Power grid system influence degree evaluation method, device and equipment and storage medium

Abstract

The application relates to a power grid system influence degree evaluation method, device, equipment and storage medium. The method comprises the following steps: obtaining a subway network and a power grid system of a target evaluation area; constructing a subway power grid model according to a subway topology structure, a power grid topology structure and an electrical connection relationship between the subway network and the power grid system; constructing a main transformer DC bias probability index and a ground potential influence index according to the subway power grid model; constructing an influence degree evaluation model about the number of subway lines based on the main transformer DC bias probability index and the ground potential influence index; obtaining the number of subway lines at an expected time and inputting the number of subway lines into the influence degree evaluation model to obtain an evaluation value; constructing an evaluation level, and evaluating the influence degree of the power grid system of the target evaluation area according to the evaluation value based on the evaluation level to obtain an evaluation result. The method can comprehensively evaluate the influence degree of the power grid system affected by the subway line stray current, and is more realistic and reliable.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computer, in particular to a power grid system influence degree evaluation method, device, equipment and storage medium. BACKGROUND

[0002] With the development of subway construction technology, the number of subways in multiple cities gradually increases. However, due to the incomplete ground insulation of subway tracks, part of the direct current will leak from the running rail to the ground, forming a stray current and invading the surrounding substation through the ground. In addition, there is an electrical connection between the subway network and the power grid system, and the stray current will also invade the power grid system through the metal path such as cable armor, which brings adverse effects to the stable operation of the power grid system. Therefore, it is necessary to evaluate the influence degree of the increase of the number of subway lines on the power grid system.

[0003] In the traditional technology, when evaluating the influence of subway stray current on the power grid system, only the influence of stray current on a single main transformer is considered. However, in the process of the increase of the volume of subway stray current, the influence range on the substation is huge, and only evaluating a single main transformer is not comprehensive, which leads to the limitation of the evaluation conclusion. SUMMARY

[0004] Therefore, it is necessary to provide a power grid system influence degree evaluation method, device, equipment and storage medium which can reasonably evaluate the influence degree of the number of subway lines on the power grid system in view of the above technical problems.

[0005] In a first aspect, the present application provides a power grid system influence degree evaluation method. The method comprises:

[0006] obtaining a subway network and a power grid system in a target evaluation area; the subway network comprises a subway topology structure, and the power grid system comprises a power grid topology structure;

[0007] constructing a subway power grid model according to the subway topology structure, the power grid topology structure and the electrical connection relationship between the subway network and the power grid system, and assigning values to the parameters of the subway power grid model;

[0008] constructing a main transformer DC bias probability index and a ground potential influence index according to the subway power grid model, and constructing an influence degree evaluation model about the number of subway lines based on the main transformer DC bias probability index and the ground potential influence index;

[0009] obtaining the number of subway lines at a prospective time, and inputting the number of subway lines into the influence degree evaluation model to obtain an evaluation value;

[0010] constructing an evaluation level, and evaluating the influence degree of the power grid system in the target evaluation area according to the evaluation value based on the evaluation level to obtain an evaluation result.

[0011] In one of the embodiments, the power grid system further comprises a number of neutral grounding main transformers; a main transformer DC bias probability index is constructed according to the subway power grid model, comprising:

[0012] The node voltages of each node in the subway power grid model are determined, and the neutral point currents of each transformer are determined based on the node voltages and the corresponding transformer winding resistances;

[0013] The main transformer DC bias probability index is constructed according to the number of neutral point currents greater than a preset current threshold and the number of main transformers.

[0014] In one of the embodiments, the subway network comprises a number of stations; the construction process of the ground potential influence index comprises:

[0015] The longitude range, latitude range and soil resistivity of the target evaluation area are obtained, the station longitude and latitude matrix of the subway network is obtained, and the substation longitude and latitude matrix of the power grid system is obtained;

[0016] The area longitude and latitude matrix of the target evaluation area is constructed according to the longitude range and the latitude range, and the grounding node matrix is constructed according to the station longitude and latitude matrix and the substation longitude and latitude matrix;

[0017] The ground potential value of each longitude and latitude in the target evaluation area is determined according to the area longitude and latitude matrix, the soil resistivity, the node voltages and the grounding node matrix;

[0018] The ground potential influence index is constructed according to the number of ground potential values greater than a preset ground potential threshold and the total number of elements in the area longitude and latitude matrix.

[0019] In one of the embodiments, the ground potential value of each longitude and latitude in the target evaluation area is determined according to the area longitude and latitude matrix, the soil resistivity, the node voltages and the grounding node matrix, comprising:

[0020] The node voltage matrix is constructed based on the node voltages of each node, and the leakage current of each grounding point of the power grid system is determined based on the node voltage matrix and the corresponding grounding resistance;

[0021] The distance matrix is constructed based on the distance between each element in the area longitude and latitude matrix and each element in the grounding node matrix;

[0022] The ground potential matrix is constructed according to the soil resistivity, the leakage current and the distance matrix, and the ground potential value of the target evaluation area at different longitude and latitude positions is obtained based on the ground potential matrix.

[0023] In one of the embodiments, the influence degree evaluation model for the number of subway lines is constructed based on the main transformer DC bias probability index and the ground potential influence index, comprising:

[0024] The number of subway lines N at the current time is obtained; wherein N is a positive integer;

[0025] According to the main transformer DC bias probability index, the probability values of the number of subway lines from 1 to N are calculated to obtain a probability evaluation matrix, and a probability evaluation function is constructed based on the probability evaluation matrix;

[0026] According to the ground potential influence index, the ground potential values of the number of subway lines from 1 to N are calculated to obtain a ground potential evaluation matrix, and a ground potential evaluation function is constructed based on the ground potential evaluation matrix;

[0027] An influence degree evaluation model is constructed according to the probability evaluation function and the ground potential evaluation function, and the weights of the probability evaluation function and the ground potential evaluation function are determined.

