Hybrid energy storage frequency modulation optimization method and system based on dynamic response and SOC cooperation

Abstract

The invention discloses a hybrid energy storage frequency modulation optimization method and system based on dynamic response and SOC cooperation. The method comprises the steps that the frequency deviation of a power grid is detected; if the absolute value of the frequency deviation is greater than the absolute value of the threshold of the frequency modulation dead zone, determining the current frequency modulation stage according to the frequency deviation and calculating the total frequency modulation power of the current frequency modulation stage; if the absolute value of the total frequency modulation power is smaller than a specified value, adjusting a utilization factor of the fuel cell for frequency modulation until the output of the fuel cell reaches the absolute value of the total frequency modulation power; if the absolute value of the total frequency modulation power is greater than a specified value, adjusting a utilization rate factor of the fuel cell to perform frequency modulation, and adjusting a charge-discharge weight of the energy storage cell according to the charge state of the energy storage cell in real time to perform frequency modulation until the output of the fuel cell reaches the specified value; and the sum of the output of the fuel cell and the output of the energy storage cell reaches the absolute value of the total frequency modulation power. According to the invention, comprehensive optimization of frequency modulation response speed, economy and energy storage life is realized.

Description

Technical Field

[0001] The present invention relates to the field of power control technology, and in particular to a hybrid energy storage frequency regulation optimization method and system based on dynamic response and SOC collaboration. Background Art

[0002] With the increasing penetration of renewable energy, grid frequency stability faces severe challenges. Traditional frequency regulation technologies primarily rely on thermal power units or single energy storage devices (such as lithium batteries and supercapacitors). These technologies suffer from issues such as slow response, high frequency regulation costs, and rapid energy storage lifespan degradation. This is particularly true in isolated, weak grids or scenarios with a high proportion of renewable energy access, where sudden load changes and intermittent generation can easily cause frequency fluctuations. Existing frequency regulation strategies struggle to balance dynamic response speed with economic efficiency.

[0003] The existing hydrogen-oxygen fuel cell model has a fixed utilization factor, which leads to an imbalance in fuel supply and demand when the load suddenly changes, poor output voltage stability, and ignores the dynamic influence of stack temperature, further reducing the response accuracy; although the hybrid energy storage system integrates multiple types of energy storage units, the static weight distribution mechanism cannot adapt to multi-stage characteristics such as frequency deterioration and recovery. The linear combination of virtual droop and inertial control can easily cause a reverse regulation effect in the frequency recovery stage, resulting in a secondary frequency drop; in addition, the state of charge (SOC) management of the energy storage unit is extensive, overcharging / over-discharging behavior occurs frequently, accelerating capacity decay. Although the existing strategy divides the SOC interval, it lacks dynamic weight distribution, making it difficult to coordinate frequency regulation economy and equipment life. Summary of the Invention

[0004] The technical problem to be solved by the present invention is: In response to the above-mentioned problems in the prior art, a hybrid energy storage frequency regulation optimization method and system based on dynamic response and SOC collaboration is provided to achieve comprehensive optimization of frequency regulation response speed, economy and energy storage life.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is: A hybrid energy storage frequency regulation optimization method based on dynamic response and SOC coordination includes the following steps: Detect frequency deviation of the power grid; If the absolute value of the frequency deviation is greater than the absolute value of the threshold of the frequency modulation dead zone, the current frequency modulation stage is determined according to the frequency deviation and the total frequency modulation power of the current frequency modulation stage is calculated; If the absolute value of the total frequency modulation power is less than the specified value, the utilization factor of the fuel cell is adjusted to perform frequency modulation until the output of the fuel cell reaches the absolute value of the total frequency modulation power; If the absolute value of the total frequency modulation power is greater than the specified value, the utilization factor of the fuel cell is adjusted for frequency modulation, and the charge and discharge weights of the energy storage battery are adjusted in real time according to the charge state of the energy storage battery to perform frequency modulation until the output of the fuel cell reaches the specified value and the sum of the output of the fuel cell and the output of the energy storage battery reaches the absolute value of the total frequency modulation power.

[0006] Furthermore, determining the current frequency modulation stage according to the frequency deviation includes: calculate dΔf / dt * Δf ,in Δf is the frequency deviation, dΔf / dt represents the derivative of the frequency deviation; If the calculated result is less than zero, the current frequency modulation stage is the frequency recovery stage; If the calculated result is greater than zero, the absolute value of the frequency deviation | Δf |Absolute value of the threshold of the FM dead zone| Δ f dead |, absolute values ​​of the preset critical values ​​of the frequency deterioration stage and the frequency deterioration severe stage| Δf set |and the absolute value of the value at the worst frequency degradation| Δf m |Compare; If | Δf dead |<| Δf |<| Δf set |, the current frequency modulation stage is the frequency deterioration stage; If | Δf set |<| Δf |<| Δf m |, the current frequency modulation stage is a stage of severe frequency deterioration.

[0007] Furthermore, when calculating the total frequency modulation power of the current frequency modulation stage, the weight coefficients of the virtual inertia control and the virtual droop control in the frequency modulation model are calculated according to the current frequency modulation stage, and then the calculation results are substituted into the frequency modulation model to obtain the total frequency modulation power of the current frequency modulation stage. The formula of the frequency modulation model is as follows:

[0008] in, α 1 and α 2 are the weight coefficients of virtual inertia control and virtual droop control, ΔP is the total FM power, ΔP M and ΔP KThey are virtual inertia control output and virtual droop control output, and the formulas are as follows:

[0009]

[0010] Among them, Δ f is the frequency change; M is the virtual inertia control coefficient; K is the virtual droop control coefficient.

