Capability verification method and system

Abstract

The invention belongs to the technical field of power grid resource allocation, and provides a capability verification method and system, and the method comprises the steps: obtaining basic data of each power grid node in a power grid, carrying out the processing and analysis of the basic data of the power grid nodes, and obtaining a key value GJZ of the power grid nodes, obtaining a resource allocation ratio of the power grid nodes according to the key values GJZ of the power grid nodes, and carrying out resource allocation on the power grid nodes; the method comprises the following steps: after power grid resource allocation is completed, obtaining power grid resource use data of a power grid node in a use cycle, obtaining a power grid resource reasonable use parameter HL based on processing and analysis of the power grid resource use data, and comparing the power grid resource reasonable use parameter HL with a power grid resource reasonable use parameter threshold HG; the reasonable degree of power grid resource use is judged according to the comparison result, power grid resource allocation rationalization is achieved, and the stability of power grid operation can be improved.

Description

Technical Field

[0001] The invention belongs to the technical field of power grid resource configuration, and in particular relates to a capability verification method and system. Background Art

[0002] With the continuous development of power systems and the improvement of their intelligence level, the problem of grid resource allocation has become increasingly prominent. Traditional grid resource allocation methods often lack pertinence and accuracy, and are difficult to adapt to the complex and changeable operation requirements of modern power grids. Therefore, developing a resource allocation optimization method based on grid node importance evaluation has important practical application value.

[0003] The existing power system needs to allocate resources to achieve stable operation of the power system; however, due to the influence of resource allocation, if the resources are unevenly allocated, the power system will be unstable, thus affecting power transmission;

[0004] Therefore, how to reasonably allocate resources according to the capabilities of power nodes and effectively and reasonably verify the allocation effects after the allocation is an important link in improving the rationality of resource allocation, which can ensure the rational operation of power resources.

[0005] To this end, the present invention provides a capability verification method and system. Summary of the invention

[0006] In order to make up for the deficiencies of the prior art, at least one technical problem raised in the background technology is solved.

[0007] The present invention combines the degree of power grid nodes and the injected power to evaluate and analyze the capabilities of power grid nodes, allocates power grid resources according to the capabilities of power grid nodes, and realizes power grid resource allocation. By combining the time when power grid resources are not fully utilized and the size of power grid resources that are not fully utilized, the sufficiency of power grid resource utilization is analyzed, thereby preventing waste of power grid resource allocation and facilitating understanding of the sufficiency of utilization of power grid configuration resources, thereby facilitating subsequent optimization of power grid resource allocation. By analyzing the number of abnormal key nodes in abnormal power grid nodes, the timeliness of power grid resource allocation optimization is analyzed, thereby preventing the occurrence of abnormal or unstable power grid operation caused by failure to timely optimize and adjust power grid resource allocation.

[0008] The technical solution adopted by the present invention to solve the technical problem is: a capability verification method, comprising:

[0009] Obtain the basic data of each grid node in the power grid, obtain the key value GJZ of the grid node based on the processing and analysis of the basic data of the grid node, and obtain the resource allocation ratio of the grid node according to the key value GJZ of the grid node, and perform resource allocation on the grid node;

[0010] After the grid resource allocation is completed, the grid resource usage data of the grid node in the usage period is obtained. Based on the processing and analysis of the grid resource usage data, the grid resource reasonable usage parameter HL is obtained, and the grid resource reasonable usage parameter HL is compared with the grid resource reasonable usage parameter threshold HG. The reasonable degree of grid resource usage is verified according to the comparison result:

[0011] If the grid resource reasonable use parameter HL>grid resource reasonable use parameter threshold HG, it means that the reasonable degree of grid resource use is low;

[0012] If the grid resource reasonable use parameter HL ≤ the grid resource reasonable use parameter threshold HG, it means that the reasonable degree of grid resource use is high.

[0013] As a further technical solution of the present invention, the basic data of the power grid node includes the degree of the power grid node and the injected power value of the power grid node;

[0014] Based on the processing and analysis of the degree of the grid node, the degree proportion of the grid node is obtained, and based on the processing and analysis of the injected power value of the grid, the power operation status performance value of the grid node is obtained;

[0015] The degree proportion of the power grid node is multiplied by the power operation status performance value to obtain the key value GJZ of the power grid node.

[0016] As a further technical solution of the present invention, the key values ​​GJZ of all power grid nodes are obtained, and the key values ​​GJZ are summed to obtain the sum of the key values ​​of the power grid nodes, and the key values ​​of the power grid nodes are respectively processed with the sum of the key values ​​of the power grid nodes to obtain the resource allocation ratio of the power grid nodes;

[0017] The total capacity of the power grid resources is obtained, and the total capacity of the power grid resources is multiplied by the resource allocation ratio of each node to obtain the power grid resource capacity allocated to each node, and it is marked as the power grid resource configuration capacity.

