A method and system for extracting key characteristic indicators of line loss in medium voltage distribution network

Abstract

The present invention discloses a method and system for extracting key characteristic indicators of line loss in a medium-voltage distribution network, and relates to the field of power grid operation and maintenance. The calculation of line loss in the existing process of extracting key characteristic indicators of feeders is complicated. This technical solution obtains characteristic information of line loss, establishes line loss evaluation indicators of a medium-voltage distribution network based on power grid loss and user loss, and combines the root mean square current method with the feeder line loss model. The common factors are extracted from the variable group through the principal factor analysis method for data statistics, and the establishment of associated common information is improved. The trapezoidal membership function is used to perform fuzzy processing on the power grid. The line loss characteristics of power grid loss and user loss are extracted to ensure the characteristic information under different losses, so as to achieve the process of extracting classified line loss characteristics, and provide data information and evaluation indicators for the extraction of key characteristic indicators of line loss in the medium-voltage distribution network.

Description

Technical Field

[0001] The present invention relates to the field of power grid operation and maintenance, and in particular to a method and system for extracting key characteristic indicators of line losses in a medium-voltage distribution network. Background Art

[0002] As the level of intelligence and reliability of power grids continue to increase, power grid line losses are increasingly important for the safe operation of power grids. Therefore, it is particularly important to detect the status of power grid line losses. When the electric energy generated by the generator is transmitted to the user, it passes through the transmission, transformation, and distribution equipment. Due to the resistance of these equipment, losses will occur when the electric energy passes through, and it will be dissipated in the surrounding medium in the form of heat energy; in addition, a part of the objective management loss is added. These two parts of power loss constitute all the line loss electricity of the power grid. Therefore, it is necessary to extract the key characteristic indicators in the distribution network line loss and obtain the line loss information.

[0003] The existing feeders are quite different from the high-voltage transmission network in terms of their basic properties, operation and management, so their line loss calculation also has its own characteristics. 1. Compared with the high-voltage transmission network, the medium-voltage distribution network lacks monitoring data and has a large data granularity, and these problems cannot be fundamentally solved in the short term; 2. The transmission network is very different from the medium-voltage distribution network in terms of topology, electrical characteristics and power flow distribution, so its line loss calculation method should be different from that of the high-voltage transmission network; 3. Compared with the high-voltage transmission network, the operation mode and operation parameters of the medium-voltage distribution network are greatly affected by the load, so its line loss is also greatly affected by the load; 4. Compared with the high-voltage transmission network, the management line loss of the medium-voltage distribution network accounts for a larger proportion of the total line loss, and this part of the line loss can only be reduced through optimized management. Summary of the invention

[0004] The technical problem to be solved and the technical task proposed by the present invention are to improve and perfect the existing technical solutions and provide a method and system for extracting key characteristic indicators of line loss in a medium voltage distribution network to solve the above problems. To this end, the present invention adopts the following technical solutions.

[0005] A method for extracting key characteristic indicators of line loss in a medium voltage distribution network comprises the following steps:

[0006] Step 1: construct a feeder line loss model with clustering characteristics, and construct the feeder line loss model with clustering characteristics by using a root mean square current method and feeder line loss characteristics;

[0007] Step 2: Fuzzy processing is performed on the power grid according to the feeder line loss model;

[0008] Step 3: Obtain the data set of line loss common factors in step 2, extract common factors from the variable group through principal factor analysis to perform data statistics, and improve the establishment of associated common information;

[0009] Step 4: Extract and process the data information of distribution network line loss in the data set, which includes power grid loss and user loss.

[0010] As a preferred technical means: in step 1), the root mean square current method is a processing method for calculating the theoretical line loss of the distribution network. The power loss generated by the root mean square current flowing through the distribution network in line transmission and the power loss generated by the distribution network load at the same time are further obtained according to the root mean square current method. The calculation formula of the line loss in the distribution network is:

[0011]

[0012] In the formula, ΔA represents the line loss in the distribution network; represents the root mean square current; R represents the component resistance; T represents the calculated value per hour; t represents the number of hours consumed in a day; It represents the root mean square current flowing per hour; 3 represents the number of phases of voltage; further, the active power, reactive power and line voltage are obtained through the load of the distribution network in one day, and the expression is as follows:

[0013]

[0014]

[0015] In the formula, P represents the active power passing through the component resistance at the hour; Q represents the reactive power passing through the component resistance at the hour; U represents the line voltage measured at the hour.

[0016] As a preferred technical means: in step 1), the line loss characteristics of the feeder are calculated by the equivalent resistance method to calculate the line loss of each base state feeder, and the steps include:

[0017] 101) Calculate the transformer loss in the distribution network of each base state feeder, and use the root mean square load calculation method to calculate the transformer loss, which is expressed as follows:

[0018] P t =T(P O +P t )*K 2 *λ 2

[0019] Where P t Indicates the total power consumption; P O Indicates the transformer no-load loss; P t represents transformer load loss; λ represents load rate; K represents RMS current coefficient; T represents transformer operation time;

[0020] 102) Calculate the line loss rate base value of each type of feeder, and the line loss rate base value of each type of feeder is the line loss rate value of the base state feeder in each type of feeder, and then calculate the following method based on the line loss rate base value:

[0021] LOSS i =Q I / LOOS I +LOOS T

[0022] Where, LOSS i Indicates the line loss rate base value of the i-th type feeder; LOOS I Indicates line loss; Q I Indicates power supply; LOOS T Indicates transformer loss.

[0023] As a preferred technical means: in step 2, a trapezoidal membership function is used to perform fuzzy processing on the power grid, which includes the following steps:

[0024] 201) Determine the evaluation indicator set;

[0025] 202) establishing an evaluation level set;

[0026] 203) Determine the indicator weights;

[0027] 204) Determine a membership matrix;

[0028] 205) Calculate the evaluation vector;

[0029] 206) Calculate the comprehensive evaluation vector to extract feature information.