[0011] Furthermore, according to the current frequency modulation stage, the weight coefficients of the virtual inertia control and the virtual droop control in the frequency modulation model are calculated, including: If the current frequency modulation stage is the frequency recovery stage, the weight coefficient calculation formula of virtual inertia control and virtual droop control is as follows:

[0012] If the current frequency modulation stage is the frequency deterioration stage, the weight coefficient calculation formula of virtual inertia control and virtual droop control is as follows:

[0013] If the current frequency modulation stage is a stage of severe frequency deterioration, the weight coefficient calculation formula of virtual inertia control and virtual droop control is as follows:

[0014] In the above formula, α 1 and α 2 are the weight coefficients of virtual inertia control and virtual droop control respectively.

[0015] Furthermore, if the absolute value of the total frequency-modulated power is less than a specified value, the utilization factor of the fuel cell is adjusted for frequency modulation. Specifically, when the total frequency-modulated power is greater than 0, the utilization factor of the fuel cell is increased, and when the total frequency-modulated power is less than 0, the utilization factor of the fuel cell is reduced, so that the output power of the fuel cell quickly reaches the target value.

[0016] Furthermore, if the absolute value of the total frequency-modulated power is greater than a specified value, the utilization factor of the fuel cell is adjusted for frequency modulation. Specifically, when the total frequency-modulated power is greater than 0, the utilization factor of the fuel cell is increased until it reaches the upper limit value; when the total frequency-modulated power is less than 0, the utilization factor of the fuel cell is reduced until it reaches the lower limit value, so that the output power of the fuel cell quickly reaches near the target value, and then the inverter phase angle is adjusted and the utilization factor of the fuel cell is maintained at the upper limit value or the lower limit value, so that the output power of the fuel cell slowly reaches the target value, and finally the utilization factor of the fuel cell is adjusted from the upper limit value or the lower limit value to the ideal value.

[0017] Furthermore, the specified value is 0.1125* P rate,FC , the upper limit is 0.9 and the lower limit is 0.7, where P rate,FC is the rated power of the fuel cell.

[0018] Furthermore, when frequency modulation is performed by adjusting the charge and discharge weight of the energy storage battery in real time according to the state of charge of the energy storage battery, it specifically includes: Obtaining the state of charge of each energy storage battery, calculating the charging or discharging weight of each energy storage battery according to the state of charge, and then calculating the charging or discharging power requirement value of each energy storage battery according to the charging or discharging weight of each energy storage battery; If the current charging or discharging power requirement of the energy storage battery exceeds the current charging or discharging power maximum value of the energy storage battery, the charging or discharging power of the current energy storage battery is adjusted to the maximum value, and the difference between the current charging or discharging power requirement and the maximum value is calculated to obtain the remaining power, and the remaining power is distributed to the remaining energy storage batteries.

[0019] Furthermore, the energy storage battery includes a sodium ion battery and an all-vanadium redox flow battery. When the charging or discharging weight of each energy storage battery is calculated according to the state of charge, and then the charging or discharging power requirement value of each energy storage battery is calculated according to the charging or discharging weight of each energy storage battery, the calculation formula is as follows: If the total FM power is greater than zero:

[0020]

[0021] In the above formula, SOC na 、 SOC VRB represent the state of charge of sodium ion battery and all-vanadium flow battery respectively, SOC min 、 SOC max Represent the minimum and maximum state of charge, W na,d 、 W VRB,d Respectively represent the discharge weights of sodium ion batteries and all-vanadium redox flow batteries. If the state of charge of the sodium ion battery or all-vanadium redox flow battery is less than the over-discharge threshold, the discharge weight of the sodium ion battery or all-vanadium redox flow battery is 0. P na,d 、 P VRB,d are the discharge powers of sodium ion batteries and all-vanadium flow batteries, respectively. P battery Indicates the difference between the absolute value of the total FM power and the specified value; If the total FM power is less than zero:

[0022]

[0023] In the above formula, SOC na 、 SOC VRB represent the state of charge of sodium ion battery and all-vanadium flow battery respectively, SOC min 、 SOC max Represent the minimum and maximum state of charge, W na,c 、 W VRB,c Represent the charging weights of sodium ion batteries and all-vanadium redox flow batteries respectively. If the state of charge of the sodium ion battery or all-vanadium redox flow battery is greater than the overcharge threshold, the charging weight of the sodium ion battery or all-vanadium redox flow battery is 0. P na,c 、 P VRB,c are the charging powers of sodium-ion batteries and all-vanadium flow batteries, respectively. P battery Indicates the difference between the absolute value of the total FM power and the specified value.

[0024] The present invention also proposes a hybrid energy storage frequency regulation optimization system based on dynamic response and SOC coordination, including a processor and a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is executed by the processor to implement the steps of the hybrid energy storage frequency regulation optimization method based on dynamic response and SOC coordination.

[0025] Compared with the prior art, the advantages of the present invention are: 1. This invention dynamically adjusts the utilization factor of the fuel cell to quickly adjust the output power when the load suddenly changes, solving the fuel supply and demand imbalance problem caused by the traditional fixed utilization factor value and improving the response speed of the fuel cell.

[0026] 2. When calculating the total frequency modulation power in the current frequency modulation stage, the present invention integrates virtual droop control and positive / negative virtual inertia control, dynamically assigns weight coefficients according to the frequency deterioration and recovery stages, suppresses the reverse regulation effect caused by traditional linear combinations, reduces the secondary frequency drop amplitude, and improves the frequency modulation effect.

