Power demand side resource elasticity measurement method and device

Abstract

The invention relates to the technical field of demand side management, and particularly provides a power demand side resource elasticity measurement method and device, and the method comprises the steps: generating a first radar map based on the weight of a preset index corresponding to a power demand side resource; taking a product of an index value of a preset index corresponding to the power demand side resource and a weight of the preset index as an actual measurement standard value of the power demand side resource; generating a second radar map based on the power demand side resource actual measurement standard value; and measuring the elasticity of the power demand side resource by using the first radar map and the second radar map. According to the technical scheme provided by the invention, the interaction among the indexes is reserved, the elasticity of the demand side resources can be accurately measured, and a basis is provided for the elasticity of releasing the demand side resources in a high proportion.

Description

Technical Field

[0001] The present invention relates to the technical field of demand side management, and in particular to a method and device for measuring the elasticity of power demand side resources. Background Art

[0002] As the world enters the era of the Internet and digital economy, new technologies such as big cloud, Internet of Things, mobile Internet and artificial intelligence have become a powerful driving force for innovation, transformation and upgrading in all walks of life. The innovative development in the field of power demand side management is also facing new opportunities.

[0003] In today's energy market and the context of the continuous development of smart grid technology, the global electrification level continues to improve, the uncertainty of power supply and demand is prominent, the number of renewable energy grid-connected has increased significantly, and the proportion of flexible and adjustable resource stations on the user side has further increased. Demand-side management has gradually become a key means to improve energy utilization efficiency, optimize resource allocation and ensure stable operation of the power grid. As the core component of demand-side management, the demand-side resource pool integrates decentralized and adjustable demand-side resources, such as energy storage systems, interruptible loads, distributed energy, etc., and realizes flexible response to the power grid through unified scheduling and control.

[0004] From the perspective of the demand side, we are currently facing problems such as the overspeed development of new energy in some regions, the lagging growth of total load, the insufficient peak-shaving capacity of the power system, and the need to tap the potential of load flexibility. Therefore, it is necessary to strengthen the construction of power demand-side response capabilities, integrate decentralized demand response resources, guide users to optimize the storage and use of electricity, and release the elasticity of residential and general industrial and commercial electricity loads at a high rate. However, for a long time, the support foundation of demand-side management business has been weak, the demand-side resource elasticity measurement methods are lacking, the information of graphs, numbers, and tables is separated, the conversion is inflexible, and it is impossible to grasp the changes on the spot in time, to accurately analyze the grassroots problems, and to control the key points in the overall situation, which makes it difficult to diagnose problems in depth, to accurately invest in projects, to coordinate plans, to control the execution of processes, and to implement planning concepts.

[0005] In view of the above reasons, there is currently no effective solution for how to select indicators to characterize the multi-dimensional elasticity of demand-side resources and accurately measure the elasticity of demand-side resources to ensure the further dynamic construction of the demand-side resource pool. Summary of the invention

[0006] In order to overcome the above-mentioned defects, the present invention proposes a method and device for measuring the elasticity of resources on the power demand side.

[0007] In a first aspect, a method for measuring the elasticity of resources on the power demand side is provided, and the method for measuring the elasticity of resources on the power demand side includes:

[0008] Generate a first radar chart based on the weights of preset indicators corresponding to the power demand side resources;

[0009] The product of the index value of the preset index corresponding to the power demand side resource and the weight of the preset index is used as the actual measurement standard value of the power demand side resource;

[0010] Generate a second radar chart based on the actual measured standard value of the power demand side resource;

[0011] The first radar chart and the second radar chart are used to measure the elasticity of power demand-side resources.

[0012] Preferably, the preset indicators corresponding to the power demand side resources include at least one of the following: resource response rate, resource response degree, resource capacity, resource online rate, and resource reliability.

[0013] Furthermore, the resource response rate C d as follows:

[0014]

[0015] The resource response level C p as follows:

[0016]

[0017] The resource capacity C s as follows:

[0018]

[0019] The resource online rate C o as follows:

[0020]

[0021] The resource reliability C r as follows:

[0022]

[0023] In the above formula, T d is the actual response time, T o is the end response time point required by the control instruction, T s is the start response time point required by the control instruction, L i is the load value at the i-th time point, L s is the load value at the time of no response, o is the end time of regulation, s is the start time of regulation, is the load value function,

[0024] Preferably, the weights of the preset indicators corresponding to the power demand side resources are obtained through an expert scoring method.

