Active scheduling method for energy storage system based on power prediction

Abstract

The invention discloses an active scheduling method for an energy storage system based on power prediction, relates to the field of energy storage system scheduling, and aims to predict load, energy storage, network access and power abandoning conditions according to wind and light output in combination with various constraints, calculate the power abandoning quantity and record the moment when the power abandoning is generated. And calculating the energy storage capacity at the moment before the abandoned electricity is generated according to the abandoned electricity quantity in combination with energy storage related constraints. And calculating and updating the energy storage capacity, the charging power, the discharging power, the on-grid power and the off-grid power before the energy storage system generates the abandoned power by combining the measured value and the calculated value, and adjusting the scheduling of energy storage. The scheduling and power prediction functions of the energy storage system are linked, active scheduling of the energy storage system is realized, the abandoned power of the system can be reduced, the new energy utilization rate is improved, and the economic benefit is improved.

Description

Technical Field

[0001] The present invention relates to the field of energy storage system scheduling, and particularly to an active scheduling method for an energy storage system based on power prediction. Background Art

[0002] Integrated control platform systems with power prediction functions are configured for projects such as wind-solar-hydrogen production, to achieve the prediction of wind power and photovoltaic power output. Based on the prediction of wind-solar output, the hydrogen production load is regulated to achieve "load following the source", so as to improve the utilization rate of new energy. Considering the economy and safety of the project, the load will not be infinitely large or zero. When the wind-solar output is greater than the maximum load value, the energy storage is charged, and the part that cannot be consumed by the energy storage is considered to be fed into the grid, and the part that cannot be consumed by the grid will result in curtailment of electricity. When the wind-solar output is less than the minimum load value, the energy storage discharges, and the part that cannot be supplied by the energy storage is considered to be off-grid electricity. In this system, the main role of the energy storage system is peak shaving, but the scheduling strategy of the energy storage system is usually based on specific wind-solar output and load curves, and is optimized with the goal of optimal economy. In the optimized result of energy storage scheduling, the energy storage system usually charges when there is surplus output and at the trough of the electricity price, and discharges when there is insufficient output and at the peak of the electricity price, so as to improve the utilization rate of wind-solar and economic benefits. However, the characteristics of the hydrogen production load following the source are usually ignored in the optimization process, and the relevant constraints of the actual power grid are ignored. In the actual wind-solar-hydrogen production system, the energy storage system usually charges when there is surplus output and discharges when there is insufficient output, and the scheduling strategy is single and passive. Summary of the Invention

[0003] Aiming at the above deficiencies in the prior art, an active scheduling method for an energy storage system based on power prediction provided by the present invention solves the problems of single strategy and a lot of curtailment of electricity in the existing active scheduling method for an energy storage system.

[0004] In order to achieve the above invention purpose, the technical solution adopted by the present invention is as follows:

[0005] Provide an active scheduling method for an energy storage system based on power prediction, which includes the following steps:

[0006] S1. Predict the wind-solar output to obtain wind-solar output data;

[0007] S2. Based on the predicted wind-solar output data, combine the adjustable range and adjustable rate of the hydrogen production load to fit the hydrogen production load and obtain the hydrogen production load curve;

[0008] S3. Based on the predicted wind-solar output data, consider the energy storage capacity constraint and charge-discharge power constraint, and combine the current energy storage capacity to predict the change of the energy storage capacity and the charge-discharge power curve;

[0009] S4. Based on the predicted wind and solar power output data and the power balance of the entire energy storage system, predict the grid-connected power, grid-down power, and curtailed power.

[0010] S5. Determine whether there is a curtailment behavior according to the predicted result of the curtailed power. If so, go to step S6; otherwise, no scheduling is required.

[0011] S6. Statistically calculate the total daily curtailed power and record the initial moment when the curtailment occurs; calculate the maximum available energy storage capacity at the moment before the curtailment occurs if the curtailment is completely absorbed, considering the energy storage capacity constraint conditions.

[0012] S7. According to the maximum available energy storage capacity at the moment before the curtailment occurs, the grid-connected power, grid-down power, charging power, discharging power, and the predicted energy storage capacity at the two moments before the curtailment occurs, update the grid-connected power, grid-down power, charging power, discharging power at the moment before the curtailment occurs, and the maximum available energy storage capacity at the two moments before the curtailment occurs.