[0030] As a preferred technical means: in step 201), the evaluation index set is determined to divide the comment set according to the actual needs of the evaluation object. Different evaluation targets have different divided comment sets:

[0031] V={v 1 , v 2 , v 3 ┄v n}

[0032] In the formula, v represents the evaluation level; n represents the number of evaluation levels;

[0033] In step 202), an evaluation level set is established by performing a hierarchical analysis on the evaluation objects to determine that all factors that have an impact on the evaluation results form a common set:

[0034] U={u 1 ,u 2 ,u 3 ┄u m}

[0035] In the formula, u represents the set; m represents the factor of the evaluation object;

[0036] In 203), determining the indicator weights is the most important in the entire evaluation system. If the weights are not determined accurately, the evaluation results will also be biased:

[0037] In 204), the membership matrix is ​​determined. The membership matrix of the index is obtained according to the membership function:

[0038] μ=EXP{-(xe x ) 2 / 2e n 2}

[0039] In the formula, e n Indicated by e x is the expected value; x represents the trapezoidal cloud model generator;

[0040] The calculation of the comprehensive evaluation vector extracts characteristic information according to the weight vector and the membership matrix as follows;

[0041] B=WR

[0042] Where B represents the membership matrix function; R represents the membership matrix; W represents the weight vector.

[0043] As a preferred technical means: in step 3), the factor analysis method selects a few representative variables from multiple variables through the process of establishing a factor model, estimating the load matrix, factor rotation and estimating the factor score function, and then selects, reduces the dimension and assigns weights to the variables, and further uses the comprehensive weight to describe the line loss rate; the following method is obtained:

[0044]

[0045] In the formula, K j(AHP) Indicates the subjective weight of using AHP; K j(FA) represents the objective weight determined using factor analysis; K j represents the comprehensive weight;

[0046] The sensitivity correction value affecting the feeder is obtained by describing the line loss rate based on the comprehensive weight, and the line loss rate of the feeder is calculated. The expression is as follows:

[0047]

[0048] In the formula, LOSS ix represents the line loss rate of the i-th type feeder; LOSS i Expressed as the base value of the line loss rate of the i-th type feeder; α irepresents the sensitivity correction value of the i-th factor to the feeder line rate;

[0049] The line loss rate benchmark values ​​of various feeders are obtained according to the feeder line loss rate. The difference between the line loss rate benchmark values ​​lies in the line loss rate values ​​of individual feeders. As a standard for judging whether the feeder line loss rate is abnormally high, the specific method is as follows:

[0050] E(L Li )-3σ i ≤LOSS ij ≤E(L Li )+3σ i

[0051] In the formula, E(L Li ) represents the judgment of the calculation result of the line loss rate of the i-th type feeder; LOSS ij represents the calculation result of line loss rate of the jth feeder of the i-th category, σ i Indicates the standard value of the calculation result of the i-th type line loss rate.

[0052] As a preferred technical means: in step 4), the power grid loss includes the branch overload degree, the bus voltage over-line degree, the line load loss ratio, and the important load loss degree, wherein the branch overload degree reflects the weight factor of the importance difference of each branch and the branch current value, and further according to the branch overload degree, the following method is obtained:

[0053]

[0054] Where η I Indicates the degree of branch overload; z indicates the total number of branches; n indicates the number of unloaded branches; ω K and ω l Represents the weight factor of each branch; I K and I l Indicates the current value of each branch; I l max and I K max Indicates the maximum current value of each branch;

[0055] The bus voltage over-line degree analysis and calculation numerical mark represent the relative value of physical quantity and parameter, and then the following method is obtained according to the bus voltage over-line degree:

[0056]

[0057] Where η U Indicates the degree of bus voltage crossing the line; M indicates the total number of buses; m indicates the number of buses without crossing the level; ω u and ω ul Indicates the weight factor of the corresponding busbar; U k and U l Indicates voltage amplitude; U l limIndicates the minimum bus voltage;

[0058] The line load loss ratio is the loss generated between the power grid and the user, and then the following method is obtained according to the line load loss ratio:

[0059]

[0060] Where η L Indicates the line load loss ratio; L loss Indicates loss load; L max Indicates the maximum load between line transmissions;

[0061] The degree of loss of important loads is expressed as follows:

[0062]

[0063] Where η p represents the degree of loss of important loads; m represents the number of important loads lost; n represents the total number of important loads; p j represents the power of the jth important load; ω j represents the weight factor of the jth important load; j Indicates that the jth important load belongs to the transmission path; i It means that the jth important load does not belong to the transmission path.

[0064] As a preferred technical means: the user loss includes the power outage ratio, the user power outage loss ratio, and the average daily power outage time ratio, wherein the power outage ratio measures the loss range of the power grid, and further according to the power outage ratio, the following method is obtained:

[0065]

[0066] Where η C Indicates the proportion of people without power; C loss represents the total number of people involved in the power outage; C represents the total number of people in the safe area of ​​the power grid site;

[0067] The user's power outage loss ratio is obtained by the estimated power supply of the power grid and the loss caused by the power outage as follows:

[0068]

[0069] Where η Q Indicates the proportion of power outage losses for users; Q pre Indicates the power supply during the power grid transmission period; f ccdf (t) represents the comprehensive power outage loss function; p irepresents the total load loss caused by the ith power outage; t i represents the time of the i-th power outage; n represents the number of power outages during the power supply period of the power grid;

[0070] The daily average power outage time ratio reflects the ability of the power grid to continuously supply power to users of each voltage level; the expression is as follows:

[0071]

[0072] Where, t loss represents the average daily power outage time ratio; p i represents the i-th power outage load; t iloss Indicates the power outage time of the grid load; s indicates the number of seconds consumed in a day; p max It represents the maximum power supply load of the power grid; m represents the number of power outages during the operation of the power grid.

