A method for constructing a general model for unified dispatch of load-side response resources in virtual power plants

Abstract

The present application relates to the field of user-side demand response in power systems, and discloses a method for constructing a general model for unified dispatch of response resources on the load side of a virtual power plant, including the following steps: S1, collecting historical user load data and historical participation in demand response; S2, dividing adjustable resources into virtual energy storage resources and physical energy storage resources; S3, constructing a virtual energy storage model; S4, constructing a physical energy storage model; S5, combining the virtual energy storage model and the physical energy storage model to construct a general energy storage model for evaluating the frequency regulation potential of VPP. The present invention determines the load frequency response potential and establishes a general model by fully considering the response capability, regulation capability, charge and discharge power, rate, battery capacity, etc. of load resources with different degrees of flexibility, which helps VPP to more accurately evaluate its overall frequency regulation response capability, thereby conducting more effective bidding and scheduling strategy planning in the power market.

Description

Technical Field

[0001] The present invention relates to the technical field of user-side demand response in an electric power system, and in particular to a method for constructing a general model for unified dispatching of load-side response resources in a virtual power plant. Background Art

[0002] Under the background of the development and construction of new power markets, with the continuous increase in electricity demand, potential resources on the user side need to be developed urgently, and the requirements for frequency regulation capability and accuracy are becoming increasingly higher. Load aggregators, virtual power plants, etc., as energy management systems that integrate various distributed energy sources and various flexible load resources, play an important role in market frequency regulation. Among them, energy storage resources have broad scheduling potential due to their significant advantages such as high flexibility of regulation, easy analysis and calculation of scheduling potential, and easy management. However, the construction and maintenance costs of physical energy storage equipment are high, and there are a large number of dispatchable resources on the user side with large scheduling potential that are idle. Therefore, it is of great significance to develop a general virtual energy storage model suitable for different types of user-side DR resources, and to intuitively compare and quantify the flexibility of various types of user-side loads by using unified expressions and parameters.

[0003] At present, most related studies only focus on a single user-side load resource and user demand. Therefore, its demand-side response evaluation method is limited in the scope of applicable objects, and it is difficult to accurately evaluate multiple types of user-side resources. Summary of the invention

[0004] In view of the shortcomings of the prior art, the present invention provides a method for constructing a general model for unified scheduling of load-side response resources of a virtual power plant. By fully considering the response capability, regulation capability, charging and discharging power, rate, battery capacity, etc. of load resources with different degrees of flexibility, the load frequency response potential is determined and a general model is established.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: A method for constructing a general model for unified dispatch of response resources on the load side of a virtual power plant, comprising the following steps:

[0006] Collect historical user load data and historical demand response participation on the load operator platform;

[0007] Divide adjustable resources into virtual energy storage resources and physical energy storage resources;

[0008] Constructing a virtual energy storage model, including collecting parameters and historical data of virtual energy storage resources, constructing a load response capability evaluation model for each device, corresponding to the battery reserve model, and constructing a virtual energy storage model;

[0009] Constructing a physical energy storage model, including collecting parameters and historical data of physical energy storage resources, constructing an adjustable power model of energy storage for each energy storage device in different time periods, and constructing a physical energy storage model based on the adjustable power model;

[0010] The virtual energy storage model and the physical energy storage model are combined to construct a universal energy storage model for VPP frequency regulation potential assessment.

[0011] Preferably, the parameters and historical data of the virtual energy storage resources include the power load curve of a specific time period within a cycle, the daily power curve, the time period for implementing demand response, the frequency of use, and the charge and discharge rate and minimum operating power of the DR resources.

[0012] Preferably, the load response capability evaluation model performs evaluation based on the usage frequency, response capability and response speed of the virtual energy storage resources.

[0013] Preferably, the construction of the virtual energy storage model specifically includes: constructing a load response capability evaluation model of the usage frequency, response capability, and response speed of each device based on the collected parameters and historical data of the virtual energy storage resources, and constructing the evaluation parameters of each load-side DR resource, combining the energy storage model, using the time period weighted function method, normalizing it, and corresponding it to the battery reserve model to construct the virtual energy storage model.

