Power grid primary frequency modulation control method capable of flexibly driving energy storage groups

Abstract

The invention belongs to the technical field of power grid frequency modulation, and relates to a power grid primary frequency modulation control method based on energy storage grouping flexible driving, which comprises the following steps: (1) establishing an energy storage grouping frequency modulation model, (2) setting energy storage equipment output, (3) calculating a virtual inertia output coefficient and a virtual droop output coefficient, (4) calculating an inertia control coefficient and a droop control coefficient, and (5) calculating an inertia control coefficient and a droop control coefficient. (5) calculating a virtual inertia output ratio; (6) calculating an energy storage unbalance index; (7) introducing an equalization factor and secondarily correcting the output of the energy storage equipment; and (8) judging whether to exchange the charging and discharging tasks of the energy storage equipment. The method has the advantages that (1) an energy storage grouping frequency modulation model is established, frequent and shallow charge-discharge circulation of energy storage is avoided, and the energy storage runs at a good discharge depth; (2) virtual inertia and droop control adaptive items are introduced, so that the adaptive capability of the energy storage system is improved; and (3) an equalization factor is introduced, secondary correction is carried out on energy storage output, and the situation that energy storage charging and discharging are unbalanced is avoided.

Description

Technical Field

[0001] The invention relates to a primary frequency modulation control method for a power grid with flexible driving of energy storage groups, and belongs to the technical field of power grid frequency modulation. Background Art

[0002] my country is currently promoting the construction of a new power system, the core of which is to adapt to a power system dominated by renewable energy generation. As representatives of renewable energy, wind power generation and photovoltaic power generation have been increasing in their access to the power grid, and the volatility of their output power has brought great challenges to the frequency stability of the power grid system. Therefore, the development of effective power grid frequency regulation technology has become an urgent problem to be solved.

[0003] The application of energy storage systems in primary frequency regulation of power grids has been fully promoted. Battery energy storage systems have the advantages of rapid response and flexibility, which can effectively improve the stability of the power grid. Compared with traditional thermal power units, energy storage batteries can quickly respond to the frequency regulation signals of the power grid, effectively reduce the frequency fluctuations of the power grid, and have great potential in assisting thermal power units to participate in frequency regulation services.

[0004] Although energy storage systems can respond quickly to grid frequency fluctuations, due to their capacity limitations, they may not be able to continuously assist thermal power units in performing frequency regulation tasks when the grid system experiences long-term or large frequency deviations. At the same time, energy storage currently participates in grid frequency regulation, and frequent and shallow charge and discharge cycles are prone to occur during the frequency regulation process, resulting in a reduction in the life and utilization of energy storage, which increases the operating and maintenance costs of the energy storage system. Summary of the invention

[0005] In order to solve the deficiencies in the prior art, the purpose of the present invention is to provide a method for controlling the primary frequency regulation of a power grid with flexible driving of energy storage groups. The method is aimed at the primary frequency regulation scenario of the power grid. First, an energy storage group frequency regulation model is established, which includes two energy storage devices with the same capacity. Each energy storage device only performs charging or discharging tasks within a certain period of time. Then, the output of the energy storage device is set, and the virtual inertia output coefficient, virtual droop output coefficient, inertia control coefficient and droop control coefficient of the energy storage device are calculated. At the same time, inertia and droop adaptive items are added to improve the adaptive ability, and the virtual inertia output ratio is calculated using fuzzy control. Then, a balancing factor is introduced according to the energy storage imbalance index, and the output of the energy storage device is corrected twice to improve the charging and discharging imbalance problem. Finally, it is determined whether the state of charge (SOC) of the energy storage device reaches the limit value. If it reaches the limit value, the charging and discharging tasks of the two energy storage devices are exchanged, otherwise, they are not exchanged, and then the primary frequency regulation task is completed. The method avoids frequent and shallow charging and discharging cycles of energy storage devices, improves the adaptive ability, and improves the effect of primary frequency regulation of the power grid.