[0073] A system for extracting key characteristic indicators of line loss in a medium voltage distribution network, characterized by comprising:

[0074] The first module is used to construct a feeder line loss model with clustering characteristics;

[0075] The second module is used to perform fuzzy processing on the power grid according to the feeder line loss model;

[0076] The third module is used to obtain the line loss commonality factor data set;

[0077] The fourth module is used to extract data information of distribution network line loss in the data set.

[0078] As the preferred technical means: the first module uses the root mean square current method and feeder line loss characteristics to build a feeder line loss model with clustering characteristics. The root mean square current method is a processing method for calculating the theoretical line loss of the distribution network. The power loss generated by the root mean square current flowing through the distribution network during line transmission and the power loss generated by the distribution network load at the same time are obtained as follows according to the root mean square current method:

[0079]

[0080] In the formula, ΔA represents the line loss in the distribution network; represents the root mean square current; R represents the component resistance; T represents the calculated value per hour; t represents the number of hours consumed in a day; It represents the root mean square current flowing per hour; 3 represents the number of phases of voltage; further, the active power, reactive power and line voltage are obtained through the load of the distribution network in one day, and the expression is as follows:

[0081]

[0082]

[0083] In the formula, P represents the active power passing through the element resistance at the hour; Q represents the reactive power passing through the element resistance at the hour; U represents the line voltage measured at the hour;

[0084] The feeder line loss characteristics are calculated by using the equivalent resistance method to calculate the line loss of each base state feeder, the transformer loss in the distribution network of each base state feeder, and the transformer loss is calculated by using the root mean square load calculation method. The expression is as follows:

[0085] P t =T(P O +P t ) / K 2 *λ 2

[0086] Where P t Indicates the total power consumption; P O Indicates the transformer no-load loss; P t represents transformer load loss; λ represents load rate; K represents RMS current coefficient; T represents transformer operation time;

[0087] Calculate the line loss rate base value of each type of feeder, and the line loss rate base value of each type of feeder is the line loss rate value of the base state feeder in each type of feeder, and then calculate the following method based on the line loss rate base value:

[0088] LOSS i =Q I / LOOS I +LOOS T

[0089] Where, LOSS i Indicates the line loss rate base value of the i-th type feeder; LOOS I Indicates line loss; Q I Indicates power supply; LOOS T Indicates transformer loss;

[0090] The second module determines the evaluation index set, establishes the evaluation level set, determines the index weight, determines the membership matrix, calculates the evaluation vector, and calculates the comprehensive evaluation vector to extract characteristic information. After the evaluation index system is established, the reasonable determination of the index weight is the basis for the evaluation work to ensure the authenticity and accuracy of the weight of each evaluation index.

[0091] The evaluation index set is determined according to the actual needs of the evaluation object to divide the comment set. Different evaluation targets will result in different divided comment sets:

[0092] V={v 1 , v2 , v 3 ┄v n}

[0093] In the formula, v represents the evaluation level; n represents the number of evaluation levels;

[0094] The evaluation level set is established by performing a hierarchical analysis on the evaluation objects to determine that all factors that affect the evaluation results form a common set:

[0095] U={u 1 ,u 2 ,u 3 ┄u m}

[0096] In the formula, u represents the set; m represents the factor of the evaluation object;

[0097] The determination of indicator weights is the most important in the entire evaluation system. If the weights are not determined accurately, the evaluation results will also be biased:

[0098] The determination of the membership matrix is ​​to obtain the membership matrix of the indicator according to the membership function:

[0099] μ=EXP{-(xe x ) 2 / 2e n 2}

[0100] In the formula, e n Indicated by e x is the expected value; x represents the trapezoidal cloud model generator;

[0101] The calculation of the comprehensive evaluation vector extracts characteristic information according to the weight vector and the membership matrix as follows;

[0102] B=WR

[0103] In the formula, B represents the membership matrix function; R represents the membership matrix; W represents the weight vector;

[0104] The third module uses the principal factor analysis method to extract common factors from the variable group for data statistics, and improves the establishment of associated common information. The factor analysis method selects a few representative variables from multiple variables through the process of establishing factor models, estimating load matrices, factor rotation, and estimating factor score functions. Then, the variables are screened, dimensionally reduced, and weighted, and the comprehensive weight is used to further describe the line loss rate. The following method is obtained:

[0105]

[0106] In the formula, Kj(AHP) Indicates the subjective weight of using AHP; K j(FA) represents the objective weight determined using factor analysis; K j represents the comprehensive weight;

[0107] The sensitivity correction value affecting the feeder is obtained by describing the line loss rate based on the comprehensive weight, and the line loss rate of the feeder is calculated. The expression is as follows:

[0108] LOSS ix =LOSS i (1+∑α i )

[0109] In the formula, LOSS ix represents the line loss rate of the i-th type feeder; LOSS i Expressed as the base value of the line loss rate of the i-th type feeder; α i represents the sensitivity correction value of the i-th factor to the feeder line rate;

[0110] The line loss rate benchmark values ​​of various feeders are obtained according to the feeder line loss rate. The difference between the line loss rate benchmark values ​​lies in the line loss rate values ​​of individual feeders. As a standard for judging whether the feeder line loss rate is abnormally high, the specific method is as follows:

[0111] E(L Li )-3σ i ≤LOSS ij ≤E(L Li )+3σ i

[0112] In the formula, E(L Li ) represents the judgment of the calculation result of the line loss rate of the i-th type feeder; LOSS ij represents the calculation result of line loss rate of the jth feeder of the i-th category, σ i It represents the standard value of the calculation result of the line loss rate of the i-th category;

[0113] The fourth module includes a power grid loss metering module and a user loss metering module, wherein the power grid loss metering module further obtains power grid loss information by statistically calculating power losses and losses in the transmission, substation, and distribution box links during the transmission of electric energy from the power plant; the user loss metering module obtains power grid losses output by the distribution box, and then counts the user's electricity consumption and the power loss generated by the user, as well as the power loss caused by different working environments.

