A distribution network vulnerability assessment method based on conflict evidence modified DS method

Abstract

The present invention discloses a distribution network vulnerability assessment method based on a conflict evidence-corrected DS method, comprising: S1, calculating the failure rate of a distribution network line under extreme weather conditions according to a first model to obtain line failure rate data; the first model comprises a two-state Markov model; obtaining line unavailability of the distribution network according to the line failure rate data; S2, obtaining node strength according to line unavailability; obtaining a state vulnerability index according to the node strength; obtaining an improved line betweenness according to line unavailability; obtaining a structural vulnerability index according to the improved line betweenness; S3, normalizing the state vulnerability index and the structural vulnerability index to obtain a first index and a second index; fusing the first index and the second index through a conflict evidence-corrected DS method to obtain a third index; S4, performing vulnerability assessment on the distribution network according to the third index to obtain a first result; a larger value of the first result indicates a higher degree of vulnerability of the distribution network.

Description

Technical Field

[0001] The present invention relates to the field of distribution network vulnerability technical assessment, and in particular to a distribution network vulnerability assessment method based on a conflict evidence modified DS method. Background Art

[0002] As modern society becomes more dependent on electricity, the stable operation of distribution networks has become particularly important. The vulnerability of distribution networks has gradually become a key issue, mainly reflected in extreme weather and equipment aging. The impact of extreme weather such as typhoons, blizzards, and high temperatures on distribution networks is obvious. These disasters can cause large-scale power outages and affect the normal operation of society. In addition, with the long-term use of distribution network equipment, the problem of equipment aging has become more prominent, resulting in an increase in failure rates and maintenance costs. These factors work together to make the vulnerability of distribution networks increasingly prominent.

[0003] The vulnerability assessment of distribution networks usually involves multiple indicators, but these indicators often have different units, dimensions and properties, making it difficult to directly integrate them into the same model for assessment. At the same time, many assessment methods treat each indicator as an independent variable, ignoring the interrelated influences between indicators. Traditional assessment methods are often based on static data or single-point data, which makes it difficult to reflect the changes in the vulnerability of distribution networks in different periods and under different load conditions. Failure to consider the dynamic changes of distribution networks will lead to a lack of comprehensiveness in the assessment results. In addition, existing technologies usually rely on expert judgment or empirical data, and this subjectivity may lead to deviations in the assessment results. That is, the vulnerability methods of distribution networks in existing technologies are often not accurate enough.

[0004] Therefore, a new technical solution is urgently needed to solve the technical problem of how to accurately assess the vulnerability of the distribution network. Summary of the invention

[0005] The present invention provides a distribution network vulnerability assessment method based on the conflict evidence modified DS method, which is used to solve the technical problem of how to accurately assess the vulnerability of the distribution network.

[0006] To achieve the above object, the present invention provides a distribution network vulnerability assessment method based on conflict evidence modified DS method, comprising the following steps:

[0007] S1. Calculate the failure rate of the distribution network line under extreme weather conditions according to the first model to obtain line failure rate data; the first model includes a two-state Markov model; obtain the line unavailability of the distribution network according to the line failure rate data.

[0008] S2. Obtain node strength based on line unavailability; obtain state vulnerability index based on node strength; obtain improved line betweenness based on line unavailability; obtain structural vulnerability index based on improved line betweenness.

[0009] S3. Normalize the state vulnerability index and the structural vulnerability index to obtain the first index and the second index; merge the first index and the second index through the conflict evidence corrected DS method to obtain the third index.

[0010] S4. Evaluate the vulnerability of the distribution network according to the third indicator to obtain a first result; a larger value of the first result indicates a higher degree of vulnerability of the distribution network.

[0011] Preferably, calculating the failure rate of the distribution network line under extreme weather conditions according to the first model to obtain line failure rate data includes:

[0012] A first model is constructed, and the failure rate of the distribution network line under extreme weather conditions is calculated according to the first model. The first model includes:

[0013] in, Indicates the failure rate of the distribution network line under extreme weather conditions, that is, the line failure rate data; Indicates the rate of transition from normal weather to extreme weather; Indicates the failure rate in normal weather; It indicates the rate of transition from extreme weather to normal weather; Indicates the failure rate during extreme weather; Indicates the maintenance rate in normal weather; Indicates the maintenance rate during extreme weather.

