An adaptive power distribution method for hybrid energy storage of optical storage and charging DC microgrid

Abstract

The application discloses a kind of light storage and charging direct current microgrid hybrid energy storage adaptive power distribution methods, including the construction of photovoltaic power generation, battery and super capacitor of light storage and charging direct current microgrid system;Collect operating parameters and calculate power imbalance;Bus disturbance evaluation quantity including bus voltage deviation, voltage change rate and power imbalance change rate is constructed and disturbance state is judged;Low-pass filtering is carried out to power imbalance to realize high-low frequency power initial distribution;According to bus voltage deviation and state of charge, reference power is dynamically corrected;The amplitude limiting of battery reference current change rate is carried out, and the power difference of the amplitude limiting is transferred to super capacitor;After bus stabilization, super capacitor state of charge is recovered control.The application unifies disturbance evaluation, high-low frequency distribution, state of charge correction, current amplitude limiting compensation and state of charge recovery into the same control process, which can improve bus voltage stability and reduce battery current impact.

Description

Technical Field

[0001] This invention relates to the field of energy management and bus voltage of photovoltaic-storage-charging DC microgrids, and in particular to an adaptive power allocation method for hybrid energy storage in photovoltaic-storage-charging DC microgrids. Background Technology

[0002] In integrated photovoltaic-storage-charging DC microgrids, photovoltaic power generation units are typically connected to a common DC bus via photovoltaic DC / DC converters. Electric vehicle charging loads are powered by the DC bus, while batteries and supercapacitors exchange energy with the DC bus through bidirectional DC / DC converters. This type of system reduces multi-stage AC / DC conversion links, improves the local absorption capacity of renewable energy, and is suitable for scenarios such as charging stations, park microgrids, service area charging facilities, and distributed energy access.

[0003] Because photovoltaic output power is subject to random fluctuations due to the influence of light intensity, temperature and shading conditions, and electric vehicle charging load is characterized by uncertain connection time, rapid power changes and obvious load abrupt changes, when photovoltaic output decreases or charging load suddenly increases, the DC bus is prone to voltage drop; when photovoltaic output increases or charging load decreases, the DC bus is prone to voltage rise.

[0004] Existing photovoltaic-storage-charging control methods include schemes based on hierarchical coordinated control, reinforcement learning, master-slave energy storage power tracking, segmented bus voltage control, and high- and low-frequency power sharing. These schemes can stabilize the bus voltage to a certain extent, but most methods focus on power balance or bus voltage amplitude judgment, and do not adequately consider the coupling between the rate of change of bus disturbance, the rate of change of power imbalance, and the constraint of sudden changes in battery current.

[0005] Existing technologies typically use the magnitude of bus voltage deviation as the primary basis for judging the disturbance state, lacking a comprehensive evaluation of the bus voltage change rate and the power imbalance change rate. This results in the system not being able to identify the severity of the disturbance in a timely manner during the initial stages of load changes or rapid photovoltaic fluctuations.

[0006] Existing hybrid energy storage methods often adopt the idea of ​​"low-frequency power is handled by batteries and high-frequency power is handled by supercapacitors". However, when only high and low frequency power is decomposed, the rate of change of the battery reference current cannot be directly constrained, and the battery may still be subjected to large current surges.

[0007] When the reference power or reference current of the battery changes rapidly, the existing methods lack a clear control mechanism to transfer the power difference that the battery cannot immediately bear due to the limiting to the supercapacitor. Therefore, it is difficult to simultaneously ensure the stability of the bus voltage and the smoothness of the battery current.

[0008] Furthermore, after repeatedly handling transient power, the SOC of a supercapacitor may deviate from the target range. If SOC recovery control is not implemented after the bus stabilizes, the supercapacitor's ability to quickly support the next load surge or photovoltaic fluctuation will be reduced. Therefore, an adaptive power allocation method for a hybrid photovoltaic-storage-charging DC microgrid is needed to address these issues. Summary of the Invention

[0009] The technical problem to be solved by this invention is to provide an adaptive power allocation method for hybrid energy storage in a photovoltaic-storage-charging DC microgrid. This method aims to overcome the problems in existing hybrid energy storage control systems, such as single disturbance identification, large battery current surges, easy deviation of supercapacitor state of charge from the target range, and lack of limiting differential compensation mechanism for high and low frequency allocation. This method unifies bus disturbance evaluation, high and low frequency power allocation, state of charge correction, battery current change rate limiting compensation, and supercapacitor state of charge recovery into a single control process to achieve stable bus voltage and smooth battery current.