[0114] Beneficial effects: This technical solution constructs a core indicator system for medium-voltage distribution network line loss, participates in feeder clustering, establishes a feeder line loss model and a comprehensive evaluation indicator system for the distribution network, uses a membership function to achieve a comprehensive evaluation of the distribution network, analyzes the indicator evaluation results, and uses a trapezoidal membership function to fuzzy the power grid. By extracting line loss features of power grid loss and user loss, the characteristic information under different losses is ensured, and the process of classified line loss feature extraction is achieved, providing data information and evaluation indicators for the extraction of key characteristic indicators of medium-voltage distribution network line losses. BRIEF DESCRIPTION OF THE DRAWINGS

[0115] Figure 1 It is a schematic diagram of the key characteristic indicator system of the distribution network of the present invention.

[0116] Figure 2 It is a feeder line loss flow chart of the present invention.

[0117] Figure 3 It is the membership function coordinate axis diagram of the present invention.

[0118] Figure 4 Schematic diagram of line loss in the distribution network of the present invention. DETAILED DESCRIPTION

[0119] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings.

[0120] like Figure 1 As shown, step 1, constructing a feeder line loss model with clustering characteristics;

[0121] Step 2: Fuzzy processing is performed on the power grid according to the feeder line loss model;

[0122] Step 3, obtaining a data set of line loss commonality factors in step 2;

[0123] Step 4: Extract the data information of distribution network line loss in the data set.

[0124] In a further embodiment, the step 1 is further:

[0125] The distribution network uses the root mean square current method and feeder line loss characteristics to build a feeder line loss model with clustering characteristics. The root mean square current method is a processing method for calculating the theoretical line loss of the distribution network. The power loss caused by the root mean square current flowing through the distribution network during line transmission and the power loss caused by the distribution network load at the same time are further obtained according to the root mean square current method as follows:

[0126]

[0127] In the formula, ΔA represents the line loss in the distribution network; represents the root mean square current; R represents the component resistance; T represents the calculated value per hour; t represents the number of hours consumed in a day; It represents the root mean square current flowing per hour; 3 represents the number of phases of voltage; further, the active power, reactive power and line voltage are obtained through the load of the distribution network in one day, and the expression is as follows:

[0128]

[0129]

[0130] In the formula, P represents the active power passing through the component resistance at the hour; Q represents the reactive power passing through the component resistance at the hour; U represents the line voltage measured at the hour.

[0131] In a further embodiment, Figure 2 As shown, the feeder line loss characteristics are calculated by the equivalent resistance method to calculate the line loss of each base state feeder, and the specific steps are as follows:

[0132] Step 11: Calculate the transformer loss in the distribution network of each base state feeder. Use the root mean square load calculation method to calculate the transformer loss, which is expressed as follows:

[0133] P t =T(P O +P t )*K 2 *λ 2

[0134] Where P t Indicates the total power consumption; P O Indicates the transformer no-load loss; P t represents transformer load loss; λ represents load rate; K represents RMS current coefficient; T represents transformer operation time;

[0135] Step 12: Calculate the line loss rate base value of each type of feeder, which is the line loss rate value of the base state feeder in each type of feeder. Then, the following method is obtained based on the line loss rate base value:

[0136] LOSS i =Q I / LOOS I +LOOS T

[0137] Where, LOSS i Indicates the line loss rate base value of the i-th type feeder; LOOS I Indicates line loss; Q I Indicates power supply; LOOS T Indicates transformer loss.

[0138] In a further embodiment, the step 2 further comprises the following steps:

[0139] Step 21, determine the evaluation index set;

[0140] Step 22: Establish an evaluation level set;

[0141] Step 23: Determine the indicator weights;

[0142] Step 24, determine the membership matrix;

[0143] Step 25, calculate the evaluation vector;

[0144] Step 26: Calculate the comprehensive evaluation vector to extract characteristic information.

[0145] In a further embodiment, the evaluation index set is determined to divide the comment set according to the actual needs of the evaluation object. Different evaluation targets result in different divided comment sets:

[0146] V={v 1 , v 2， v 3 ┄v n}

[0147] In the formula, v represents the evaluation level; n represents the number of evaluation levels;

[0148] The evaluation level set is established by performing a hierarchical analysis on the evaluation objects to determine that all factors that affect the evaluation results form a common set:

[0149] U={u 1 ,u 2 ,u 3 ┄u m}

[0150] In the formula, u represents the set; m represents the factor of the evaluation object;

[0151] Determining the weight of the indicators is the most important in the entire evaluation system. If the weight is not determined accurately, the evaluation results will be biased:

[0152] The determination of the membership matrix obtains the membership matrix of the index according to the membership function:

[0153] μ=EXP{-(xe x ) 2 / 2e n 2}

[0154] In the formula, e n Indicated by e xis the expected value; x represents the trapezoidal cloud model generator;

[0155] The calculation of the comprehensive evaluation vector extracts characteristic information according to the weight vector and the membership matrix as follows;

[0156] B=WR

[0157] Where B represents the membership matrix function; R represents the membership matrix; W represents the weight vector.