[0014] Preferably, obtaining the line unavailability of the distribution network according to the line failure rate data includes:

[0015] Calculating Line Unavailability :

[0016] in, Indicates The percentage of lines in all lines; Indicates Repair rate of the line.

[0017] Preferably, obtaining the node strength according to the line unavailability includes:

[0018] Set the line weight of each line in the distribution network according to the module value of the impedance value , the corrected line weight is obtained through line unavailability , and then get the node strength :

[0019] in, Indicates The modulus of the line impedance; Indicates the total number of lines; Indicates The modulus of the line impedance; Indicates Unavailability of lines; Indicates Unavailability of lines; Indicates the number of lines connected to a node; Indicates the node strength.

[0020] Preferably, the state vulnerability index obtained according to the node strength includes:

[0021] According to the node Voltage over-limit probability and nodes Voltage over-limit damage degree Get Node Voltage over-limit indicator ;according to Combined node strength Get state vulnerability index ,include:

[0022] in, Representation Node Voltage; Indicates the allowable voltage deviation of the distribution network.

[0023] Preferably, obtaining an improved line betweenness according to line unavailability; and obtaining a structural vulnerability index according to the improved line betweenness include:

[0024] in, represents the improved line betweenness; Indicates the weights of different types of load nodes; Indicates the lines from the source node to each load node The number of times; Indicates the total number of lines in the distribution network; Indicates the risk index of line power flow exceeding the limit; node Indicates the total number of nodes; Represents a node; and Respectively represent nodes Active and reactive output; Representation Node With Node The equivalent impedance between Representation Node With Node The equivalent impedance between Representation Node With Node The equivalent impedance between Represents the structural vulnerability index.

[0025] Preferably, the state vulnerability index and the structural vulnerability index are normalized to obtain the first index and the second index, which include:

[0026] Normalization processing includes:

[0027] in, Represents the result after normalization; Indicates the result before normalization; Indicates the maximum value within the indicator; Indicates the minimum value within the indicator;

[0028] According to the normalization process, the state vulnerability index and the structural vulnerability index are normalized respectively to obtain the first index and the second index.

[0029] Preferably, the first indicator and the second indicator are merged by the conflict evidence modified DS method to obtain a third indicator including:

[0030] Define a set Θ,2 consisting of mutually exclusive propositions Θ is the set of all subsets of set Θ. The basic probability distribution function m in set Θ is called mass function, including:

[0031] Among them, if ,and , then A is the focal element; Reflecting the evidence on the proposition A the level of support; is an empty set, i.e. an impossible proposition;

[0032] Since the conflict between the distribution network state vulnerability index and the structural vulnerability index is serious, the conflict evidence correction DS method is used to merge the first index and the second index. The conflict evidence correction includes:

[0033] in, represents mutually exclusive propositions, with a total of m propositions; n represents that each proposition has n sets of evidence; I to indicate evidence; Represents the average basic probability assignment of n sets of evidence, reflecting the impact of all evidence on the proposition The average support level of Represents the basic probability assignment of n sets of evidence; Indicates I The distance between the basic probability distribution of each body of evidence and the average basic probability distribution; Indicates the weight of each body of evidence; Indicates conflicting evidence I Correction factor of represents the basic probability distribution function of each proposition after correction; represents the basic probability distribution function of each proposition before modification; represents the basic probability distribution function of the modified set; represents the basic probability distribution function of the set before correction;

[0034] After the conflicting evidence is corrected, the first indicator and the second indicator are merged to obtain the third indicator, including:

[0035] in, Indicates the third indicator; and A I Respectively n The basic trust allocation function and focal element corresponding to the group evidence respectively.