[0018] As a further technical solution of the present invention, the method for obtaining the degree ratio of the power grid node is:

[0019] According to the degrees of all grid nodes, the total degree value of all grid nodes is obtained by summing up, and the degree of the grid node is compared with the total degree value of all grid nodes to obtain the degree ratio of the grid node;

[0020] The power operation status performance value of the power grid node is obtained in the following manner:

[0021] The detection duration is divided into a plurality of continuous and equal time subunits, and the injection power mean value in the time subunit is obtained according to the maximum injection power value and the minimum injection power value in each time subunit, and the injection power mean values ​​in all time subunits are summed and averaged to obtain the injection power mean value of the power grid node, and the injection power mean values ​​of all power grid nodes are summed and averaged to obtain the injection power comparison mean value of the power grid node;

[0022] The average value of the injected power of the grid node is processed by ratio with the average value of the injected power comparison of the grid node to obtain the average value ratio of the injected power of the grid node;

[0023] Obtaining the injected power values ​​at several different detection time points within the detection time, and marking and connecting them in an XY two-dimensional coordinate system to obtain an injected power variation curve;

[0024] The average value of the injected power of the power grid node is used as the reference injected power value to make a reference injected power line;

[0025] Measure the area enclosed by the reference injection power line and the injection power variation curve, and mark it as the actual area; measure the area enclosed by the reference injection power line and the X-axis, and mark it as the reference area; perform ratio processing on the actual area and the reference area to obtain the fluctuation area ratio;

[0026] The reference injection power line is compared with the injection power variation curve, the horizontal length of the overlapped line segment between the reference injection power line and the injection power variation curve is measured, and the horizontal length of the overlapped line segment is measured, and the horizontal length of the reference injection power line is subjected to difference processing, and the absolute value of the difference is taken to obtain the fluctuation length, and the fluctuation length is subjected to ratio processing to the horizontal length of the reference injection power line to obtain the fluctuation length ratio;

[0027] According to the fluctuation area ratio, the fluctuation length ratio and the average ratio of the injected power of the power grid node, the power operation status performance value of the power grid node is obtained by processing the output.

[0028] As a further technical solution of the present invention, the grid resource usage data includes the usage capacity of the grid resources, and the grid resource deviation capacity ratio is obtained by processing and outputting the usage capacity of the grid resources and the grid resource configuration capacity of the grid node;

[0029] comparing the power grid resource deviation capacity ratio with the power grid resource deviation capacity ratio threshold, and generating an abnormal deviation signal if the power grid resource deviation capacity ratio is greater than the power grid resource deviation capacity ratio threshold;

[0030] Based on processing the abnormal deviation signal, a sufficient parameter DWg of the grid resource usage of the grid node is obtained, and the grid node is marked according to the sufficient parameter DWg of the grid resource usage of the grid node, and is marked as a normal grid node and an abnormal grid node;

[0031] The number of abnormal grid nodes is counted, and the ratio of the number of abnormal grid nodes to the number of grid nodes is processed to obtain the grid resource reasonable utilization parameter HL.

[0032] As a further technical solution of the present invention, the grid resource utilization sufficient parameter DWg of the grid node is obtained in the following manner:

[0033] According to the duration of each occurrence of the abnormal deviation signal, the total duration of the abnormal deviation signal is obtained, and the total duration of the abnormal deviation signal is processed by ratio with the use cycle to obtain the total duration ratio of the abnormal deviation signal;

[0034] Mark the duration of the abnormal deviation signal as an abnormal time period, divide the abnormal time period into several equal time sub-units, obtain the average power grid resource deviation capacity ratio in the time sub-unit according to the maximum power grid resource deviation capacity ratio and the minimum power grid resource deviation capacity ratio in the time sub-unit, sum and average the average power grid resource deviation capacity ratios in all time sub-units to obtain the average power grid resource deviation capacity ratio in the abnormal time period, perform ratio processing on the average power grid resource deviation capacity ratio in the abnormal time period and the power grid resource deviation capacity ratio threshold to obtain the average power grid resource deviation capacity ratio proportion in the abnormal time period;

[0035] According to the proportion of the total duration of the abnormal deviation signal and the average proportion of the power grid resource deviation capacity ratio in the abnormal time period, the processing output is obtained to obtain the power grid resource utilization sufficiency parameter DWg of the power grid node.

[0036] As a further technical solution of the present invention, it also includes:

[0037] Based on the low rationality of grid resource use, the key value of the abnormal grid node is obtained, and the key value of the abnormal grid node is compared with the key threshold. The abnormal grid node is marked according to the comparison result, and it is marked as an abnormal key node and an abnormal non-key node, and the quantity data of the abnormal key node is obtained. Based on the analysis of the quantity data of the abnormal key nodes, the optimization timeliness value KF is obtained, and the optimization timeliness value KF is compared with the optimization timeliness threshold:

[0038] If the optimization timeliness value KF ≥ optimization timeliness threshold, it means that the configuration of power grid resources needs to be optimized in time;

[0039] If the optimization timeliness value KF is less than the optimization timeliness threshold, the configuration of the power grid resources does not need to be optimized in a timely manner.

[0040] As a further technical solution of the present invention, the optimization timeliness value KF is obtained in the following manner:

[0041] Compare the critical value of the abnormal grid node with the critical threshold:

[0042] If the critical value of the abnormal power grid node is ≥ the critical threshold, the abnormal power grid node is marked as an abnormal critical node;

[0043] If the critical value of the abnormal power grid node is less than the critical threshold, the abnormal power grid node is marked as an abnormal non-critical node;

[0044] The number of abnormal key nodes and the number of abnormal power grid nodes in the abnormal power grid nodes are counted, and the ratios are processed to obtain the optimized timeliness value KF.

[0045] As a further technical solution of the present invention, timely optimization is required based on the configuration of power grid resources, the average power grid resource usage capacity of abnormal power grid nodes in the use period is obtained and compared with the power grid resource configuration capacity of abnormal power grid nodes, and the abnormal power grid nodes are marked as abnormal power grid nodes with insufficient resource usage and abnormal power grid nodes with insufficient resource usage according to the comparison results;

[0046] The average grid resource usage capacity of the abnormal grid node with insufficient resource utilization during the usage period is processed with the grid configuration resource capacity of the abnormal grid node with insufficient resource utilization, and the absolute value of the difference is taken to obtain the grid dispatching resource capacity of the abnormal grid node with insufficient resource utilization. According to the grid dispatching resource capacity, the grid configuration resources of the abnormal grid node with insufficient resource utilization with the same resource capacity are used as dispatching resources in the grid configuration resources, and the dispatching resources are allocated to the abnormal grid node with insufficient resource utilization.