[0028] In one embodiment, an evaluation level is constructed, and based on the evaluation level, the influence degree of the power grid system of the target evaluation area is evaluated according to the evaluation value to obtain an evaluation result, including:

[0029] A first preset evaluation threshold and a second preset evaluation threshold are obtained, and an evaluation level is constructed; the evaluation level includes slight, general and serious;

[0030] If the evaluation value is greater than 0 and less than the first preset evaluation threshold, it is determined that the influence degree of the power grid system is slight;

[0031] If the evaluation value is greater than or equal to the first preset evaluation threshold and less than the second preset evaluation threshold, it is determined that the influence degree of the power grid system is general;

[0032] If the evaluation value is greater than or equal to the second preset evaluation threshold and less than 1, it is determined that the influence degree of the power grid system is serious.

[0033] In a second aspect, the application also provides a power grid system influence degree evaluation device. The device comprises:

[0034] A parameter acquisition module is configured to acquire a subway network and a power grid system of a target evaluation area; the subway network comprises a subway topology structure, and the power grid system comprises a power grid topology structure;

[0035] A subway power grid model construction module is configured to construct a subway power grid model according to the subway topology structure, the power grid topology structure and the electrical connection relationship between the subway network and the power grid system, and to assign values to the parameters of the subway power grid model;

[0036] An evaluation model construction module is configured to construct a main transformer DC bias probability index and a ground potential influence index according to the subway power grid model, and to construct an influence degree evaluation model about the number of subway lines based on the main transformer DC bias probability index and the ground potential influence index;

[0037] An evaluation value determination module is configured to acquire the number of subway lines at an expected time and input the number into the influence degree evaluation model to obtain an evaluation value;

[0038] An evaluation result determination module is configured to construct an evaluation level, and evaluate the influence degree of the power grid system in the target evaluation area according to the evaluation value based on the evaluation level, to obtain an evaluation result.

[0039] In a third aspect, the present application further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the following steps when executing the computer program:

[0040] The metro network and the power grid system in the target evaluation area are acquired; the metro network comprises a metro topology structure, and the power grid system comprises a power grid topology structure;

[0041] A metro power grid model is constructed according to the metro topology structure, the power grid topology structure and the electrical connection relationship between the metro network and the power grid system, and the metro power grid model parameters are valued;

[0042] The main transformer DC bias probability index and the ground potential influence index are constructed according to the metro power grid model, and the influence degree evaluation model about the number of metro lines is constructed based on the main transformer DC bias probability index and the ground potential influence index;

[0043] The number of metro lines at the expected time is acquired and input into the influence degree evaluation model, to obtain an evaluation value;

[0044] An evaluation level is constructed, and the influence degree of the power grid system in the target evaluation area is evaluated according to the evaluation value based on the evaluation level, to obtain an evaluation result.

[0045] In a fourth aspect, the present application further provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the following steps:

[0046] The metro network and the power grid system in the target evaluation area are acquired; the metro network comprises a metro topology structure, and the power grid system comprises a power grid topology structure;

[0047] A metro power grid model is constructed according to the metro topology structure, the power grid topology structure and the electrical connection relationship between the metro network and the power grid system, and the metro power grid model parameters are valued;

[0048] The main transformer DC bias probability index and the ground potential influence index are constructed according to the metro power grid model, and the influence degree evaluation model about the number of metro lines is constructed based on the main transformer DC bias probability index and the ground potential influence index;

[0049] The number of metro lines at the expected time is acquired and input into the influence degree evaluation model, to obtain an evaluation value;

[0050] An assessment level is constructed, and based on the assessment level, the degree of impact on the power grid system in the target assessment area is assessed according to the assessment value to obtain the assessment result.

[0051] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0052] Obtain the metro network and power grid system of the target assessment area; the metro network includes the metro topology, and the power grid system includes the power grid topology;

[0053] A subway power grid model is constructed based on the subway topology, power grid topology, and electrical connection relationships between the subway network and power grid systems, and the parameters of the subway power grid model are assigned values.

[0054] Based on the subway power grid model, the DC bias probability index and ground potential influence index of the main transformer are constructed. Based on the DC bias probability index and ground potential influence index of the main transformer, an evaluation model for the degree of influence of the number of subway lines is constructed.

[0055] Obtain the number of subway lines at the expected time and input it into the impact assessment model to obtain the assessment value;

[0056] An assessment level is constructed, and based on the assessment level, the degree of impact on the power grid system in the target assessment area is assessed according to the assessment value to obtain the assessment result.

[0057] The aforementioned method, apparatus, equipment, and storage medium for assessing the impact on the power grid system construct a metro power grid model based on the metro topology and power grid topology of the target assessment area and their electrical connections, and determine the parameter values ​​in the metro power grid model. Based on the determined metro power grid model, a main transformer DC bias probability index and a ground potential impact index are constructed, and an impact assessment model is built based on these two impact indices. This impact assessment model is a function model of the number of metro lines and the assessment value; that is, different numbers of metro lines yield different assessment values. After obtaining the expected number of metro lines at a future time, inputting this value into the impact assessment model yields the corresponding assessment value. Then, an assessment level is constructed based on the assessment value, and the assessment result is determined based on the assessment value. Compared to traditional technologies that use the impact of stray currents on a single main transformer, the method provided in this application combines the topology of both the metro lines and the power grid system, and constructs an evaluation model based on DC bias and ground potential to comprehensively evaluate the degree of impact of stray currents from metro lines on the power grid system, making it more realistic and reliable. Attached Figure Description

[0058] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related art, the drawings needed to be used in the embodiments or related art description will be briefly introduced. Obviously, the drawings in the following description only constitute some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0059] Figure 1 An application environment diagram of the power grid system influence degree evaluation method in an embodiment;

[0060] Figure 2 A flowchart of the power grid system influence degree evaluation method in an embodiment;

[0061] Figure 3 A flowchart of the power grid system influence degree evaluation method in another embodiment;

[0062] Figure 4 A structural block diagram of the power grid system influence degree evaluation device in an embodiment;

[0063] Figure 5 An internal structure diagram of the computer device in an embodiment. DETAILED DESCRIPTION

[0064] In order to make the purposes, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and not to limit the present application.