[0010] To achieve the above technical solution, the technical solution adopted by the present invention is as follows: An adaptive power allocation method for hybrid energy storage in a photovoltaic-storage-charging DC microgrid includes the following steps: S1, construct a photovoltaic-storage-charging DC microgrid hybrid energy storage system. The system includes photovoltaic power generation units, photovoltaic DC / DC converters, a common DC bus, DC bus capacitors, electric vehicle charging loads, battery energy storage units, battery-side bidirectional DC / DC converters, supercapacitor energy storage units, supercapacitor-side bidirectional DC / DC converters, and an energy management and adaptive power distribution control unit. The photovoltaic power generation units are connected to the DC bus via photovoltaic DC / DC converters, the battery energy storage units are bidirectionally connected to the DC bus via battery-side bidirectional DC / DC converters, the supercapacitor energy storage units are bidirectionally connected to the DC bus via supercapacitor-side bidirectional DC / DC converters, and the electric vehicle charging loads draw power from the DC bus. S2, Collect operating parameters and calculate system power imbalance. , For photovoltaic output power, The charging load power for electric vehicles; S3, Construct bus disturbance evaluation quantity And determine the disturbance state, based on The magnitude of the disturbance determines the system state into steady state, small disturbance, general disturbance, and load or photovoltaic sudden change state. S4, for power imbalance Perform initial high- and low-frequency power allocation, and obtain the low-frequency continuous power component to be supplied by the battery through low-pass filtering. and the remaining high-frequency components Distributed to supercapacitors; S5 dynamically corrects the supercapacitor reference power based on the bus voltage deviation and voltage change rate, and adjusts it according to the battery state of charge. and the state of charge of supercapacitors Adaptive adjustment is performed on the corrected power; S6 limits the rate of change of the battery reference current and transfers the power difference caused by the limiting to the supercapacitor. S7, when the bus disturbance evaluation quantity When the voltage is reduced to below the stability threshold and the DC bus voltage deviation is within the allowable range, the state of charge of the supercapacitor is... Perform recovery control to enable Return to the target range.

[0011] Preferably, in S3, the disturbance evaluation quantity is: ; in , This is the DC bus voltage. This is the DC bus reference voltage. , , These are the weighting coefficients.

[0012] Preferably, the bus voltage change rate and the rate of change of power imbalance The discrete computational relationship is as follows: ; ; in, To control the sampling period, Indicates the first One control cycle.

[0013] Preferably, the weighting coefficients in S3 , , Determine by the following formula: ; ; ; in This is the DC bus reference voltage. To control the sampling frequency, The rated power of the system, , , It is a configurable scaling factor, and its value range is within the interval [0.1, 10].

[0014] Furthermore, the rule for dividing the disturbance state is as follows: when When it is determined to be in a steady state; when When it is determined to be a small disturbance; when When it is determined to be a general disturbance; when The time is determined to be a load or photovoltaic sudden change state.

[0015] Preferably, the discrete calculation relationship for low-pass filtering in S4 is as follows: ; ; ; in, The time constant of the low-pass filter. To control the sampling period; low-pass filter time constant The selection satisfies: ; in This is the upper limit of the power fluctuation frequency that the battery can respond to smoothly. The range of values ​​is .

[0016] Preferably, the specific method for correcting the bus voltage in S5 is as follows: ; ; in, This is the voltage deviation correction factor. Voltage change rate correction factor; voltage deviation correction factor and voltage change rate correction factor The tuning rules are as follows: ; ; in The rated power of the system, This represents the maximum allowable deviation of the bus voltage. This represents the maximum allowable rate of change of bus voltage.

[0017] Preferably, in S5 according to and The specific method for adaptive correction is as follows: Introducing a battery SOC correction factor and supercapacitor SOC correction factor According to the formula below and After correction and : ; ; in The rules for determining the value are as follows: when Within the normal range hour, ; when and hour, ; when and hour, ; The rules for determining the value are as follows: when Within the normal range hour, ; when and hour, ; when and hour, ; in , , , These are the minimum SOC, lower discharge limit, upper charge limit, and maximum charge limit of the battery, respectively. , , , These represent the minimum SOC, lower discharge limit, upper charge limit, and maximum charge limit of the supercapacitor, respectively; 1 indicates the discharge direction, and -1 indicates the charging direction.