[0158] In a further embodiment, the step 3 is further:

[0159] The factor analysis method of hierarchical analysis is used to calculate the comprehensive weight of the basic indicators of line loss rate. The factor analysis method selects a few representative variables from multiple variables through process processing, through the establishment of factor model, estimation of load matrix, factor rotation and estimation of factor score function, and then screens, reduces the dimension and assigns weights to the variables, and further uses the comprehensive weight to describe the line loss rate; the following method is obtained:

[0160]

[0161] In the formula, K j(AHP) Indicates the subjective weight of using AHP; K j(FA) represents the objective weight determined using factor analysis; K j represents the comprehensive weight;

[0162] Step 31: Describe the line loss rate based on the comprehensive weight to obtain the sensitivity correction value affecting the feeder, and calculate the line loss rate of the feeder. The expression is as follows:

[0163] LOSS ix =LOSS i (1+∑α i )

[0164] In the formula, LOSS ix represents the line loss rate of the i-th type feeder; LOSS i Expressed as the base value of the line loss rate of the i-th type feeder; α i represents the sensitivity correction value of the i-th factor to the feeder line rate;

[0165] Step 32: According to the feeder line loss rate, the line loss rate benchmark values ​​of various feeders are obtained. The difference between the line loss rate benchmark values ​​lies in the line loss rate values ​​of individual feeders. The line loss rate benchmark values ​​are used as a standard for judging whether the feeder line loss rate is abnormally high. The specific method is as follows:

[0166] E(L Li )-3σ i ≤LOSS ij ≤E(L Li )+3σi

[0167] In the formula, E(L Li ) represents the judgment of the calculation result of the line loss rate of the i-th type feeder; LOSS ij represents the calculation result of line loss rate of the jth feeder of the i-th category, σ i Indicates the standard value of the calculation result of the i-th type line loss rate.

[0168] In a further embodiment, the step 4 is further:

[0169] like Figure 1 , 4 As shown, the data information of power grid line loss includes power grid loss and user loss, wherein the power grid loss includes branch overload degree, bus voltage overline degree, line load loss ratio, and important load loss degree, wherein the branch overload degree reflects the weight factor of the importance difference of each branch and the branch current value, and further according to the branch overload degree, the following method is obtained:

[0170]

[0171] Where η I Indicates the degree of branch overload; z indicates the total number of branches; n indicates the number of unloaded branches; ω K and ω l Represents the weight factor of each branch; I K and I l Indicates the current value of each branch; I l max and I K max Indicates the maximum current value of each branch;

[0172] The bus voltage over-line degree analysis and calculation numerical mark represent the relative value of physical quantity and parameter, and then the following method is obtained according to the bus voltage over-line degree:

[0173]

[0174] Where η U Indicates the degree of bus voltage crossing the line; M indicates the total number of buses; m indicates the number of buses without crossing the level; ω u and ω ul Indicates the weight factor of the corresponding busbar; U k and U l Indicates voltage amplitude; U l lim Indicates the minimum bus voltage;

[0175] The line load loss ratio is the loss generated between the power grid and the user, and then the following method is obtained according to the line load loss ratio:

[0176]

[0177] Where η L Indicates the line load loss ratio; L loss Indicates loss load; L max Indicates the maximum load between line transmissions;

[0178] The degree of loss of important loads is expressed as follows:

[0179]

[0180] Where η p represents the degree of loss of important loads; m represents the number of important loads lost; n represents the total number of important loads; p j represents the power of the jth important load; ω j represents the weight factor of the jth important load; j Indicates that the jth important load belongs to the transmission path; i It means that the jth important load does not belong to the transmission path.

[0181] A system for extracting key characteristic indicators of medium voltage distribution network line loss, comprising the following modules:

[0182] The first module is used to construct a feeder line loss model with clustering characteristics; the first module further constructs a feeder line loss model with clustering characteristics using the root mean square current method and feeder line loss characteristics, and the root mean square current method is a processing method for calculating the theoretical line loss of the distribution network. The power loss generated by the root mean square current flowing through the distribution network during line transmission and the power loss generated by the distribution network load at the same time are further obtained according to the root mean square current method as follows:

[0183]

[0184] In the formula, ΔA represents the line loss in the distribution network; represents the root mean square current; R represents the component resistance; T represents the calculated value per hour; t represents the number of hours consumed in a day; It represents the root mean square current flowing per hour; 3 represents the number of phases of voltage; further, the active power, reactive power and line voltage are obtained through the load of the distribution network in one day, and the expression is as follows:

[0185]

[0186]

[0187] In the formula, P represents the active power passing through the element resistance at the hour; Q represents the reactive power passing through the element resistance at the hour; U represents the line voltage measured at the hour;

[0188] The feeder line loss characteristics are calculated by using the equivalent resistance method to calculate the line loss of each base state feeder, the transformer loss in the distribution network of each base state feeder, and the transformer loss is calculated by using the root mean square load calculation method. The expression is as follows:

[0189] P t =T(P O +P t )*K 2 *λ 2

[0190] Where P t Indicates the total power consumption; P O Indicates the transformer no-load loss; P t represents transformer load loss; λ represents load rate; K represents RMS current coefficient; T represents transformer operation time;

[0191] Calculate the line loss rate base value of each type of feeder, and the line loss rate base value of each type of feeder is the line loss rate value of the base state feeder in each type of feeder, and then calculate the following method based on the line loss rate base value:

[0192] LOSS i =Q I / LOOS I +LOOS T

[0193] Where, LOSS i Indicates the line loss rate base value of the i-th type feeder; LOOS I Indicates line loss; Q I Indicates power supply; LOOS T Indicates transformer loss;

[0194] A second module for fuzzy processing of the power grid according to the feeder line loss model; the second module further includes determining an evaluation index set, establishing an evaluation level set, determining an index weight, determining a membership matrix, calculating an evaluation vector, and calculating a comprehensive evaluation vector to extract characteristic information, wherein after establishing an evaluation index system, reasonably determining the index weight is the basis for evaluation work, and the authenticity and accuracy of each evaluation index weight is ensured;

