Load resource aggregation method, system, equipment and medium in power system

Abstract

The invention discloses a load resource aggregation method, system, equipment and medium in a power system, and relates to the technical field of power system control, and the method comprises the steps: obtaining an adjustment characteristic matrix of all load side resources participating in aggregation in the power system; acquiring scene fitness indexes of all kinds of load side resources participating in aggregation; screening the load side resources based on the scene fitness index, screening out various load side resources suitable for different balance scenes of the power grid, and forming a peak clipping, valley filling and climbing scene resource aggregation group; and obtaining a load aggregation group adjustment capability duration curve satisfying climbing, peak clipping and valley filling scenes. According to the method, the multi-dimension complementary characteristic of the multi-type resources is considered, the scene fitness index system is constructed, the multi-type resources are flexibly aggregated based on the scene fitness index, the load regulation capability duration curve for different typical scenes is obtained, and the aggregation capability analysis problem of load side resources participating in power grid operation in different scenes is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of power system control, and in particular to a method, system, equipment and medium for aggregating load resources in a power system. Background Art

[0002] In the power system, in order to implement the development concept of innovation, coordination, green, openness and sharing, promote the transformation and upgrading of the power grid to energy Internet, actively adapt to the structural changes of power sources, power grids and power loads, effectively expand the power grid regulation resources, and promote the transformation of the traditional "source follows load" to "source, grid, load and storage coordinated interaction" mode. From the four dimensions of "observable, measurable, controllable and adjustable", the regulation and control capabilities of load regulation resources should be improved, and the aggregation, sharing and regulation of "source-load-storage" regulation resources in the region should be realized, and the adjustable load management capabilities should be improved, so as to effectively improve the safety and stability level of the power grid, the level of new energy consumption, and the level of lean dispatching.

[0003] For power load, with the continuous increase in diversified market demand, the proportion of external power continues to increase, and the contradiction of system peak load regulation becomes more prominent. For the whole links of energy production, transmission, and consumption, the supply and demand docking of all factors and the optimal allocation of resources, it is necessary to continuously improve the construction of load-side generators and their supporting transmission and distribution networks, which increases the burden on the regulation and control capabilities of the power system, resulting in poor aggregation capabilities, and corresponding deviations will occur in different scenarios. Summary of the invention

[0004] The purpose of the present invention is to provide a method, system, device and medium for aggregating load resources in an electric power system in view of the deficiencies of the above-mentioned prior art, so as to solve the problems in the prior art.

[0005] The present invention specifically provides the following technical solutions:

[0006] A method for aggregating load resources in a power system comprises the following steps:

[0007] Obtain the regulation characteristic matrix of all load-side resources participating in aggregation in the power system;

[0008] According to the load-side resource regulation characteristic matrix, the scenario fitness indexes of all types of load-side resources participating in the aggregation are obtained, and the load-side resources are screened based on the scenario fitness indexes to select various load-side resources suitable for different balance scenarios of the power grid, forming a resource aggregation group for peak shaving, valley filling and slope climbing scenarios;

[0009] The relationship between the regulation power and regulation time of all loads in the load aggregation group is obtained, and a regulation capacity continuity curve is drawn based on the relationship to aggregate the load resources.

[0010] Preferably, the step of obtaining the regulation characteristic matrix of all load-side resources participating in aggregation in the power system includes:

[0011] The specific expression of the adjustment characteristic matrix is:

[0012]

[0013] Among them, A k is the regulation characteristic matrix, each row m represents various regulation characteristic indicators of this type of load side resources, and each column n represents the value of a certain regulation characteristic indicator of different load side resources;

[0014] The regulation characteristics of the load resources in the regulation characteristic matrix include: maximum adjustable capacity, response time, regulation rate and adjustable duration, and the regulation characteristic matrix is ​​constructed with the regulation characteristics. The specific expression is:

[0015]

[0016] in, is the maximum adjustable capacity, that is, the remaining power output value of the largest power generation unit, the output value is the output power, t n is the response time, θ n To adjust the rate, T n c The duration is adjustable.