[0018] Preferably, the specific methods for limiting the rate of change of battery current and compensating for the difference in supercapacitor in S6 are as follows: ; ; ; ; ; ; in This refers to the battery terminal voltage. The threshold for the rate of change of battery current. This is the reference current for the battery. For the difference in limiting power, Indicates will The amplitude is limited within the range of [L,H].

[0019] Furthermore, the battery current change rate threshold The method for determining it is as follows: ,in Battery capacity, measured in ampere-hours. This represents the maximum allowable rate of change of charge / discharge rate for the battery, with a value range of [value range missing]. .

[0020] Preferably, the recovery power of the supercapacitor SOC recovery control in S7 is... for: ; ; ; in This is the SOC recovery gain coefficient. This is the target reference value for the SOC of the supercapacitor.

[0021] Furthermore, the SOC recovery control of the supercapacitor in S7 adopts a recovery gain or slope limit that is less than the gain of the power distribution stage, so as to avoid introducing new power disturbances when the bus has just recovered to stability.

[0022] Furthermore, the SOC recovery gain coefficient The range of values ​​is ,in The system's rated power and restored power. The rate of change is limited by the slope, and the change in recovery power within adjacent control cycles does not exceed [a certain percentage]. .

[0023] Furthermore, the positive direction of the energy storage unit power in S2 is defined as follows: the power is positive when the energy storage unit discharges to the DC bus, and the power is negative when the energy storage unit absorbs energy from the DC bus.

[0024] Furthermore, the system also includes an optional grid-connected interface converter, which is connected to the DC bus.

[0025] Preferably, the low-pass filter time constant Selected based on the frequency characteristics of system power fluctuations, so that ,in This is the low-pass filter cutoff frequency. This is the upper limit of the power fluctuation frequency that the battery can respond to smoothly.

[0026] Furthermore, the scaling factor , , The typical configuration is , , .

[0027] Furthermore, the typical set value of the SOC threshold is taken as follows: , , , , , , , .

[0028] Furthermore, The typical value is .

[0029] Furthermore, the SOC recovery gain coefficient The typical value is .

[0030] The beneficial effects of this invention are as follows: 1. This invention achieves comprehensive identification of system disturbance states by constructing a bus disturbance evaluation quantity that is a weighted combination of three indicators: bus voltage deviation, bus voltage change rate, and power imbalance change rate. This evaluation quantity can identify dynamic disturbances caused by sudden load changes or rapid photovoltaic changes in advance, even before a significant deviation in the bus voltage occurs, through the rapid response of the voltage change rate and power imbalance change rate. This overcomes the shortcomings of existing technologies that rely solely on voltage amplitude segmentation for delayed disturbance identification.

[0031] 2. This invention superimposes bus voltage correction and adaptive state of charge correction on top of the initial high- and low-frequency power allocation. This allows the supercapacitor to prioritize the transient power corresponding to rapid voltage fluctuations, while dynamically adjusting the power allocation of each energy storage unit based on the state of charge of the battery and supercapacitor. This method takes into account the frequency characteristics of power, the dynamic state of the bus, and the energy storage safety boundary, avoiding overcharging or over-discharging of energy storage units and solving the problem that existing high- and low-frequency allocation methods do not fully consider the constraints of the energy storage state of charge.

[0032] 3. This invention constrains the reference current change in adjacent control cycles by setting a battery current change rate threshold, and allocates the power difference that the battery cannot immediately handle due to amplitude limiting to the supercapacitor, thus achieving smooth changes in battery current. This method reduces the high-frequency charging and discharging impact on the battery while maintaining DC bus power balance, which is beneficial to extending battery life. Simultaneously, after the bus stabilizes, supercapacitor state-of-charge recovery control is initiated, using low gain or slope limiting to slowly restore the supercapacitor's state of charge to the target range, preserving rapid support capability for the next load surge or rapid photovoltaic fluctuation. Attached Figure Description

[0033] Figure 1 This is a schematic diagram of the method flow in an embodiment of the present invention; Figure 2 This is a schematic diagram of the system structure in an embodiment of the present invention; Figure 3 The figure shows the simulation results of adaptive power allocation for hybrid energy storage in an embodiment of the present invention. Detailed Implementation

[0034] Example 1: like Figure 1 As shown in the figure, this embodiment proposes an adaptive power allocation method for hybrid energy storage in a photovoltaic-storage-charging DC microgrid. This method takes operating parameters such as photovoltaic output power, charging load power, DC bus voltage, battery SOC, supercapacitor SOC, and battery current as inputs, and battery reference power and supercapacitor reference power as outputs. It unifies bus disturbance evaluation, initial allocation of high and low frequency power, adaptive SOC correction, battery current change rate limiting, and supercapacitor SOC restoration into the same control process.