[0027] 3. The present invention adjusts the charge and discharge weights of the energy storage battery in real time according to the state of charge of the energy storage battery to perform frequency modulation, dynamically allocates the charge and discharge weights, avoids overcharge / overdischarge behavior, and extends the cycle life of the energy storage battery. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is the topology diagram of the hydrogen-oxygen fuel cell.

[0029] Figure 2 Schematic diagram of the dynamic response of a fuel cell according to an embodiment of the present invention.

[0030] Figure 3 This is a schematic diagram of a frequency modulation stage.

[0031] Figure 4 This is a frequency modulation flow chart of the method according to an embodiment of the present invention.

[0032] Figure 5 2 is a flow chart of determining the total frequency modulation power of the current frequency modulation stage according to the frequency deviation in an embodiment of the present invention. DETAILED DESCRIPTION

[0033] The present invention will be further described below in conjunction with the accompanying drawings and specific preferred embodiments, but the scope of protection of the present invention is not limited thereby.

[0034] Example 1 In hydrogen-oxygen fuel cell systems, the utilization factor ( β ) is a core parameter for measuring fuel utilization efficiency, defined as the ratio of the hydrogen flow rate participating in the electrochemical reaction in the fuel cell stack to the total input flow rate. This parameter has a dual impact on the dynamic response characteristics and operating life of the system: when the utilization factor exceeds 0.9, insufficient fuel supply will cause irreversible damage to the catalyst layer; when it is lower than 0.7, excess fuel may cause abnormally high voltage in the single cell. Existing research shows that traditional control strategies usually fix the utilization factor at 0.8. This static setting cannot cope with the imbalance of fuel supply and demand during sudden load changes. By rationally controlling the utilization factor and hydrogen flow rate of the fuel cell, its dynamic response performance can be significantly improved.

[0035] Based on this, this embodiment proposes a hybrid energy storage frequency regulation optimization method based on dynamic response and SOC coordination, combining fuel cell control with a comprehensive primary frequency regulation control strategy. The fuel cell can quickly compensate for power through the comprehensive primary frequency regulation control strategy and work in conjunction with the energy storage battery to effectively support the primary frequency regulation of the power grid and improve the primary frequency fluctuation of the power grid. Specifically, the following steps are included: S1) Build a fuel cell control strategy to improve transient response speed.

[0036] A dynamic response model of a hydrogen-oxygen fuel cell is constructed, and the quantitative relationship between hydrogen partial pressure, current and molar flow rate is derived. The output voltage expression is established by combining polarization, ohmic and concentration voltage losses. A dynamic adjustment strategy for the utilization factor is introduced. The utilization factor is dynamically adjusted when the load changes suddenly to improve transient response. The output power is quickly adjusted when the frequency modulation power demand exceeds a certain set value, and the power and utilization factor are controlled through phase angle adjustment.

[0037] S2) Construct a comprehensive control strategy for primary frequency regulation of hybrid energy storage.

[0038] For the hybrid energy storage system including fuel cells and energy storage batteries, a dynamic weight distribution mechanism is proposed, which integrates virtual droop control and positive / negative virtual inertia control, adaptively adjusts the weight coefficient according to the frequency change stage, suppresses the secondary frequency drop and enhances the regulation kinetic energy.

[0039] S3) Frequency regulation power distribution of hybrid energy storage system.

[0040] The grid frequency signal and fuel cell operating power are collected in real time and input into the energy management system, enabling precise power regulation of the grid. When the grid frequency deviation is detected to be greater than the frequency regulation dead zone, the primary frequency regulation integrated control strategy constructed in step S2 is first used to calculate the total primary frequency regulation output of the hybrid energy storage as the frequency regulation power demand. The fuel cell control strategy constructed in step S1 is then used to preferentially utilize the hydrogen-oxygen fuel cell for frequency regulation control, thereby extending the service life of the energy storage battery.

[0041] The following is a detailed description of each step.

[0042] In step S1 of this embodiment, during modeling, based on the assumption of constant pressure gas supply and constant temperature environment, the quantitative relationship between hydrogen partial pressure, output current, and hydrogen molar flow rate is derived. The actual output voltage expression of the fuel cell is established by combining polarization loss, ohmic loss, and concentration voltage loss. The process is as follows: Assuming that the supplied hydrogen and air are ideal and uniformly distributed gases supplied at constant pressure, the ambient temperature remains constant, and the thermodynamic properties are evaluated at the average stack temperature. Temperature variations throughout the stack are ignored, and the overall specific heat capacity of the stack is assumed to be constant. The parameters of individual cells can be lumped together to represent a fuel cell stack, and individual fuel cell stacks can be lumped together to represent a fuel cell array.

[0043] Based on the ideal gas law, the hydrogen partial pressure in the anode can be expressed as: (1) Where, is the hydrogen partial pressure, is the anode volume, is the number of moles of hydrogen in the anode, Ris the gas constant, T is the temperature. To derive the above formula, we can get: (2) (3) Where, is the hydrogen gas flow rate, 、 、 In order to accurately describe the quantitative relationship between the molar flow rate of hydrogen participating in the electrochemical reaction in the fuel cell and the battery output current, the hydrogen partial pressure is derived based on Faraday's law: (4) Where, N 0 is the number of battery cells connected in series, I is the battery current, F is the Faraday constant, K r Is a constant whose value is N 0 / 4 F , is the fuel cell unit current. Substituting formula (4) into (3), we can obtain: (5) Since the molar flow rate of hydrogen in the anode and the hydrogen partial pressure are proportional, the relationship between the two is expressed as: (6) Where, K an is the valve characteristic constant; M H2 is the molar mass of hydrogen; K H2 is the molar constant of hydrogen.