[0017] Preferably, the regulation characteristics of the load resources in the regulation characteristic matrix include: maximum adjustable capacity, response time, regulation rate and adjustable duration, specifically:

[0018] The specific expression of the maximum adjustable capacity is:

[0019]

[0020] in, It indicates the average value of baseline load power of adjustable load group before adjustment during the adjustment period; It represents the average aggregate power of the adjustable load group after being adjusted in the maximum adjustment mode during the adjustment period. FL refers to the adjustable load group, which corresponds to each row m in the matrix, including temperature control load group, electric vehicle load group, energy storage load group or other combination groups;

[0021] The specific expression of the response time is:

[0022] t FL =t first -t strat ;

[0023] Among them, t first Indicates the moment when the load group power reaches the regulation target value for the first time; tstrat Indicates the start time of adjustment;

[0024] The specific expression of the adjustment rate is:

[0025] θ FL =ΔP FL / t FL ;

[0026] Where ΔP FL Indicates the adjustable capacity of the adjustable load group; t FL Indicates the response time;

[0027] During the adjustable duration, Adjust power duration for flexible load groups.

[0028] Preferably, the step of obtaining the scenario adaptability indexes of all types of load-side resources participating in the aggregation according to the load-side resource regulation characteristic matrix includes:

[0029] For the ramp scenario, obtain the ramp scenario index Y of load i C,i ; The specific expression is:

[0030]

[0031] Where sign(x) is the sign function; P t is the adjustable power of load i at time t, that is, the adjustable capacity. Load i is one of FL. When load i has the potential to adjust upward at time t, P t > 0, when load i has the potential to adjust downward at time t, P t <0;v i is the regulation rate of load i; v slope Load regulation rate required for ramping scenarios;

[0032] When P t >0, that is, sign(P t )=1, Y C,i The value of v i is proportional to, and its value range is When P t <0, that is, sign(P t )=-1, Y C,i The value of v i Inversely proportional, Y C,i The value range is

[0033] Preferably, the step of obtaining the scenario adaptability index of all types of load-side resources participating in the aggregation according to the load-side resource regulation characteristic matrix further includes:

[0034] For the peak shaving scenario, obtain the peak shaving scenario fitness index Y of load i P,i ; The specific expression is:

[0035]

[0036] Among them, P t is the adjustable power of load i at time t. When load i has the potential to be adjusted upward at time t, P t > 0, when load i has the potential to adjust downward at time t, P t <0;v i is the regulation rate of load i; v peak Load regulation rate required for peak shaving scenarios; The load adjustable power duration required for peak shaving scenarios, T i c is the adjustable power duration of load i.

[0037] Preferably, the step of obtaining the scenario adaptability index of all types of load-side resources participating in the aggregation according to the load-side resource regulation characteristic matrix further includes:

[0038] In the valley filling scenario, obtain the peak shaving scenario fitness index Y of load i V,i ; The specific expression is:

[0039]

[0040] Where: P t is the adjustable power of load i at time t. When load i has the potential to be adjusted upward at time t, P t > 0, when load i has the potential to adjust downward at time t, P t <0;v i is the regulation rate of load i; v valley The load adjustment rate required for valley filling scenarios; The load adjustable power duration required for valley filling scenario, T i c is the adjustable power duration of load i.

[0041] Preferably, the step of drawing a continuous adjustment capability curve according to the relationship between the adjustment power and the adjustment time of all loads in the load aggregation group includes:

[0042] Get the adjustment power and adjustment time relationship f(P k ,t k ), the specific expression is:

[0043]

[0044] Where i represents the load, P i represents the regulation power of load i, t i represents the adjustment time of load i, and k represents the total number of loads;

[0045] By f(P k ,t k ) Obtain the continuous curve of the regulation capacity of the load aggregation group.

[0046] The present invention provides a load resource aggregation system in an electric power system, comprising:

[0047] A collection module is used to obtain the regulation characteristic matrix of all load-side resources participating in aggregation in the power system;

[0048] The indicator acquisition module is used to obtain the scenario fitness indicators of all types of load-side resources participating in the aggregation according to the load-side resource regulation characteristic matrix, screen the load-side resources based on the scenario fitness indicators, and screen out various load-side resources suitable for different balance scenarios of the power grid to form a resource aggregation group for peak shaving, valley filling and slope climbing scenarios;

[0049] The output module is used to obtain the relationship between the regulation power and regulation time of all loads in the load aggregation group, and to draw a regulation capacity continuity curve based on the relationship to aggregate the load resources.