[0065] The power grid system influence degree evaluation method provided by the embodiments of the present application can be applied in the application environment as shown in the figure. Figure 1 The terminal 102 communicates with the server 104 through the network. The data storage system can store the data required to be processed by the server 104. The data storage system can be integrated on the server 104, or placed on the cloud or other network servers. The increase of the number of subway lines brings the increase of the stray current, which causes the influence on the power grid system. The influence degree evaluation model is constructed based on the existing subway lines in the target evaluation area, and then the preset number of subway lines at the future time is input into the influence degree evaluation model to obtain the influence degree evaluation result of the power grid system when the number of subway lines is increased.

[0066] The terminal 102 can be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers, Internet of Things devices, and portable wearable devices. The Internet of Things device can be a smart speaker, a smart television, a smart air conditioner, a smart vehicle-mounted device, etc. The portable wearable device can be a smart watch, a smart bracelet, a head-mounted device, etc. The server 104 can be implemented by a stand-alone server or a server cluster composed of multiple servers.

[0067] In an exemplary embodiment, as shown in Figure 2 , a power grid system influence degree evaluation method is provided. The method is applied to the server 104 in Figure 1 for illustration, including the following steps S202 to S210. Wherein:

[0068] S202, obtaining a subway network and a power grid system in a target evaluation area; the subway network includes a subway topology structure, and the power grid system includes a power grid topology structure.

[0069] The target evaluation area is an area where subway lines are constructed, and the influence of the number of subway lines on the power grid system in the target evaluation area needs to be evaluated. Illustratively, the target evaluation area can be a city.

[0070] The subway network refers to a network composed of the subway system operated in the target evaluation area, which is composed of subway lines, stations, and related facilities and equipment. The subway topology structure is the topology structure of the subway network, which refers to the connection mode and layout between the subway lines and stations. Illustratively, the subway line is taken as the edge of the topology structure, and the station is taken as the node.

[0071] The power grid system refers to a set of power supply system composed of power plants, substations, transmission lines, distribution networks, and users. Among them, the substation is an important link in the power grid system, which is used to convert high-voltage electric energy into low-voltage electric energy or to convert different levels of voltage into each other. The substation is usually located at the node of the distribution network to ensure the stability of the voltage and the quality of the electric energy in the transmission process.

[0072] The power grid topology structure refers to the connection mode and layout between various power devices and elements in the power grid system. It determines the transmission path and flow mode of electric energy in the power grid. Illustratively, the elements such as substations in the power grid system are taken as nodes, and the transmission lines are taken as edges.

[0073] S204, constructing a subway power grid model according to the subway topology structure, the power grid topology structure, and the electrical connection relationship between the subway network and the power grid system, and assigning values to the parameters of the subway power grid model.

[0074] The subway train needs electric energy to run, so the subway system needs to obtain power supply from the power grid system. And the subway system adopts the way of track electrification, that is, the power supply to the train is realized through the contact network and the current collection device. The contact network is provided with electric energy by the power grid system, and the current collection device is installed on the subway train. Through the contact with the contact network, the electric energy is transmitted to the traction system of the train to drive the train to run.

[0075] The electrical connection relationship includes series connection, parallel connection, star connection and mesh connection. Since the subway network relies on the power grid system for power supply, the subway network and the power grid system have a dense electrical connection relationship, thereby constructing a subway power grid model. Illustratively, the subway power grid model can be a subway power grid DC resistance network model constructed based on DC resistance.

[0076] The subway system usually adopts a direct current power supply mode. In order to describe the connection relationship between the subway and the city power grid, a DC resistance network model can be used. Specifically, the subway line is equivalent to a lumped parameter DC resistance network model, including up / down contact network, steel rail, through ground wire and reference ground structure, wherein the up / down contact network structure model includes traction substation node and train node. The traction substation node is equivalent to a DC resistance parallel DC current source structure, connected between the contact network traction substation node and the steel rail traction substation node. According to the topology structure of the power grid system, a lumped parameter DC resistance network model is equivalent, which includes transformer bus node and substation grounding node. That is, based on the cable armored connection relationship between the subway network and the power grid system substation grounding network, the subway DC resistance network model and the power grid DC resistance network model are coupled to obtain the subway power grid model.

[0077] The DC resistance between the nodes of the subway power grid model, the current excitation, the grounding resistance of the grounding node, the mutual impedance between the grounding nodes, the series voltage of the grounding nodes and the voltage of the substation grounding node are determined. And further calculate and determine the equivalent current of the grounding node, the node current and the node voltage in the subway power grid model.

[0078] S206, according to the subway power grid model, the main transformer DC bias probability index and the ground potential influence index are constructed, and the influence degree evaluation model about the number of subway lines is constructed based on the main transformer DC bias probability index and the ground potential influence index.

[0079] The main transformer refers to the main transformer, which is used to realize voltage conversion. The DC bias of the transformer refers to the DC current entering the transformer through the neutral point grounding of the high voltage side of the transformer, which makes the core of the transformer produce a magnetic field. The DC current passes through the magnetized core, increases the magnetic flux of the transformer magnetic circuit, and causes the noise and vibration caused by the magnetostriction and electromagnetic force of the transformer to increase. Thus, through the main transformer DC bias probability index, the influence of the DC current on the transformer when the number of subway lines increases is evaluated.

[0080] The ground potential refers to the potential difference between a location and the earth ground. When there is a leakage current at the grounding point, the ground potential changes, and the ground potential can quantitatively represent the leakage current at the grounding point in the subway power grid model. Thus, the influence of the leakage current caused by the increase in the number of subway lines can be evaluated through the ground potential influence index.