[0044] By combining formulas (1), (2), (4) and (6), we can obtain: (7) Where, is the hydrogen gas response time.

[0045] When the theoretical maximum output electromotive force takes various voltage losses into account, the expression for the actual fuel cell output voltage can be obtained: (8) Where, BLni, rI FC 、m ( exp ( ni)) represent polarization overvoltage loss, ohmic voltage loss and concentration voltage loss respectively; N 0 is the number of fuel cells connected in series.

[0046] The utilization rate of a hydrogen-oxygen fuel cell is defined as the ratio of the hydrogen flow rate involved in the electrochemical reaction to the total input flow rate, as expressed by: (9) According to formula (4), it can also be defined as (10) In the traditional model, the output voltage of the DC / AC inverter ( V ac ) can be controlled by the modulation index and the phase angle of the output AC voltage, then: (11) In the formula δ is the inverter modulation coefficient; V cell is the fuel cell output voltage. Figure 1 The fuel cell topology diagram in the figure can be used to obtain the output active power of the hydrogen and oxygen fuel cell ( P ac ) and reactive power ( Q ) is expressed as: (12) (13) Where, V s is the load terminal voltage; X is the line reactance; in order to obtain the relationship between the required power value and the hydrogen fuel flow rate injected into the fuel cell stack, this embodiment adopts a simplified model of the power inverter. Assuming that the inverter does not produce losses, the input of the inverter ( P dc ) and output power ( P ac ) The following relationship exists: (14) From formula (4) and formula (9), we can get the following relationship between the flow rate of hydrogen and the fuel cell current: (15) Combining (12), (14) and (15) we can get: (16) In order to solve the dynamic response hysteresis problem of traditional fuel cell control strategy, the control strategy of this embodiment is based on the dynamic adjustment of utilization factor, which defines the utilization factor βThe safety interval is 0.7≤ β ≤0.9, set in steady state β =0.8, dynamic adjustment when load suddenly changes β To improve the transient response speed, and to achieve the fuel cell active power and β The mapping control is achieved by allowing the utilization factor β Real-time adjustments within its safe range (0.7-0.9) effectively address the fuel cell system's response delay during sudden load changes. The optimal value of the utilization factor under steady-state conditions is set at 0.8. The core objective of this control strategy is to establish a mapping between the utilization factor and the fuel cell system's active power, improving system transient performance by rationally adjusting the utilization factor.

[0047] Assume that the output power of the fuel cell can be adjusted by a factor k’ Changes occur, then: (17) Following formula (16), we get: (18) From formula (18), it can be seen that the change of the utilization factor within its safety range will affect the phase angle And the active output of the fuel cell, we can get the relationship between the fuel cell output power and utilization factor: (19) (20) (twenty one) It can be inferred that the output power of the hydrogen-oxygen fuel cell can be rapidly adjusted based on the amplitude in formula (21). Specifically, when the required frequency modulation power change exceeds 0.1125 per unit (Pu), the fuel cell's active power output can be rapidly changed within 0.1125 Pu. When the required frequency modulation power change is less than 0.1125 Pu, the fuel cell can quickly adjust its output power to meet the frequency modulation requirements.

[0048] The dynamic performance of a fuel cell can be divided into three stages. In the first stage, the fuel cell can change its power output rapidly. In this stage, its performance is similar to that of a conventional battery. In the second stage, the fuel cell slowly increases its power output until it reaches the required value. In the final stage, the utilization factor returns to the ideal value (0.8), and the fuel cell output power equals the power required by the load. Figure 2 As shown, Figure 2 (a) represents the control strategy when the required FM power change exceeds 0.1125 Pu. Figure 2(b) shows the control strategy when the required FM power change is less than 0.1125 Pu, where the limit of rapid output power change is represented by the red line.

[0049] According to formula (21), the utilization factor is changed by adjusting the ratio of the hydrogen flow rate participating in the electrochemical reaction to the total input flow rate. β , and adjust the inverter phase angle to achieve the fuel cell active power and utilization factor β Mapping control allows the fuel cell output power to change rapidly within its allowable range. If the step load change is less than 0.1125 per unit (Pu), the fuel cell's output power can quickly reach the load's required value as the utilization factor changes. If the step load change is greater than 0.1125 per unit (Pu), the fuel cell first achieves a rapid change in output power by changing the utilization factor. When the output power reaches the upper or lower limit defined by the utilization factor, the output power change is restricted to within the allowable range. At this point, the fuel cell's output power changes slowly and dynamically. Ultimately, the output power reaches the load's required power, and the utilization factor returns to its ideal value of 0.8. At this point, the fuel cell meets the load's power requirements while also ensuring its own normal operation.

[0050] Step S2 of this embodiment addresses the limitations of traditional frequency regulation control strategies by constructing a dynamic weight allocation model for virtual droop control and positive / negative virtual inertia control. This is a hybrid energy storage collaborative frequency regulation model based on a dynamic weight allocation mechanism, which adaptively adjusts the weight coefficient according to the frequency change stage (frequency deterioration stage, severe deterioration stage, and recovery stage).

[0051] The linear combination of traditional virtual droop control and virtual inertia control has a dynamic response mismatch problem during the transient frequency modulation process, which is specifically manifested as a reverse regulation effect in the initial stage of frequency recovery, eventually leading to a secondary frequency drop in the system.