[0025] Preferably, the measuring the elasticity of power demand-side resources by using the first radar chart and the second radar chart includes:

[0026] determining the area and perimeter of the first radar chart and the area and perimeter of the second radar chart respectively;

[0027] An elasticity metric value of the power demand side resource is determined based on the area and perimeter of the first radar map and the area and perimeter of the second radar map.

[0028] Furthermore, the area S and perimeter C of the first radar chart are as follows:

[0029]

[0030] In the above formula, q i is the weight of the preset indicator corresponding to the power demand side resource numbered i, q i+1 is the weight of the preset indicator corresponding to the power demand side resource numbered i+1, q 0 is the weight of the preset indicator corresponding to the power demand side resource numbered 0, q 4 is the weight of the preset indicator corresponding to the power demand side resource numbered 4, π is pi, and i is the number of the preset indicator corresponding to the power demand side resource.

[0031] Furthermore, the area S' and the perimeter C' of the second radar chart are as follows:

[0032]

[0033] In the above formula, μ i is the distance from the center of the circle of the preset indicator corresponding to the power demand side resource numbered i in the second radar chart, μ i+1 is the distance from the center of the circle of the preset indicator corresponding to the power demand side resource numbered i+1 in the second radar chart, μ 0 is the distance from the center of the circle of the preset indicator corresponding to the power demand side resource numbered 0 in the second radar chart, μ 4 The distance from the center of the circle of the preset indicator corresponding to the power demand side resource numbered 4 in the second radar chart.

[0034] Furthermore, the process of obtaining the serial number of the preset indicator corresponding to the power demand side resource includes:

[0035] Sorting the preset indicators in descending order according to the weights of the preset indicators corresponding to the power demand side resources;

[0036] Starting from 0, the indicators in the sequence are assigned numbers.

[0037] Furthermore, the elasticity metric value p of the power demand side resource is as follows:

[0038]

[0039] In the above formula, S" is the similarity area coefficient.

[0040] Furthermore, the similarity area coefficient is S"=(C' / C) 2 ·S.

[0041] In a second aspect, a device for measuring the elasticity of resources on the power demand side is provided, and the device for measuring the elasticity of resources on the power demand side comprises:

[0042] A first drawing module, used to generate a first radar chart based on the weights of preset indicators corresponding to the power demand side resources;

[0043] A first analysis module, configured to use the product of the index value of the preset index corresponding to the power demand side resource and the weight of the preset index as the actual measurement standard value of the power demand side resource;

[0044] A second drawing module, used for generating a second radar chart based on the actual measurement standard value of the power demand side resource;

[0045] The second analysis module is used to measure the elasticity of power demand side resources using the first radar chart and the second radar chart.

[0046] Preferably, the preset indicators corresponding to the power demand side resources include at least one of the following: resource response rate, resource response degree, resource capacity, resource online rate, and resource reliability.

[0047] Furthermore, the resource response rate C d as follows:

[0048]

[0049] The resource response level C p as follows:

[0050]

[0051] The resource capacity C s as follows:

[0052]

[0053] The resource online rate C o as follows:

[0054]

[0055] The resource reliability C ras follows:

[0056]

[0057] In the above formula, T d is the actual response time, T o is the end response time point required by the control instruction, T s is the start response time point required by the control instruction, L i is the load value at the i-th time point, L s is the load value at the time of no response, o is the end time of regulation, s is the start time of regulation, is the load value function,

[0058] Preferably, the weights of the preset indicators corresponding to the power demand side resources are obtained through an expert scoring method.

[0059] Preferably, the second analysis module is specifically used for:

[0060] determining the area and perimeter of the first radar chart and the area and perimeter of the second radar chart respectively;

[0061] An elasticity metric value of the power demand side resource is determined based on the area and perimeter of the first radar map and the area and perimeter of the second radar map.

[0062] Furthermore, the area S and perimeter C of the first radar chart are as follows:

[0063]

[0064] In the above formula, q i is the weight of the preset indicator corresponding to the power demand side resource numbered i, q i+1 is the weight of the preset indicator corresponding to the power demand side resource numbered i+1, q 0 is the weight of the preset indicator corresponding to the power demand side resource numbered 0, q 4 is the weight of the preset indicator corresponding to the power demand side resource numbered 4, π is pi, and i is the number of the preset indicator corresponding to the power demand side resource.