[0050] The present invention provides a computer device, comprising a memory and a processor, wherein a program is stored in the memory, and when the program is executed by the processor, the processor executes the steps of the above-mentioned method for aggregating load resources in an electric power system.

[0051] The present invention provides a storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned method for aggregating load resources in an electric power system are implemented.

[0052] Compared with the prior art, the present invention has the following significant advantages:

[0053] The present invention takes into account the multi-dimensional complementary characteristics of multiple types of resources, constructs a load-side resource regulation characteristic matrix, obtains the scenario fitness index of the load-side resources through the matrix, and screens multiple types of resources based on the scenario fitness index. There is no need to continuously improve the construction of the generator sets on the load side and their supporting transmission and distribution networks. The goal of aggregating load resources for climbing, cutting peaks and filling valleys is achieved through the scenario fitness index, and the load regulation capability of the power grid is effectively improved. Flexible aggregation is performed through the relationship between the load regulation power and the regulation time, and a continuous curve of load regulation capability for different typical scenarios is obtained, which solves the problem of analyzing the aggregation capability of load-side resources participating in power grid operations in different scenarios. The curve provides technical support for different scenarios, reduces aggregation deviation, and provides a dispatching decision basis for the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 The present invention is an overall flow chart of load resource aggregation in an electric power system. DETAILED DESCRIPTION

[0055] The following is a clear and complete description of the technical solutions of the embodiments of the present invention in conjunction with the drawings in the present invention. Obviously, the described embodiments are 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 should fall within the scope of protection of the present invention.

[0056] like Figure 1 As shown, the present invention provides a method for aggregating load resources in a power system, which specifically includes the following steps:

[0057] Step S1: Obtain the regulation characteristic matrix of all load-side resources participating in aggregation in the power system.

[0058] The specific expression of the adjustment characteristic matrix is:

[0059]

[0060] Among them, A k is a regulation characteristic matrix, each row m represents various regulation characteristic indicators of this type of load side resources, and each column n represents the value of a certain regulation characteristic indicator of different load side resources.

[0061] The regulation characteristics of the load resources in the regulation characteristic matrix include: maximum adjustable capacity, response time, regulation rate and adjustable duration, and the regulation characteristic matrix is ​​constructed with the regulation characteristics. The specific expression is:

[0062]

[0063] in, is the maximum adjustable capacity, that is, the remaining power output value of the largest power generation unit, the output value is the output power, t n is the response time, θ n To adjust the rate, T n c The duration is adjustable.

[0064] The regulation characteristics of load resources in the regulation characteristic matrix include: maximum adjustable capacity, response time, regulation rate and adjustable duration, specifically:

[0065] The specific expression of the maximum adjustable capacity (kW) is:

[0066]

[0067] in, It indicates the average value of baseline load power of adjustable load group before adjustment during the adjustment period; It represents the average aggregate power of the adjustable load group after being adjusted in the maximum adjustment mode during the adjustment period. FL refers to the adjustable load group, which corresponds to each row m in the matrix, including temperature control load group, electric vehicle load group, energy storage load group or other combination groups.

[0068] The specific expression of response time is:

[0069] t FL =t first -t strat ;

[0070] Among them, t first Indicates the moment when the load group power reaches the regulation target value for the first time; t strat Indicates the time when adjustment starts.

[0071] The specific expression of the adjustment rate is:

[0072] θ FL =ΔP FL / t FL ;

[0073] Where ΔP FL Indicates the adjustable capacity of the adjustable load group; t FL Indicates the response time.

[0074] Adjustable duration, Adjust power duration for flexible load groups.

[0075] Step S2: According to the load-side resource regulation characteristic matrix, the scenario fitness indexes of all types of load-side resources participating in the aggregation are obtained, and the load-side resources are screened based on the scenario fitness indexes to select various load-side resources suitable for different balancing scenarios of the power grid, forming a resource aggregation group for peak shaving, valley filling and climbing scenarios.

[0076] According to the load-side resource regulation characteristic matrix, the scenario fitness indicators of all types of load-side resources participating in the aggregation are obtained, including:

[0077] According to the characteristics of ramping scenarios that generally require high response speed, the ramping scenario index Y of the adjustable load i is obtained. C,i ; The specific expression is:

[0078]

[0079] Where sign(x) is the sign function; P tis the adjustable power of load i (here the load is an adjustable load) at time t, that is, the adjustable capacity. Load i is one of FL. When load i has the potential to adjust upward at time t, P t > 0, when load i has the potential to adjust downward at time t, P t <0;v i is the regulation rate of load i; v slope The load adjustment rate required for the ramp scenario.