[0013] S8. Determine whether the predicted energy storage capacity at the two moments before the curtailment occurs is equal to the updated maximum available energy storage capacity at the two moments before the curtailment occurs. If so, obtain the active scheduling scheme for the energy storage system; otherwise, go to step S9.

[0014] S9. Update the moment before the curtailment occurs to the initial moment when the curtailment occurs, update the absolute value of the difference between the predicted energy storage capacity at the two moments before the curtailment occurs and the updated maximum available energy storage capacity at the two moments before the curtailment occurs to the total daily curtailed power, and return to step S6.

[0015] Provide an electronic device, which includes: a memory and a processor;

[0016] The memory is used to store computer execution instructions;

[0017] The processor is used to execute the computer execution instructions stored in the memory to implement the active scheduling method for the energy storage system based on power prediction.

[0018] Provide a storage medium, which includes: a readable storage medium and a computer program, and the computer program is used to implement the active scheduling method for the energy storage system based on power prediction.

[0019] The beneficial effects of the present invention are as follows: By linking the scheduling of the energy storage system with the power prediction function, the present invention realizes the active scheduling of the energy storage system, which can reduce the curtailment of the energy storage system, improve the utilization rate of new energy, and thus improve economic benefits. Description of the Drawings

[0020] Figure 1 It is a schematic flow chart of this method;

[0021] Figure 2 It is the production simulation curve before and after the active scheduling of energy storage in Case 1;

[0022] Figure 3 It is the production simulation curve before and after the active scheduling of energy storage in Case 2;

[0023] Figure 4 It is the production simulation curve before and after the active scheduling of energy storage in Case 3. Detailed implementation manners

[0024] The following describes the detailed implementation manners of the present invention to facilitate those skilled in the art of the present technology to understand the present invention. However, it should be clear that the present invention is not limited to the scope of the detailed implementation manners. For those ordinary skilled in the art of the present technology, as long as various changes are within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions and creations using the concept of the present invention are within the scope of protection.

[0025] As Figure 1 shown, the active scheduling method of the energy storage system based on power prediction includes the following steps:

[0026] S1. Predict the wind and light output to obtain wind and light output data;

[0027] S2. Based on the predicted wind and light output data, combine the adjustable range and adjustable rate of the hydrogen production load to fit the hydrogen production load and obtain the hydrogen production load curve;

[0028] S3. Based on the predicted wind and light output data, consider the energy storage capacity constraint and charge and discharge power constraint, and combine the current energy storage capacity to predict the change of the energy storage capacity and the charge and discharge power curve;

[0029] S4. Based on the predicted wind and light output data, and based on the power balance of the entire energy storage system, predict the grid-connected power, off-grid power and curtailed power;

[0030] S5. Judge whether there is a curtailment behavior according to the predicted result of the curtailed power. If so, go to step S6; otherwise, no scheduling is required;

[0031] S6. Statistically count the total curtailed power of the whole day and record the initial moment when the curtailment occurs; calculate the maximum available energy storage capacity at the moment before the curtailment occurs if the curtailment is completely absorbed under the condition of considering the energy storage capacity constraint;

[0032] S7. Update the grid-connected power, off-grid power, charging power, discharging power at the previous moment when curtailment occurs, and the maximum energy storage capacity at the two previous moments when curtailment occurs, based on the maximum energy storage capacity, grid-connected power, off-grid power, charging power, discharging power at the previous moment when curtailment occurs, and the predicted energy storage capacity at the two previous moments when curtailment occurs.

[0033] S8. Determine whether the predicted energy storage capacity at the two previous moments when curtailment occurs is equal to the updated maximum energy storage capacity at the two previous moments when curtailment occurs. If so, obtain the active scheduling scheme for the energy storage system; otherwise, proceed to step S9.

[0034] S9. Update the previous moment when curtailment occurs to the initial moment when curtailment occurs, update the absolute value of the difference between the predicted energy storage capacity at the two previous moments when curtailment occurs and the updated maximum energy storage capacity at the two previous moments when curtailment occurs to the all-day curtailment amount, and return to step S6.

[0035] In this embodiment, the prediction of wind and light output can be carried out using existing technologies. For example, the all-day wind data and light data can be obtained based on weather data, and then the wind and light output data can be obtained according to the wind power generation efficiency and photovoltaic conversion efficiency.