[0036] The present invention has the following beneficial effects:

[0037] The distribution network vulnerability assessment method based on the conflict evidence modified DS method of the present invention integrates the state vulnerability index and the structural vulnerability index based on the conflict evidence modified DS method, avoiding the mutual influence relationship between the indicators, making the assessment process of the method of the present invention more accurate. The conflict evidence modified DS method used in the present invention is modified for conflict evidence, not for all data, which can reduce the amount of calculation and ensure the authenticity and validity of the data in the method. The method of the present invention takes into account both the state vulnerability index and the structural vulnerability index, that is, it takes into account both static data and dynamic data, avoiding the lack of comprehensiveness of the assessment results. By identifying in advance the potential threats to the power system from more frequent and more severe extreme climate events in the future, distributed power sources and energy storage are given priority in more vulnerable or potentially high-risk areas to avoid power outages, thereby improving the reliability of the distribution network.

[0038] In addition to the above-described purposes, features and advantages, the present invention has other purposes, features and advantages. The present invention will be further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The drawings constituting a part of this application are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0040] Figure 1 It is a flow chart of a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0041] The embodiments of the present invention are described in detail below with reference to the accompanying drawings, but the present invention can be implemented in many different ways as defined and covered by the claims.

[0042] See also Figure 1 In a preferred embodiment of the present invention, a distribution network vulnerability assessment method based on conflict evidence modified DS method is provided, comprising the following steps:

[0043] S1. Calculate the failure rate of the distribution network line under extreme weather conditions according to the first model to obtain line failure rate data; the first model includes a two-state Markov model; obtain the line unavailability of the distribution network according to the line failure rate data.

[0044] In a preferred embodiment of the present invention, the failure rate of the distribution network line under extreme weather conditions is calculated according to the first model, and the line failure rate data obtained includes:

[0045] A first model is constructed, and the failure rate of the distribution network line under extreme weather conditions is calculated according to the first model. The first model includes:

[0046] in, Indicates the failure rate of distribution network lines under extreme weather conditions; Indicates the rate of transition from normal weather to extreme weather; Indicates the failure rate in normal weather; It indicates the rate of transition from extreme weather to normal weather; Indicates the failure rate during extreme weather; Indicates the maintenance rate in normal weather; Indicates the maintenance rate during extreme weather.

[0047] In a preferred embodiment of the present invention, obtaining the line unavailability of the distribution network according to the line failure rate data includes:

[0048] Calculating Line Unavailability :

[0049] in, Indicates The percentage of lines in all lines; Indicates Repair rate of the line.

[0050] S2. Obtain node strength based on line unavailability; obtain state vulnerability index based on node strength; obtain improved line betweenness based on line unavailability; obtain structural vulnerability index based on improved line betweenness.

[0051] In a preferred embodiment of the present invention, obtaining the node strength according to the line unavailability includes:

[0052] Set the line weight of each line in the distribution network according to the module value of the impedance value , the corrected line weight is obtained through line unavailability , and then get the node strength :

[0053] in, Indicates The modulus of the line impedance; Indicates the total number of lines; Indicates The modulus of the line impedance; Indicates Unavailability of lines; Indicates Unavailability of lines; Indicates the number of lines connected to a node; Indicates the node strength.

[0054] In a preferred embodiment of the present invention, obtaining a state vulnerability index according to node strength includes:

[0055] According to the node Voltage over-limit probability and nodes Voltage over-limit damage degree Get Node Voltage over-limit indicator ;according to Combined node strength Get state vulnerability index ,include:

[0056] in, Representation Node Voltage; Indicates the allowable voltage deviation of the distribution network.

[0057] In a preferred embodiment of the present invention, obtaining an improved line betweenness according to line unavailability; obtaining a structural vulnerability index according to the improved line betweenness includes:

[0058] in, represents the improved line betweenness; Indicates the weights of different types of load nodes; Indicates the lines from the source node to each load node The number of times; Indicates the total number of lines in the distribution network; Indicates the risk index of line power flow exceeding the limit; node Indicates the total number of nodes; Represents a node; and Respectively represent nodes Active and reactive output; Representation Node With Node The equivalent impedance between Representation Node With Node The equivalent impedance between Representation Node With Node The equivalent impedance between Represents the structural vulnerability index.

[0059] S3. Normalize the state vulnerability index and the structural vulnerability index to obtain the first index and the second index; merge the first index and the second index through the conflict evidence corrected DS method to obtain the third index.