[0080] When P t >0, that is, sign(P t )=1, Y C,i The value of v i is proportional to, and its value range is When P t <0, that is, sign(P t )=-1, Y C,i The value of v i Inversely proportional, Y C,i The value range is

[0081] For the peak shaving scenario, the response speed requirement is average, and the duration requirement is relatively long, generally at the level of 15 minutes. However, the peak shaving call frequency is generally low, and the controllable load can usually meet the conditions. The peak shaving scenario adaptability index Y of load i is obtained. P,i ; The specific expression is:

[0082]

[0083] Among them, P t is the adjustable power of load i (here the load is a controllable load) at time t. When load i has the potential to be adjusted upward at time t, P t > 0, when load i has the potential to adjust downward at time t, P t <0;v i is the regulation rate of load i; v peak Load regulation rate required for peak shaving scenarios; The load adjustable power duration required for peak shaving scenarios, T i c is the adjustable power duration of load i.

[0084] Threshold value L peak The value range is: L peak ≥0, the higher the threshold value, the stricter the screening of adjustable resource conditions.

[0085] In the valley filling scenario, since the valley filling scenario is the same as the peak shaving scenario, the response speed requirement is general, the duration requirement is relatively long, and the calling frequency is generally low, the controllable load can basically meet the conditions, and the peak shaving scenario fitness index Y of load i is obtained. V,i ; The specific expression is:

[0086]

[0087] Where: P t is the adjustable power of load i (here the load is a controllable load) at time t. When load i has the potential to be adjusted upward at time t, P t > 0, when load i has the potential to adjust downward at time t, P t <0;v i is the regulation rate of load i; v valley The load adjustment rate required for valley filling scenarios; The load adjustable power duration required for valley filling scenario, T i c is the adjustable power duration of load i.

[0088] Threshold value L valley The value range is: L valley ≥0, the higher the threshold value, the stricter the screening of adjustable resource conditions.

[0089] Step S3: Obtain the relationship between the regulation power and regulation time of all loads in the load aggregation group, and draw a regulation capacity continuity curve based on the relationship to aggregate the load resources.

[0090] According to the previous steps, the load aggregation group that meets the climbing, peak shaving and valley filling scenarios is screened out, and the regulation capacity continuity curve is drawn according to the regulation power and regulation time relationship of all loads in the load aggregation group, including:

[0091] Get the adjustment power and adjustment time relationship f(P k ,t k ), the specific expression is:

[0092]

[0093] Where i represents the load, P i represents the regulation power of load i, t i represents the adjustment time of load i, and k represents the total number of loads.

[0094] By f(P k ,t k ) Obtain the continuous curve of the regulation capacity of the load aggregation group, that is, the regulation capacity of the load group at different times and the duration.

[0095] Among them, the classification aggregation method based on scene fitness indicators is as follows:

[0096] (1) Load aggregation in ramp scenarios:

[0097] ① Calculate the climbing scenario fitness index Y of all types of load-side resources participating in the aggregation C,i .

[0098] ② Set the load-side resource screening threshold value L for the ramping scenario slope . (Threshold value L slope The value range is: L slope ≥1, the higher the threshold value, the stricter the screening of adjustable resource conditions)

[0099] ③Filter the load-side resources according to the scenario threshold value. If Y C,i ≥L slope , then the scene requirements are met.

[0100] ④ Calculate the adjustable capacity continuity curve of the load aggregation group composed of all load-side resources that meet the scenario requirements.

[0101] (2) Load aggregation in peak shaving scenarios:

[0102] ① Calculate the climbing scenario fitness index Y of all types of load-side resources participating in the aggregation P,i .

[0103] ② Set the load-side resource screening threshold value L for peak shaving scenarios peak . (Threshold value L peak The value range is: L peak ≥0, the higher the threshold value, the stricter the screening of adjustable resource conditions)

[0104] ③Filter the load-side resources according to the scenario threshold value. If Y P,i ≥L peak , then the scene requirements are met.

[0105] ④ Calculate the adjustable capacity continuity curve of the load aggregation group composed of all load-side resources that meet the scenario requirements.