[0036] The expressions for the energy storage capacity constraint and the charge-discharge power constraint in step S3 are as follows:

[0037]

[0038]

[0039] Among them and are the energy storage capacity, the lower limit of the energy storage capacity, and the upper limit of the energy storage capacity at time t, respectively; is the energy storage capacity at time t - 1; is the charging power at time t; is the energy storage charging efficiency; is the discharging power at time t; is the energy storage discharging efficiency; is the charge-discharge power at time t. When is negative, it means that the energy storage system is charging at time t. When is positive, it means that the energy storage system is discharging at time t; is the upper limit of the discharging power; is the upper limit of the charging power.

[0040] The expression for the power balance of the entire energy storage system in step S4 is as follows:

[0041]

[0042] Among them is the power of the load at time t, that is, the hydrogen production power; is the output power of wind power at time t; is the output power of photovoltaic at time t; is the power of power grid connection at time t; is the power of power grid connection at time t; is the power of abandoned electricity at time t; and are the maximum power of power grid connection and the maximum power of power grid connection allowed by the power grid respectively; when abandoned electricity will occur.

[0043] The statistical expression of the total amount of abandoned electricity in step S6 is:

[0044]

[0045] where W EXS is the predicted total amount of abandoned electricity for the whole day.

[0046] The specific method for calculating the maximum energy storage capacity at the moment before the occurrence of abandoned electricity when considering the energy storage capacity constraint condition in step S6 includes the following steps:

[0047] S6-1. According to the formula:

[0048]

[0049] Calculate the maximum energy storage capacity at the moment before the occurrence of abandoned electricity where is the energy storage capacity at the initial moment of the predicted abandoned electricity; t1 represents the initial moment of the abandoned electricity;

[0050] S6-2. Judge whether it is greater than or equal to the lower limit of the energy storage capacity If so, go to step S6-3; otherwise, update the lower limit of the energy storage capacity to the maximum energy storage capacity at the moment before the occurrence of abandoned electricity Go to step S7;

[0051] S6-3. Judge whether it is less than or equal to the upper limit of the energy storage capacity If so, go to step S7; otherwise, update the upper limit of the energy storage capacity to the maximum energy storage capacity at the moment before the occurrence of abandoned electricity Go to step S7.

[0052] The specific method for updating the grid-connected power, off-grid power, charging power, discharging power at the previous moment when curtailment occurs, and the maximum energy storage capacity at the two previous moments when curtailment occurs in step S7 includes the following steps:

[0053] S7-1. Determine the maximum energy storage capacity at the previous moment when curtailment occurs Whether it is less than or equal to the energy storage capacity at the two previous moments when curtailment occurs If so, go to step S7-2; otherwise, go to step S7-6;

[0054] S7-2. According to the formula:

[0055]

[0056] Obtain the updated discharging power at the previous moment when curtailment occurs Where when Is greater than the upper limit of discharging power Update the upper limit of discharging power To the discharging power at the previous moment when curtailment occurs

[0057] S7-3. According to the formula:

[0058]

[0059] Obtain the updated grid-connected power at the previous moment when curtailment occurs Where Is the output power of wind power at the previous moment when curtailment occurs; Is the output power of photovoltaic power at the previous moment when curtailment occurs; Is the power of the load at the previous moment when curtailment occurs; when Is greater than Update To the grid-connected power at the previous moment when curtailment occurs And go to step S7-4; otherwise, directly go to step S7-5;

[0060] S7-4. According to the formula:

[0061]

[0062] Obtain the updated discharging power at the previous moment when curtailment occurs

[0063] S7-5. According to the formula:

[0064]

[0065] Obtain the updated maximum energy storage capacity at the two previous moments when curtailment occurs Enter step S8;

[0066] S7-6. According to the formula:

[0067]

[0068] Obtain the updated charging power at the previous moment when curtailment occurs where when is greater than then update to the charging power at the previous moment when curtailment occurs

[0069] S7-7. According to the formula:

[0070]

[0071] Obtain the updated grid connection power at the previous moment when curtailment occurs where when is greater than then update to the grid connection power at the previous moment when curtailment occurs and enter step S7-8; otherwise, directly enter step S7-9;

[0072] S7-8. According to the formula:

[0073]

[0074] Obtain the updated charging power at the previous moment when curtailment occurs

[0075] S7-9. According to the formula:

[0076]

[0077] Obtain the maximum available energy storage capacity at the two previous moments when curtailment occurs Enter step S8. In this embodiment, the discharge power is calculated based on the energy storage capacity at the previous moment and the two previous moments, and the discharge power needs to consider the upper limit of the energy storage discharge power. The electricity discharged from the energy storage is used for grid connection, and there is a limit on the grid connection power. If the grid connection power limit is exceeded, the energy storage discharge power needs to be reduced. Therefore, the upper limit of the energy storage discharge power and the upper limit of the grid connection power are considered as two constraint conditions to measure the energy storage discharge power.