[0065] Furthermore, the area S' and the perimeter C' of the second radar chart are as follows:

[0066]

[0067] In the above formula, μ i is the distance from the center of the circle of the preset indicator corresponding to the power demand side resource numbered i in the second radar chart, μ i+1is the distance from the center of the circle of the preset indicator corresponding to the power demand side resource numbered i+1 in the second radar chart, μ 0 is the distance from the center of the circle of the preset indicator corresponding to the power demand side resource numbered 0 in the second radar chart, μ 4 The distance from the center of the circle of the preset indicator corresponding to the power demand side resource numbered 4 in the second radar chart.

[0068] Furthermore, the process of obtaining the serial number of the preset indicator corresponding to the power demand side resource includes:

[0069] Sorting the preset indicators in descending order according to the weights of the preset indicators corresponding to the power demand side resources;

[0070] Starting from 0, the indicators in the sequence are assigned numbers.

[0071] Furthermore, the elasticity metric value p of the power demand side resource is as follows:

[0072]

[0073] In the above formula, S" is the similarity area coefficient.

[0074] Furthermore, the similarity area coefficient is S"=(C' / C) 2 ·S.

[0075] In a third aspect, a computer device is provided, comprising: one or more processors;

[0076] The processor is configured to execute one or more programs;

[0077] When the one or more programs are executed by the one or more processors, the method for measuring the elasticity of resources on the power demand side is implemented.

[0078] In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed, the method for measuring the elasticity of resources on the power demand side is implemented.

[0079] The above one or more technical solutions of the present invention have at least one or more of the following beneficial effects:

[0080] The present invention provides a method and device for measuring the elasticity of power demand-side resources, including: generating a first radar chart based on the weight of a preset indicator corresponding to the power demand-side resource; taking the product of the index value of the preset indicator corresponding to the power demand-side resource and the weight of the preset indicator as the actual measurement standard value of the power demand-side resource; generating a second radar chart based on the actual measurement standard value of the power demand-side resource; and measuring the elasticity of power demand-side resources using the first radar chart and the second radar chart. The technical solution provided by the present invention retains the interaction between the indicators, avoids the separation between the indicators, characterizes the mutual influence between the elasticity indicators, uses the radar chart as the basis for measuring the elasticity of demand-side resources, that is, performs polygonal visualization of the elasticity of demand-side resources, and can also calculate the specific elasticity of demand-side resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] Figure 1 This is a schematic flow chart of the main steps of the method for measuring the elasticity of power demand-side resources according to an embodiment of the present invention;

[0082] Figure 2 is a schematic diagram of a first radar chart according to an embodiment of the present invention;

[0083] Figure 3 4 is a schematic diagram comparing the second radar chart and the first radar chart according to an embodiment of the present invention. DETAILED DESCRIPTION

[0084] The specific implementation modes of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0085] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of 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 are within the scope of protection of the present invention.

[0086] As disclosed in the background technology, as the world enters the era of the Internet and digital economy, new technologies such as big cloud, Internet of Things, mobile Internet and artificial intelligence have become a powerful driving force for innovation, transformation and upgrading in all walks of life, and the innovative development in the field of power demand side management is also facing new opportunities.

[0087] In today's energy market and the context of the continuous development of smart grid technology, the global electrification level continues to improve, the uncertainty of power supply and demand is prominent, the number of renewable energy grid-connected has increased significantly, and the proportion of flexible and adjustable resource stations on the user side has further increased. Demand-side management has gradually become a key means to improve energy utilization efficiency, optimize resource allocation and ensure stable operation of the power grid. As the core component of demand-side management, the demand-side resource pool integrates decentralized and adjustable demand-side resources, such as energy storage systems, interruptible loads, distributed energy, etc., and realizes flexible response to the power grid through unified scheduling and control.