[0047] A capability verification system, comprising:

[0048] Grid resource configuration module: obtains the basic data of each grid node in the grid, processes and analyzes the basic data of the grid node, obtains the key value GJZ of the grid node, obtains the resource allocation ratio of the grid node according to the key value GJZ of the grid node, and configures the resources of the grid node;

[0049] Rationality of use verification module: After the grid resource allocation is completed, the grid resource usage data of the grid node in the usage period is obtained, and the grid resource reasonable use parameter HL is obtained based on the processing and analysis of the grid resource usage data. The grid resource reasonable use parameter HL is compared with the grid resource reasonable use parameter threshold HG, and the rationality of grid resource use is judged according to the comparison result:

[0050] If the grid resource reasonable use parameter HL>grid resource reasonable use parameter threshold HG, it means that the reasonable degree of grid resource use is low;

[0051] If the grid resource reasonable use parameter HL ≤ the grid resource reasonable use parameter threshold HG, it means that the reasonable degree of grid resource use is high.

[0052] The beneficial effects of the present invention are as follows:

[0053] 1. The present invention processes and analyzes the degree and injected power of the power grid node to obtain the key value GJZ of the power grid node, and obtains the resource allocation ratio of the power grid node according to the key value GJZ of the power grid node. According to the resource allocation ratio of the power grid node, the power grid node is configured with resources. The present invention combines the degree and injected power of the power grid node to evaluate and analyze the capacity of the power grid node, and allocates power grid resources according to the capacity of the power grid node. While realizing the allocation of power grid resources, it ensures that the power grid nodes with higher capabilities have matching power grid resource configurations at critical moments, realizes the rationalization of the allocation of power grid resources, and is conducive to improving the stability of power grid operation.

[0054] 2. The present invention obtains grid resource usage data of a grid node within a usage period, wherein the grid resource usage data includes the usage capacity of the grid resources, obtains a grid resource usage sufficiency parameter DWg of the grid node based on processing and analysis of the grid resource usage data, marks the grid node according to the grid resource usage sufficiency parameter DWg of the grid node, analyzes the marked grid node, obtains a grid resource reasonable usage parameter HL, and compares the grid resource reasonable usage parameter HL with a grid resource reasonable usage parameter threshold, verifies the reasonableness of grid resource usage based on the comparison result, and analyzes the sufficiency of grid resource utilization by combining the time when grid resources are not fully utilized and the size of grid resources that are not fully utilized, thereby preventing waste of grid resource allocation and facilitating understanding of the sufficiency of grid configuration resources, facilitating subsequent optimization of grid resource allocation, and being beneficial to improving grid operation efficiency and operation stability.

[0055] 3. Based on the low rationality of power grid resource utilization, the present invention obtains the key values ​​of abnormal power grid nodes, marks the abnormal power grid nodes according to the key values ​​of the power grid root nodes, distinguishes them from abnormal key power grid nodes and abnormal non-key nodes, and obtains the quantity data of the abnormal key nodes. Based on the analysis of the quantity data of the abnormal key nodes, the optimization timeliness value KF is obtained, and the optimization timeliness value KF is compared with the optimization timeliness threshold value. According to the comparison result, it is judged whether the configuration of power grid resources needs to be optimized in time. The present invention realizes the analysis of the timeliness of power grid resource configuration optimization by analyzing the number of abnormal key nodes in the abnormal power grid nodes, which can prevent the occurrence of abnormal or unstable power grid operation caused by the failure to timely optimize and adjust the power grid resource configuration, and timely optimize the power grid resource configuration, thereby reducing the waste of power grid resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The present invention will be further described below in conjunction with the accompanying drawings.

[0057] Figure 1 is a flow chart of a capability verification method according to Embodiment 1 of the present invention;

[0058] Figure 2 is a flow chart of a capability verification method according to Embodiment 2 of the present invention;

[0059] Figure 3 Flow chart of a capability verification method according to Embodiment 3 of the present invention

[0060] Figure 4 It is a flowchart of a capability verification system according to Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0061] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0062] Example 1

[0063] like Figure 1 As shown, a capability verification method according to an embodiment of the present invention includes:

[0064] Step 1: Obtain basic data of each grid node in the power grid, wherein the basic data includes the degree of the grid node and the injected power value of the grid node, obtain the key value GJZ of the grid node based on the processing and analysis of the basic data of the grid node, and obtain the resource allocation ratio of the grid node according to the key value GJZ of the grid node, and configure resources for the grid node according to the resource allocation ratio of the grid node;

[0065] In some embodiments, topological data of the power grid is obtained through a power grid resource management system, wherein the topological data is used to analyze the connection status of each node, and the number of edges connected to each node is counted to determine the degree of the node;

[0066] In some embodiments, a measuring device is installed at a grid node, and the power data of each node is accurately acquired by the measuring device and setting a detection duration, so as to obtain the injected power of the grid node;

[0067] Among them, the key value GJZ of the power grid node is obtained as follows:

[0068] Based on the processing and analysis of the degree of the grid node, the degree proportion of the grid node is obtained, and based on the processing and analysis of the injected power value of the grid, the power operation status performance value of the grid node is obtained;