[0195] The evaluation index set is determined according to the actual needs of the evaluation object to divide the comment set. Different evaluation targets will result in different divided comment sets:

[0196] V={v 1 , v 2 , v 3 ┄v n}

[0197] In the formula, v represents the evaluation level; n represents the number of evaluation levels;

[0198] The evaluation level set is established by performing a hierarchical analysis on the evaluation objects to determine that all factors that affect the evaluation results form a common set:

[0199] U={u 1 ,u 2 ,u 3 ┄u m}

[0200] In the formula, u represents the set; m represents the factor of the evaluation object;

[0201] The determination of indicator weights is the most important in the entire evaluation system. If the weights are not determined accurately, the evaluation results will also be biased:

[0202] The determination of the membership matrix is ​​to obtain the membership matrix of the indicator according to the membership function:

[0203] μ=EXP{-(xe x ) 2 / 2e n 2}

[0204] In the formula, e n Indicated by e x is the expected value; x represents the trapezoidal cloud model generator;

[0205] The calculation of the comprehensive evaluation vector extracts characteristic information according to the weight vector and the membership matrix as follows;

[0206] B=WR

[0207] In the formula, B represents the membership matrix function; R represents the membership matrix; W represents the weight vector; the membership function coordinate axis diagram is as follows Figure 3 shown.

[0208] The third module is used to obtain the data set of common factors of line loss; the third module further calculates the hierarchical analysis factor analysis method of the comprehensive weight of the basic indicators of line loss rate, and the factor analysis method selects a few representative variables from multiple variables through the process of establishing a factor model, estimating the load matrix, factor rotation and estimating the factor score function, and then selects the variables, reduces the dimension, assigns weights, and further uses the comprehensive weight to describe the line loss rate; the following method is obtained:

[0209]

[0210] In the formula, K j(AHP) Indicates the subjective weight of using AHP; Kj(FA) represents the objective weight determined using factor analysis; K j represents the comprehensive weight;

[0211] The sensitivity correction value affecting the feeder is obtained by describing the line loss rate based on the comprehensive weight, and the line loss rate of the feeder is calculated. The expression is as follows:

[0212] LOSS ix =LOSS i (1+∑α i )

[0213] In the formula, LOSS ix represents the line loss rate of the i-th type feeder; LOSS i Expressed as the base value of the line loss rate of the i-th type feeder; α i represents the sensitivity correction value of the i-th factor to the feeder line rate;

[0214] The line loss rate benchmark values ​​of various feeders are obtained according to the feeder line loss rate. The difference between the line loss rate benchmark values ​​lies in the line loss rate values ​​of individual feeders. As a standard for judging whether the feeder line loss rate is abnormally high, the specific method is as follows:

[0215] E(L Li )-3σ i ≤LOSS ij ≤E(L Li )+3σ i

[0216] In the formula, E(L Li ) represents the judgment of the calculation result of the line loss rate of the i-th type feeder; LOSS ij represents the calculation result of line loss rate of the jth feeder of the i-th category, σ i It represents the standard value of the calculation result of the line loss rate of the i-th category;

[0217] The fourth module is used to extract data information of distribution network line loss in the data set, and the fourth module further includes a power grid loss metering module and a user loss metering module, wherein the power grid loss metering module further obtains power grid loss information by statistically calculating power losses and losses in the transmission, substation, and distribution box links during the transmission of electric energy from the power plant; the user loss metering module calculates the power grid loss output by the distribution box, and then counts the user's power consumption and the power loss generated by the user, as well as the power loss caused by different working environments.

[0218] In summary, the present invention has the following advantages: using the membership function to realize the comprehensive evaluation of the distribution network, analyzing the index evaluation results, using the trapezoidal membership function to perform fuzzy processing on the power grid, extracting the line loss features of the power grid loss and user loss, ensuring the characteristic information under different losses, achieving the process of classified line loss feature extraction, and providing data information and evaluation indicators for the extraction of key characteristic indicators of line loss in the medium-voltage distribution network.

[0219] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present invention will not further describe various possible combinations.

[0220] above Figure 1-4 The method and system for extracting key characteristic indicators of line loss in a medium-voltage distribution network shown in the figure are specific embodiments of the present invention, which have embodied the substantial characteristics and progress of the present invention. According to actual use needs and under the guidance of the present invention, equivalent modifications in shape, structure, etc. can be made to the method and system, which are all within the protection scope of this scheme.

Claims

1. A method for extracting key characteristic indicators of line loss in a medium voltage distribution network, characterized in that The following steps are involved: Step 1: construct a feeder line loss model with clustering characteristics, and construct the feeder line loss model with clustering characteristics by using the root mean square current method and feeder line loss characteristics; Step 2: Fuzzy processing is performed on the power grid according to the feeder line loss model; Step 3: Obtain the data set of the line loss common factors in step 2, extract the common factors from the variable group by principal factor analysis method to perform data statistics, and improve the establishment of associated common information; Step 4: extract and process the data information of distribution network line loss in the data set, the data information includes power grid loss and user loss; In step 2, the power grid is fuzzy processed using a trapezoidal membership function, which includes the following steps: 201) Determine the evaluation indicator set; 202) Establishing a set of evaluation levels; 203) Determine the indicator weights; 204) Determine the membership matrix; 205) Calculate the evaluation vector; 206) Calculate the comprehensive evaluation vector to extract feature information.