[0060] In a preferred embodiment of the present invention, the state vulnerability index and the structural vulnerability index are normalized to obtain the first index and the second index, including:

[0061] Normalization processing includes:

[0062] in, Represents the result after normalization; Indicates the result before normalization; Indicates the maximum value within the indicator; Indicates the minimum value within the indicator;

[0063] According to the normalization process, the state vulnerability index and the structural vulnerability index are normalized respectively to obtain the first index and the second index.

[0064] In a preferred embodiment of the present invention, the first indicator and the second indicator are fused by the DS method corrected by conflicting evidence, and the third indicator includes:

[0065] Define a set Θ,2 consisting of mutually exclusive propositions Θ is the set of all subsets of set Θ. The basic probability distribution function m in set Θ is called mass function, including:

[0066] Among them, if ,and , then A is the focal element; Reflecting the evidence on the proposition A the level of support; is an empty set, i.e. an impossible proposition;

[0067] Since the conflict between the distribution network state vulnerability index and the structural vulnerability index is serious, the conflict evidence correction DS method is used to merge the first index and the second index. The conflict evidence correction includes:

[0068] in, represents mutually exclusive propositions, with a total of m propositions; n represents that each proposition has n sets of evidence; I to indicate evidence; Represents the average basic probability assignment of n sets of evidence, reflecting the impact of all evidence on the proposition The average support level of Represents the basic probability assignment of n sets of evidence; Indicates I The distance between the basic probability distribution of each body of evidence and the average basic probability distribution; Indicates the weight of each body of evidence; Indicates conflicting evidence I Correction factor of represents the basic probability distribution function of each proposition after correction; represents the basic probability distribution function of each proposition before modification; represents the basic probability distribution function of the modified set; represents the basic probability distribution function of the set before correction;

[0069] After the conflicting evidence is corrected, the first indicator and the second indicator are merged to obtain the third indicator, including:

[0070] in, Indicates the third indicator; and A I Respectively n The basic trust allocation function and focal element corresponding to the group evidence respectively.

[0071] S4. Evaluate the vulnerability of the distribution network according to the third indicator to obtain a first result; a larger value of the first result indicates a higher degree of vulnerability of the distribution network.

[0072] In summary, the distribution network vulnerability assessment method based on the conflict evidence modified DS method of the present invention integrates the state vulnerability index and the structural vulnerability index based on the conflict evidence modified DS method, avoids the mutual influence relationship between the indicators, and makes the assessment process of the method of the present invention more accurate. The conflict evidence modified DS method used in the present invention is modified for conflict evidence, not for all data, which can reduce the amount of calculation and ensure the authenticity and validity of the data in the method. The method of the present invention takes into account the state vulnerability index and the structural vulnerability index at the same time, that is, it takes into account static data and dynamic data at the same time, avoiding the lack of comprehensiveness of the assessment results. By identifying in advance the potential threats to the power system from more frequent and more severe extreme climate events in the future, distributed power sources and energy storage are given priority to be used in more vulnerable or potentially high-risk areas to avoid power outages, thereby improving the reliability of the distribution network.

[0073] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A distribution network vulnerability assessment method based on conflict evidence modified DS method, characterized in that: The following steps are involved: S1. Calculate the failure rate of the distribution network line under extreme weather conditions according to a first model to obtain line failure rate data; the first model includes a two-state Markov model; obtain the line unavailability of the distribution network according to the line failure rate data; Calculating the failure rate of the distribution network line under extreme weather conditions according to the first model to obtain line failure rate data includes: The first model is constructed, and the failure rate of the distribution network line under extreme weather is calculated according to the first model, wherein the first model includes: in, Indicates the failure rate of the distribution network line under extreme weather conditions, that is, the line failure rate data; Indicates the rate of transition from normal weather to extreme weather; Indicates the failure rate in normal weather; It indicates the rate of transition from extreme weather to normal weather; Indicates the failure rate during extreme weather; Indicates the maintenance rate in normal weather; Indicates the maintenance rate during extreme weather; S2. Obtaining node strength according to the line unavailability; obtaining a state vulnerability index according to the node strength; obtaining an improved line betweenness according to the line unavailability; and obtaining a structural vulnerability index according to the improved line betweenness; S3, normalizing the state vulnerability index and the structural vulnerability index to obtain a first index and a second index; fusing the first index and the second index by using the conflict evidence corrected DS method to obtain a third index; S4. Evaluate the vulnerability of the distribution network according to the third indicator to obtain a first result; a larger value of the first result indicates a higher degree of vulnerability of the distribution network.