[0014] Preferably, the parameters and historical data of the physical energy storage resources include the charging and discharging electricity price of each energy storage device to the load aggregator in the day-ahead stage, the maximum and minimum charging and discharging power of the energy storage device, the maximum and minimum power of the energy storage device, and the charging and discharging efficiency of the energy storage device.

[0015] Preferably, the constructing of the physical energy storage model specifically includes: constructing a time-divided energy storage adjustable power model of each energy storage device according to the collected parameters and historical data of the physical energy storage resources, and constructing the physical energy storage model according to the power model of each energy storage device.

[0016] Preferably, the step of combining the virtual energy storage model and the physical energy storage model to construct a universal energy storage model for evaluating the frequency regulation potential of VPP specifically includes: constructing a universal energy storage model for evaluating the frequency regulation potential of VPP by confidence weighting according to the constructed virtual energy storage model and the physical energy storage model.

[0017] The present invention also provides a virtual power plant load side response resource unified dispatch general model construction device, comprising:

[0018] A collection unit, used to collect historical load data and historical demand response participation of users on the load operator platform;

[0019] A division unit, used to divide the adjustable resources into virtual energy storage resources and physical energy storage resources;

[0020] A virtual energy storage model building unit, used to build a virtual energy storage model, including collecting parameters and historical data of virtual energy storage resources, building a load response capability evaluation model for each device, corresponding to the battery reserve model, and building a virtual energy storage model;

[0021] A physical energy storage model construction unit is used to construct a physical energy storage model, including collecting parameters and historical data of physical energy storage resources, constructing a time-divided energy storage adjustable power model for each energy storage device, and constructing a physical energy storage model based on the adjustable power model;

[0022] The general energy storage model construction unit is used to combine the virtual energy storage model and the physical energy storage model to construct a general energy storage model for VPP frequency regulation potential assessment.

[0023] The present invention also provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the above method is implemented.

[0024] The present invention also provides a storage medium on which a computer program is stored. When the computer program is executed by a processor, the method described above is implemented.

[0025] The present invention provides a method for constructing a general model for unified dispatching of load-side response resources of a virtual power plant. It has the following beneficial effects:

[0026] 1. The present invention determines the load frequency response potential by fully considering the response capability, regulation capability, charge and discharge power, rate, battery capacity, etc. of load resources with different flexibility levels, and establishes a general model, which helps VPP to more accurately evaluate its overall frequency response capability, thereby conducting more effective bidding and scheduling strategy planning in the power market.

[0027] 2. The present invention combines different types of user-side loads, quantifies and normalizes their frequency regulation response capabilities and frequency regulation response ranges, and converts power into corresponding virtual energy storage resources to construct a universal virtual energy storage model, so that the load aggregator as a whole can flexibly store and release energy in different time periods to achieve better frequency regulation demand response effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a general model block diagram of unified dispatching of response resources on the load side of a virtual power plant of the present invention;

[0029] Figure 2 It is a schematic diagram of load operator resources of the present invention;

[0030] Figure 3 It is a schematic diagram of the general model construction method of the present invention;

[0031] Figure 4 It is a schematic diagram of the structure of the device of the present invention;

[0032] Figure 5 It is a schematic diagram of the computer device structure of the present invention.

[0033] Among them, 100, acquisition unit; 200, division unit; 300, virtual energy storage model construction unit; 400, physical energy storage model construction unit; 500, general energy storage model construction unit; 40, computer equipment; 41, processor; 42, memory; 43, storage medium. DETAILED DESCRIPTION

[0034] The following will be combined with the drawings in the specification of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] Please see attached Figure 1-3 , an embodiment of the present invention provides a method for constructing a general model for unified dispatch of response resources on the load side of a virtual power plant, including steps S1 to S5;

[0036] Wherein, step S1, collecting historical load data and historical demand response participation of users on the load operator platform;

[0037] Specifically, load operator resources such as Figure 2 As shown, the data collection system can use advanced data collection technologies, such as smart meters, sensor networks, etc., to collect user load data in real time or periodically. At the same time, historical participation in demand response will also be recorded and organized, including the various load regulation activities in which users participate, such as response frequency, regulation amplitude, etc.