[0081] The influence degree evaluation model is constructed based on the main transformer DC bias probability index and the ground potential influence index, and reflects the synergistic effect of the two.

[0082] In S208, the number of subway lines at the expected time is obtained and input into the influence degree evaluation model to obtain an evaluation value.

[0083] The influence degree evaluation model is constructed based on the existing number of subway lines. When the number of subway lines changes, the evaluation value is generated based on the influence degree evaluation model. The evaluation value is used to quantitatively evaluate the influence degree.

[0084] In S210, an evaluation level is constructed, and based on the evaluation level, the influence degree of the power grid system of the target evaluation area is evaluated according to the evaluation value to obtain an evaluation result.

[0085] The evaluation level is a relationship model between the evaluation value interval and the influence degree. According to the interval to which the evaluation value belongs, the evaluation result is obtained, which reflects the influence degree of the number of subway lines on the power grid system.

[0086] In the above power grid system influence degree evaluation method, a subway power grid model is constructed based on the subway topology structure and the power grid topology structure of the target evaluation area and the electrical connection relationship between the two, and the parameter values in the subway power grid model are determined. The main transformer DC bias probability index and the ground potential influence index are constructed based on the determined subway power grid model, and the influence degree evaluation model is constructed based on the two influence indexes. At this time, the influence degree evaluation model is a function model about the number of subway lines and the evaluation value, that is, different evaluation values can be obtained corresponding to different numbers of subway lines. After obtaining the number of subway lines at the future expected time, the input value is input into the influence degree evaluation model to obtain the evaluation value corresponding to the number. Then, an evaluation level about the evaluation value is constructed, and the evaluation result is determined based on the evaluation value. Compared with the influence of the stray current on a single main transformer in the traditional technology, the method provided in the present application simultaneously combines the topology structures of the subway lines and the power grid system, and constructs an evaluation model based on the DC bias and the ground potential, which comprehensively evaluates the influence degree of the power grid system affected by the stray current of the subway lines, and is more realistic and reliable.

[0087] In an exemplary embodiment, the power grid system further comprises a number of neutral point grounded main transformers; the main transformer DC bias probability index is constructed according to the subway power grid model, comprising: determining the node voltage of each node in the subway power grid model, determining the neutral point current of each transformer based on the node voltage and the corresponding transformer winding resistance; and constructing the main transformer DC bias probability index according to the number of neutral point currents greater than the preset current threshold and the number of main transformers.

[0088] The number of center point grounded main transformers refers to the number of main transformers in the power grid system, the neutral point of which is connected to the ground to form a grounding point, denoted as M.

[0089] The node admittance method is used to calculate the model node voltage matrix U, and the neutral point current I of each transformer is calculated according to the node voltage matrix U and the transformer winding resistance z z1 z2 zM .

[0090] The preset current threshold I th is obtained, the number of elements m that satisfy I z >I th is counted, and the main transformer DC bias probability index η is obtained according to the number of elements m and the number of center point grounded main transformers M, as shown in formula (1):

[0091] η=m / M (1)

[0092] In this embodiment, the node voltage of each node in the subway power grid model is first determined, the neutral point current of each transformer is obtained based on the node voltage, and is compared with the preset current threshold, so as to construct the main transformer DC bias probability index. In this way, the evaluation mode of the neutral point current is integrated in the evaluation index, and the evaluation reliability is improved.

[0093] In an exemplary embodiment, the subway network comprises a number of stations; the construction process of the ground potential influence index comprises: obtaining the longitude range, latitude range and soil resistivity of the target evaluation area, obtaining the station longitude and latitude matrix of the subway network, and obtaining the substation longitude and latitude matrix of the power grid system; constructing the area longitude and latitude matrix of the target evaluation area according to the longitude range and the latitude range, and constructing the grounding node matrix according to the station longitude and latitude matrix and the substation longitude and latitude matrix; determining the ground potential value of each longitude and latitude of the target evaluation area according to the area longitude and latitude matrix, the soil resistivity, the node voltage and the grounding node matrix; and constructing the ground potential influence index according to the number of ground potential values greater than the preset ground potential threshold and the total number of elements of the area longitude and latitude matrix.

[0094] The subway network comprises a number of stations V, and the station longitude and latitude matrix L m ​​​, a substation longitude and latitude matrix L is constructed according to the longitude and latitude of each substation in the power grid system p . The longitude range of the target evaluation area is (a, b), the latitude range is (c, d), and the soil resistivity is p.

[0095] The longitude and latitude of the target evaluation area are divided according to the degree accuracy of 0.001, and then the area longitude and latitude matrix G of [1000(b-a)]*[1000(d-c)] is obtained. Each element in the area longitude and latitude matrix G represents the longitude and latitude of a point in the target evaluation area.

[0096] In one embodiment, the step of determining the geoelectric potential value of each longitude and latitude of the target evaluation area includes: constructing a node voltage matrix based on the node voltage of each node, and determining the leakage current of each grounding point of the power grid system based on the node voltage matrix and the corresponding grounding resistance; constructing a distance matrix based on the distance between each element in the area longitude and latitude matrix and each element in the grounding node matrix; constructing a geoelectric potential matrix according to the soil resistivity, the leakage current and the distance matrix, and obtaining the geoelectric potential value of the target evaluation area at different longitude and latitude positions based on the geoelectric potential matrix.

[0097] The node voltage matrix U is calculated by using the node admittance method, and the leakage current I of each grounding point is calculated according to the node voltage matrix U and the grounding resistance x =[I x1 , I x2 , …, I x(M+V) ].

[0098] The grounding node matrix L=[L m , L p ] is constructed based on the station longitude and latitude matrix L M and the substation longitude and latitude matrix L P , and the distance matrix R is constructed based on the distance between each element in the area longitude and latitude matrix G and each element in the grounding node matrix L. The distance between each element in the area longitude and latitude matrix G and each element in the grounding node matrix L can be obtained according to formula (2):

[0099]

[0100] Where r is the distance between points Q and P in the calculation, in kilometers; Lng1 and Lat1 represent the longitude and latitude of point Q, respectively, and Lng2 and Lat2 represent the longitude and latitude of point P, respectively; q=Lat1-Lat2 is the difference between the latitudes of the two points, and p=Lng1-Lng2 is the difference between the longitudes of the two points; 6378.137 is the radius of the earth's equator, in kilometers.