[0088] From the perspective of the demand side, we are currently facing problems such as the overspeed development of new energy in some regions, the lagging growth of total load, the insufficient peak-shaving capacity of the power system, and the need to tap the potential of load flexibility. Therefore, it is necessary to strengthen the construction of power demand-side response capabilities, integrate decentralized demand response resources, guide users to optimize the storage and use of electricity, and release the elasticity of residential and general industrial and commercial electricity loads at a high rate. However, for a long time, the support foundation of demand-side management business has been weak, the demand-side resource elasticity measurement methods are lacking, the information of graphs, numbers, and tables is separated, the conversion is inflexible, and it is impossible to grasp the changes on the spot in time, to accurately analyze the grassroots problems, and to control the key points in the overall situation, which makes it difficult to diagnose problems in depth, to accurately invest in projects, to coordinate plans, to control the execution of processes, and to implement planning concepts.

[0089] In view of the above reasons, there is currently no effective solution for how to select indicators to characterize the multi-dimensional elasticity of demand-side resources and accurately measure the elasticity of demand-side resources to ensure the further dynamic construction of the demand-side resource pool.

[0090] In order to improve the above problems, the present invention provides a method and device for measuring the elasticity of power demand-side resources, including: generating a first radar chart based on the weight of the preset index corresponding to the power demand-side resources; taking the product of the index value of the preset index corresponding to the power demand-side resources and the weight of the preset index as the actual measurement standard value of the power demand-side resources; generating a second radar chart based on the actual measurement standard value of the power demand-side resources; and measuring the elasticity of power demand-side resources using the first radar chart and the second radar chart. The technical solution provided by the present invention retains the interaction between the various indicators, avoids the separation between the various indicators, characterizes the mutual influence between the elasticity indicators, uses the radar chart as the basis for measuring the elasticity of demand-side resources, that is, performs polygonal visualization of the elasticity of demand-side resources, and can also calculate the specific elasticity of demand-side resources.

[0091] The above scheme is described in detail below.

[0092] Example 1

[0093] See attached Figure 1 , Figure 1FIG. 1 is a flow chart showing the main steps of a method for measuring the elasticity of power demand side resources according to an embodiment of the present invention. Figure 1 As shown, the power demand side resource elasticity measurement method in the embodiment of the present invention mainly includes the following steps:

[0094] Step S101: Generate a first radar chart based on the weights of preset indicators corresponding to power demand side resources, such as Figure 2 As shown;

[0095] Step S102: taking the product of the index value of the preset index corresponding to the power demand side resource and the weight of the preset index as the actual measurement standard value of the power demand side resource;

[0096] Step S103: Generate a second radar chart based on the actual measurement standard value of the power demand side resource, for example, import the actual measurement standard value of the power demand side resource and compare it with the first radar chart, as shown in the following example: Figure 3 As shown;

[0097] Step S104: using the first radar chart and the second radar chart to measure the elasticity of power demand-side resources.

[0098] In this embodiment, before executing the power demand side resource elasticity measurement method provided by the present invention, the initial data of the demand side resources (power load data) needs to be preprocessed, missing values ​​are filled, and data of different dimensions are normalized. For example, 96-point load data of various types of resources are input, and the missing data in the data set is filled with 0. While preprocessing the data, it is beneficial to statistically calculate the resources in the process of calculating the online rate of demand side resources, and the data of 0 is equivalent to the resources being offline, thereby simplifying the calculation process.

[0099] In this embodiment, the preset indicators corresponding to the power demand side resources include at least one of the following: resource response rate, resource response degree, resource capacity, resource online rate, and resource reliability.

[0100] In this embodiment, the resource response rate C d as follows:

[0101]

[0102] The resource response level C p as follows:

[0103]

[0104] The resource capacity C s as follows:

[0105]

[0106] The resource online rate C o as follows:

[0107]

[0108] The resource reliability C r as follows:

[0109]

[0110] In the above formula, T d is the actual response time, T o is the end response time point required by the control instruction, T s is the start response time point required by the control instruction, L i is the load value at the i-th time point, L s is the load value at the time of no response, o is the end time of regulation, s is the start time of regulation, is the load value function,

[0111] In this embodiment, the weights of the preset indicators corresponding to the power demand side resources are obtained by expert scoring. For example, the expert scoring method is used to rank the values ​​of the five indicators of resource response rate, resource response degree, resource capacity, resource online rate, and resource reliability. i ={0.31,0.27,0.21,0.14,0.07}.

[0112] In this embodiment, the use of the first radar map and the second radar map to measure the elasticity of power demand-side resources includes:

[0113] determining the area and perimeter of the first radar chart and the area and perimeter of the second radar chart respectively;

[0114] An elasticity metric value of the power demand side resource is determined based on the area and perimeter of the first radar map and the area and perimeter of the second radar map.