[0038] Step S2: dividing the adjustable resources into virtual energy storage resources and physical energy storage resources;

[0039] Specifically, through step S2, the user's historical load data and the adjustable resources in the historical demand response situation collected in step S1 are divided into virtual energy storage resources and physical energy storage resources;

[0040] The parameters and historical data of the virtual energy storage resources include the power load curve and daily power curve of a specific time period within a certain cycle, the time period for implementing demand response, the frequency of use, the charge and discharge rate of the DR resources, and the minimum operating power;

[0041] The parameters and historical data of the physical energy storage resources include the charging and discharging electricity price of each energy storage device to the load aggregator in the day-ahead stage, the maximum and minimum charging and discharging power of the energy storage device, the maximum and minimum power of the energy storage device, and the charging and discharging efficiency of the energy storage device.

[0042] This division is conducive to adopting different modeling and scheduling methods for different types of resources.

[0043] Step S3, constructing a virtual energy storage model, including collecting parameters and historical data of virtual energy storage resources, constructing a load response capability evaluation model of each device, corresponding to the battery reserve model, and constructing a virtual energy storage model;

[0044] Specifically, step S3 includes the following detailed steps:

[0045] S31. Data collection: collect frequency regulation characteristic-related parameter data of DR resources on the VPP user side and their historical dispatch response data, including the power load curve and daily power curve of a specific time period within a cycle, the time period for implementing demand response, the frequency of use, the charge and discharge rate of DR resources, and the minimum operating power.

[0046] S32. Data preprocessing: preprocess the multi-day load curve, power consumption curve, and demand response time period of the user-side DR resources to calculate various baseline characteristic values, including the load of the DR resources participating in the demand response period, the power consumption of each period, the daily maximum power consumption, the daily minimum power consumption, the daily maximum load, the daily minimum load, etc., combined with the load change rate in the demand response period, to prepare for the subsequent fitting of the usage frequency, response time, and response speed of different devices of each user.

[0047] S33, load characteristic model construction, based on the power consumption of different load-side DR resources aggregated by the virtual power plant in each time period and combined with their usage frequency, response capability, and response speed, mapped to the state of charge SOC of the energy storage system 虚 , rated capacity, and charge and discharge rates, and other key parameters that reflect its frequency regulation capability, in order to construct a virtual energy storage model.

[0048] S331, standardized observation value, assuming that the power consumption of the a-th load-side DR resource on the x-th day is P ax , P ax(t) Represents the standardized observation value of load-side DR resource a on day x in period t.

[0049] S332, define the usage frequency, define the usage frequency as the frequency of a certain load-side DR resource of the user being used in the same time period each time, and quantify the usage frequency between [0,1]. The usage frequency can be expressed as the usage probability, which indicates the proportion of days when the load-side DR resource is used to the total number of days tested. In this embodiment, it is shown as follows:

[0050] U a =|{x|max(P ax(t) >εa,x∈(1,X))}| / X

[0051] Among them U a It represents the relative value of the usage frequency potential of the load-side DR resource a, εa represents the minimum power of the load-side DR resource a, and X represents the number of historical days of the test.

[0052] S333, response capability definition, which is defined as the size of the load that can be interrupted, transferred or translated by the load-side DR resources in a certain period of time. The higher the response capability, the greater the amount of change that the user can make in response to the incentive mechanism to change his or her electricity consumption behavior, and the higher the load response potential. In this embodiment, it is shown in the following formula:

[0053]

[0054] Assuming that the power consumption period is [t1, t2], then R a Indicates responsiveness.

[0055] S334, response speed definition, define the response speed as the average of the load increase and decrease rates of the load-side DR resources during peak hours, and the potential relative value of the response speed is the value after the response time is standardized. In this embodiment, it is shown as follows:

[0056]

[0057] Where S a Indicates the potential relative value of response speed, It means that during the peak period of electricity consumption, the power consumption of the load-side DR resource a on the xth day reaches the maximum value at time t. Indicates Δt before the peak of electricity consumption 1 The power consumption at the time, Indicates Δt after the peak period of electricity consumption 2 The power consumption at the time, Δt 1 ,Δt 2 Represents the rising and falling time intervals respectively. a* Represents the normalized response speed.