2. A method for extracting key characteristic indicators of line loss in a medium voltage distribution network according to claim 1, characterized in that: In step 1), the root mean square current method is used to calculate the theoretical line loss of the distribution network. The power loss caused by the root mean square current flowing through the distribution network in line transmission is the power loss caused by the distribution network load at the same time. The calculation formula of the line loss in the distribution network is further obtained based on the root mean square current method: In the formula, Indicates the power loss in the neutral line of the distribution network; represents the root mean square current; Indicates the resistance of a component; Indicates the calculated value per hour; Indicates the number of hours consumed in a day; It represents the RMS current flowing per hour; Indicates the number of phases of voltage; further, the active power, reactive power and line voltage are obtained through the load of the distribution network in one day, and the expression is as follows: In the formula, Indicates the active power passing through the component resistance at the hour; Indicates the reactive power passing through the resistor at every hour; Indicates the line voltage measured at the hour.

3. A method for extracting key characteristic indicators of line loss in a medium voltage distribution network according to claim 2, characterized in that: In step 1), the feeder line loss characteristics are used to calculate the line loss of each base state feeder by an equivalent resistance method, and the steps include: 101) Calculate the transformer loss in the distribution network of each base-state feeder, and use the root mean square load calculation method to calculate the transformer loss, which is expressed as follows: In the formula, Indicates the total power consumption; Indicates the transformer no-load loss; Indicates transformer load loss; Indicates the load factor; represents the RMS current coefficient; Indicates the operating time of the transformer; 102) Calculate the base value of line loss rate of each type of feeder, which is the line loss rate value of the base state feeder in each type of feeder. Then, the following formula is obtained based on the base value of line loss rate: In the formula, Indicates Base value of line loss rate of feeder type; Indicates line loss; Indicates the power supply; Indicates transformer loss.

4. A method for extracting key characteristic indicators of line loss in a medium voltage distribution network according to claim 1, characterized in that: In step 201), the evaluation index set is determined to divide the comment set according to the actual needs of the evaluation object. Different evaluation targets will result in different divided comment sets: In the formula, Indicates the evaluation level; Indicates the number of evaluation levels; In step 202), an evaluation level set is established by performing a hierarchical analysis on the evaluation objects to determine that all factors that have an impact on the evaluation results form a common set: In the formula, Represents a collection; Factors representing the object of evaluation; In 203), determining the indicator weights is the most important in the entire evaluation system. If the weights are not determined accurately, the evaluation results will also be biased: In 204), the membership matrix is ​​determined. The membership matrix of the indicator is obtained according to the membership function: In the formula, Indicates is the expected value; represents the trapezoidal cloud model generator; The calculation of the comprehensive evaluation vector extracts characteristic information according to the weight vector and the membership matrix as follows; In the formula, represents the membership matrix function; represents the membership matrix; represents the weight vector.

5. A method for extracting key characteristic indicators of line loss in a medium voltage distribution network according to claim 4, characterized in that: In step 3), the factor analysis method selects a few representative variables from multiple variables through process processing, through the establishment of factor model, estimation of load matrix, factor rotation and estimation of factor score function, and then screens, reduces dimensions and assigns weights to the variables, and further uses the comprehensive weight to describe the line loss rate; the following method is obtained: In the formula, Indicates the subjective weights using the AHP method; represents the objective weights determined using factor analysis; represents the comprehensive weight; The sensitivity correction value affecting the feeder is obtained by describing the line loss rate based on the comprehensive weight, and the line loss rate of the feeder is calculated. The expression is as follows: In the formula, Indicates Feeder line loss rate; Expressed as Base value of line loss rate of feeder type; Indicates The sensitivity correction value of the feeder line rate to the factors; The line loss rate benchmark values ​​of various feeders are obtained according to the feeder line loss rate. The difference between the line loss rate benchmark values ​​lies in the line loss rate values ​​of individual feeders. As a standard for judging whether the feeder line loss rate is abnormally high, the specific method is as follows: In the formula, Indicates Determination of the calculation results of feeder line loss rate; Indicates Class The calculation results of line loss rate of feeder lines are: Indicates The standard value of the line loss rate calculation result.

6. A method for extracting key characteristic indicators of line loss in a medium voltage distribution network according to claim 5, characterized in that: In step 4), the power grid loss includes the branch overload degree, bus voltage over-line degree, line load loss ratio, and important load loss degree, wherein the branch overload degree reflects the weight factor of the importance difference of each branch and the branch current value, and further according to the branch overload degree, the following method is obtained: In the formula, Indicates the branch overload degree; Indicates the total number of branches; Indicates the number of unloaded branches; and Represents the weight factor of each branch; and Indicates the current value of each branch; and Indicates the maximum current value of each branch; The bus voltage over-line degree analysis and calculation numerical mark represent the relative value of physical quantity and parameter, and then the following method is obtained according to the bus voltage over-line degree: In the formula, Indicates the degree of bus voltage crossing the line; Indicates the total number of buses; Indicates the number of buses without skipping levels; and represents the weight factor of the corresponding busbar; and Indicates voltage amplitude; Indicates the minimum bus voltage; The line load loss ratio is the loss generated between the power grid and the user, and then the following method is obtained according to the line load loss ratio: In the formula, Indicates the line load loss ratio; Indicates loss load; Indicates the maximum load between line transmissions; The degree of loss of important loads is the interruption of power supply at different load levels, resulting in loss of important loads, and is expressed as follows: In the formula, Indicates the degree of loss of important loads; The number of important loads indicating loss; Indicates the total number of important loads; Indicates The power of important loads; Indicates The weighting factors of important loads; Indicates An important load belongs to the transmission path; Indicates An important load does not belong to the transmission path.