[0052] In order to solve the above problems, the frequency regulation model of this embodiment introduces negative virtual inertia control with compensation characteristics, which can generate additional power instructions in the same direction as the system frequency change rate in the frequency recovery stage, and effectively enhance the regulation kinetic energy of the frequency recovery process by improving the dynamic response sensitivity of the energy storage system. Based on the dynamic characteristics of different frequency regulation stages, a weight distribution primary frequency regulation model including positive / negative virtual inertia control is constructed, and virtual droop control is combined with positive and negative virtual inertia control. The weight coefficients are distributed accordingly according to the different frequency regulation stages to obtain the total output of the hybrid energy storage primary frequency regulation. By integrating the technical advantages of virtual droop control and virtual inertia control, a collaborative control mechanism is established in which the output weight is dynamically adjusted with the frequency deviation, so as to achieve effective suppression of grid frequency fluctuations under the same energy storage capacity. The model formula is as follows: (twenty two) In the formula, the total output of the hybrid energy storage primary frequency regulation is ΔP , ΔP M and ΔP K They are virtual inertia control output and virtual droop control output, α 1 and α 2 are the weight coefficients of virtual inertia control and virtual droop control respectively. According to the principles of virtual droop control and positive and negative virtual inertia control, we can get: (twenty three) (twenty four) Where, Δ f is the frequency change; M is the virtual inertia control coefficient; K is the virtual droop control coefficient.

[0053] Figure 3 It is the process of dynamic change and regulation of power grid frequency. The frequency regulation process can be divided into three stages: frequency deterioration stage, severe deterioration stage and recovery stage. The weight coefficient is adaptively adjusted accordingly for different stages.

[0054] (1) Frequency deterioration stage, dΔf / dt * Δf >0 。

[0055] Pick Δf set is the critical value of the frequency deterioration stage and the severe frequency deterioration stage, Δf dead is the FM dead zone threshold, Δf m is the value when the frequency deteriorates the most. Δf dead |<| Δf |<| Δf set |, because the frequency is in the deterioration stage, the frequency change rate is large, set α 1> α 2. As time goes by, the proportion of droop virtual control gradually increases, and the proportion of droop inertia virtual control gradually decreases. The formula is as follows: (25) Frequency deterioration serious stage, when | Δf set |<| Δf |<| Δf m |time, this seasonα 1< α 2. The proportion of droop virtual control gradually increases and is greater than the proportion of droop inertia virtual control. The formula is as follows: (26) (2) Frequency recovery phase, dΔf / dt * Δf <0 。

[0056] This season α 1< α 2， And as the frequency increases, the proportion of virtual droop control increases and the proportion of virtual inertia control decreases. The formula is as follows: (27) In this embodiment, step S3 is used to combine the fuel cell control system constructed in step S1 with the primary frequency regulation integrated control strategy proposed in step S2 to improve the primary frequency fluctuation of the power grid and optimize the power allocation priority between the fuel cell and different energy storage batteries (such as sodium ion batteries and all-vanadium redox flow batteries). The specific workflow is as follows: Figure 4 As shown, including: S101) Detect the frequency deviation of the power grid, specifically by using the energy management system to detect the frequency deviation of the power grid Δf ; S102) If the absolute value of the frequency deviation is greater than the absolute value of the threshold of the frequency regulation dead zone, based on the primary frequency regulation integrated control strategy constructed in step S2, the current frequency regulation stage is determined according to the frequency deviation and the total frequency regulation power of the current frequency regulation stage is calculated; if the absolute value of the frequency deviation is less than the absolute value of the threshold of the frequency regulation dead zone, the frequency regulation action is not performed and the frequency deviation of the power grid is continuously detected; In step S102, determining the current frequency modulation stage according to the frequency deviation includes: calculate dΔf / dt * Δf ,in Δf is the frequency deviation, dΔf / dt represents the derivative of the frequency deviation; If the calculated result is less than zero, the current frequency modulation stage is the frequency recovery stage; If the calculated result is greater than zero, the absolute value of the frequency deviation | Δf |Absolute value of the threshold of the FM dead zone| Δ f dead |, absolute values ​​of the preset critical values ​​of the frequency deterioration stage and the frequency deterioration severe stage| Δf set |and the absolute value of the value at the worst frequency degradation| Δf m |Compare; If |Δf dead |<| Δf |<| Δf set |, the current frequency modulation stage is the frequency deterioration stage; If | Δf set |<| Δf |<| Δf m |, the current frequency modulation stage is a stage of severe frequency deterioration.

[0057] like Figure 5 As shown, when calculating the total frequency modulation power of the current frequency modulation stage, specifically, according to the current frequency modulation stage, the weight coefficients of the virtual inertia control and the virtual droop control in the frequency modulation model are calculated, and then the calculation results are substituted into the frequency modulation model corresponding to formulas (22) to (24) in the previous article to obtain the total frequency modulation power of the current frequency modulation stage. According to the current frequency modulation stage, when calculating the weight coefficients of the virtual inertia control and the virtual droop control in the frequency modulation model, it includes: If the current frequency modulation stage is the frequency deterioration stage, the weight coefficients of virtual inertia control and virtual droop control are calculated using the formula (25) above; If the current frequency modulation stage is a stage of severe frequency deterioration, the weight coefficients of virtual inertia control and virtual droop control are calculated using the above formula (26); If the current frequency modulation stage is the frequency recovery stage, the weight coefficients of virtual inertia control and virtual droop control are calculated using the previous formula (27).