[0101] After obtaining the distance matrix R, the geoelectric potential matrix is constructed by formula (3):

[0102]

[0103] wherein, denotes the transpose matrix of the ground point leakage current sequence, R i is the distance matrix between the i-th point in the regional latitude and longitude matrix G and each matrix element in the ground node matrix L.

[0104] After the ground potential matrix is constructed, the ground potential values of each latitude and longitude in the target evaluation region can be determined based on the values of the matrix elements in the ground potential matrix.

[0105] In this embodiment, the ground potential values of each latitude and longitude are determined based on the soil resistivity, the leakage current, and the latitude and longitude of the target evaluation region, and the evaluation is performed with the latitude and longitude as the reference, thereby improving the evaluation accuracy.

[0106] Then, a preset ground potential threshold is obtained, and a ground potential influence index ζ is constructed according to formula (4):

[0107] ζ = o / O (4)

[0108] wherein, o is the number of ground potential values greater than the preset ground potential threshold, and O is the total number of elements in the regional latitude and longitude matrix G.

[0109] In this embodiment, the ground potential influence index is constructed according to the ground potential value and the number of elements in the regional latitude and longitude matrix, and is constructed based on the latitude and longitude of the target evaluation region, so that the ground potential influence index is a parameter related to the latitude and longitude, thereby improving the evaluation accuracy.

[0110] In one exemplary embodiment, an influence degree evaluation model related to the number of subway lines is constructed based on the main transformer DC bias probability index and the ground potential influence index, including: obtaining the number of subway lines N at the current time; wherein N is a positive integer; calculating the probability values of each of the number of subway lines from 1 to N according to the main transformer DC bias probability index, obtaining a probability evaluation matrix, and constructing a probability evaluation function based on the probability evaluation matrix; calculating the ground potential values of each of the number of subway lines from 1 to N according to the ground potential influence index, obtaining a ground potential evaluation matrix, and constructing a ground potential evaluation function based on the ground potential evaluation matrix; constructing the influence degree evaluation model according to the probability evaluation function and the ground potential evaluation function, and determining the weights of the probability evaluation function and the ground potential evaluation function.

[0111] At the current time, the number of subway lines in the target evaluation region is N. The least square method is used to perform linear regression analysis on the evaluation indexes under different numbers of subway lines, and a fitting trend line is obtained.

[0112] Specifically, for the main transformer DC bias probability index η of different numbers of subway lines, the main transformer DC bias probability index η of the number of subway lines from 1 to N is calculated, and the probability evaluation matrix J = [η1, η2... ηN] is obtained by summarizing.N ], where η i This represents the DC bias probability index value of the main transformer when the number of subway lines is i.

[0113] For the ground potential impact index ζ under different numbers of subway lines, the ground potential impact index ζ is calculated for subway lines from 1 to N, and the ground potential assessment matrix H = [ζ1, ζ2, ... ζ] is obtained by summing the results. N ], where ζ i This represents the ground potential influence index value when the number of subway lines is i.

[0114] The least squares method was used to perform linear regression analysis on the number of subway lines and the probability evaluation matrix J to obtain the fitting function, which is also the probability evaluation function, as shown in formula (5):

[0115] W = a0 + a1x + ... + a N x N (5)

[0116] Where W is the DC bias probability index of the main transformer of the power grid; X is the number of subway lines; a0…a N These are the coefficients of the fitted function obtained in linear regression analysis.

[0117] The least squares method was used to perform linear regression analysis on the number of subway lines and the ground potential assessment matrix H to obtain the fitting function, which is also the ground potential assessment function, as shown in formula (6):

[0118] E = b0 + b1x + ... + b N x N (6)

[0119] Where E is the power grid ground potential impact index; X is the number of subway lines; b0…b N These are the coefficients of the fitted function obtained in linear regression analysis.

[0120] Subsequently, an impact assessment model is constructed based on the obtained probability assessment function and ground potential assessment function, and the model is evaluated based on expert scoring or by pre-setting the weights of the two, as shown in formula (7):

[0121] Z = αW + βE (7)

[0122] Where Z is the evaluation value, and α and β are the weights of the probability evaluation function and the ground potential evaluation function, respectively. Illustratively, α and β can be obtained from historical data using expert scoring or can be preset values.

[0123] In the embodiment, an evaluation matrix about the number of subway lines is constructed based on the evaluation indexes, an evaluation fitting function is constructed based on the least square method, an evaluation model is constructed based on the evaluation fitting function, and the weight is determined. In this way, the evaluation mode based on the number of subway lines is constructed, so as to output the evaluation value based on the number of subway lines, and the probability of the main transformer DC bias and the ground potential value are comprehensively judged, which has higher evaluation credibility.

[0124] In an exemplary embodiment, an evaluation level is constructed, and the affected degree of the power grid system of the target evaluation area is evaluated according to the evaluation value based on the evaluation level to obtain an evaluation result, including: obtaining a first preset evaluation threshold and a second preset evaluation threshold, and constructing an evaluation level; the evaluation level includes slight, general and serious; if the evaluation value is greater than 0 and less than the first preset evaluation threshold, it is determined that the affected degree of the power grid system is slight; if the evaluation value is greater than or equal to the first preset evaluation threshold and less than the second preset evaluation threshold, it is determined that the affected degree of the power grid system is general; if the evaluation value is greater than or equal to the second preset evaluation threshold and less than 1, it is determined that the affected degree of the power grid system is serious.