[0035] like Figure 2 As shown, an adaptive power allocation method for hybrid energy storage in a photovoltaic-storage-charging DC microgrid includes the following steps: S1, construct a photovoltaic-storage-charging DC microgrid hybrid energy storage system. The system includes photovoltaic power generation units, photovoltaic DC / DC converters, a common DC bus, DC bus capacitors, electric vehicle charging loads, battery energy storage units, battery-side bidirectional DC / DC converters, supercapacitor energy storage units, supercapacitor-side bidirectional DC / DC converters, and an energy management and adaptive power distribution control unit. The photovoltaic power generation units are connected to the DC bus via photovoltaic DC / DC converters, the battery energy storage units are bidirectionally connected to the DC bus via battery-side bidirectional DC / DC converters, the supercapacitor energy storage units are bidirectionally connected to the DC bus via supercapacitor-side bidirectional DC / DC converters, and the electric vehicle charging loads draw power from the DC bus. S2, Collect operating parameters and calculate system power imbalance. , For photovoltaic output power, The charging load power for electric vehicles; S3, Construct bus disturbance evaluation quantity And determine the disturbance state, based on The magnitude of the disturbance determines the system state into steady state, small disturbance, general disturbance, and load or photovoltaic sudden change state. S4, for power imbalance Perform initial high- and low-frequency power allocation, and obtain the low-frequency continuous power component to be supplied by the battery through low-pass filtering. and the remaining high-frequency components Distributed to supercapacitors; S5 dynamically corrects the supercapacitor reference power based on the bus voltage deviation and voltage change rate, and adjusts it according to the battery state of charge. and the state of charge of supercapacitors Adaptive adjustment is performed on the corrected power; S6 limits the rate of change of the battery reference current and transfers the power difference caused by the limiting to the supercapacitor. S7, when the bus disturbance evaluation quantity When the voltage is reduced to below the stability threshold and the DC bus voltage deviation is within the allowable range, the state of charge of the supercapacitor is... Perform recovery control to enable Return to the target range.

[0036] Preferably, in S3, the disturbance evaluation quantity is: ; in , This is the DC bus voltage. This is the DC bus reference voltage. , , These are the weighting coefficients.

[0037] Preferably, the bus voltage change rate and the rate of change of power imbalance The discrete computational relationship is as follows: ; ; in, To control the sampling period, Indicates the first One control cycle.

[0038] Preferably, the weighting coefficients in S3 , , Determine by the following formula: ; ; ; in This is the DC bus reference voltage. To control the sampling frequency, The rated power of the system, , , It is a configurable scaling factor, and its value range is within the interval [0.1, 10].

[0039] Furthermore, the rule for dividing the disturbance state is as follows: when When it is determined to be in a steady state; when When it is determined to be a small disturbance; when When it is determined to be a general disturbance; when The time is determined to be a load or photovoltaic sudden change state.

[0040] Preferably, the discrete calculation relationship for low-pass filtering in S4 is as follows: ; ; ; in, The time constant of the low-pass filter. To control the sampling period; low-pass filter time constant The selection satisfies: ; in This is the upper limit of the power fluctuation frequency that the battery can respond to smoothly. The range of values ​​is .

[0041] Preferably, the specific method for correcting the bus voltage in S5 is as follows: ; ; in, This is the voltage deviation correction factor. Voltage change rate correction factor; voltage deviation correction factor and voltage change rate correction factor The tuning rules are as follows: ; ; in The rated power of the system, This represents the maximum allowable deviation of the bus voltage. This represents the maximum allowable rate of change of bus voltage.