[0058] S103) If the absolute value of the total frequency-modulated power is less than a specified value, based on the fuel cell control strategy constructed in step S1, the utilization factor of the fuel cell is adjusted to perform frequency modulation until the output of the fuel cell reaches the absolute value of the total frequency-modulated power; As can be seen from step S1, similar to batteries, fuel cells can quickly adjust to 11.25% of their rated power. Therefore, in step S103 of this embodiment, 11.25% of the fuel cell's rated power is used as the designated value, and the hydrogen-oxygen fuel cell is preferentially used to respond to the rapid frequency modulation requirement. When load fluctuations cause frequency fluctuations, the hybrid energy storage primary frequency modulation integrated control strategy in step S2 determines the absolute value of the power required for frequency modulation. ΔP | is less than 11.25% of the fuel cell's rated power, i.e. | ΔP |<0.1125* P rate,FC At this time, only the fuel cell utilization factor is changed to meet the frequency modulation demand, and the formula is as follows: (28) Where, ΔP FC, P na , P VRB Represent the total output of hydrogen-oxygen fuel cells, sodium-ion batteries and all-vanadium redox flow batteries respectively.

[0059] As mentioned above, the utilization factor can be changed by reasonably controlling the hydrogen flow rate of the fuel cell. After changing the utilization factor, the dynamic response performance of the fuel cell can be significantly improved. If the absolute value of the total frequency modulation power is less than the specified value, the utilization factor of the fuel cell is adjusted for frequency modulation. Specifically, when the total frequency modulation power is greater than 0, the utilization factor of the fuel cell is increased by increasing the hydrogen flow rate and increasing the ratio of the hydrogen flow rate participating in the electrochemical reaction to the total input flow rate. When the total frequency modulation power is less than 0, the utilization factor of the fuel cell is reduced by reducing the hydrogen flow rate and reducing the ratio of the hydrogen flow rate participating in the electrochemical reaction to the total input flow rate, so that the output power of the fuel cell quickly reaches the target value, that is, the power value required for frequency modulation. ΔP |.

[0060] S104) If the absolute value of the total frequency-modulated power is greater than the specified value, based on the fuel cell control strategy constructed in step S1, the utilization factor of the fuel cell is adjusted to perform frequency modulation, and the charge and discharge weights of the energy storage battery are adjusted in real time according to the state of charge of the energy storage battery to perform frequency modulation until the output of the fuel cell reaches the specified value and the sum of the output of the fuel cell and the output of the energy storage battery reaches the absolute value of the total frequency-modulated power.

[0061] When the required power value | ΔP |>0.1125* P rate,FC When the sodium ion battery and the all-vanadium flow battery participate in the action, the formula is as follows: (29) If the absolute value of the total frequency modulation power is greater than the specified value, the utilization factor of the fuel cell is adjusted for frequency modulation. Specifically, when the total frequency modulation power is greater than 0, the utilization factor of the fuel cell is increased by increasing the hydrogen flow rate and improving the ratio of the hydrogen flow rate participating in the electrochemical reaction to the total input flow, until the utilization factor upper limit of 0.9 is reached. When the total frequency modulation power is less than 0, the utilization factor of the fuel cell is reduced by reducing the hydrogen flow rate and reducing the ratio of the hydrogen flow rate participating in the electrochemical reaction to the total input flow, until the utilization factor lower limit of 0.7 is reached, so that the output power of the fuel cell quickly reaches the target value, that is, the power value required for frequency modulation. ΔP|nearby, the mapping control of the fuel cell active power and β is achieved by adjusting the inverter phase angle, and the ratio of the hydrogen flow rate participating in the electrochemical reaction to the total input flow rate is adjusted. While keeping the utilization factor of the fuel cell at the upper or lower limit value, the output power of the fuel cell slowly reaches the target value, and finally the utilization factor of the fuel cell is adjusted from the upper or lower limit value to the ideal value.

[0062] For FM required power value | ΔP Any power exceeding the specified value is supplemented by the energy storage battery. This embodiment proposes an optimized control strategy based on coordinated state of charge (SOC) regulation, targeting the operational characteristics of a hybrid sodium-ion battery and all-vanadium flow battery energy storage system. This strategy monitors the charge and discharge power of the energy storage unit in real time. If power exceeds the limit, it is allocated at maximum power, with the remaining power being taken up by other batteries, ensuring total power balance and a safe SOC range.