[0115] In one embodiment, the area S and perimeter C of the first radar chart are as follows:

[0116]

[0117] In the above formula, q i is the weight of the preset indicator corresponding to the power demand side resource numbered i, q i+1 is the weight of the preset indicator corresponding to the power demand side resource numbered i+1, q 0 is the weight of the preset indicator corresponding to the power demand side resource numbered 0, q 4is the weight of the preset indicator corresponding to the power demand side resource numbered 4, π is pi, and i is the number of the preset indicator corresponding to the power demand side resource.

[0118] In one embodiment, the area S' and the perimeter C' of the second radar chart are as follows:

[0119]

[0120] In the above formula, μ i is the distance from the center of the circle of the preset indicator corresponding to the power demand side resource numbered i in the second radar chart, μ i+1 is the distance from the center of the circle of the preset indicator corresponding to the power demand side resource numbered i+1 in the second radar chart, μ 0 is the distance from the center of the circle of the preset indicator corresponding to the power demand side resource numbered 0 in the second radar chart, μ 4 The distance from the center of the circle of the preset indicator corresponding to the power demand side resource numbered 4 in the second radar chart.

[0121] In one embodiment, the process of obtaining the serial number of the preset indicator corresponding to the power demand side resource includes:

[0122] Sorting the preset indicators in descending order according to the weights of the preset indicators corresponding to the power demand side resources;

[0123] Starting from 0, the indicators in the sequence are assigned numbers.

[0124] Furthermore, the elasticity metric value p of the power demand side resource is as follows:

[0125]

[0126] In the above formula, S" is the similarity area coefficient.

[0127] Furthermore, the similarity area coefficient is S"=(C' / C) 2 ·S.

[0128] Example 2

[0129] Based on the same inventive concept, the present invention also provides a power demand side resource elasticity measurement device, the power demand side resource elasticity measurement device comprising:

[0130] A first drawing module, used to generate a first radar chart based on the weights of preset indicators corresponding to the power demand side resources;

[0131] A first analysis module, configured to use the product of the index value of the preset index corresponding to the power demand side resource and the weight of the preset index as the actual measurement standard value of the power demand side resource;

[0132] A second drawing module, used for generating a second radar chart based on the actual measurement standard value of the power demand side resource;

[0133] The second analysis module is used to measure the elasticity of power demand side resources using the first radar chart and the second radar chart.

[0134] Preferably, the preset indicators corresponding to the power demand side resources include at least one of the following: resource response rate, resource response degree, resource capacity, resource online rate, and resource reliability.

[0135] Preferably, the resource response rate C d as follows:

[0136]

[0137] The resource response level C p as follows:

[0138]

[0139] The resource capacity C s as follows:

[0140]

[0141] The resource online rate C o as follows:

[0142]

[0143] The resource reliability C r as follows:

[0144]

[0145] In the above formula, T d is the actual response time, T o is the end response time point required by the control instruction, T s is the start response time point required by the control instruction, L i is the load value at the i-th time point, L s is the load value at the time of no response, o is the end time of regulation, s is the start time of regulation, is the load value function,

[0146] Preferably, the weights of the preset indicators corresponding to the power demand side resources are obtained through an expert scoring method.

[0147] Preferably, the second analysis module is specifically used for:

[0148] determining the area and perimeter of the first radar chart and the area and perimeter of the second radar chart respectively;

[0149] An elasticity metric value of the power demand side resource is determined based on the area and perimeter of the first radar map and the area and perimeter of the second radar map.

[0150] Furthermore, the area S and perimeter C of the first radar chart are as follows:

[0151]

[0152] In the above formula, q i is the weight of the preset indicator corresponding to the power demand side resource numbered i, q i+1 is the weight of the preset indicator corresponding to the power demand side resource numbered i+1, q 0 is the weight of the preset indicator corresponding to the power demand side resource numbered 0, q 4 is the weight of the preset indicator corresponding to the power demand side resource numbered 4, π is pi, and i is the number of the preset indicator corresponding to the power demand side resource.