[0042] Preferably, in S5 according to and The specific method for adaptive correction is as follows: Introducing a battery SOC correction factor and supercapacitor SOC correction factor According to the formula below and After correction and : ; ; in The rules for determining the value are as follows: when Within the normal range hour, ; when and hour, ; when and hour, ; The rules for determining the value are as follows: when Within the normal range hour, ; when and hour, ; when and hour, ; in , , , These are the minimum SOC, lower discharge limit, upper charge limit, and maximum charge limit of the battery, respectively. , , , These represent the minimum SOC, lower discharge limit, upper charge limit, and maximum charge limit of the supercapacitor, respectively; 1 indicates the discharge direction, and -1 indicates the charging direction.

[0043] Preferably, the specific methods for limiting the rate of change of battery current and compensating for the difference in supercapacitor in S6 are as follows: ; ; ; ; ; ; in This refers to the battery terminal voltage. The threshold for the rate of change of battery current. This is the reference current for the battery. For the difference in limiting power, Indicates will The amplitude is limited within the range of [L,H].

[0044] Furthermore, the battery current change rate threshold The method for determining it is as follows: ,in Battery capacity, measured in ampere-hours. This represents the maximum allowable rate of change of charge / discharge rate for the battery, with a value range of [value range missing]. .

[0045] like Figure 3 As shown, when the charging load suddenly increases at 2 seconds, the supercapacitor quickly takes over the transient power, and the battery power and current rise smoothly according to the set rate of change. The DC bus voltage remains within the allowable fluctuation range, indicating that this method can stabilize the DC bus voltage and reduce the battery current surge under sudden load conditions.

[0046] Preferably, the recovery power of the supercapacitor SOC recovery control in S7 is... for: ; ; ; in This is the SOC recovery gain coefficient. This is the target reference value for the SOC of the supercapacitor.

[0047] Furthermore, the SOC recovery control of the supercapacitor in S7 adopts a recovery gain or slope limit that is less than the gain of the power distribution stage, so as to avoid introducing new power disturbances when the bus has just recovered to stability.

[0048] Furthermore, the SOC recovery gain coefficient The range of values ​​is ,in The system's rated power and restored power. The rate of change is limited by the slope, and the change in recovery power within adjacent control cycles does not exceed [a certain percentage]. .

[0049] Furthermore, the positive direction of the energy storage unit power in S2 is defined as follows: the power is positive when the energy storage unit discharges to the DC bus, and the power is negative when the energy storage unit absorbs energy from the DC bus.

[0050] Furthermore, the system also includes an optional grid-connected interface converter, which is connected to the DC bus.

[0051] Preferably, the low-pass filter time constant Selected based on the frequency characteristics of system power fluctuations, so that ,in This is the low-pass filter cutoff frequency. This is the upper limit of the power fluctuation frequency that the battery can respond to smoothly.

[0052] Furthermore, the scaling factor , , The typical configuration is , , .

[0053] Furthermore, the typical set value of the SOC threshold is taken as follows: , , , , , , , .

[0054] Furthermore, The typical value is .

[0055] Furthermore, the SOC recovery gain coefficient The typical value is .

[0056] Example 2: This embodiment provides an example of verifying the method on a photovoltaic-storage-charging DC microgrid experimental platform in a certain park. The system consists of: a photovoltaic simulator with a rated power output of 100kW, connected to a 750V DC bus via a photovoltaic DC / DC converter; a battery pack using lithium iron phosphate batteries with a rated capacity of 200Ah and a rated voltage of 400V, connected to the bus via a bidirectional DC / DC converter; a supercapacitor module with a rated voltage of 400V and a capacitance of 100F, connected to the bus via a bidirectional DC / DC converter; and an electric vehicle charging load simulated by a programmable electronic load with a power range of 0~150kW. The control algorithm is implemented on the DSPTMS320F28379 platform, with a sampling period of... The control cycle is synchronized with the sampling cycle.

[0057] Key parameters are set as follows: DC bus reference voltage System rated power Bus disturbance evaluation weighting coefficient and proportional factor , , The disturbance state threshold is based on and Proportional settings; low-pass filter time constant SOC adaptive correction thresholds: Minimum SOC for batteries and supercapacitors is 0.1, lower discharge limit is 0.2, upper charge limit is 0.8, and maximum SOC is 0.9. Battery current change rate threshold: ,correspond SOC recovery gain Restoring power change rate limit .

[0058] The comparative method employs a traditional low-pass filter power allocation method and segmented bus voltage control: it only decomposes the power imbalance into high and low frequency components through a low-pass filter, which are then handled by the battery and supercapacitor respectively. It does not include bus disturbance evaluation, SOC adaptive correction coefficient, battery current change rate limiting and differential compensation, or SOC recovery control. The low-pass filter time constant in the comparative method is the same as in this method. This ensures consistency with the comparison benchmark.