[0069] The degree proportion of the power grid node is multiplied by the power operation status performance value to obtain the key value GJZ of the power grid node;

[0070] It should be noted that the concept and purpose of obtaining the key value GJZ of the power grid node is that the key value GJZ of the power grid node is obtained by analyzing the degree and injected power of the power grid node, and the purpose of obtaining the key value GJZ of the power grid node is to evaluate the capacity of the power grid node, so as to facilitate the subsequent reasonable allocation of power grid resources. The reason for analyzing the degree and injected power of the power grid node is that among the power grid nodes, the power grid nodes with higher capacity have the obvious characteristics of: large power transmission effect, that is, in the power transmission process, it plays the role of a transmission bridge, and its corresponding degree is large, and secondly, strong transmission stability and strong transmission capacity, that is, in the power transmission process, it not only requires high power transmission, but also needs to have a relatively stable transmission state;

[0071] Exemplarily, the degree ratio of the power grid node is obtained as follows:

[0072] The degrees of all grid nodes are summed up to obtain the total degree value of all grid nodes, and the degree of the grid node is ratioed to the total degree value of all grid nodes to obtain the degree ratio of the grid node;

[0073] Exemplarily, the power operation status performance value of the power grid node is obtained in the following manner:

[0074] The detection duration is divided into a plurality of continuous and equal time sub-units, the maximum injection power value and the minimum injection power value in each time sub-unit are obtained, and the sum and average thereof are taken to obtain the injection power mean value in the time sub-unit, and the injection power value means in all time sub-units are summed and averaged to obtain the injection power mean value of the power grid node;

[0075] The injected power mean values ​​of all grid nodes are summed and averaged to obtain the injected power comparison mean value of the grid nodes;

[0076] The average value of the injected power of the grid node is processed by ratio with the average value of the injected power comparison of the grid node to obtain the average value ratio of the injected power of the grid node;

[0077] Obtaining the injected power values ​​at several different detection time points within the detection time, and marking and connecting them in an XY two-dimensional coordinate system to obtain an injected power variation curve;

[0078] The average value of the injected power of the grid node is marked on the Y axis as the reference injected power value, and a straight line parallel to the X axis is drawn through the reference injected power value mark point, which is marked as the reference injected power line;

[0079] It should be noted that the horizontal length of the reference injection power line is equal to the horizontal length of the injection power variation curve;

[0080] Measure the area enclosed between the reference injection power line and the injection power variation curve, and mark it as the actual area;

[0081] Measure the area enclosed by the reference injection power line and the X-axis, and mark it as the reference area;

[0082] The actual area is compared with the reference area to obtain the fluctuation area ratio;

[0083] The reference injection power line is compared with the injection power variation curve, the horizontal length of the overlapped line segment between the reference injection power line and the injection power variation curve is measured, and the horizontal length of the overlapped line segment is measured, and the horizontal length of the reference injection power line is subjected to difference processing, and the absolute value of the difference is taken to obtain the fluctuation length, and the fluctuation length is subjected to ratio processing to the horizontal length of the reference injection power line to obtain the fluctuation length ratio;

[0084] Label the fluctuation area ratio as Ai;

[0085] The fluctuation length ratio is labeled Bi;

[0086] The average ratio of injected power at the grid node is marked as Ci;

[0087] By formula: Obtain the power operation state performance value Gi of the grid node, where a1 and a2 are both preset proportional coefficients;

[0088] The resource allocation ratio of the grid node is obtained according to the key value GJZ of the grid node, and the resource allocation of the grid node is performed according to the resource allocation ratio of the grid node. The specific process is as follows:

[0089] Obtain the key values ​​GJZ of all power grid nodes, sum them up to obtain the sum of the key values ​​of the power grid nodes, perform ratio processing on the key values ​​of the power grid nodes and the sum of the key values ​​of the power grid nodes, and obtain the resource allocation ratio of the power grid nodes;

[0090] Obtain the total capacity of the power grid resources, multiply the total capacity of the power grid resources by the resource allocation ratio of each node, obtain the power grid resource capacity allocated to each node, and mark it as the power grid resource configuration capacity;

[0091] The technical solution of the embodiment of the present invention is: based on processing and analyzing the degree and injected power of the power grid node, the key value GJZ of the power grid node is obtained, and the resource allocation ratio of the power grid node is obtained according to the key value GJZ of the power grid node, and the resource allocation ratio of the power grid node is used to configure the resources of the power grid node. The present invention combines the degree and injected power of the power grid node to evaluate and analyze the capacity of the power grid node, and allocates power grid resources according to the capacity of the power grid node. While realizing the allocation of power grid resources, it ensures that the power grid nodes with higher capabilities have matching power grid resource configurations at critical moments, realizes the rationalization of the allocation of power grid resources, and is conducive to improving the stability of power grid operation.