[0153] Furthermore, the area S' and the perimeter C' of the second radar chart are as follows:

[0154]

[0155] In the above formula, μ i is the distance from the center of the circle of the preset indicator corresponding to the power demand side resource numbered i in the second radar chart, μ i+1 is the distance from the center of the circle of the preset indicator corresponding to the power demand side resource numbered i+1 in the second radar chart, μ 0 is the distance from the center of the circle of the preset indicator corresponding to the power demand side resource numbered 0 in the second radar chart, μ 4 The distance from the center of the circle of the preset indicator corresponding to the power demand side resource numbered 4 in the second radar chart.

[0156] Furthermore, the process of obtaining the serial number of the preset indicator corresponding to the power demand side resource includes:

[0157] Sorting the preset indicators in descending order according to the weights of the preset indicators corresponding to the power demand side resources;

[0158] Starting from 0, the indicators in the sequence are assigned numbers.

[0159] Furthermore, the elasticity metric value p of the power demand side resource is as follows:

[0160]

[0161] In the above formula, S" is the similarity area coefficient.

[0162] Furthermore, the similarity area coefficient is S"=(C' / C) 2 ·S.

[0163] Example 3

[0164] Based on the same inventive concept, the present invention also provides a computer device, which includes a processor and a memory, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions in a computer storage medium to implement the corresponding method flow or corresponding function, so as to implement the steps of a method for measuring the elasticity of resources on the power demand side in the above embodiment.

[0165] Example 4

[0166] Based on the same inventive concept, the present invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device for storing programs and data. It can be understood that the computer-readable storage medium here can include both built-in storage media in a computer device and, of course, extended storage media supported by the computer device. The computer-readable storage medium provides a storage space that stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by a processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of a method for measuring the elasticity of resources on the power demand side in the above embodiment.

[0167] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0168] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0169] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0170] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0171] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for measuring the elasticity of power demand-side resources. It is characterized in that The method comprises: Generate a first radar chart based on the weights of preset indicators corresponding to the power demand side resources; The product of the index value of the preset index corresponding to the power demand side resource and the weight of the preset index is used as the actual measurement standard value of the power demand side resource; Generate a second radar chart based on the actual measured standard value of the power demand side resource; The first radar chart and the second radar chart are used to measure the elasticity of power demand-side resources.

2. The method according to claim 1, It is characterized in that The preset indicators corresponding to the power demand side resources include at least one of the following: resource response rate, resource response degree, resource capacity, resource online rate, and resource reliability.

3. The method according to claim 2, It is characterized in that The resource response rate C d as follows: The resource response level C p as follows: The resource capacity C s as follows: The resource online rate C o as follows: The resource reliability C r as follows: In the above formula, T d is the actual response time, T o is the end response time point required by the control instruction, T s is the start response time point required by the control instruction, L i is the load value at the i-th time point, L s is the load value at the time of no response, o is the end time of regulation, s is the start time of regulation, is the load value function, 4. The method according to claim 1, It is characterized in that The weights of the preset indicators corresponding to the power demand side resources are obtained through an expert scoring method.

5. The method according to claim 1, It is characterized in that The using the first radar map and the second radar map to measure the elasticity of power demand-side resources includes: determining the area and perimeter of the first radar chart and the area and perimeter of the second radar chart respectively; An elasticity metric value of the power demand side resource is determined based on the area and perimeter of the first radar map and the area and perimeter of the second radar map.

6. The method according to claim 5, It is characterized in that The area S and perimeter C of the first radar chart are as follows: In the above formula, q i is the weight of the preset indicator corresponding to the power demand side resource numbered i, q i+1 is the weight of the preset indicator corresponding to the power demand side resource numbered i+1, q 0 is the weight of the preset indicator corresponding to the power demand side resource numbered 0, q 4 is the weight of the preset indicator corresponding to the power demand side resource numbered 4, π is pi, and i is the number of the preset indicator corresponding to the power demand side resource.

7. The method according to claim 6, It is characterized in that The area S' and perimeter C' of the second radar chart are as follows: In the above formula, μ i is the distance from the center of the circle of the preset indicator corresponding to the power demand side resource numbered i in the second radar chart, μ i+1 is the distance from the center of the circle of the preset indicator corresponding to the power demand side resource numbered i+1 in the second radar chart, μ 0 is the distance from the center of the circle of the preset indicator corresponding to the power demand side resource numbered 0 in the second radar chart, μ 4 The distance from the center of the circle of the preset indicator corresponding to the power demand side resource numbered 4 in the second radar chart.