[0059] In practice, the initial operating conditions are first set: photovoltaic output power. Charging load power System power imbalance The surplus energy storage is in a charging state, and the bus voltage is stable at... Nearby. At that moment, the charging load of electric vehicles suddenly increased to , jump to The system entered a disturbance state due to a shortage. Key indicators such as bus voltage, battery / supercapacitor power distribution, and battery current change rate were recorded for the following 600 seconds. A comparison method was also run under the same operating conditions, recording the same indicators for comparison; the data are shown in Tables 1 and 2 below.

[0060] Table 1: Operational data of this method at different time points;

[0061] Table 2: Operational data of this method at different time points;

[0062] As can be seen from the comparison data in Tables 1 and 2, this method has the following significant advantages over the traditional low-pass filter distribution plus bus voltage segmented control method; in terms of dynamic response, when When a sudden load increase of 90kW occurs, this method evaluates the bus disturbance quantity. Within a single sampling period, the voltage jumped from 1.1 to 47.2. By combining the bus voltage change rate and the power imbalance change rate, the severity of the disturbance was identified in advance. The supercapacitor instantaneously absorbed 84.8kW of power deficit, and the maximum bus voltage drop was only 11.5V. In contrast, the comparison method relied solely on voltage amplitude segmentation, resulting in a delayed disturbance identification and a maximum bus voltage drop of 28.3V, exceeding the allowable fluctuation range.

[0063] Regarding battery protection, this method... The current rate of change limiting mechanism strictly constrains the battery reference current within a set slope, allowing the battery current to smoothly transition from -63.3A to +132.0A within 300 seconds without any abrupt changes. In contrast, the comparative method lacks a current rate of change limiting mechanism, resulting in a peak battery current rate of change of 12.30A / s, which is 111 times higher than that of this method, significantly and adversely affecting the battery's cycle life.

[0064] Regarding power distribution balance, in this method, the supercapacitor initially bears most of the power deficit during the initial disturbance phase. As the battery power gradually increases at a set slope, the supercapacitor power gradually decreases from 84.8kW to 7.2kW at 300s, achieving automatic power distribution balance throughout. In the comparative method, the supercapacitor... The supercapacitor was still carrying 35.0kW, and the power output was slow, indicating that the lack of a limiting differential compensation mechanism prevented the supercapacitor from transferring the base load back to the battery in a timely manner.

[0065] Regarding bus voltage stability, this method allows the bus voltage to enter... Within range, it only takes 28 seconds to enter. The stabilization period takes 182 seconds, and the peak-to-peak voltage fluctuation in steady state is only 1.8V. The corresponding indicators for the comparison methods are 95s, 485s, and 4.2V, respectively. The bus voltage recovery speed is significantly slower, and the steady-state fluctuation is larger.

[0066] In summary, this method, by unifying bus disturbance evaluation, high and low frequency power allocation, SOC adaptive correction, battery current change rate limiting differential compensation, and supercapacitor SOC recovery into the same control flow, outperforms traditional methods in four aspects: dynamic response speed, battery protection, power allocation balance, and bus voltage stability.

Claims

1. A hybrid energy storage adaptive power allocation method for photovoltaic-storage-charging DC microgrids, characterized in that, Includes the following steps: S1, Construct a photovoltaic-storage-charging DC microgrid hybrid energy storage system. The system includes a photovoltaic power generation unit, which is connected to the DC bus via a photovoltaic DC / DC converter. The battery energy storage unit is bidirectionally connected to the DC bus via a bidirectional DC / DC converter on the battery side. The supercapacitor energy storage unit is bidirectionally connected to the DC bus via a bidirectional DC / DC converter on the supercapacitor side. The electric vehicle charging load draws power from the DC bus. S2, Collect operating parameters and calculate system power imbalance. , For photovoltaic output power, The charging load power for electric vehicles; S3, Construct bus disturbance evaluation quantity And determine the disturbance state, based on The magnitude of the disturbance determines the system state into steady state, small disturbance, general disturbance, and load or photovoltaic sudden change state. S4, for power imbalance Perform initial high- and low-frequency power allocation, and obtain the low-frequency continuous power component to be supplied by the battery through low-pass filtering. and the remaining high-frequency components Distributed to supercapacitors; S5 dynamically corrects the supercapacitor reference power based on the bus voltage deviation and voltage change rate, and adjusts it according to the battery state of charge. and the state of charge of supercapacitors Adaptive adjustment is performed on the corrected power; S6 limits the rate of change of the battery reference current and transfers the power difference caused by the limiting to the supercapacitor. S7, when the bus disturbance evaluation quantity When the voltage is reduced to below the stability threshold and the DC bus voltage deviation is within the allowable range, the state of charge of the supercapacitor is... Perform recovery control to enable Return to the target range.