[0106] (3) Load aggregation in valley filling scenario:

[0107] ① Calculate the climbing scenario fitness index Y of all types of load-side resources participating in the aggregation V,i .

[0108] ② Set the load-side resource screening threshold value L for the valley-filling scenario valley . (Threshold value L valley The value range is: L valley≥0, the higher the threshold value, the stricter the screening of adjustable resource conditions)

[0109] ③Filter the load-side resources according to the scenario threshold value. If Y V,i ≥L valley , then the scene requirements are met.

[0110] ④ Calculate the adjustable capacity continuity curve of the load aggregation group composed of all load-side resources that meet the scenario requirements.

[0111] Based on the above method, the present invention provides a load resource aggregation system in an electric power system, comprising: a collection module, an indicator acquisition module and an output module.

[0112] Among them, the acquisition module is used to obtain the regulation characteristic matrix of all load-side resources participating in the aggregation in the power system; the indicator acquisition module is used to obtain the scenario fitness indicators of all types of load-side resources participating in the aggregation according to the load-side resource regulation characteristic matrix, and screen the load-side resources based on the scenario fitness indicators to screen out various load-side resources suitable for different balance scenarios of the power grid, forming a resource aggregation group for peak shaving, valley filling and climbing scenarios; the output module is used to obtain the relationship between the regulation power and regulation time of all loads in the load aggregation group, and draw the regulation capacity continuous curve through the relationship to aggregate the load resources.

[0113] The present invention also provides a computer device, including a memory and a processor, wherein a program is stored in the memory, and when the program is executed by the processor, the processor executes the steps of a load resource aggregation method in an electric power system.

[0114] In accordance with the disclosed embodiments, a computing device may communicate with one or more external devices (e.g., keyboards, pointing devices, Bluetooth communications, etc.), or with any device (e.g., routers, modems, etc.) that enables a computing device to communicate with one or more other computing devices.

[0115] The present invention also provides a storage medium on which a computer program is stored. When the computer program is executed by a processor, steps of a method for aggregating load resources in an electric power system are implemented.

[0116] According to the disclosed embodiments, the storage medium may be a non-volatile computer-readable storage medium, such as but not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, the storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0117] The above content is a further detailed description of the present invention in combination with a specific preferred embodiment. For technicians in the technical field to which the present invention belongs, several simple deductions or substitutions can be made without departing from the concept of the present invention, which should be regarded as belonging to the protection scope of the present invention.

Claims

1. A method for aggregating load resources in a power system, characterized in that: The steps include: Obtain the regulation characteristic matrix of all load-side resources participating in aggregation in the power system; According to the load-side resource regulation characteristic matrix, the scenario fitness indexes of all types of load-side resources participating in the aggregation are obtained, and the load-side resources are screened based on the scenario fitness indexes to select various load-side resources suitable for different balance scenarios of the power grid, forming a resource aggregation group for peak shaving, valley filling and slope climbing scenarios; The relationship between the regulation power and regulation time of all loads in the load aggregation group is obtained, and a regulation capacity continuity curve is drawn based on the relationship to aggregate the load resources.

2. A method for aggregating load resources in a power system according to claim 1, characterized in that: The step of obtaining the regulation characteristic matrix of all the load-side resources participating in the aggregation in the power system includes: The specific expression of the adjustment characteristic matrix is: Among them, A k is the regulation characteristic matrix, each row m represents various regulation characteristic indicators of this type of load side resources, and each column n represents the value of a certain regulation characteristic indicator of different load side resources; The regulation characteristics of the load resources in the regulation characteristic matrix include: maximum adjustable capacity, response time, regulation rate and adjustable duration, and the regulation characteristic matrix is ​​constructed with the regulation characteristics. The specific expression is: in, is the maximum adjustable capacity, that is, the remaining power output value of the largest power generation unit, the output value is the output power, t n is the response time, θ n To adjust the rate, T n c The duration is adjustable.