[0092] Example 2

[0093] like Figure 2 As shown, based on Example 1, a capability verification method described in an embodiment of the present invention includes:

[0094] Step 2: After the grid resource allocation is completed, the grid resource usage data of the grid node in the usage period is obtained, wherein the grid resource usage data includes the usage capacity of the grid resource, and based on the processing and analysis of the grid resource usage data, the grid resource reasonable usage parameter HL is obtained, and the grid resource reasonable usage parameter HL is compared with the grid resource reasonable usage parameter threshold, and the reasonable degree of grid resource usage is verified according to the comparison result;

[0095] Specifically, the utilization capacity of the power grid resources is obtained, the utilization capacity of the power grid resources is subjected to difference processing with the power grid resource configuration capacity of the power grid node, and the absolute value of the difference is taken to obtain the power grid resource deviation capacity, and the power grid resource deviation capacity is subjected to ratio processing with the power grid resource configuration capacity to obtain the power grid resource deviation capacity ratio;

[0096] comparing the power grid resource deviation capacity ratio with the power grid resource deviation capacity ratio threshold, and generating an abnormal deviation signal if the power grid resource deviation capacity ratio is greater than the power grid resource deviation capacity ratio threshold;

[0097] Obtain the duration of each occurrence of the abnormal deviation signal within the use cycle, and sum them to obtain the total duration of the abnormal deviation signal, and perform ratio processing on the total duration of the abnormal deviation signal and the use cycle to obtain the total duration ratio of the abnormal deviation signal;

[0098] Mark the duration of the abnormal deviation signal as an abnormal time period, divide the abnormal time period into several equal time sub-units, obtain the maximum power grid resource deviation capacity ratio and the minimum power grid resource deviation capacity ratio in the time sub-unit, sum and average them to obtain the average power grid resource deviation capacity ratio in the time sub-unit, sum and average the average power grid resource deviation capacity ratios in all time sub-units to obtain the average power grid resource deviation capacity ratio in the abnormal time period, perform ratio processing on the average power grid resource deviation capacity ratio in the abnormal time period and the power grid resource deviation capacity ratio threshold to obtain the average power grid resource deviation capacity ratio proportion in the abnormal time period;

[0099] The total duration of the abnormal deviation signal is marked as DS;

[0100] The power grid resource deviation capacity ratio in the abnormal time period is marked as DB;

[0101] By formula: The grid resource utilization sufficient parameter DWg of the grid node is obtained, where s1 and s2 are both preset proportional coefficients;

[0102] The grid resource utilization sufficient parameter DWg of the grid node is compared with the grid resource utilization sufficient parameter threshold, and the grid node is marked according to the comparison result, specifically:

[0103] If the grid resource utilization sufficient parameter DWg of the grid node is greater than or equal to the grid resource utilization sufficient parameter threshold, then the grid node is marked as a normal grid node;

[0104] If the grid resource utilization sufficient parameter DWg of the grid node is less than the grid resource utilization sufficient parameter threshold, the grid node is marked as an abnormal grid node;

[0105] It should be noted that the concept and purpose of obtaining the parameter DWg for reasonable use of power grid resources is that the parameter DWg for reasonable use of power grid resources combines the total duration ratio of abnormal deviation signals with the average ratio of power grid resource deviation capacity ratio in the abnormal time period, wherein the total duration ratio of abnormal deviation signals reflects the duration of underutilization of power grid resource configuration capacity in the use cycle, and the average ratio of power grid resource deviation capacity ratio in the abnormal time period reflects the size of underutilization of power grid resource configuration capacity during the duration of underutilization of power grid resource configuration capacity, and through their combination, it reflects the adequacy of the power grid resource capacity configured by the power grid node in actual use;

[0106] Count the number of abnormal grid nodes, perform ratio processing on the number of abnormal grid nodes and the number of grid nodes, and obtain the grid resource reasonable use parameter HL;

[0107] The grid resource reasonable use parameter HL is compared with the grid resource reasonable use parameter threshold. The specific comparison process is as follows:

[0108] The preset threshold of the reasonable use parameter of power grid resources is HG;

[0109] If the grid resource reasonable use parameter HL>grid resource reasonable use parameter threshold HG, it means that the reasonable degree of grid resource use is low;

[0110] If the grid resource reasonable use parameter HL ≤ the grid resource reasonable use parameter threshold HG, it means that the reasonable degree of grid resource use is high;

[0111] The technical solution of the embodiment of the present invention is: obtaining grid resource usage data of a grid node within a usage period, wherein the grid resource usage data includes the usage capacity of the grid resources, obtaining a grid resource usage sufficiency parameter DWg of the grid node based on processing and analysis of the grid resource usage data, marking the grid node according to the grid resource usage sufficiency parameter DWg of the grid node, analyzing the marked grid node, obtaining a grid resource reasonable usage parameter HL, and comparing the grid resource reasonable usage parameter HL with a grid resource reasonable usage parameter threshold, and verifying the reasonableness of grid resource usage according to the comparison result. The present invention analyzes the sufficiency of grid resource utilization by combining the time when grid resources are not fully utilized and the size of grid resources that are not fully utilized, thereby preventing waste of grid resource allocation and facilitating understanding of the sufficiency of grid configuration resources, facilitating subsequent optimization of grid resource allocation, and being beneficial to improving grid operation efficiency and operation stability.

[0112] Example 3

[0113] like Figure 3 As shown, based on Example 1 and Example 2, a capability verification method described in an embodiment of the present invention further includes:

[0114] Step 3: Based on the low rationality of the use of power grid resources, the key value of the abnormal power grid node is obtained, and the key value of the abnormal power grid node is compared with the key threshold. According to the comparison result, the abnormal power grid node is marked as an abnormal key node and an abnormal non-key node, and the quantity data of the abnormal key node is obtained. Based on the analysis of the quantity data of the abnormal key nodes, the optimization timeliness value KF is obtained, and the optimization timeliness value KF is compared with the optimization timeliness threshold. According to the comparison result, it is judged whether the configuration of power grid resources needs to be optimized in time;

[0115] Specifically, the optimization timeliness value KF is obtained in the following manner:

[0116] Compare the critical value of the abnormal grid node with the critical threshold:

[0117] If the critical value of the abnormal power grid node is ≥ the critical threshold, the abnormal power grid node is marked as an abnormal critical node;

[0118] If the critical value of the abnormal power grid node is less than the critical threshold, the abnormal power grid node is marked as an abnormal non-critical node;

[0119] Count the number of abnormal key nodes and the number of abnormal power grid nodes in the abnormal power grid nodes, and perform ratio processing on them to obtain the optimized timeliness value KF;

[0120] Compare the optimization timeliness value KF with the optimization timeliness threshold:

[0121] If the optimization timeliness value KF ≥ optimization timeliness threshold, it means that the configuration of power grid resources needs to be optimized in time;

[0122] If the optimization timeliness value KF is less than the optimization timeliness threshold, the configuration of power grid resources does not need to be optimized in time;

[0123] It should be noted that the concept and purpose of obtaining the optimization timeliness value KF is: the optimization timeliness value KF is obtained by analyzing the number of abnormal key nodes in the abnormal power grid nodes. If the number of abnormal key nodes in the abnormal power grid nodes is large, it can be said that there are many relatively key power grid nodes with abnormal power grid resource utilization, and timely processing is required to prevent the relatively key power grid nodes from operating abnormally due to abnormal power grid resource utilization, thereby causing abnormal or unstable power grid operation. This is the key purpose of obtaining the optimization timeliness value KF;

[0124] Step 4: Based on the need for timely optimization of the configuration of power grid resources, the power grid resource usage data of the abnormal power grid nodes within the usage period are analyzed to obtain the average power grid resource usage capacity of the abnormal power grid nodes within the usage period, and the average power grid resource usage capacity of the abnormal power grid nodes within the usage period is compared with the power grid resource configuration capacity of the abnormal power grid nodes. According to the comparison results, the abnormal power grid nodes are marked as abnormal power grid nodes with insufficient resource usage and abnormal power grid nodes with insufficient resource usage, and the underutilized power grid resources of the abnormal power grid nodes with insufficient resource usage are obtained, and they are allocated as scheduling resources to the abnormal power grid nodes with insufficient resource usage;

[0125] Specifically, the usage cycle is divided into a number of continuous and equal time sub-units, the maximum power grid resource usage capacity and the minimum power grid resource usage capacity in the time sub-unit are obtained, and the sum is taken to obtain the average power grid resource usage capacity in the time sub-unit, and the average power grid resource usage capacity in all time sub-units is summed and averaged to obtain the average power grid resource usage capacity of the abnormal power grid node in the usage cycle;

[0126] Compare the average grid resource usage capacity of the abnormal grid node during the usage period with the grid resource configuration capacity of the abnormal grid node;

[0127] If the average grid resource usage capacity of the abnormal grid node during the usage period is greater than the grid resource configuration capacity of the abnormal grid node, the abnormal grid node is marked as a resource usage-deficient abnormal grid node;

[0128] If the average grid resource usage capacity of the abnormal grid node during the usage period is equal to the grid resource configuration capacity of the abnormal grid node, no operation is performed;

[0129] If the average grid resource usage capacity of the abnormal grid node during the usage period is less than the grid resource configuration capacity of the abnormal grid node, the abnormal grid node is marked as an abnormal grid node with insufficient resource usage;

[0130] The average grid resource usage capacity of the abnormal grid node with insufficient resource utilization during the usage period is processed with the grid configuration resource capacity of the abnormal grid node with insufficient resource utilization, and the absolute value of the difference is taken to obtain the grid dispatching resource capacity of the abnormal grid node with insufficient resource utilization. According to the grid dispatching resource capacity, the grid configuration resources of the abnormal grid node with insufficient resource utilization with the same resource capacity are used as dispatching resources in the grid configuration resources, and the dispatching resources are allocated to the abnormal grid node with insufficient resource utilization.

[0131] The technical solution of the embodiment of the present invention is: based on the low rationality of power grid resource utilization, the key values ​​of abnormal power grid nodes are obtained, the abnormal power grid nodes are marked according to the key values ​​of the power grid root nodes, and the abnormal key power grid nodes and abnormal non-key nodes are distinguished, and the quantity data of the abnormal key nodes are obtained, and based on the analysis of the quantity data of the abnormal key nodes, the optimization timeliness value KF is obtained, and the optimization timeliness value KF is compared with the optimization timeliness threshold, and it is judged according to the comparison result whether the configuration of power grid resources needs to be optimized in time. The present invention analyzes the number of abnormal key nodes in the abnormal power grid nodes to realize the analysis of the timeliness of the optimization of power grid resource configuration, which can prevent the occurrence of abnormal or unstable power grid operation caused by the failure to timely optimize and adjust the power grid resource configuration, and timely optimize the power grid resource configuration, thereby reducing the waste of power grid resources.

