these embodiments, and the general principles described herein can be applied to other embodiments without inventive effort. Therefore, the present invention is not limited to the above embodiments, and any improvements and modifications made by those skilled in the art based on the disclosure of the present invention without departing from the scope of the invention should be within the protection scope of the present invention.

Claims

1. A method for dynamic balancing speed control of a multi-microgrid energy storage unit's State of Charge (SOC), characterized in that, A fuzzy rule control table is established based on the state characteristics of the multi-microgrid energy storage units. The balance factor of each energy storage unit is dynamically adjusted. The droop coefficient is updated by the fuzzy control power function of the dynamic balance factor. Based on the droop control technology, the output voltage of each energy storage unit is adjusted so that the SOC level of each energy storage unit tends to be balanced. The state characteristics of the multi-microgrid energy storage units include power margin, balance degree and battery temperature. The dynamic equilibrium factor fuzzy control power function The expression is: ， in, As a balance factor, For all energy storage units mean For energy storage units ; output current; The droop coefficient is Its update formula is: ， in This is the initial droop coefficient. For the total capacity of all energy storage units, For energy storage units capacity, It is a fuzzy control power function for dynamic equilibrium factors.

2. The method for dynamic balancing speed control of SOC in an interconnected multi-microgrid energy storage unit according to claim 1, characterized in that, In the fuzzy rule control table, different state characteristic quantities of multi-microgrid energy storage units have a unique corresponding equilibrium factor.

3. The method for dynamic balancing speed control of SOC in interconnected multi-microgrid energy storage units according to claim 1, characterized in that, The expression for the droop control is: ， in For energy storage units The output voltage, The droop coefficient is... The rated voltage of the common DC bus. This is the line resistance compensation voltage. This is the secondary compensation amount for the bus voltage.

4. The method for dynamic balancing speed control of SOC in an interconnected multi-microgrid energy storage unit according to claim 3, characterized in that, The line resistance compensation voltage The calculation formula is as follows: ， in, and The PI control constant is For the transfer function factor, For energy storage units Ideal output current.

5. The method for dynamic balancing speed control of SOC in an interconnected multi-microgrid energy storage unit according to claim 3, characterized in that, The secondary compensation amount of the bus voltage The calculation formula is as follows: ， in, and This is the PI control constant.

6. The method for dynamic balancing speed control of SOC in interconnected multi-microgrid energy storage units according to claim 1, characterized in that, The power margin is The calculation formula is: ， in and These are the maximum charge and discharge smoothing power, respectively. This is the net load power.

7. The method for dynamic balancing speed control of SOC in interconnected multi-microgrid energy storage units according to claim 1, characterized in that, The degree of balance is Each microgrid energy storage unit is used Standard deviation describes the effect of equilibrium and is calculated using the following formula: ， in This is the battery energy storage switching state. The SOC is the average value of all microgrid energy storage units. For energy storage units The SOC value.

8. A dynamic balancing speed control system for interconnected multi-microgrid energy storage units (SOCs), characterized in that, Includes a communication control subsystem and multiple interconnected microgrids; The communication control subsystem is used to obtain the state characteristic quantities of multiple microgrid energy storage units from the interconnected microgrid, establish a fuzzy rule control table based on the state characteristic quantities of the multiple microgrid energy storage units, dynamically adjust the balance factor of each energy storage unit, update the droop coefficient in the interconnected microgrid through the fuzzy control power function of the dynamic balance factor, and adjust the output voltage of each energy storage unit so that the SOC level of each energy storage unit tends to be balanced. The state characteristic quantities of the multiple microgrid energy storage units include power margin, balance degree and battery temperature. The dynamic equilibrium factor fuzzy control power function The expression is: ， in, As a balance factor, For all energy storage units mean For energy storage units ; output current; The droop coefficient is Its update formula is: ， in This is the initial droop coefficient. For the total capacity of all energy storage units, For energy storage units capacity, It is a fuzzy control power function for dynamic equilibrium factors.

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