[0006] In order to achieve the above-mentioned invention object and solve the problems existing in the prior art, the technical solution adopted by the present invention is: a primary frequency modulation control method of a power grid with flexible drive of energy storage grouping, comprising the following steps:

[0007] Step 1: Establish an energy storage group frequency modulation model, including a first energy storage device and a second energy storage device with the same rated capacity, wherein the first energy storage device is an initial discharge energy storage device, and the second energy storage device is an initial charge energy storage device. When the energy storage group participates in the primary frequency modulation of the power grid, the first energy storage device and the second energy storage device can only perform continuous charging or discharging tasks, and the two energy storage devices cannot work at the same time;

[0008] Step 2: Set the output of the energy storage device. At any time during the time period when the first energy storage device and the second energy storage device participate in the primary frequency modulation of the power grid, set their output to be composed of a combination of virtual inertia control and virtual droop control methods. The output of the first energy storage device and the second energy storage device when participating in the primary frequency modulation of the power grid is described by formula (1).

[0009]

[0010] Where s is the Laplace operator, Contribute to energy storage equipment, It indicates the frequency modulation output obtained by the energy storage device through virtual inertia control. It represents the frequency modulation output obtained by the energy storage device through virtual droop control. is the virtual inertia output ratio, and are the virtual inertia output coefficient and virtual droop output coefficient of the energy storage device, is the grid frequency deviation;

[0011] Step 3: Calculate the virtual inertia output coefficient and virtual droop output coefficient, and calculate the virtual inertia output coefficient of the first and second energy storage devices. and virtual droop output coefficient , virtual inertia output coefficient It is composed of inertia control coefficient and inertia control adaptive term; virtual droop output coefficient It consists of the droop control coefficient and the droop control adaptive term, and specifically includes the following sub-steps:

[0012] (a) Calculate the virtual inertia output coefficient , which consists of the inertia control coefficient and the inertia control adaptive term, and is described by formula (2):

[0013] (2)

[0014] In the formula, is the inertia control coefficient, is the inertial control adaptive term, which is described by formula (3):

[0015] (3)

[0016] In the formula, is the inertial control adaptive coefficient, and , is the rate of change of grid frequency deviation;

[0017] (b) Calculate the virtual droop output coefficient , which consists of the droop control coefficient and the droop control adaptive term, and is described by formula (4):

[0018] (4)

[0019] In the formula, is the droop control coefficient, is the droop control adaptive term, which is described by formula (5):

[0020] (5)

[0021] In the formula, is the droop control adaptive coefficient, and , is the grid frequency deviation;

[0022] Step 4: Calculate the inertia control coefficient and the droop control coefficient, and calculate the inertia control coefficient of the first and second energy storage devices. and droop control coefficient To maintain the state of charge (SOC) of the first and second energy storage devices, the inertia control coefficients are adjusted according to their SOC and grid frequency deviation. and droop control coefficient Constraints are made to calculate the inertia control coefficients of the two during charging and discharging And the droop control coefficient , specifically including the following sub-steps:

[0023] (a) If , the energy storage device does not operate. , = ,in is the grid frequency deviation;

[0024] (b) If , the energy storage equipment fully assists the grid frequency regulation, , ,in is the maximum droop control coefficient of the first and second energy storage devices, and , is the maximum inertia control coefficient of the two, and ;

[0025] (c) If , the output of the energy storage device is constrained by its SOC. When the energy storage device is charging, , and its quantitative relationship with SOC is described by formula (6):

[0026] (6)

[0027] In the formula, The droop control coefficient when charging the first and second energy storage devices, is the maximum droop control coefficient of the two, is its minimum SOC, and , is its SOC median value, and , is its maximum SOC, and , is its SOC real-time value,

[0028] When the energy storage device is discharged, , and its quantitative relationship with SOC is described by formula (7):

[0029] (7)

[0030] In the formula, is the droop control coefficient when the first and second energy storage devices are discharged,

[0031] When the energy storage device is charging, , and its quantitative relationship with SOC is described by formula (8):

[0032] (8)

[0033] In the formula, Inertia control coefficient when charging the first and second energy storage devices, is the maximum inertia control coefficient of the two,

[0034] When the energy storage device is discharged, , and its quantitative relationship with SOC is described by formula (9):

[0035] (9)

[0036] In the formula, is the inertia control coefficient when the first and second energy storage devices are discharged;

[0037] (d) Using sub-steps (a) to (c) of step 4, according to the grid frequency deviation and the different charge and discharge states of the first and second energy storage devices, the inertia control coefficients of the two are obtained. And the droop control coefficient ;