[0058] S34, construct a virtual energy storage load characteristic model. According to the usage frequency, response capability, and response speed model of the load-side DR resources in step S33, use the time-division weighted function method to correspond it to the battery reserve model to construct a virtual energy storage load characteristic model. The virtual energy storage load characteristic model is to analyze the characteristics of the load-side DR resources aggregated in the VPP, evaluate and calculate its response characteristics for participating in frequency regulation, and map it into key parameters when energy storage resources participate in frequency regulation, which is ultimately equivalent to a virtual energy storage load characteristic model. In this embodiment, the virtual energy storage load characteristic model is as follows:

[0059]

[0060]

[0061]

[0062] Among them, SOC 虚 Represents the power of virtual energy storage load, P ax (t) represents the standardized observation value of the load-side DR resource a in the xth day in the period t, S a represents the average value of the load increase and decrease rate of the DR resource on the load side during peak hours, λ a,c ,λ a,d Defined as the charging and discharging efficiency of the DR resource on the load side, They represent the peak period of electricity consumption, and the power consumption of the load-side DR resource a on the xth day reaches the maximum and minimum values ​​at time t. a It is a Boolean variable, indicating that a load-side DR resource cannot be used for peak shaving or valley filling at the same time.

[0063] The embodiment of the present invention uses a time-division weighted function method to match the characteristics of the load-side DR resources with the battery energy storage model, and constructs a virtual energy storage load characteristic model. This model can analyze the characteristics of the load-side DR resources aggregated in the VPP, and evaluate and calculate their participation in the frequency regulation response characteristics, and finally map and transform them into key parameters when the energy storage resources participate in frequency regulation. This enables the VPP to more effectively evaluate and utilize the frequency regulation capabilities of these resources, helps the VPP to perform demand response operations more accurately, and optimizes the overall operating efficiency of the power grid.

[0064] Step S4, constructing a physical energy storage model, including collecting parameters and historical data of physical energy storage resources, constructing a time-divided energy storage adjustable power model for each energy storage device, and constructing a physical energy storage model based on the adjustable power model;

[0065] Specifically, step S4 includes the following detailed steps:

[0066] S41. Data collection: collect historical data of distributed energy storage devices owned by load aggregators, such as battery energy storage, compressed air energy storage, supercapacitors, etc., including the electricity price of charging and discharging to VPP in the day-ahead period, the maximum and minimum charging and discharging power of energy storage devices, the maximum and minimum power of energy storage devices, and the charging and discharging efficiency of energy storage devices.

[0067] S42, physical energy storage model construction, k is the type of energy storage, there are K types of energy storage resources, Pk(t) is the power of energy storage k at time t; λk is the charge and discharge efficiency of energy storage k. In this embodiment, the physical energy storage model is as follows:

[0068]

[0069] 0 <SOCk<100%

[0070] SOC k,0 =SOC k,T

[0071] Among them, SOC 实 is the amount of energy stored in the energy storage system, Indicates the maximum storage capacity of the k energy storage device, SOCk ,t represents the charge state of the k energy storage device at time t, P k (t) represents the operating power of k energy storage at time t, λ k is the charge and discharge efficiency of energy storage k, SOC k,0 , SOC k,T are the initial and final states of charge of device k, respectively.

[0072] Integral expressions in the model and It is used to calculate the total amount of charge and discharge of the energy storage device in a given period of time. These total amounts are multiplied by the charge and discharge efficiency (λ k ) and maximum storage capacity To update the state of charge SOC of the energy storage device 实 The model also ensures that the state of charge of the energy storage device remains between 0% and 100%, and that the initial and final states of charge of the device are equal, indicating that the total charge amount equals the total discharge amount during the considered time period, that is, the state of charge of the energy storage device is closed-loop.

[0073] Through such a model, load aggregators can monitor and manage the performance of physical energy storage equipment and make scheduling decisions accordingly to meet the needs and market opportunities of VPPs. This helps optimize the use of energy storage resources, thereby improving the economy and reliability of the entire system.