8. The method according to claim 6, It is characterized in that The process of obtaining the number of the preset indicator corresponding to the power demand side resource includes: Sorting the preset indicators in descending order according to the weights of the preset indicators corresponding to the power demand side resources; Starting from 0, the indicators in the sequence are assigned numbers.

9. The method according to claim 7, It is characterized in that The elasticity metric value p of the power demand side resource is as follows: In the above formula, S" is the similarity area coefficient.

10. The method according to claim 9, It is characterized in that The similarity area coefficient is S" = (C' / C) 2 ·S.

11. A device for measuring the elasticity of power demand-side resources. It is characterized in that The device comprises: A first drawing module, used to generate a first radar chart based on the weights of preset indicators corresponding to the power demand side resources; A first analysis module, configured to use the product of the index value of the preset index corresponding to the power demand side resource and the weight of the preset index as the actual measurement standard value of the power demand side resource; A second drawing module, used for generating a second radar chart based on the actual measurement standard value of the power demand side resource; The second analysis module is used to measure the elasticity of power demand side resources using the first radar chart and the second radar chart.

12. The device according to claim 11, It is characterized in that The preset indicators corresponding to the power demand side resources include at least one of the following: resource response rate, resource response degree, resource capacity, resource online rate, and resource reliability.

13. The device according to claim 12, It is characterized in that The resource response rate C d as follows: The resource response level C p as follows: The resource capacity C s as follows: The resource online rate C o as follows: The resource reliability C r as follows: In the above formula, T d is the actual response time, T o is the end response time point required by the control instruction, T s is the start response time point required by the control instruction, L i is the load value at the i-th time point, L s is the load value at the time of no response, o is the end time of regulation, s is the start time of regulation, f Li≠0 is the load value function, 14. The device according to claim 11, It is characterized in that The weights of the preset indicators corresponding to the power demand side resources are obtained through an expert scoring method.

15. The device according to claim 11, It is characterized in that The second analysis module is specifically used for: determining the area and perimeter of the first radar chart and the area and perimeter of the second radar chart respectively; An elasticity metric value of the power demand side resource is determined based on the area and perimeter of the first radar map and the area and perimeter of the second radar map.

16. The device according to claim 15, It is characterized in that The area S and perimeter C of the first radar chart are as follows: In the above formula, q i is the weight of the preset indicator corresponding to the power demand side resource numbered i, q i+1 is the weight of the preset indicator corresponding to the power demand side resource numbered i+1, q 0 is the weight of the preset indicator corresponding to the power demand side resource numbered 0, q 4 is the weight of the preset indicator corresponding to the power demand side resource numbered 4, π is pi, and i is the number of the preset indicator corresponding to the power demand side resource.

17. The device according to claim 16, It is characterized in that The area S' and perimeter C' of the second radar chart are as follows: In the above formula, μ i is the distance from the center of the circle of the preset indicator corresponding to the power demand side resource numbered i in the second radar chart, μ i+1 is the distance from the center of the circle of the preset indicator corresponding to the power demand side resource numbered i+1 in the second radar chart, μ 0 is the distance from the center of the circle of the preset indicator corresponding to the power demand side resource numbered 0 in the second radar chart, μ 4 The distance from the center of the circle of the preset indicator corresponding to the power demand side resource numbered 4 in the second radar chart.

18. The device according to claim 16, It is characterized in that The process of obtaining the number of the preset indicator corresponding to the power demand side resource includes: Sorting the preset indicators in descending order according to the weights of the preset indicators corresponding to the power demand side resources; Starting from 0, the indicators in the sequence are assigned numbers.

19. The device according to claim 17, It is characterized in that The elasticity metric value p of the power demand side resource is as follows: In the above formula, S" is the similarity area coefficient.

20. The device according to claim 19, It is characterized in that The similarity area coefficient is S" = (C' / C) 2 ·S.

21. A computer device, It is characterized in that include: one or more processors; The processor is configured to execute one or more programs; When the one or more programs are executed by the one or more processors, the power demand side resource elasticity measurement method as described in any one of claims 1 to 10 is implemented.

22. A computer-readable storage medium, It is characterized in that A computer program is stored thereon, and when the computer program is executed, the method for measuring the elasticity of power demand-side resources as described in any one of claims 1 to 10 is implemented.

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