[0038] Step 5: Calculate the virtual inertia output ratio. Use fuzzy control to calculate the virtual inertia output ratio (α). Set the input and output of the fuzzy controller and the domain of the input and output quantities. Determine the membership function of the input and output quantities, divide the domain, and obtain the virtual inertia output ratio according to the fuzzy rules and solution algorithm. Specifically, it includes the following sub-steps:

[0039] (a) Set the input of the fuzzy controller to the frequency deviation of the power grid system and its rate of change , the output is the output ratio of virtual inertia control (α), the domains of the two inputs of the fuzzy controller are set to [-1,1], the domain of the output is [-1,1], and the triangle membership function is used as the membership function to determine the input and output quantities;

[0040] (b) The input quantity domain is symmetrically divided into 7 fuzzy subsets {NB, NM, NS, Z, PS, PM, PB}, which respectively represent the input quantity grid system frequency deviation and its change rate as negative bias (NB), negative bias (NM), negative bias (NS), zero (Z), positive bias (PS), positive bias (PM), positive bias (PB);

[0041] (c) The domain of output quantity is symmetrically divided into 7 fuzzy subsets {NB, NM, NS, Z, PS, PM, PB}, indicating that the virtual inertial output ratio (α) of output quantity is negatively biased (NB), negatively biased (NM), negatively biased (NS), zero (Z), positively biased (PS), positively biased (PM), and positively biased (PB).

[0042] (d) Set the fuzzy rules as follows:

[0043]

[0044] According to the designed fuzzy logic rules, the solution is based on the Mamdani reasoning algorithm. The design of fuzzy rules takes into account virtual inertia and virtual droop control, as well as virtual negative inertia control. In the early stage of grid frequency change, a large output proportion (α) of virtual inertia control can effectively suppress the rapid change of grid frequency; in the frequency recovery stage, α is a negative value, that is, virtual negative inertia control, which can speed up the recovery of grid frequency;

[0045] Step 6: Calculate the energy storage imbalance index. The energy storage imbalance is described by formula (10):

[0046]

[0047] Where b is the energy storage imbalance, is the real-time SOC value of the first energy storage device, is the real-time SOC value of the second energy storage device, is the minimum SOC value of the first and second energy storage devices, and ; is the maximum SOC of the first and second energy storage devices, and ;

[0048] Step 7: Introduce the balancing factor and perform secondary correction on the output of the energy storage device. According to the energy storage imbalance, introduce the balancing factor and dynamically perform secondary correction on the output of the first and second energy storage devices. Add the balancing factor h to the output of the energy storage device, which is described by formula (11).

[0049]

[0050] Where s is the Laplace operator, Provide power for the 1st and 2nd energy storage devices, It represents the frequency modulation output obtained by the first and second energy storage devices through virtual inertia control. represents the frequency modulation output of the first and second energy storage devices obtained through virtual droop control, h is the balancing factor, is the virtual inertia output ratio, and are the virtual inertia output coefficient and virtual droop output coefficient of the first and second energy storage devices, respectively. is the grid frequency deviation, and the balancing factor h is described by formula (12):

[0051] (12)

[0052] In the formula, b is the energy storage imbalance index, is the grid frequency deviation;

[0053] Step 8: Determine whether to swap the energy storage device charging and discharging tasks, calculate the real-time SOC values ​​of the first and second energy storage devices, and determine whether they have reached the limit. The upper limit of the SOC of the first and second energy storage devices is 75%, and the lower limit is 25%. If the limit is reached, swap the charging and discharging tasks of the first and second energy storage devices, otherwise do not swap; finally complete the primary frequency modulation task of the power grid.

[0054] The beneficial effect of the present invention is: a primary frequency regulation control method for a power grid with flexible drive of energy storage grouping, comprising the following steps: (1) establishing an energy storage grouping frequency regulation model, (2) setting the output of energy storage equipment, (3) calculating the virtual inertia output coefficient and the virtual droop output coefficient (4) calculating the inertia control coefficient and the droop control coefficient, (5) calculating the virtual inertia output ratio, (6) calculating the energy storage imbalance index, (7) introducing a balancing factor, and correcting the output of the energy storage equipment for a second time, and (8) judging whether to exchange the charge and discharge tasks of the energy storage equipment. Compared with the prior art, the present invention has the following advantages: first, the present invention establishes an energy storage grouping frequency regulation model, avoids frequent and shallow charge and discharge cycles of energy storage, and enables energy storage to operate at a good discharge depth; second, the present invention introduces virtual inertia and droop control adaptive items, and improves the adaptive ability of the energy storage system; third, the present invention introduces a balancing factor according to the energy storage imbalance, and corrects the energy storage output for a second time, avoiding the imbalance of energy storage charge and discharge. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 It is a flow chart of the steps of the method of the present invention.