3. A method for aggregating load resources in a power system according to claim 2, characterized in that: The regulation characteristics of the load resources in the regulation characteristic matrix include: maximum adjustable capacity, response time, regulation rate and adjustable duration, specifically: The specific expression of the maximum adjustable capacity is: in, It indicates the average value of baseline load power of adjustable load group before adjustment during the adjustment period; It represents the average aggregate power of the adjustable load group after being adjusted in the maximum adjustment mode during the adjustment period. FL refers to the adjustable load group, which corresponds to each row m in the matrix, including temperature control load group, electric vehicle load group, energy storage load group or other combination groups; The specific expression of the response time is: t FL =t first -t strat ; Among them, t first Indicates the moment when the load group power reaches the regulation target value for the first time; t strat Indicates the start time of adjustment; The specific expression of the adjustment rate is: i FL =ΔP FL / t FL ; Among them, ΔP FL Indicates the adjustable capacity of the adjustable load group; t FL Indicates the response time; During the adjustable duration, Adjust power duration for flexible load groups.

4. A method for aggregating load resources in a power system according to claim 1, characterized in that: According to the load-side resource regulation characteristic matrix, the scenario adaptability indexes of all types of load-side resources participating in the aggregation are obtained, including: For the ramp scenario, obtain the ramp scenario index Y of load i C,i ; The specific expression is: Where sign(x) is the sign function; P t is the adjustable power of load i at time t, that is, the adjustable capacity. Load i is one of FL. When load i has the potential to adjust upward at time t, P t > 0, when load i has the potential to adjust downward at time t, P t <0;v i is the regulation rate of load i; v slope Load adjustment rate required for ramping scenarios; When P t >0, that is, sign(P t )=1, Y C,i The value of v i is proportional to, and its value range is When P t <0, that is, sign(P t )=-1, Y C,i The value of v i Inversely proportional, Y C,i The value range is 5. A method for aggregating load resources in a power system according to claim 4, characterized in that: The step of obtaining the scenario adaptability index of all types of load-side resources participating in the aggregation according to the load-side resource regulation characteristic matrix also includes: For the peak shaving scenario, obtain the peak shaving scenario fitness index Y of load i P,i ; The specific expression is: Among them, P t is the adjustable power of load i at time t. When load i has the potential to be adjusted upward at time t, P t > 0, when load i has the potential to adjust downward at time t, P t <0;v i is the regulation rate of load i; v peak Load regulation rate required for peak shaving scenarios; The load adjustable power duration required for peak shaving scenarios, T i c is the adjustable power duration of load i.

6. A method for aggregating load resources in a power system according to claim 5, characterized in that: The step of obtaining the scenario adaptability index of all types of load-side resources participating in the aggregation according to the load-side resource regulation characteristic matrix also includes: In the valley filling scenario, obtain the peak shaving scenario fitness index Y of load i V,i ; The specific expression is: Where: P t is the adjustable power of load i at time t. When load i has the potential to be adjusted upward at time t, P t > 0, when load i has the potential to adjust downward at time t, P t <0;v i is the regulation rate of load i; v valley The load adjustment rate required for valley filling scenarios; The load adjustable power duration required for valley filling scenario, T i c is the adjustable power duration of load i.

7. A method for aggregating load resources in a power system according to claim 1, characterized in that: The step of drawing a continuous adjustment capability curve according to the relationship between the adjustment power and the adjustment time of all loads in the load aggregation group includes: Get the adjustment power and adjustment time relationship f(P k ,t k ), the specific expression is: Where i represents the load, P i represents the regulation power of load i, t i represents the adjustment time of load i, and k represents the total number of loads; By f(P k ,t k ) Obtain the continuous curve of the regulation capacity of the load aggregation group.

8. A load resource aggregation system in a power system, characterized in that: include: A collection module is used to obtain the regulation characteristic matrix of all load-side resources participating in aggregation in the power system; The indicator acquisition module is used to obtain the scenario fitness indicators of all types of load-side resources participating in the aggregation according to the load-side resource regulation characteristic matrix, screen the load-side resources based on the scenario fitness indicators, and screen out various load-side resources suitable for different balance scenarios of the power grid to form a resource aggregation group for peak shaving, valley filling and slope climbing scenarios; The output module is used to obtain the relationship between the regulation power and regulation time of all loads in the load aggregation group, and to draw a regulation capacity continuity curve based on the relationship to aggregate the load resources.

9. A computer device, characterized in that: It comprises a memory and a processor, wherein a program is stored in the memory, and when the program is executed by the processor, the processor executes the steps of a load resource aggregation method in a power system as described in any one of claims 1 to 7.

10. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of a method for aggregating load resources in a power system according to any one of claims 1 to 7 are implemented.

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