[0078] In this embodiment, the charging power is calculated based on the energy storage capacity at the previous moment and the previous two moments, and the charging power needs to consider the upper limit of the energy storage charging power. If the energy storage capacity at the previous moment is greater than that at the previous two moments, the energy storage is in the charging state at the previous moment (t1-1). Now the energy storage does not need to charge so much, and the part originally used for energy storage charging will be increased to the grid connection, and the limit of the grid connection power needs to be considered.

[0079] In the specific implementation process, this embodiment also provides an electronic device, which includes: a memory and a processor;

[0080] The memory is used to store computer execution instructions;

[0081] The processor is used to execute the computer execution instructions stored in the memory to implement the active scheduling method of the energy storage system based on power prediction.

[0082] In the specific implementation process, this embodiment also provides a storage medium, which includes: a readable storage medium and a computer program, and the computer program is used to implement the active scheduling method of the energy storage system based on power prediction.

[0083] In an embodiment of the present invention, the installed capacity of wind power is 300 MW; the installed capacity of photovoltaic is 200 MW; the electrochemical energy storage system uses lithium iron phosphate batteries with a capacity of 75 MW / 150 MWh, the upper limit of the energy storage capacity is 150 MWh, the lower limit of the energy storage capacity is 15 MWh, the self-cycle efficiency of the battery is 90%, and the inversion efficiency and rectification efficiency of the energy storage converter are both 95%; the maximum power consumption on the load side is 235 MW, the minimum power consumption is 32 MW, and the load is flexibly adjustable within this range; the maximum power of grid connection is 200 MW; the maximum power of grid disconnection is 200 MW. Using historical data as the basis, it is considered that the power prediction is completely accurate, and the influence brought by the power prediction accuracy is ignored to reflect the advantages of the scheduling strategy.

[0084] In this embodiment, the grid connection, grid disconnection, curtailment of electricity, and energy storage scheduling conditions under the unadjusted energy storage scheduling strategy are calculated by using historical data through HOMER Pro software. According to the curtailment of electricity situation, the active energy storage scheduling strategy of the present invention is implemented by using VBA, and various data are adjusted, and the adjusted grid connection, grid disconnection, curtailment of electricity, and energy storage scheduling conditions are output.

[0085] The moment when curtailment occurs within a day is usually at noon. At this time, the combined output of wind and solar is relatively large, the load reaches its maximum value, the energy storage capacity reaches its upper limit, the grid connection power reaches its maximum, and the excess part results in curtailment. Based on historical data, the annual grid connection power, curtailment amount, etc. are calculated. Under the original energy storage scheduling strategy, the annual curtailment amount of the system is approximately 2.2968 million kWh, and the annual grid connection power is approximately 98.9393 million kWh. By using the scheduling strategy described in the present invention to adjust the energy storage scheduling, after the adjustment, the annual curtailment amount of the system is approximately 0.2487 million kWh, and the annual grid connection power is approximately 100.6428 million kWh. By using the scheduling strategy described in the present invention to adjust the energy storage scheduling, the curtailment of the system can be reduced and the utilization rate of new energy can be improved.

[0086] In Case 1, the energy storage capacity has reached its maximum value at the moment immediately before curtailment occurs, and the curtailment amount can be completely absorbed by the energy storage scheduling. As Figure 2 shown, it is the production simulation curve before and after the active energy storage scheduling. Before curtailment occurs, by discharging the energy storage, the grid connection is increased so that the energy storage can absorb the curtailment when curtailment occurs. The production simulation data before and after the active energy storage scheduling is shown in Table 1.