[0056] Figure 2 It is a schematic diagram of the energy storage group frequency modulation model.

[0057] Figure 3 This is a schematic diagram of adaptive adjustment of the output ratio of virtual inertia control based on fuzzy control.

[0058] Figure 4 It is a surface diagram of virtual inertia output ratio.

[0059] Figure 5 It is a schematic diagram of energy storage charging and discharging task switching. DETAILED DESCRIPTION

[0060] The present invention will be further described below in conjunction with the accompanying drawings.

[0061] like Figure 1 As shown, a method for controlling primary frequency regulation of a power grid with flexible driving of energy storage groups comprises the following steps:

[0062] Step 1: Establish a frequency modulation model for energy storage grouping, including the first energy storage device and the second energy storage device with the same rated capacity. The first energy storage device is an initial discharge energy storage device, and the second energy storage device is an initial charge energy storage device. When the energy storage group participates in the primary frequency modulation of the power grid, the first energy storage device and the second energy storage device can only perform continuous charging or discharging tasks, and the two energy storage devices cannot work at the same time at the same time. Figure 2 shown.

[0063] Step 2: Set the output of the energy storage device. At any time during the time period when the first energy storage device and the second energy storage device participate in the primary frequency modulation of the power grid, set their output to be composed of a combination of virtual inertia control and virtual droop control methods. The output of the first energy storage device and the second energy storage device when participating in the primary frequency modulation of the power grid is described by formula (1).

[0064]

[0065] Where s is the Laplace operator, Contribute to energy storage equipment, It indicates the frequency modulation output obtained by the energy storage device through virtual inertia control. It represents the frequency modulation output obtained by the energy storage device through virtual droop control. is the virtual inertia output ratio, and are the virtual inertia output coefficient and virtual droop output coefficient of the energy storage device, is the grid frequency deviation;

[0066] Step 3: Calculate the virtual inertia output coefficient and virtual droop output coefficient, and calculate the virtual inertia output coefficient of the first and second energy storage devices. and virtual droop output coefficient , virtual inertia output coefficient It is composed of inertia control coefficient and inertia control adaptive term; virtual droop output coefficient It consists of the droop control coefficient and the droop control adaptive term, and specifically includes the following sub-steps:

[0067] (a) Calculate the virtual inertia output coefficient , which consists of the inertia control coefficient and the inertia control adaptive term, and is described by formula (2):

[0068] (2)

[0069] In the formula, is the inertia control coefficient, is the inertial control adaptive term, which is described by formula (3):

[0070] (3)

[0071] In the formula, is the inertial control adaptive coefficient, and , is the rate of change of grid frequency deviation;

[0072] (b) Calculate the virtual droop output coefficient , which consists of the droop control coefficient and the droop control adaptive term, and is described by formula (4):

[0073] (4)

[0074] In the formula, is the droop control coefficient, is the droop control adaptive term, which is described by formula (5):

[0075] (5)

[0076] In the formula, is the droop control adaptive coefficient, and , is the grid frequency deviation;

[0077] Step 4: Calculate the inertia control coefficient and the droop control coefficient, and calculate the inertia control coefficient of the first and second energy storage devices. and droop control coefficient To maintain the state of charge (SOC) of the first and second energy storage devices, the inertia control coefficients are adjusted according to their SOC and grid frequency deviation. and droop control coefficient Constraints are made to calculate the inertia control coefficients of the two during charging and discharging And the droop control coefficient , specifically including the following sub-steps:

[0078] (a) If , the energy storage device does not operate. , = ,in is the grid frequency deviation;

[0079] (b) If , the energy storage equipment fully assists the grid frequency regulation, , ,in is the maximum droop control coefficient of the first and second energy storage devices, and , is the maximum inertia control coefficient of the two, and ;

[0080] (c) If , the output of the energy storage device is constrained by its SOC. When the energy storage device is charging, , and its quantitative relationship with SOC is described by formula (6):