[0125] According to the division of the affected degree of the power grid system of the target evaluation area by the stray current, the first evaluation threshold λ1 and the second preset evaluation threshold λ2 are preset, and λ1<λ2. The number of planned subway lines N T is input into the affected degree evaluation model, and the obtained evaluation value is Z.

[0126] If 0<Z<λ1, it represents that the current subway stray current growth volume has a slight influence on the substation in the power grid system. If λ1≤Z<λ2, it represents that the current subway stray current growth volume has a general influence on the substation in the power grid system. If λ2≤Z<1, it represents that the current subway stray current growth volume has a serious influence on the substation in the power grid system.

[0127] In the embodiment, the evaluation level is constructed, which is divided into three division levels, and the affected degree level is determined based on the evaluation value, so as to directly obtain the affected degree result for the user and improve the evaluation speed.

[0128] As shown in FIG. Figure 3 In an exemplary embodiment, a power grid system affected degree evaluation method includes the following steps:

[0129] S302, obtaining the subway network and the power grid system of the target evaluation area; the subway network includes the subway topology structure and the number of stations, and the power grid system includes the power grid topology structure and the number of neutral point grounded main transformers.

[0130] S304, construct a metro power grid model according to the metro topology structure, the power grid topology structure, and the electrical connection relationship between the metro network and the power grid system, and assign values to the metro power grid model parameters;

[0131] S306, determine the node voltages of each node in the metro power grid model, and determine the neutral point currents of each transformer based on the node voltages and the corresponding transformer winding resistances;

[0132] S308, construct a main transformer DC magnetic bias probability index according to the number of neutral point currents greater than a preset current threshold and the number of main transformers.

[0133] S310, obtain the longitude range, latitude range, and soil resistivity of the target evaluation area, obtain the station longitude and latitude matrix of the metro network, and obtain the substation longitude and latitude matrix of the power grid system;

[0134] S312, construct an area longitude and latitude matrix of the target evaluation area according to the longitude range and the latitude range, and construct a grounding node matrix according to the station longitude and latitude matrix and the substation longitude and latitude matrix;

[0135] S314, construct a node voltage matrix based on the node voltages of each node, and determine the leakage currents of each grounding point of the power grid system based on the node voltage matrix and the corresponding grounding resistances;

[0136] S316, construct a distance matrix based on the distance between each element in the area longitude and latitude matrix and each element in the grounding node matrix;

[0137] S318, construct a ground potential matrix according to the soil resistivity, the leakage current, and the distance matrix, and obtain the ground potential values of the target evaluation area at different longitude and latitude positions based on the ground potential matrix.

[0138] S320, construct a ground potential influence index according to the number of ground potential values greater than a preset ground potential threshold, the number of main transformers, and the number of stations.

[0139] S322, obtain the number N of metro lines at the current time; wherein N is a positive integer; calculate the probability values of the number of metro lines from 1 to N according to the main transformer DC magnetic bias probability index, obtain a probability evaluation matrix, and construct a probability evaluation function based on the probability evaluation matrix;

[0140] S324, calculate the ground potential values of the number of metro lines from 1 to N according to the ground potential influence index, obtain a ground potential evaluation matrix, and construct a ground potential evaluation function based on the ground potential evaluation matrix;

[0141] S326, construct an influence degree evaluation model according to the probability evaluation function and the ground potential evaluation function, and determine the weights of the probability evaluation function and the ground potential evaluation function.

[0142] S328, obtain the number of subway lines at the expected time and input into the influence degree evaluation model to obtain an evaluation value;

[0143] S330, construct an evaluation level, and based on the evaluation level, evaluate the influence degree of the power grid system in the target evaluation area according to the evaluation value to obtain an evaluation result.

[0144] It should be understood that, although each step in the flowchart involved in each embodiment as described above is shown in sequence according to the arrow, these steps are not necessarily executed in sequence according to the arrow. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other sequences. Moreover, at least part of the steps in the flowchart involved in each embodiment as described above can include multiple steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution sequence of these steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least part of other steps or steps or stages in other steps.

[0145] Based on the same inventive concept, the embodiments of the present application also provide a power grid system influence degree evaluation device for implementing the power grid system influence degree evaluation method described above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme described in the above method, so the specific limitations in one or more power grid system influence degree evaluation device embodiments provided below can refer to the limitations of the power grid system influence degree evaluation method described above, which will not be repeated here.

[0146] In one exemplary embodiment, as shown in Figure 4 a power grid system influence degree evaluation device 400 is provided, which includes a parameter acquisition module 402, a subway power grid model construction module 404, an evaluation model construction module 406, an evaluation value determination module 408, and an evaluation result determination module 410, wherein:

[0147] The parameter acquisition module 402 is configured to acquire a subway network and a power grid system in a target evaluation area; the subway network includes a subway topology structure, and the power grid system includes a power grid topology structure.

[0148] The subway power grid model construction module 404 is configured to construct a subway power grid model according to the subway topology structure, the power grid topology structure, and the electrical connection relationship between the subway network and the power grid system, and assign values to the parameters of the subway power grid model.

[0149] The evaluation model construction module 406 is configured to construct a main transformer DC bias probability index and a ground potential influence index according to the subway power grid model, and construct an influence degree evaluation model about the number of subway lines based on the main transformer DC bias probability index and the ground potential influence index.

[0150] The evaluation value determination module 408 is configured to obtain the number of subway lines at the expected time and input the number of subway lines into the influence degree evaluation model to obtain an evaluation value.

[0151] The evaluation result determination module 410 is configured to construct an evaluation grade, and evaluate the influence degree of the power grid system in the target evaluation area according to the evaluation value based on the evaluation grade to obtain an evaluation result.

[0152] In one of the embodiments, the power grid system further includes a number of neutral point grounded main transformers; and the evaluation model construction module 406 is specifically configured to: determine node voltages of nodes in the subway power grid model, determine neutral point currents of the transformers based on the node voltages and corresponding transformer winding resistances, and construct the main transformer DC bias probability index according to the number of the neutral point currents greater than a preset current threshold and the number of the main transformers.