2. The adaptive power allocation method for hybrid energy storage in a photovoltaic-storage-charging DC microgrid according to claim 1, characterized in that, In S3, the disturbance evaluation quantity is: ； in , This is the DC bus voltage. This is the DC bus reference voltage. , , These are the weighting coefficients.

3. The adaptive power allocation method for hybrid energy storage in a photovoltaic-storage-charging DC microgrid according to claim 2, characterized in that, Bus voltage change rate and the rate of change of power imbalance The discrete computational relationship is as follows: ； ； in, To control the sampling period, Indicates the first One control cycle.

4. The adaptive power allocation method for hybrid energy storage in a photovoltaic-storage-charging DC microgrid according to claim 3, characterized in that, Weighting coefficients in S3 , , Determine using the following formula: ； ； ； in This is the DC bus reference voltage. To control the sampling frequency, The rated power of the system, , , It is a configurable scaling factor, and its value range is within the interval [0.1, 10].

5. The adaptive power allocation method for hybrid energy storage in a photovoltaic-storage-charging DC microgrid according to claim 1, characterized in that, The discrete calculation relationship for low-pass filtering in S4 is as follows: ； ； ； in, The time constant of the low-pass filter. To control the sampling period; low-pass filter time constant The selection satisfies: ； in This is the upper limit of the power fluctuation frequency that the battery can respond to smoothly.

6. The adaptive power allocation method for hybrid energy storage in a photovoltaic-storage-charging DC microgrid according to claim 1, characterized in that, The specific method for bus voltage correction in S5 is as follows: ； ； in, This is the voltage deviation correction factor. Voltage change rate correction factor; voltage deviation correction factor and voltage change rate correction factor The tuning rules are as follows: ； ； in The rated power of the system, This represents the maximum allowable deviation of the bus voltage. This represents the maximum allowable rate of change of bus voltage.

7. The adaptive power allocation method for hybrid energy storage in a photovoltaic-storage-charging DC microgrid according to claim 6, characterized in that, According to S5 and The specific method for adaptive correction is as follows: Introducing a battery SOC correction factor and supercapacitor SOC correction factor According to the following formula and After correction and : ； ； in The rules for determining the value are as follows: when Within the normal range hour, ; when and hour, ; when and hour, ; The rules for determining the value are as follows: when Within the normal range hour, ; when and hour, ; when and hour, ; in , , , These are the minimum SOC, lower discharge limit, upper charge limit, and maximum charge limit of the battery, respectively. , , , These represent the minimum SOC, lower discharge limit, upper charge limit, and maximum charge limit of the supercapacitor, respectively; 1 indicates the discharge direction, and -1 indicates the charging direction.

8. The adaptive power allocation method for hybrid energy storage in a photovoltaic-storage-charging DC microgrid according to claim 1, characterized in that, The specific methods for limiting the rate of change of battery current and compensating for the difference in supercapacitor capacity in S6 are as follows: ； ； ； ； ； ； in This refers to the battery terminal voltage. The threshold for the rate of change of battery current. This is the battery reference current. For the difference in limiting power, Indicates will The amplitude is limited within the range of [L,H].

9. The adaptive power allocation method for hybrid energy storage in a photovoltaic-storage-charging DC microgrid according to claim 1, characterized in that, Recovery power of supercapacitor SOC recovery control in S7 for: ； ； ； in This is the SOC recovery gain coefficient. This is the target reference value for the SOC of the supercapacitor.

10. The adaptive power allocation method for hybrid energy storage in a photovoltaic-storage-charging DC microgrid according to claim 5, characterized in that, Low-pass filter time constant Selected based on the frequency characteristics of system power fluctuations, so that ,in This is the low-pass filter cutoff frequency. This is the upper limit of the power fluctuation frequency that the battery can respond to smoothly.

Images