7. A method for extracting key characteristic indicators of line loss in a medium voltage distribution network according to claim 6, characterized in that: The user losses include the power outage ratio, the user power outage loss ratio, and the average daily power outage time ratio. The power outage ratio measures the loss range of the power grid. The following method is further derived based on the power outage ratio: In the formula, Indicates the proportion of people without power; Indicates the total number of people affected by the power outage; Indicates the total number of people in the safe area of ​​the power grid construction site; The user's power outage loss ratio is obtained by the estimated power supply of the power grid and the loss caused by the power outage as follows: In the formula, Indicates the proportion of power outage losses for users; Indicates the power supply during the power grid transmission period; represents the comprehensive power outage loss function; Indicates Total load lost in a power outage; Indicates The duration of power outage; Indicates the number of power outages during the power supply period of the grid; The daily average power outage time ratio reflects the ability of the power grid to continuously supply power to users of each voltage level; the expression is as follows: In the formula, It indicates the average daily power outage time ratio; Indicates Power outage load; Indicates the power outage time of the grid load; Represents the number of seconds consumed in a day; Indicates the maximum power supply load of the power grid; Indicates the number of power outages during grid operation.

8. A system using the method for extracting key characteristic indicators of line loss in a medium voltage distribution network according to any one of claims 1 to 7, characterized in that include: The first module is used to construct a feeder line loss model with clustering characteristics; The second module is used to perform fuzzy processing on the power grid according to the feeder line loss model; The third module is used to obtain the line loss commonality factor data set; The fourth module is used to extract data information of distribution network line loss in the data set.

9. A method for extracting key characteristic indicators of line loss in a medium voltage distribution network according to claim 8, characterized in that: The first module builds a feeder line loss model with clustering characteristics using the root mean square current method and feeder line loss characteristics. The root mean square current method is a processing method for calculating the theoretical line loss of the distribution network. The power loss generated by the root mean square current flowing through the distribution network during line transmission and the power loss generated by the distribution network load at the same time are obtained as follows based on the root mean square current method: In the formula, Indicates the power loss in the neutral line of the distribution network; represents the root mean square current; Indicates the resistance of a component; Indicates the calculated value per hour; Indicates the number of hours consumed in a day; It represents the RMS current flowing per hour; Indicates the number of phases of voltage; further, the active power, reactive power and line voltage are obtained through the load of the distribution network in one day, and the expression is as follows: In the formula, Indicates the active power passing through the component resistance at the hour; Indicates the reactive power passing through the resistor at every hour; Indicates the line voltage measured at the hour; The feeder line loss characteristics are calculated by using the equivalent resistance method to calculate the line loss of each base state feeder, the transformer loss in the distribution network of each base state feeder, and the transformer loss is calculated by using the root mean square load calculation method. The expression is as follows: In the formula, Indicates the total power consumption; Indicates the transformer no-load loss; Indicates transformer load loss; Indicates the load factor; represents the RMS current coefficient; Indicates the operating time of the transformer; Calculate the line loss rate base value of each type of feeder, and the line loss rate base value of each type of feeder is the line loss rate value of the base state feeder in each type of feeder, and then calculate the following method based on the line loss rate base value: In the formula, Indicates Base value of line loss rate of feeder type; Indicates line loss; Indicates the power supply; Indicates transformer loss; The second module determines the evaluation index set, establishes the evaluation level set, determines the index weight, determines the membership matrix, calculates the evaluation vector, and calculates the comprehensive evaluation vector to extract characteristic information. After the evaluation index system is established, the reasonable determination of the index weight is the basis for the evaluation work to ensure the authenticity and accuracy of the weight of each evaluation index. The evaluation index set is determined according to the actual needs of the evaluation object to divide the comment set. Different evaluation targets will result in different divided comment sets: In the formula, Indicates the evaluation level; Indicates the number of evaluation levels; The evaluation level set is established by performing a hierarchical analysis on the evaluation objects to determine that all factors that affect the evaluation results form a common set: In the formula, Represents a collection; Factors representing the object of evaluation; The determination of indicator weights is the most important in the entire evaluation system. If the weights are not determined accurately, the evaluation results will also be biased: The determination of the membership matrix is ​​to obtain the membership matrix of the indicator according to the membership function: In the formula, Indicates is the expected value; represents the trapezoidal cloud model generator; The calculation of the comprehensive evaluation vector extracts characteristic information according to the weight vector and the membership matrix as follows; In the formula, represents the membership matrix function; represents the membership matrix; represents the weight vector; The third module uses the principal factor analysis method to extract common factors from the variable group for data statistics, and improves the establishment of associated common information. The factor analysis method selects a few representative variables from multiple variables through the process of establishing factor models, estimating load matrices, factor rotation, and estimating factor score functions. Then, the variables are screened, dimensionally reduced, and weighted, and the comprehensive weight is used to further describe the line loss rate. The following method is obtained: In the formula, Indicates the subjective weights using the AHP method; represents the objective weights determined using factor analysis; represents the comprehensive weight; 、 The sensitivity correction value affecting the feeder is obtained by describing the line loss rate based on the comprehensive weight, and the line loss rate of the feeder is calculated. The expression is as follows: In the formula, Indicates Feeder line loss rate; Expressed as Base value of line loss rate of feeder type; Indicates The sensitivity correction value of the feeder line rate to the factors; The line loss rate benchmark values ​​of various feeders are obtained according to the feeder line loss rate. The difference between the line loss rate benchmark values ​​lies in the line loss rate values ​​of individual feeders. As a standard for judging whether the feeder line loss rate is abnormally high, the specific method is as follows: In the formula, Indicates Determination of the calculation results of feeder line loss rate; Indicates Class The calculation results of line loss rate of feeder lines are: Indicates Standard value of the calculation result of the class line loss rate; The fourth module includes a power grid loss metering module and a user loss metering module, wherein the power grid loss metering module further obtains power grid loss information by statistically calculating power losses and losses in the transmission, substation, and distribution box links during the transmission of electric energy from the power plant; the user loss metering module obtains power grid losses output by the distribution box, and then counts the user's electricity consumption and the power loss generated by the user, as well as the power loss caused by different working environments.

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