[0153] In one of the embodiments, the subway network includes a number of stations; and the evaluation model construction module 406 is specifically configured to: obtain a longitude range, a latitude range and a soil resistivity of the target evaluation area, obtain a station longitude-latitude matrix of the subway network, and obtain a substation longitude-latitude matrix of the power grid system; construct a region longitude-latitude matrix of the target evaluation area according to the longitude range and the latitude range, construct a grounding node matrix according to the station longitude-latitude matrix and the substation longitude-latitude matrix, determine ground potential values of each longitude-latitude of the target evaluation area according to the region longitude-latitude matrix, the soil resistivity, the node voltages and the grounding node matrix, and construct the ground potential influence index according to the number of the ground potential values greater than a preset ground potential threshold and an element total amount of the region longitude-latitude matrix.

[0154] In one of the embodiments, the evaluation model construction module 406 is specifically configured to: construct a node voltage matrix based on the node voltages of the nodes, determine leakage currents of grounding points of the power grid system based on the node voltage matrix and corresponding grounding resistances, construct a distance matrix based on distances between each element in the region longitude-latitude matrix and each element in the grounding node matrix, construct a ground potential matrix according to the soil resistivity, the leakage currents and the distance matrix, and obtain the ground potential values of the target evaluation area at different longitude-latitude positions based on the ground potential matrix.

[0155] In one of the embodiments, the evaluation model construction module 406 is specifically configured to: acquire the number N of metro lines at the current time; wherein N is a positive integer; calculate each probability value of the number of metro lines from 1 to N according to the main variable DC bias magnetic probability index, obtain a probability evaluation matrix, and construct a probability evaluation function based on the probability evaluation matrix; calculate each ground potential value of the number of metro lines from 1 to N according to the ground potential influence index, obtain a ground potential evaluation matrix, and construct a ground potential evaluation function based on the ground potential evaluation matrix; construct an influence degree evaluation model according to the probability evaluation function and the ground potential evaluation function, and determine the weights of the probability evaluation function and the ground potential evaluation function.

[0156] In one of the embodiments, the evaluation result determination module 410 is specifically configured to: acquire a first preset evaluation threshold and a second preset evaluation threshold, and construct an evaluation level; the evaluation level includes slight, general and serious; if the evaluation value is greater than 0 and less than the first preset evaluation threshold, it is determined that the influence degree of the power grid system is slight; if the evaluation value is greater than or equal to the first preset evaluation threshold and less than the second preset evaluation threshold, it is determined that the influence degree of the power grid system is general; if the evaluation value is greater than or equal to the second preset evaluation threshold and less than 1, it is determined that the influence degree of the power grid system is serious.

[0157] The above-mentioned modules in the power grid system influence degree evaluation device can be all or partially realized by software, hardware and combinations thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in hardware form, or can be stored in the memory in the computer device in software form, so as to call and execute the operations corresponding to the above-mentioned modules by the processor.

[0158] In one exemplary embodiment, a computer device is provided, which can be a server, and the internal structure diagram thereof can be as shown in Figure 5 The computer device includes a processor, a memory, an input / output interface (I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is configured to store metro network and power grid system data. The input / output interface of the computer device is configured to exchange information between the processor and external devices. The communication interface of the computer device is configured to communicate with external terminals through network connection. The computer program is executed by the processor to implement a power grid system influence degree evaluation method.

[0159] Those skilled in the art can understand that Figure 5 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0160] In one embodiment, a computer device is provided, including a memory and a processor, the memory storing a computer program, and the processor implementing the steps in the above method embodiments when executing the computer program.

[0161] In one embodiment, a computer readable storage medium is provided, storing a computer program, and the computer program is executed by a processor to implement the steps in the above method embodiments.

[0162] In one embodiment, a computer program product is provided, including a computer program, and the computer program is executed by a processor to implement the steps in the above method embodiments.

[0163] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (Read-Only Memory, ROM), magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive memory (ReRAM), magnetoresistive random access memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric memory (Ferroelectric Random Access Memory, FRAM), phase change memory (Phase Change Memory, PCM), graphene memory, etc. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, etc. As an illustration but not limitation, RAM can be in various forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), etc. The database involved in the embodiments provided in the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a block chain, etc., without being limited thereto. The processor involved in the embodiments provided in the present application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., without being limited thereto.

[0164] Any combination of the technical features of the above embodiments can be made. In order to make the description simple, all possible combinations of the technical features in the above embodiments are not described, however, as long as the combination of the technical features does not exist contradictory, it should be considered as the scope of the present application.

[0165] The above embodiments only express several implementation manners of the present application, and the description is more specific and detailed, but it should not be understood as a limitation on the scope of the patent of the present application. It should be pointed out that for ordinary skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are within the scope of protection of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A method for assessing the degree of influence of a power grid system, characterized by, The method comprises: acquiring a subway network and a power grid system of a target evaluation area; the subway network comprises a subway topology and a number of stations, and the power grid system comprises a power grid topology and a number of neutral point grounding main transformers; constructing a subway power grid model according to the subway topology, the power grid topology and an electrical connection relationship between the subway network and the power grid system, and performing parameter assignment on the subway power grid model; determining node voltages of each node in the subway power grid model, and determining neutral point currents of each transformer based on the node voltages and corresponding transformer winding resistances; constructing a main transformer DC bias magnetism probability index according to a number of the neutral point currents greater than a preset current threshold and the number of the main transformers; acquiring a longitude range, a latitude range and a soil resistivity of the target evaluation area, acquiring a station longitude-latitude matrix of the subway network, and acquiring a substation longitude-latitude matrix of the power grid system; constructing an area longitude-latitude matrix of the target evaluation area according to the longitude range and the latitude range, and constructing a grounding node matrix according to the station longitude-latitude matrix and the substation longitude-latitude matrix; determining a ground potential value of each longitude-latitude of the target evaluation area according to the area longitude-latitude matrix, the soil resistivity, the node voltages and the grounding node matrix; constructing a ground potential influence index according to a number of ground potential values greater than a preset ground potential threshold and an element total amount of the area longitude-latitude matrix; acquiring a number N of subway lines at a current time; wherein N is a positive integer; calculating each probability value of the number of subway lines from 1 to N according to the main transformer DC bias magnetism probability index, obtaining a probability evaluation matrix, and constructing a probability evaluation function based on the probability evaluation matrix; calculating each ground potential value of the number of subway lines from 1 to N according to the ground potential influence index, obtaining a ground potential evaluation matrix, and constructing a ground potential evaluation function based on the ground potential evaluation matrix; constructing an influence degree evaluation model according to the probability evaluation function and the ground potential evaluation function, and determining weights of the probability evaluation function and the ground potential evaluation function; acquiring a number of subway lines at an expected time, and inputting the number into the influence degree evaluation model to obtain an evaluation value; constructing an evaluation level, and evaluating an influence degree of a power grid system of the target evaluation area according to the evaluation value based on the evaluation level to obtain an evaluation result.