[0081] (6)

[0082] In the formula, The droop control coefficient when charging the first and second energy storage devices, is the maximum droop control coefficient of the two, is its minimum SOC, and , is its SOC median value, and , is its maximum SOC, and , is its SOC real-time value,

[0083] When the energy storage device is discharged, , and its quantitative relationship with SOC is described by formula (7):

[0084] (7)

[0085] In the formula, is the droop control coefficient when the first and second energy storage devices are discharged,

[0086] When the energy storage device is charging, , and its quantitative relationship with SOC is described by formula (8):

[0087] (8)

[0088] In the formula, Inertia control coefficient when charging the first and second energy storage devices, is the maximum inertia control coefficient of the two,

[0089] When the energy storage device is discharged, , and its quantitative relationship with SOC is described by formula (9):

[0090] (9)

[0091] In the formula, is the inertia control coefficient when the first and second energy storage devices are discharged;

[0092] (d) Using sub-steps (a) to (c) of step 4, according to the grid frequency deviation and the different charge and discharge states of the first and second energy storage devices, the inertia control coefficients of the two are obtained. And the droop control coefficient ;

[0093] Step 5: Calculate the virtual inertia output ratio. Use fuzzy control to calculate the virtual inertia output ratio (α). Set the input and output of the fuzzy controller and the domain of the input and output quantities. Determine the membership function of the input and output quantities, divide its domain, and obtain the virtual inertia output ratio according to the fuzzy rules and solution algorithm, such as Figure 3 The specific steps include the following:

[0094] (a) Set the input of the fuzzy controller to the frequency deviation of the power grid system and its rate of change , the output is the output ratio of virtual inertia control (α), the domains of the two inputs of the fuzzy controller are set to [-1,1], the domain of the output is [-1,1], and the triangle membership function is used as the membership function to determine the input and output quantities;

[0095] (b) The input quantity domain is symmetrically divided into 7 fuzzy subsets {NB, NM, NS, Z, PS, PM, PB}, which respectively represent the input quantity grid system frequency deviation and its change rate as negative bias (NB), negative bias (NM), negative bias (NS), zero (Z), positive bias (PS), positive bias (PM), positive bias (PB);

[0096] (c) The domain of output quantity is symmetrically divided into 7 fuzzy subsets {NB, NM, NS, Z, PS, PM, PB}, indicating that the virtual inertial output ratio (α) of output quantity is negatively biased (NB), negatively biased (NM), negatively biased (NS), zero (Z), positively biased (PS), positively biased (PM), and positively biased (PB).

[0097] (d) Set the fuzzy rules as follows:

[0098]

[0099] According to the designed fuzzy logic rules, the solution is based on the Mamdani reasoning algorithm. The design of fuzzy rules takes into account virtual inertia and virtual droop control, as well as virtual negative inertia control. In the early stage of grid frequency change, a large output ratio (α) of virtual inertia control can effectively suppress the rapid change of grid frequency; in the frequency recovery stage, α is a negative value, that is, virtual negative inertia control, which can speed up the recovery of grid frequency; the output virtual inertia output ratio surface diagram of the fuzzy controller is as follows: Figure 4 shown.

[0100] Step 6: Calculate the energy storage imbalance index. The energy storage imbalance is described by formula (10):

[0101]

[0102] Where b is the energy storage imbalance, is the real-time SOC value of the first energy storage device, for

[0103] The real-time SOC value of the second energy storage device, is the minimum SOC value of the first and second energy storage devices, and ; is the maximum SOC of the first and second energy storage devices, and ;

[0104] Step 7: Introduce the balancing factor and make a secondary correction to the output of the energy storage device. Introduce the balancing factor according to the energy storage imbalance, dynamically make a secondary correction to the output of the first and second energy storage devices, and add the balancing factor h to the output of the energy storage device. This is described by formula (11).