[0074] Step S5: Combine the virtual energy storage model and the physical energy storage model to build a general energy storage model for VPP frequency regulation potential assessment, and define the overall general load energy storage response potential model as follows:

[0075] SOC 总 =μ 1 SOC 虚 +μ 2 SOC 实

[0076] μ 1 ∈(0,1)

[0077] μ 2 ∈(0.95,1)

[0078] The model aims to evaluate the total energy storage response potential of the VPP at a specific moment, that is, the total amount of energy that the VPP can use to respond to frequency regulation needs. This total energy SOC 总 It is a virtual energy storage SOC 虚 and physical energy storage SOC 实 The weighted sum of 1 and μ 2 to be sure.

[0079] Among them, SOC 虚 : Indicates the state of charge of the virtual energy storage model defined in the previous step. SOC 实 : represents the state of charge of the physical energy storage model defined in the previous step. 1 : Indicates the credibility of the virtual energy storage model. The value of this parameter is between 0 and 1, reflecting the reduced credibility of the load-side DR resource when it is equivalent to a virtual energy storage model due to its own uncertainty. μ 2 : Indicates the confidence of the physical energy storage model. The value of this parameter is between 0.95 and 1, reflecting the higher credibility of the physical energy storage model compared to the virtual energy storage model.

[0080] By adjusting μ 1 and μ 2 The value of can be customized according to the different performance of user equipment aggregated by different load operators and the different scheduling difficulties. For example, if a load operator aggregates user equipment with stable performance and relatively simple scheduling, a higher confidence value μ can be selected for its physical energy storage model. 2 On the contrary, if the device has large performance fluctuations or is difficult to call, the confidence μ 2 Should be reduced accordingly.

[0081] This overall model helps VPPs to more accurately assess their overall frequency response capabilities, leading to more effective bidding and dispatch strategy planning in the electricity market.

[0082] The device for constructing a general model for unified dispatching of load-side response resources of a virtual power plant described below and the method for constructing a general model for unified dispatching of load-side response resources of a virtual power plant described above can refer to each other.

[0083] Please see attached Figure 4 The present invention also provides a general model construction device for unified dispatch of virtual power plant load-side response resources, including:

[0084] The collection unit 100 is used to collect the historical load data and historical demand response participation status of users on the load operator platform;

[0085] A division unit 200, used to divide the adjustable resources into virtual energy storage resources and physical energy storage resources;

[0086] A virtual energy storage model construction unit 300 is used to construct a virtual energy storage model, including collecting parameters and historical data of virtual energy storage resources, constructing a load response capability evaluation model of each device, corresponding to the battery reserve model, and constructing a virtual energy storage model;

[0087] The physical energy storage model construction unit 400 is used to construct the physical energy storage model, including collecting parameters and historical data of physical energy storage resources, constructing a time-divided energy storage adjustable power model of each energy storage device, and constructing the physical energy storage model according to the adjustable power model;

[0088] The general energy storage model construction unit 500 is used to combine the virtual energy storage model and the physical energy storage model to construct a general energy storage model for VPP frequency regulation potential assessment.

[0089] The device of this embodiment can be used to execute the above method embodiment, and its principles and technical effects are similar, which will not be repeated here.

[0090] Please see attached Figure 5 The present invention further provides a computer device 40, comprising: a processor 41 and a memory 42, wherein the memory 42 stores a computer program executable by the processor, and when the computer program is executed by the processor, the above method is executed.

[0091] The present invention further provides a storage medium 43 on which a computer program is stored. When the computer program is run by the processor 41, the above method is executed.

[0092] Among them, the storage medium 43 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable red-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, disk or optical disk.