[0132] Example 4

[0133] like Figure 4 As shown, a capability verification system according to an embodiment of the present invention includes:

[0134] Grid resource configuration module: obtains the basic data of each grid node in the grid, processes and analyzes the basic data of the grid node, obtains the key value GJZ of the grid node, obtains the resource allocation ratio of the grid node according to the key value GJZ of the grid node, and configures the resources of the grid node;

[0135] Rationality of use verification module: After the grid resource allocation is completed, the grid resource usage data of the grid node in the usage period is obtained, and the grid resource reasonable use parameter HL is obtained based on the processing and analysis of the grid resource usage data. The grid resource reasonable use parameter HL is compared with the grid resource reasonable use parameter threshold HG, and the rationality of grid resource use is judged according to the comparison result:

[0136] If the grid resource reasonable use parameter HL>grid resource reasonable use parameter threshold HG, it means that the reasonable degree of grid resource use is low;

[0137] If the grid resource reasonable use parameter HL ≤ the grid resource reasonable use parameter threshold HG, it means that the reasonable degree of grid resource use is high;

[0138] Optimization timeliness analysis module: based on the low rationality of grid resource use, the key value of abnormal grid nodes is obtained, the key value of abnormal grid nodes is compared with the key threshold, and the abnormal grid nodes are marked according to the comparison results, and are marked as abnormal key grid nodes and abnormal non-key nodes, and the quantity data of abnormal key nodes is obtained. Based on the analysis of the quantity data of abnormal key nodes, the optimization timeliness value KF is obtained, and the optimization timeliness value KF is compared with the optimization timeliness threshold, and it is judged whether the configuration of grid resources needs to be optimized in time according to the comparison results;

[0139] Configuration optimization module: Based on the need for timely optimization of the configuration of power grid resources, the power grid resource usage data of abnormal power grid nodes during the usage period is analyzed to obtain the average power grid resource usage capacity of the abnormal power grid nodes during the usage period, and the average power grid resource usage capacity of the abnormal power grid nodes during the usage period is compared with the power grid resource configuration capacity of the abnormal power grid nodes. According to the comparison results, the abnormal power grid nodes are marked as abnormal power grid nodes with insufficient resource usage and abnormal power grid nodes with insufficient resource usage, and the underutilized power grid resources of the abnormal power grid nodes with insufficient resource usage are obtained and allocated as scheduling resources to the abnormal power grid nodes with insufficient resource usage.

[0140] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A capability verification method, characterized in that: include: Obtain the basic data of each grid node in the power grid, obtain the key value GJZ of the grid node based on the processing and analysis of the basic data of the grid node, and obtain the resource allocation ratio of the grid node according to the key value GJZ of the grid node, and perform resource allocation on the grid node; After the grid resource allocation is completed, the grid resource usage data of the grid node in the usage period is obtained. Based on the processing and analysis of the grid resource usage data, the grid resource reasonable usage parameter HL is obtained, and the grid resource reasonable usage parameter HL is compared with the grid resource reasonable usage parameter threshold HG. The reasonable degree of grid resource usage is verified according to the comparison result: If the grid resource reasonable use parameter HL>grid resource reasonable use parameter threshold HG, it means that the reasonable degree of grid resource use is low; If the grid resource reasonable use parameter HL ≤ the grid resource reasonable use parameter threshold HG, it means that the reasonable degree of grid resource use is high.

2. A capability verification method according to claim 1, characterized in that: The basic data of the grid node includes the degree of the grid node and the injected power value of the grid node; Based on the processing and analysis of the degree of the grid node, the degree ratio of the grid node is obtained, and based on the processing and analysis of the injected power value of the grid, the power operation status performance value of the grid node is obtained; The degree proportion of the power grid node is multiplied by the power operation status performance value to obtain the key value GJZ of the power grid node.

3. A capability verification method according to claim 2, characterized in that: Obtain the key values ​​GJZ of all power grid nodes, sum them up to obtain the sum of the key values ​​of the power grid nodes, perform ratio processing on the key values ​​of the power grid nodes and the sum of the key values ​​of the power grid nodes, and obtain the resource allocation ratio of the power grid nodes; The total capacity of the power grid resources is obtained, and the total capacity of the power grid resources is multiplied by the resource allocation ratio of each node to obtain the power grid resource capacity allocated to each node, and it is marked as the power grid resource configuration capacity.

4. A capability verification method according to claim 2, characterized in that: The degree ratio of the power grid node is obtained as follows: According to the degrees of all grid nodes, the total degree value of all grid nodes is obtained by summing up, and the degree of the grid node is compared with the total degree value of all grid nodes to obtain the degree ratio of the grid node; The power operation status performance value of the power grid node is obtained in the following manner: The detection duration is divided into a plurality of continuous and equal time subunits, and the injection power mean value in the time subunit is obtained according to the maximum injection power value and the minimum injection power value in each time subunit, and the injection power mean values ​​in all time subunits are summed and averaged to obtain the injection power mean value of the power grid node, and the injection power mean values ​​of all power grid nodes are summed and averaged to obtain the injection power comparison mean value of the power grid node; The average value of the injected power of the grid node is processed by ratio with the average value of the injected power comparison of the grid node to obtain the average value ratio of the injected power of the grid node; Obtaining the injected power values ​​at several different detection time points within the detection time, and marking and connecting them in an XY two-dimensional coordinate system to obtain an injected power variation curve; The average value of the injected power of the power grid node is used as the reference injected power value to make a reference injected power line; Measure the area enclosed by the reference injection power line and the injection power variation curve, and mark it as the actual area; measure the area enclosed by the reference injection power line and the X-axis, and mark it as the reference area; perform ratio processing on the actual area and the reference area to obtain the fluctuation area ratio; The reference injection power line is compared with the injection power variation curve, the horizontal length of the overlapped line segment between the reference injection power line and the injection power variation curve is measured, and the horizontal length of the overlapped line segment is measured, and the horizontal length of the reference injection power line is subjected to difference processing, and the absolute value of the difference is taken to obtain the fluctuation length, and the fluctuation length is subjected to ratio processing to the horizontal length of the reference injection power line to obtain the fluctuation length ratio; According to the fluctuation area ratio, the fluctuation length ratio and the average ratio of the injected power of the power grid node, the power operation status performance value of the power grid node is obtained by processing the output.