[0087] Table 1

[0088]

[0089]

[0090]

[0091]

[0092] In Case 2, the energy storage capacity has reached its maximum value at the moment immediately before curtailment occurs, and the curtailment amount cannot be completely absorbed by the energy storage scheduling. As Figure 3 shown, it is the production simulation curve before and after the active energy storage scheduling. Before curtailment occurs, by discharging the energy storage, the grid connection is increased so that the energy storage can absorb as much curtailment as possible when curtailment occurs. The production simulation data before and after the active energy storage scheduling is shown in Table 2.

[0093] Table 2

[0094]

[0095]

[0096]

[0097]

[0098] In Case 3, the energy storage capacity has not reached its maximum value at the moment immediately before curtailment occurs, and the curtailment amount can be completely absorbed by the energy storage scheduling. As Figure 4As shown, it is the production simulation curve before and after the active scheduling of energy storage. Before the curtailment of electricity occurs, by adjusting the charging time and charging amount of the energy storage, the energy storage can absorb the curtailed electricity when the curtailment occurs. The production simulation data before and after the active scheduling of the energy storage are shown in Table 3.

[0099] Table 3

[0100]

[0101]

[0102]

[0103] In summary, the present invention predicts the load, energy storage, grid connection and disconnection, and curtailment situation according to the wind and light output combined with various constraints, calculates the curtailment amount and records the moment when the curtailment occurs, and calculates the energy storage capacity at the moment before the curtailment occurs according to the curtailment amount combined with the relevant constraints of the energy storage. Combining the measured value with the calculated value, the energy storage capacity, charging power, discharging power, grid connection power, and grid disconnection power of the energy storage system before the curtailment occurs are calculated and updated, and the scheduling of the energy storage is adjusted. By linking the scheduling of the energy storage system with the power prediction function, the present invention realizes the active scheduling of the energy storage system, which can reduce the curtailment of the system, improve the utilization rate of new energy, and improve the economic benefits.

Claims

1. An active scheduling method for an energy storage system based on power prediction, characterized in that, It includes the following steps: S1. Forecast the wind and light output to obtain wind and light output data; S2. Based on the predicted wind and light output data, combine the adjustable range and adjustable rate of the hydrogen production load to fit the hydrogen production load and obtain the hydrogen production load curve; S3. Based on the predicted wind and light output data, consider the energy storage capacity constraint and charge-discharge power constraint, and combine the current energy storage capacity to predict the change of energy storage capacity and the charge-discharge power curve; S4. Based on the predicted wind and light output data, predict the grid-connected power, off-grid power and curtailed power based on the power balance of the entire energy storage system; S5. Judge whether there is a curtailment behavior according to the predicted result of the curtailed power. If so, go to step S6; otherwise, no scheduling is required; S6. Statistically calculate the daily curtailed power and record the initial time when the curtailment occurs; calculate the maximum energy storage capacity at the moment before the curtailment occurs if the curtailment is completely absorbed under the condition of considering the energy storage capacity constraint; S7. According to the maximum energy storage capacity at the moment before the curtailment occurs, grid-connected power, off-grid power, charging power, discharging power and the energy storage capacity at the two moments before the predicted curtailment occurs, update the grid-connected power, off-grid power, charging power, discharging power at the moment before the curtailment occurs and the maximum energy storage capacity at the two moments before the curtailment occurs; S8. Judge whether the energy storage capacity at the two moments before the predicted curtailment occurs is equal to the updated maximum energy storage capacity at the two moments before the curtailment occurs. If so, obtain the active scheduling scheme of the energy storage system; otherwise, go to step S9; S9. Update the moment before the curtailment occurs to the initial time when the curtailment occurs, update the absolute value of the difference between the energy storage capacity at the two moments before the predicted curtailment occurs and the updated maximum energy storage capacity at the two moments before the curtailment occurs to the daily curtailed power, and return to step S6.

2. The method according to claim 1, wherein The expressions of the energy storage capacity constraint and charge-discharge power constraint in step S3 are: where and are the energy storage capacity, the lower limit of the energy storage capacity, and the upper limit of the energy storage capacity at time t, respectively; is the energy storage capacity at time t-1; is the charging power at time t; is the energy storage charging efficiency; is the discharging power at time t; is the energy storage discharging efficiency; is the charging and discharging power at time t. When is negative, it means that the energy storage system is charging at time t. When is positive, it means that the energy storage system is discharging at time t; is the upper limit of the discharging power; is the upper limit of the charging power.