[0105]

[0106] Where s is the Laplace operator, Provide power for the 1st and 2nd energy storage devices, It represents the frequency modulation output obtained by the first and second energy storage devices through virtual inertia control. represents the frequency modulation output of the first and second energy storage devices obtained through virtual droop control, h is the balancing factor, is the virtual inertia output ratio, and are the virtual inertia output coefficient and virtual droop output coefficient of the first and second energy storage devices, respectively. is the grid frequency deviation, and the balancing factor h is described by formula (12):

[0107] (12)

[0108] In the formula, b is the energy storage imbalance index, is the grid frequency deviation;

[0109] Step 8: Determine whether to swap the energy storage device charging and discharging tasks, calculate the real-time SOC values ​​of the first and second energy storage devices, and determine whether they have reached the limit. The upper limit of the SOC of the first and second energy storage devices is 75%, and the lower limit is 25%. If the limit is reached, swap the charging and discharging tasks of the first and second energy storage devices, otherwise do not swap. Figure 5 As shown, the primary frequency regulation task of the power grid is finally completed.

[0110] The advantages of the present invention are as follows: the present invention utilizes energy storage group frequency modulation to avoid frequent and shallow charge and discharge cycles of energy storage, enables energy storage to operate at a good discharge depth, introduces inertia and droop control adaptive items, improves the adaptive ability of the energy storage system, performs secondary correction on the energy storage output according to the energy storage imbalance, and avoids the imbalance of energy storage charge and discharge.