[0063] Given that both energy storage media experience significant capacity decay under deep cycling conditions, and that overcharge / overdischarge not only accelerates device degradation but also potentially triggers chain reactions such as grid power fluctuations, this strategy divides energy storage units into the following three operating modes: Over-discharge zone: SOC ≤10%, only charge but not discharge Normal operating range: 20%<SOC ≤90% normal charge and discharge Overcharge zone: SOC>95% only discharges but not charges When frequency modulation is performed by adjusting the charge and discharge weight of the energy storage battery in real time according to the state of charge of the energy storage battery, it specifically includes: Obtain the state of charge of each energy storage battery, calculate the charging or discharging weight of each energy storage battery according to the state of charge, and then calculate the charging or discharging power requirement of each energy storage battery according to the charging or discharging weight of each energy storage battery. The calculation formula is as follows: If the total FM power ΔP Greater than zero, indicating that the battery pack is in a discharging state: (30) (31) In the above formula, SOC na 、 SOC VRB represent the state of charge of sodium ion battery and all-vanadium flow battery respectively, SOC min 、 SOC max Represent the minimum and maximum state of charge, W na,d 、 W VRB,dRepresents the discharge weights of sodium ion batteries and all-vanadium redox flow batteries respectively. If the state of charge of the sodium ion battery or all-vanadium redox flow battery is less than the over-discharge threshold, the discharge weight of the sodium ion battery or all-vanadium redox flow battery is 0 (no more discharge). P na,d 、 P VRB,d are the discharge powers of sodium ion batteries and all-vanadium flow batteries, respectively. P battery Indicates the difference between the absolute value of the total FM power and the specified value; If the total FM power ΔP Less than zero, indicating that the battery pack is in charging state: (32) (33) In the above formula, SOC na 、 SOC VRB represent the state of charge of sodium ion battery and all-vanadium flow battery respectively, SOC min 、 SOC max Represent the minimum and maximum state of charge, W na,c 、 W VRB,c Represents the charging weights of sodium ion batteries and all-vanadium redox flow batteries respectively. If the state of charge of the sodium ion battery or all-vanadium redox flow battery is greater than the overcharge threshold, the charging weight of the sodium ion battery or all-vanadium redox flow battery is 0 (no longer charged). P na,c 、 P VRB,c are the charging powers of sodium-ion batteries and all-vanadium flow batteries, respectively. P battery Indicates the difference between the absolute value of the total FM power and the specified value; During its operation, it checks in real time whether the charging and discharging power exceeds the maximum power limit. If the current charging or discharging power requirement of the energy storage battery exceeds the current charging or discharging power maximum value of the energy storage battery, the charging or discharging power of the current energy storage battery is adjusted to the maximum value. The difference between the current charging or discharging power requirement and the maximum value is calculated to obtain the remaining power, and the remaining power is distributed to the remaining energy storage batteries to ensure that the total distributed power is equal to the input power (meeting power balance). At the same time, the battery is kept operating within a safe SOC range, effectively utilizing the characteristics of the two batteries and extending the system life.

[0064] Example 2 This embodiment proposes a hybrid energy storage frequency regulation optimization system based on dynamic response and SOC collaboration, including a processor and a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is executed by the processor to implement the steps of the hybrid energy storage frequency regulation optimization method based on dynamic response and SOC collaboration described in Example 1.

[0065] In summary, the present invention proposes a hybrid energy storage frequency modulation optimization method and system based on dynamic response and SOC coordination, which dynamically adjusts the utilization factor of hydrogen and oxygen fuel cells and quickly adjusts the output power when the load suddenly changes, solving the problem of traditional fixed β The fuel supply and demand imbalance caused by the value is improved, which increases the response speed of the fuel cell.

[0066] The present invention integrates virtual droop control and positive / negative virtual inertia control, dynamically allocates weight coefficients according to the frequency deterioration and recovery stages, suppresses the reverse regulation effect caused by traditional linear combination, reduces the secondary frequency drop amplitude, and improves the frequency modulation effect.

[0067] The present invention sets an SOC collaborative management strategy to divide the area into an over-discharge zone (SOC ≤ 10%), a normal operating zone (20% < SOC ≤ 90%) and an overcharge zone (SOC > 95%), dynamically allocates charge and discharge weights, avoids overcharge / over-discharge behavior, and extends the cycle life of sodium-ion batteries and all-vanadium redox flow batteries.

[0068] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiment. All technical solutions based on the concept of the present invention are within the scope of protection of the present invention. It should be noted that for those skilled in the art, various improvements and modifications that do not depart from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A hybrid energy storage frequency modulation optimization method based on dynamic response and SOC coordination, characterized in that: The following steps are involved: Detect frequency deviation of the power grid; If the absolute value of the frequency deviation is greater than the absolute value of the threshold of the frequency modulation dead zone, the current frequency modulation stage is determined according to the frequency deviation and the total frequency modulation power of the current frequency modulation stage is calculated; If the absolute value of the total frequency modulation power is less than the specified value, the utilization factor of the fuel cell is adjusted to perform frequency modulation until the output of the fuel cell reaches the absolute value of the total frequency modulation power; If the absolute value of the total frequency modulation power is greater than the specified value, the utilization factor of the fuel cell is adjusted for frequency modulation, and the charge and discharge weights of the energy storage battery are adjusted in real time according to the charge state of the energy storage battery to perform frequency modulation until the output of the fuel cell reaches the specified value and the sum of the output of the fuel cell and the output of the energy storage battery reaches the absolute value of the total frequency modulation power.

2. The hybrid energy storage frequency modulation optimization method based on dynamic response and SOC coordination according to claim 1 is characterized in that: When determining the current frequency modulation stage based on the frequency deviation, it includes: calculate dΔf / dt*Δf ,in Δf is the frequency deviation, dΔf / dt represents the derivative of the frequency deviation; If the calculated result is less than zero, the current frequency modulation stage is the frequency recovery stage; If the calculated result is greater than zero, the absolute value of the frequency deviation | Δf |Absolute value of the threshold of the FM dead zone| Δf dead |, absolute values ​​of the preset critical values ​​of the frequency deterioration stage and the frequency deterioration severe stage| Δf set |and the absolute value of the value at the worst frequency degradation| Δf m |Compare; If | Δf dead |<| Δf |<| Δf set |, the current frequency modulation stage is the frequency deterioration stage; If | Δf set |<| Δf |<| Δf m |, the current frequency modulation stage is a stage of severe frequency deterioration.

3. The hybrid energy storage frequency modulation optimization method based on dynamic response and SOC coordination according to claim 1 is characterized in that: When calculating the total frequency modulation power of the current frequency modulation stage, the weight coefficients of the virtual inertia control and virtual droop control in the frequency modulation model are calculated according to the current frequency modulation stage, and then the calculation results are substituted into the frequency modulation model to obtain the total frequency modulation power of the current frequency modulation stage. The formula of the frequency modulation model is as follows: in, α 1 and α 2 are the weight coefficients of virtual inertia control and virtual droop control, ΔP is the total FM power, ΔP M and ΔP K They are virtual inertia control output and virtual droop control output, and the formulas are as follows: Among them, Δ f is the frequency change; M is the virtual inertia control coefficient; K is the virtual droop control coefficient.