2. The distribution network vulnerability assessment method based on conflict evidence modified DS method according to claim 1 is characterized in that: The line unavailability of the distribution network obtained according to the line failure rate data includes: Calculate the line unavailability : in, Indicates The percentage of lines in all lines; Indicates Repair rate of the line.

3. The distribution network vulnerability assessment method based on conflict evidence modified DS method according to claim 2 is characterized in that: The node strength obtained according to the line unavailability includes: Set the line weight of each line in the distribution network according to the module value of the impedance value , the corrected line weight is obtained by the line unavailability , and then get the node strength : in, Indicates The modulus of the line impedance; Indicates the total number of lines; Indicates The modulus of the line impedance; Indicates Unavailability of lines; Indicates Unavailability of lines; Indicates the number of lines connected to a node; Indicates the node strength.

4. The distribution network vulnerability assessment method based on conflict evidence modified DS method according to claim 3 is characterized in that: The state vulnerability index obtained according to the node strength includes: According to the node Voltage over-limit probability and nodes Voltage over-limit damage degree Get Node Voltage over-limit indicator ;according to Combined with the node strength Get the state vulnerability index ,include: in, Representation Node Voltage; Indicates the allowable voltage deviation of the distribution network.

5. The distribution network vulnerability assessment method based on conflict evidence modified DS method according to claim 4 is characterized in that: An improved line betweenness is obtained according to the line unavailability; The structural vulnerability indexes obtained according to the improved line betweenness include: in, represents the improved line betweenness; Indicates the weights of different types of load nodes; Indicates the lines from the source node to each load node The number of times; Indicates the total number of lines in the distribution network; Indicates the risk index of line power flow exceeding the limit; node Indicates the total number of nodes; Represents a node; and Respectively represent nodes Active and reactive output; Representation Node With Node The equivalent impedance between Representation Node With Node The equivalent impedance between Representation Node With Node The equivalent impedance between It represents the structural vulnerability index.

6. The distribution network vulnerability assessment method based on conflict evidence modified DS method according to claim 5 is characterized in that: The state vulnerability index and the structural vulnerability index are normalized to obtain the first index and the second index, including: The normalization process includes: in, Represents the result after normalization; Indicates the result before normalization; Indicates the maximum value within the indicator; Indicates the minimum value within the indicator; According to the normalization process, the state vulnerability index and the structural vulnerability index are normalized respectively to obtain a first index and a second index.

7. The distribution network vulnerability assessment method based on conflict evidence modified DS method according to claim 6 is characterized in that: The DS method modified by conflict evidence combines the first indicator and the second indicator to obtain a third indicator including: Define a set Θ,2 consisting of mutually exclusive propositions Θ is the set of all subsets of set Θ. The basic probability distribution function m in set Θ is called mass function, including: Among them, if ,and , then A is the focal element; Reflecting the evidence on the proposition A the level of support; is an empty set, i.e. an impossible proposition; Since the conflict between the distribution network state vulnerability index and the structural vulnerability index is serious, the conflict evidence correction DS method is used to merge the first index and the second index. The conflict evidence correction includes: in, represents mutually exclusive propositions, with a total of m propositions; n represents that each proposition has n sets of evidence; I to indicate evidence; Represents the average basic probability assignment of n sets of evidence, reflecting the impact of all evidence on the proposition The average support level of Represents the basic probability assignment of n sets of evidence; Indicates I The distance between the basic probability distribution of each body of evidence and the average basic probability distribution; Indicates the weight of each body of evidence; Representing conflicting evidence I Correction factor of represents the basic probability distribution function of each proposition after correction; represents the basic probability distribution function of each proposition before modification; represents the basic probability distribution function of the modified set; represents the basic probability distribution function of the set before correction; After the conflicting evidence is corrected, the first indicator and the second indicator are merged to obtain a third indicator, including: in, represents the third indicator; and A I Respectively n The basic trust allocation function and focal element corresponding to the group evidence respectively.

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