2. The method of claim 1, wherein, The subway topology takes subway lines as edges of the topology structure and takes stations as nodes; and the power grid topology takes each substation in the power grid system as a node and takes power transmission lines as edges.

3. The method of claim 1, wherein, The probability evaluation function is constructed based on the probability evaluation matrix, which comprises: performing linear regression analysis on the number of subway lines and the probability evaluation matrix by using a least square method to obtain the probability evaluation function.

4. The method of claim 1, wherein, The ground potential evaluation function is constructed based on the ground potential evaluation matrix, which comprises: performing linear regression analysis on the number of subway lines and the ground potential evaluation matrix by using a least square method to obtain the ground potential evaluation function.

5. The method of claim 1, wherein, The ground potential value of each longitude and latitude of the target evaluation area is determined according to the area longitude and latitude matrix, the soil resistivity, each node voltage and the grounding node matrix, and the method comprises the steps of: A node voltage matrix is constructed based on the node voltage of each node, and the leakage current of each grounding point of the power grid system is determined based on the node voltage matrix and the corresponding grounding resistance; A distance matrix is constructed based on the distance between each element in the area longitude and latitude matrix and each element in the grounding node matrix; A ground potential matrix is constructed according to the soil resistivity, the leakage current and the distance matrix, and the ground potential value of the target evaluation area at different longitude and latitude positions is obtained based on the ground potential matrix.

6. The method according to any one of claims 1 to 5, characterized in that, The evaluation grade is constructed, and the affected degree of the power grid system of the target evaluation area is evaluated according to the evaluation value based on the evaluation grade, so as to obtain an evaluation result, and the method comprises the steps of: A first preset evaluation threshold and a second preset evaluation threshold are obtained, and an evaluation grade is constructed; the evaluation grade comprises slight, general and serious; If the evaluation value is greater than 0 and less than the first preset evaluation threshold, it is determined that the affected degree of the power grid system is slight; If the evaluation value is greater than or equal to the first preset evaluation threshold and less than the second preset evaluation threshold, it is determined that the affected degree of the power grid system is general; If the evaluation value is greater than or equal to the second preset evaluation threshold and less than 1, it is determined that the affected degree of the power grid system is serious.

7. A power grid system impact degree assessment device, characterized by, The device comprises: A parameter acquisition module is configured to acquire a subway network and a power grid system of a target evaluation area; the subway network comprises a subway topology structure and a number of stations, and the power grid system comprises a power grid topology structure and a number of neutral point grounding main transformers; A subway power grid model construction module is configured to construct a subway power grid model according to the subway topology structure, the power grid topology structure and an electrical connection relationship between the subway network and the power grid system, and to perform parameter assignment on the subway power grid model; The evaluation model construction module is configured to determine node voltages of nodes in the subway power grid model, determine neutral point currents of the transformers based on the node voltages and corresponding transformer winding resistances, construct a main transformer DC bias probability index according to a number of the neutral point currents greater than a preset current threshold and the number of the main transformers, obtain a longitude range, a latitude range and a soil resistivity of the target evaluation area, obtain a station longitude-latitude matrix of the subway network, and obtain a substation longitude-latitude matrix of the power grid system; construct an area longitude-latitude matrix of the target evaluation area according to the longitude range and the latitude range, construct a grounding node matrix according to the station longitude-latitude matrix and the substation longitude-latitude matrix, determine geoelectric potential values of each longitude-latitude of the target evaluation area according to the area longitude-latitude matrix, the soil resistivity, the node voltages and the grounding node matrix, construct a geoelectric potential influence index according to a number of geoelectric potential values greater than a preset geoelectric potential threshold and a total number of elements of the area longitude-latitude matrix, obtain a number N of subway lines at a current time, wherein N is a positive integer, calculate each probability value of the number of subway lines from 1 to N according to the main transformer DC bias probability index to obtain a probability evaluation matrix, construct a probability evaluation function based on the probability evaluation matrix, calculate each geoelectric potential value of the number of subway lines from 1 to N according to the geoelectric potential influence index to obtain a geoelectric potential evaluation matrix, and construct a geoelectric potential evaluation function based on the geoelectric potential evaluation matrix; and construct an influence degree evaluation model according to the probability evaluation function and the geoelectric potential evaluation function, and determine weights of the probability evaluation function and the geoelectric potential evaluation function. The evaluation value determination module is configured to obtain the number of subway lines at an expected time and input the number into the influence degree evaluation model to obtain an evaluation value. The evaluation result determination module is configured to construct an evaluation level, evaluate an influence degree of a power grid system of the target evaluation area according to the evaluation value based on the evaluation level, and obtain an evaluation result.

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that, The processor executes the computer program to implement the steps of the method of any one of claims 1 to 6.

9. A computer readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method of any one of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method of any one of claims 1 to 6.

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