3. The method according to claim 2, characterized in that, The expression of the power balance of the entire energy storage system in step S4 is: Among them is the power of the load at time t, i.e., the hydrogen production power; is the output power of wind power at time t; is the output power of photovoltaic power at time t; is the power of power flowing out of the grid at time t; is the power of power flowing into the grid at time t; is the power of curtailed electricity at time t; and are respectively the maximum power of power flowing out of the grid and the maximum power of power flowing into the grid allowed by the power grid; when occurs, curtailed electricity will be generated.

4. The method according to claim 3, characterized in that, The statistical expression of the daily curtailed power in step S6 is: Among which W EXS is the predicted all-day curtailment volume of electricity.

5. The method according to claim 4, wherein The specific method for calculating the maximum energy storage capacity at the moment before the curtailment occurs if the curtailment is completely absorbed under the condition of considering the energy storage capacity constraint in step S6 includes the following steps: S6-1. According to the formula: Calculate the maximum energy storage capacity at the moment immediately before curtailment occurs where is the energy storage capacity at the initial moment of curtailment obtained by prediction; t1 represents the initial moment of curtailment S6-2. Judgment Is it greater than or equal to the lower limit of the energy storage capacity If yes, go to step S6-3; otherwise, set the lower limit of the energy storage capacity Update it to the maximum energy storage capacity at the moment immediately before the abandonment of electricity Go to step S7; S6-3. Judgment Is it less than or equal to the upper limit of the energy storage capacity If yes, go to step S7; otherwise, set the upper limit of the energy storage capacity Update it to the maximum energy storage capacity at the moment immediately before the abandonment of electricity occurs Go to step S7 6. The method according to claim 5, wherein The specific method for updating the grid-connected power, off-grid power, charging power, discharging power at the moment before the curtailment occurs and the maximum energy storage capacity at the two moments before the curtailment occurs in step S7 includes the following steps: S7-1. Determine the maximum energy storage capacity at the moment immediately before the curtailment occurs Is it less than or equal to the energy storage capacity at the two moments before the curtailment occurs? If yes, go to step S7-2; otherwise, go to step S7-6; S7-2. According to the formula: Obtain the discharge power at the previous moment generated by curtailed power obtained from the update S7-3. According to the formula: Obtain the grid-connected power at the previous moment generated by curtailment of electricity after getting the update Wherein is the output power of wind power at the previous moment when curtailment of electricity occurs; is the output power of photovoltaic power at the previous moment when curtailment of electricity occurs; is the power of the load at the previous moment when curtailment of electricity occurs; When is greater than then is updated to the grid-connected power at the previous moment when curtailment of electricity occurs and enter step S7-4; Otherwise, directly enter step S7-5; S7-4. According to the formula: Obtain the discharge power at the previous moment generated by curtailed electricity obtained by the update S7-5. According to the formula: Obtain the maximum energy storage capacity at the first two moments when curtailment occurs after obtaining the update Proceed to step S8; S7-6. According to the formula: Obtain the charging power at the previous moment generated by curtailed electricity obtained through the update S7-7. According to the formula: Obtain the grid-connected power at the previous moment generated by curtailment of electricity for the updated value Where when is greater than then is updated to the grid-connected power at the previous moment generated by curtailment of electricity And proceed to step S7-8; otherwise, directly proceed to step S7-9; S7-8. According to the formula: Obtain the charging power at the previous moment generated by curtailed electricity in the obtained update S7-9. According to the formula: Obtain the maximum energy storage capacity at the first two moments generated by curtailed electricity obtained from the update Proceed to step S8.

7. The method according to claim 6, characterized in that, In step S7-2, if the discharge power at the previous moment generated by curtailment updated is greater than the upper limit of the discharge power , update the upper limit of the discharge power to the discharge power at the previous moment generated by curtailment 8. The method according to claim 6, wherein In step S7-6, if the charging power at the previous moment generated by the abandoned power updated is greater than , then is updated to the charging power at the previous moment generated by the abandoned power 9. An electronic device, characterized in that, It includes: A memory and a processor; The memory is used to store computer execution instructions; The processor is used to execute the computer execution instructions stored in the memory to implement the method according to any one of claims 1 to 6.

10. A storage medium, characterized in that, It includes: A readable storage medium and a computer program, and the computer program is used to implement the method according to any one of claims 1 to 8.

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