Claims

1. A method for controlling primary frequency modulation of a power grid with flexible driving of energy storage groups, characterized in that: The following steps are involved: Step 1: Establish an energy storage group frequency modulation model, including a first energy storage device and a second energy storage device with the same rated capacity, wherein the first energy storage device is an initial discharge energy storage device, and the second energy storage device is an initial charge energy storage device. When the energy storage group participates in the primary frequency modulation of the power grid, the first energy storage device and the second energy storage device can only perform continuous charging or discharging tasks, and the two energy storage devices cannot work at the same time; Step 2: Set the output of the energy storage device. At any time during the time period when the first energy storage device and the second energy storage device participate in the primary frequency modulation of the power grid, set their output to be composed of a combination of virtual inertia control and virtual droop control methods. The output of the first energy storage device and the second energy storage device when participating in the primary frequency modulation of the power grid is described by formula (1). ； Where s is the Laplace operator, Contribute to energy storage equipment, It indicates the frequency modulation output obtained by the energy storage device through virtual inertia control. It represents the frequency modulation output obtained by the energy storage device through virtual droop control. is the virtual inertia output ratio, and are the virtual inertia output coefficient and virtual droop output coefficient of the energy storage device, is the grid frequency deviation; Step 3: Calculate the virtual inertia output coefficient and virtual droop output coefficient, and calculate the virtual inertia output coefficient of the first and second energy storage devices. and virtual droop output coefficient , virtual inertia output coefficient It is composed of inertia control coefficient and inertia control adaptive term; virtual droop output coefficient It consists of the droop control coefficient and the droop control adaptive term, and specifically includes the following sub-steps: (a) Calculate the virtual inertia output coefficient , which consists of the inertia control coefficient and the inertia control adaptive term, and is described by formula (2): (2) In the formula, is the inertia control coefficient, is the inertial control adaptive term, which is described by formula (3): (3) In the formula, is the inertial control adaptive coefficient, and , is the rate of change of grid frequency deviation; (b) Calculate the virtual droop output coefficient , which consists of the droop control coefficient and the droop control adaptive term, and is described by formula (4): (4) In the formula, is the droop control coefficient, is the droop control adaptive term, which is described by formula (5): (5) In the formula, is the droop control adaptive coefficient, and , is the grid frequency deviation; Step 4: Calculate the inertia control coefficient and the droop control coefficient, and calculate the inertia control coefficient of the first and second energy storage devices. and droop control coefficient To maintain the state of charge (SOC) of the first and second energy storage devices, the inertia control coefficients are adjusted according to their SOC and grid frequency deviation. and droop control coefficient Constraints are made to calculate the inertia control coefficients of the two during charging and discharging And the droop control coefficient , specifically including the following sub-steps: (a) If , the energy storage device does not operate. , = ,in is the grid frequency deviation; (b) If , the energy storage equipment fully assists the grid frequency regulation, , ,in is the maximum droop control coefficient of the first and second energy storage devices, and , is the maximum inertia control coefficient of the two, and ; (c) If , the output of the energy storage device is constrained by its SOC. When the energy storage device is charging, , and its quantitative relationship with SOC is described by formula (6): (6) In the formula, The droop control coefficient when charging the first and second energy storage devices, is the maximum droop control coefficient of the two, is its minimum SOC, and , is its SOC median value, and , is its maximum SOC, and , is the real-time value of SOC, When the energy storage device is discharged, , and its quantitative relationship with SOC is described by formula (7): (7) In the formula, is the droop control coefficient when the first and second energy storage devices are discharged, When the energy storage device is charging, , and its quantitative relationship with SOC is described by formula (8): (8) In the formula, Inertia control coefficient when charging the first and second energy storage devices, is the maximum inertia control coefficient of the two, When the energy storage device is discharged, , and its quantitative relationship with SOC is described by formula (9): (9) In the formula, is the inertia control coefficient when the first and second energy storage devices are discharged; (d) Using sub-steps (a) to (c) of step 4, according to the grid frequency deviation and the different charge and discharge states of the first and second energy storage devices, the inertia control coefficients of the two are obtained. And the droop control coefficient ; Step 5: Calculate the virtual inertia output ratio. Use fuzzy control to calculate the virtual inertia output ratio (α). Set the input and output of the fuzzy controller and the domain of the input and output quantities. Determine the membership function of the input and output quantities, divide the domain, and obtain the virtual inertia output ratio according to the fuzzy rules and solution algorithm. Specifically, it includes the following sub-steps: (a) Set the input of the fuzzy controller to the frequency deviation of the power grid system and its rate of change , the output is the output ratio of virtual inertia control (α), the domains of the two inputs of the fuzzy controller are set to [-1,1], the domain of the output is [-1,1], and the triangular membership function is used as the membership function to determine the input and output quantities; (b) The input quantity domain is symmetrically divided into 7 fuzzy subsets {NB, NM, NS, Z, PS, PM, PB}, which respectively represent the input quantity grid system frequency deviation and its change rate as negative bias (NB), negative bias (NM), negative bias (NS), zero (Z), positive bias (PS), positive bias (PM), positive bias (PB); (c) The domain of output quantity is symmetrically divided into 7 fuzzy subsets {NB, NM, NS, Z, PS, PM, PB}, indicating that the virtual inertial output ratio (α) of output quantity is negatively biased (NB), negatively biased (NM), negatively biased (NS), zero (Z), positively biased (PS), positively biased (PM), and positively biased (PB). (d) Set the fuzzy rules as follows: ； According to the designed fuzzy logic rules, the solution is based on the Mamdani reasoning algorithm. The design of fuzzy rules takes into account virtual inertia and virtual droop control, as well as virtual negative inertia control. In the early stage of grid frequency change, a large output proportion (α) of virtual inertia control can effectively suppress the rapid change of grid frequency; in the frequency recovery stage, α is a negative value, that is, virtual negative inertia control, which can speed up the recovery of grid frequency; Step 6: Calculate the energy storage imbalance index. The energy storage imbalance is described by formula (10): ； Where b is the energy storage imbalance, is the real-time SOC value of the first energy storage device, is the real-time SOC value of the second energy storage device, is the minimum SOC value of the first and second energy storage devices, and ; is the maximum SOC of the first and second energy storage devices, and ; Step 7: Introduce the balancing factor and make a secondary correction to the output of the energy storage device. Introduce the balancing factor according to the energy storage imbalance, dynamically make a secondary correction to the output of the first and second energy storage devices, and add the balancing factor h to the output of the energy storage device. This is described by formula (11). ； Where s is the Laplace operator, Provide power for the 1st and 2nd energy storage devices, It represents the frequency modulation output obtained by the first and second energy storage devices through virtual inertia control. represents the frequency modulation output of the first and second energy storage devices obtained through virtual droop control, h is the balancing factor, is the virtual inertia output ratio, and are the virtual inertia output coefficient and virtual droop output coefficient of the first and second energy storage devices, respectively. is the grid frequency deviation, and the balancing factor h is described by formula (12): (12) In the formula, b is the energy storage imbalance index, is the grid frequency deviation; Step 8: Determine whether to swap the energy storage device charging and discharging tasks, calculate the real-time SOC values ​​of the first and second energy storage devices, and determine whether they have reached the limit. The upper limit of the SOC of the first and second energy storage devices is 75%, and the lower limit is 25%. If the limit is reached, swap the charging and discharging tasks of the first and second energy storage devices, otherwise do not swap; finally complete the primary frequency modulation task of the power grid.

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