5. A capability verification method according to claim 1, characterized in that: The grid resource usage data includes the usage capacity of the grid resources, and the grid resource deviation capacity ratio is obtained by processing and outputting the usage capacity of the grid resources and the grid resource configuration capacity of the grid node; comparing the power grid resource deviation capacity ratio with the power grid resource deviation capacity ratio threshold, and generating an abnormal deviation signal if the power grid resource deviation capacity ratio is greater than the power grid resource deviation capacity ratio threshold; Based on processing the abnormal deviation signal, a sufficient parameter DWg of the grid resource usage of the grid node is obtained, and the grid node is marked according to the sufficient parameter DWg of the grid resource usage of the grid node, and is marked as a normal grid node and an abnormal grid node; The number of abnormal grid nodes is counted, and the ratio of the number of abnormal grid nodes to the number of grid nodes is processed to obtain the grid resource reasonable utilization parameter HL.

6. A capability verification method according to claim 4, characterized in that: The grid resource utilization sufficient parameter DWg of the grid node is obtained in the following manner: According to the duration of each occurrence of the abnormal deviation signal, the total duration of the abnormal deviation signal is obtained, and the total duration of the abnormal deviation signal is processed by ratio with the use cycle to obtain the total duration ratio of the abnormal deviation signal; Mark the duration of the abnormal deviation signal as an abnormal time period, divide the abnormal time period into several equal time sub-units, obtain the average power grid resource deviation capacity ratio in the time sub-unit according to the maximum power grid resource deviation capacity ratio and the minimum power grid resource deviation capacity ratio in the time sub-unit, sum and average the average power grid resource deviation capacity ratios in all time sub-units, obtain the average power grid resource deviation capacity ratio in the abnormal time period, perform ratio processing on the average power grid resource deviation capacity ratio in the abnormal time period and the power grid resource deviation capacity ratio threshold, and obtain the average power grid resource deviation capacity ratio proportion in the abnormal time period; According to the proportion of the total duration of the abnormal deviation signal and the average proportion of the power grid resource deviation capacity ratio in the abnormal time period, the processing output is obtained to obtain the power grid resource utilization sufficiency parameter DWg of the power grid node.

7. A capability verification method according to claim 1, characterized in that: Also includes: Based on the low rationality of grid resource use, the key value of the abnormal grid node is obtained, and the key value of the abnormal grid node is compared with the key threshold. The abnormal grid node is marked according to the comparison result, and it is marked as an abnormal key node and an abnormal non-key node, and the quantity data of the abnormal key node is obtained. Based on the analysis of the quantity data of the abnormal key nodes, the optimization timeliness value KF is obtained, and the optimization timeliness value KF is compared with the optimization timeliness threshold: If the optimization timeliness value KF ≥ optimization timeliness threshold, it means that the configuration of power grid resources needs to be optimized in time; If the optimization timeliness value KF is less than the optimization timeliness threshold, the configuration of the power grid resources does not need to be optimized in a timely manner.

8. A capability verification method according to claim 7, characterized in that: The optimization timeliness value KF is obtained in the following manner: Compare the critical value of the abnormal grid node with the critical threshold: If the critical value of the abnormal power grid node is ≥ the critical threshold, the abnormal power grid node is marked as an abnormal critical node; If the critical value of the abnormal power grid node is less than the critical threshold, the abnormal power grid node is marked as an abnormal non-critical node; The number of abnormal key nodes and the number of abnormal power grid nodes in the abnormal power grid nodes are counted, and the ratios are processed to obtain the optimized timeliness value KF.

9. A capability verification method according to claim 7, characterized in that: Based on the need for timely optimization of the configuration of power grid resources, the average power grid resource usage capacity of abnormal power grid nodes during the use period is obtained and compared with the power grid resource configuration capacity of the abnormal power grid nodes. According to the comparison results, the abnormal power grid nodes are marked as abnormal power grid nodes with insufficient resource usage and abnormal power grid nodes with insufficient resource usage; The average grid resource usage capacity of the abnormal grid node with insufficient resource utilization during the usage period is processed with the grid configuration resource capacity of the abnormal grid node with insufficient resource utilization, and the absolute value of the difference is taken to obtain the grid dispatching resource capacity of the abnormal grid node with insufficient resource utilization. According to the grid dispatching resource capacity, the grid configuration resources of the abnormal grid node with insufficient resource utilization with the same resource capacity are used as dispatching resources in the grid configuration resources, and the dispatching resources are allocated to the abnormal grid node with insufficient resource utilization.

10. A capability verification system, the system implementing the capability verification method according to any one of claims 1 to 9, characterized in that: include: Grid resource configuration module: obtains the basic data of each grid node in the grid, processes and analyzes the basic data of the grid node, obtains the key value GJZ of the grid node, obtains the resource allocation ratio of the grid node according to the key value GJZ of the grid node, and configures the resources of the grid node; Rationality of use verification module: After the grid resource allocation is completed, the grid resource usage data of the grid node in the usage period is obtained, and the grid resource reasonable use parameter HL is obtained based on the processing and analysis of the grid resource usage data. The grid resource reasonable use parameter HL is compared with the grid resource reasonable use parameter threshold HG, and the rationality of grid resource use is judged according to the comparison result: If the grid resource reasonable use parameter HL>grid resource reasonable use parameter threshold HG, it means that the reasonable degree of grid resource use is low; If the grid resource reasonable use parameter HL ≤ the grid resource reasonable use parameter threshold HG, it means that the reasonable degree of grid resource use is high.

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