[0093] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for constructing a general model for unified dispatching of load-side response resources in a virtual power plant, characterized in that: The following steps are involved: Collect historical load data and historical demand response participation of users on the load operator platform; Divide adjustable resources into virtual energy storage resources and physical energy storage resources; Constructing a virtual energy storage model, including collecting parameters and historical data of virtual energy storage resources, constructing a load response capability evaluation model for each device, corresponding to the battery reserve model, and constructing a virtual energy storage model; Constructing a physical energy storage model, including collecting parameters and historical data of physical energy storage resources, constructing an adjustable power model of energy storage for each energy storage device in different time periods, and constructing a physical energy storage model based on the adjustable power model; Combining virtual energy storage model and physical energy storage model, a universal energy storage model for VPP frequency regulation potential assessment is constructed; The parameters and historical data of the virtual energy storage resources include the power load curve and daily power curve of a specific time period within a certain cycle, the time period for implementing demand response, the frequency of use, the charge and discharge rate of the DR resources, and the minimum operating power; The load response capability evaluation model is evaluated based on the usage frequency, response capability and response speed of the virtual energy storage resources; The construction of the virtual energy storage model specifically includes: constructing a load response capability evaluation model of the use frequency, response capability, and response speed of each device according to the collected parameters and historical data of the virtual energy storage resources, and constructing the evaluation parameters of the DR resources on the load side, combining the energy storage model, using the time period weighted function method, performing normalization processing, and corresponding it to the battery reserve model to construct the virtual energy storage model, which is expressed as: in, Indicates the charge state of the virtual energy storage model; Indicates load-side DR resources No. Day in time The standardized observed value of It represents the average of the load increase and decrease rates of the DR resources on the load side during peak hours; , is the charging and discharging efficiency of DR resources on the load side; , They represent the peak period of electricity consumption and the load-side DR resources. No. The daily electricity consumption is The maximum and minimum values ​​are obtained at all times; It is a Boolean variable, indicating that a load-side DR resource cannot be used for peak shaving or valley filling at the same time; Indicates responsiveness; Indicates a time interval; The construction of the physical energy storage model specifically includes: constructing a time-divided energy storage adjustable power model of each energy storage device according to the collected parameters and historical data of the physical energy storage resources, and constructing a physical energy storage model according to the power model of each energy storage device; The step of combining the virtual energy storage model and the physical energy storage model to construct a universal energy storage model for evaluating the frequency regulation potential of VPP specifically includes: constructing a universal energy storage model for evaluating the frequency regulation potential of VPP by means of confidence weighting according to the constructed virtual energy storage model and the physical energy storage model, which is expressed as: in, Indicates the charge state of the virtual energy storage model; Indicates the state of charge of the physical energy storage model; Indicates the state of charge of the virtual energy storage model and the state of charge of the physical energy storage model The weighted sum of is used to evaluate the total energy storage response potential of the VPP at a specific moment; and Represent the confidence of the virtual energy storage model and the physical energy storage model respectively.

2. A method for constructing a general model for unified dispatching of load-side response resources of a virtual power plant according to claim 1, characterized in that: The parameters and historical data of the physical energy storage resources include the charging and discharging electricity price of each energy storage device to the load aggregator in the day-ahead stage, the maximum and minimum charging and discharging power of the energy storage device, the maximum and minimum power of the energy storage device, and the charging and discharging efficiency of the energy storage device.

3. A virtual power plant load side response resource unified dispatch general model construction device, using a virtual power plant load side response resource unified dispatch general model construction method as claimed in claim 1 or 2, characterized in that: include: A collection unit, used to collect historical load data and historical demand response participation of users on the load operator platform; A division unit, used to divide the adjustable resources into virtual energy storage resources and physical energy storage resources; A virtual energy storage model building unit, used to build a virtual energy storage model, including collecting parameters and historical data of virtual energy storage resources, building a load response capability evaluation model for each device, corresponding to the battery reserve model, and building a virtual energy storage model; A physical energy storage model construction unit is used to construct a physical energy storage model, including collecting parameters and historical data of physical energy storage resources, constructing a time-divided energy storage adjustable power model for each energy storage device, and constructing a physical energy storage model based on the adjustable power model; The general energy storage model construction unit is used to combine the virtual energy storage model and the physical energy storage model to construct a general energy storage model for VPP frequency regulation potential assessment.

4. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to claim 1 or 2 is implemented.

5. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to claim 1 or 2 is implemented.

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