4. The hybrid energy storage frequency modulation optimization method based on dynamic response and SOC coordination according to claim 3 is characterized in that: According to the current frequency regulation stage, the weight coefficients of virtual inertia control and virtual droop control in the frequency regulation model are calculated, including: If the current frequency modulation stage is the frequency recovery stage, the weight coefficient calculation formula of virtual inertia control and virtual droop control is as follows: If the current frequency modulation stage is the frequency deterioration stage, the weight coefficient calculation formula of virtual inertia control and virtual droop control is as follows: If the current frequency modulation stage is a stage of severe frequency deterioration, the weight coefficient calculation formula of virtual inertia control and virtual droop control is as follows: In the above formula, α 1 and α 2 are the weight coefficients of virtual inertia control and virtual droop control respectively.

5. The hybrid energy storage frequency modulation optimization method based on dynamic response and SOC coordination according to claim 1 is characterized in that: If the absolute value of the total frequency modulation power is less than the specified value, the utilization factor of the fuel cell is adjusted for frequency modulation. Specifically, when the total frequency modulation power is greater than 0, the utilization factor of the fuel cell is increased, and when the total frequency modulation power is less than 0, the utilization factor of the fuel cell is reduced, so that the output power of the fuel cell quickly reaches the target value.

6. The hybrid energy storage frequency modulation optimization method based on dynamic response and SOC coordination according to claim 1 is characterized in that: If the absolute value of the total frequency modulation power is greater than the specified value, the utilization factor of the fuel cell is adjusted for frequency modulation. Specifically, when the total frequency modulation power is greater than 0, the utilization factor of the fuel cell is increased until it reaches the upper limit value. When the total frequency modulation power is less than 0, the utilization factor of the fuel cell is reduced until it reaches the lower limit value, so that the output power of the fuel cell quickly reaches near the target value, and then the inverter phase angle is adjusted and the utilization factor of the fuel cell is maintained at the upper limit value or the lower limit value, so that the output power of the fuel cell slowly reaches the target value, and finally the utilization factor of the fuel cell is adjusted from the upper limit value or the lower limit value to the ideal value.

7. The hybrid energy storage frequency modulation optimization method based on dynamic response and SOC coordination according to claim 6 is characterized in that: The specified value is 0.1125* P rate,FC , the upper limit is 0.9 and the lower limit is 0.7, where P rate,FC is the rated power of the fuel cell.

8. The hybrid energy storage frequency modulation optimization method based on dynamic response and SOC coordination according to claim 1 is characterized in that: When frequency modulation is performed by adjusting the charge and discharge weight of the energy storage battery in real time according to the state of charge of the energy storage battery, it specifically includes: Obtaining the state of charge of each energy storage battery, calculating the charging or discharging weight of each energy storage battery according to the state of charge, and then calculating the charging or discharging power requirement value of each energy storage battery according to the charging or discharging weight of each energy storage battery; If the current charging or discharging power requirement of the energy storage battery exceeds the current charging or discharging power maximum value of the energy storage battery, the charging or discharging power of the current energy storage battery is adjusted to the maximum value, and the difference between the current charging or discharging power requirement and the maximum value is calculated to obtain the remaining power, and the remaining power is distributed to the remaining energy storage batteries.

9. The hybrid energy storage frequency modulation optimization method based on dynamic response and SOC coordination according to claim 8 is characterized in that: The energy storage batteries include sodium ion batteries and all-vanadium redox flow batteries. The charging or discharging weight of each energy storage battery is calculated according to the state of charge, and then the charging or discharging power requirement of each energy storage battery is calculated according to the charging or discharging weight of each energy storage battery. The calculation formula is as follows: If the total FM power is greater than zero: In the above formula, SOC na 、 SOC VRB represent the state of charge of sodium ion battery and all-vanadium flow battery respectively, SOC min 、 SOC max Represent the minimum and maximum state of charge, W na,d 、 W VRB,d Respectively represent the discharge weights of sodium ion batteries and all-vanadium redox flow batteries. If the state of charge of the sodium ion battery or all-vanadium redox flow battery is less than the over-discharge threshold, the discharge weight of the sodium ion battery or all-vanadium redox flow battery is 0. P na,d 、 P VRB,d are the discharge powers of sodium ion batteries and all-vanadium flow batteries, respectively. P battery Indicates the difference between the absolute value of the total FM power and the specified value; If the total FM power is less than zero: In the above formula, SOC na 、 SOC VRB represent the state of charge of sodium ion battery and all-vanadium flow battery respectively, SOC min 、 SOC max Represent the minimum and maximum state of charge, W na,c 、 W VRB,c Represent the charging weights of sodium ion batteries and all-vanadium redox flow batteries respectively. If the state of charge of the sodium ion battery or all-vanadium redox flow battery is greater than the overcharge threshold, the charging weight of the sodium ion battery or all-vanadium redox flow battery is 0. P na,c 、 P VRB,c are the charging powers of sodium-ion batteries and all-vanadium flow batteries, respectively. P battery Indicates the difference between the absolute value of the total FM power and the specified value.

10. A hybrid energy storage frequency regulation optimization system based on dynamic response and SOC coordination, characterized in that: The method comprises a processor and a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is executed by the processor to implement the steps of the hybrid energy storage frequency regulation optimization method based on dynamic response and SOC coordination as described in any one of claims 1 to 9.

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