CN112258030A - Site selection method and system for intelligent switching station of power distribution network and information data processing terminal - Google Patents
Site selection method and system for intelligent switching station of power distribution network and information data processing terminal Download PDFInfo
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Abstract
The invention discloses a site selection method and system for an intelligent switching station of a power distribution network and an information data processing terminal, belonging to the technical field of power distribution networks and comprising the following steps: firstly, compiling a distribution network block forming algorithm; defining element sets with the same distribution network load loss as power supply blocks, analyzing the distribution network in the form of the power supply blocks, and compiling a distribution network block forming algorithm; secondly, grading the load importance degree of a power supply block of the power distribution network; counting the load size of the block by using a user electricity utilization information acquisition system, and grading according to the load size degree to form a heat distribution diagram of the load importance degree of the power supply block; thirdly, counting the elements in each power supply block, evaluating a set of possible element failure events one by using a FEMA method, determining the influence of the set on the power supply block, forming a failure mode consequence analysis table and further obtaining a required system reliability index; and fourthly, determining the site selection position of the intelligent switching station according to the target of reducing the expected value of the power shortage of the system.
Description
Technical Field
The invention belongs to the technical field of power distribution networks, and particularly relates to a site selection method and system for an intelligent switching station of a power distribution network and an information data processing terminal.
Background
At present, the construction of the power distribution network in China has certain hysteresis conditions, and the main performance is that many overhead lines, the automation level is not high, the distribution network structure is unreasonable and a series of problems are presented. Under the condition that the power distribution network breaks down, the 10kV switching-off is directly caused by the master switch, large-area power failure is caused, not only is the production and the living of enterprises and residents badly influenced, but also the power selling quantity of the power grid enterprises is lost, and the economic benefit of the enterprises is reduced. The intelligent switching station has the functions of remote signaling, remote measuring and remote control, can realize the functions of automatically acquiring the operation data of equipment, remotely controlling a switch and the like, and when a fault occurs in the power distribution network, the intelligent switch can automatically alarm and quickly isolate a fault area by using an automatic means, so that the aims of reducing the fault influence range and reducing the load loss of the power distribution network are fulfilled. However, the intelligent switch station is expensive, and the modification project can also cause power failure of the distribution network line, so that the modification project cannot be carried out by a large axe, and needs to be propelled gradually. Therefore, under the condition of limited resources, the position of the intelligent switching station is reasonably selected, so that the power supply reliability of the power distribution network is improved to the maximum extent, and the method has important research significance.
Disclosure of Invention
The invention provides a site selection method for an intelligent switching station of a power distribution network, aiming at the conditions that the transformation project of the intelligent switching station of the power distribution network is carried out by experience, the related data analysis support is lacked, and the advantages of the intelligent switching station cannot be exerted to the maximum extent, and the site selection method for the intelligent switching station of the power distribution network is provided.
The invention aims to provide a site selection method for an intelligent switching station of a power distribution network, which comprises the following steps:
s1, compiling a distribution network block forming algorithm; defining element sets with the same distribution network load loss on a distribution network as power supply blocks, analyzing the distribution network in the form of the power supply blocks, and further compiling a distribution network block forming algorithm;
s2, grading the load importance of the power supply block of the power distribution network; counting the load size of the block by using a user electricity utilization information acquisition system, and grading according to the load size degree to finally form a heat distribution diagram of the load importance degree of the power supply block;
s3, counting the elements in each power supply block, evaluating a set of possible element failure events one by using a FEMA method, determining the influence of the set on the power supply block, forming a failure mode consequence analysis table and further obtaining a required system reliability index;
and S4, determining the site selection position of the intelligent switch station according to the target of reducing the expected value of the power shortage of the system.
Preferably, in S3, the expected power shortage of each power supply block is used as a standard.
Preferably, the S1 is specifically: analyzing the power distribution network by using the adjacent matrix among the nodes;
firstly, dividing nodes in a power distribution network into two major classes, wherein one class is a father node, and the other class is a child node; the definition of parent and child nodes is as follows: node A, B is two nodes directly connected in a power distribution network, and if active power flows from node a to node B, node a is called a parent node of node B, and node B is a child node of node a; since the 10kV distribution network is in a tree-shaped operation mode with a closed-loop design, it is determined that any node has one and only one parent node, but each node may have a plurality of child nodes.
The adjacency matrix L is used for describing the connection relationship between the nodes of the power distribution network, and is recorded as L ═ L (L)ij)n×n。
In the above formula L ij0 indicates that there is no join relationship between nodes i and j, i.e. there is no parent-child relationship; l isij1 indicates that there is a parent-child relationship between nodes i and j, and a switching device is arranged at i, i.e. an open circuit is arranged at iA disconnector or isolating switch or fuse; l isijAnd 2, showing that the nodes i and j have a parent-child relationship, but no switching device is configured at the position i, and obtaining the adjacent matrix of the distribution network system according to the steps.
Preferably, in S2, the user electricity information collection system collects and analyzes the electricity data of the distribution transformer and the end user to realize electricity monitoring, ladder pricing, load management, and line loss analysis, and finally, automatic meter reading, off-peak electricity utilization, electricity inspection, load prediction, and electricity cost saving are achieved.
Preferably, the calculation steps of the FEMA method are as follows:
enumerating the outage of a single element, and determining the contribution of the outage to the outage rate and the outage time of each load point in consideration of the processes of switching on and off, isolating and recovering power supply of a switch;
respectively analyzing the outage rate and the power failure time list of each load point after each element is independently shut down, and obtaining the outage rate and the power failure time index of each load point after the lists are summarized;
judging whether the power failure occurs at the load point according to the analysis result of the step I, and if the power failure occurs, calculating the expected value lambda of the corresponding power failure rateLPExpected value r of power supply recovery timeLPAnd expected value u of power failure timeLP；
The expected value calculation formula of the outage rate of the power supply block is as follows:
equipment failure outage rate;
the expected value calculation formula of the power failure time of the power supply block fault is as follows: the product of the equipment failure outage rate and the power supply block load restoration power supply time after the failure is equal to the equipment failure outage rate x;
thirdly, calculating a system reliability index based on the reliability indexes of the load points;
the average power supply reliability expected value calculation formula of the power supply blocks is as follows: ASAILP＝(1-uLP/8760)
The power shortage expected value calculation formula of the distribution network system is as follows: EENSLPSigma-delta power supply regionBlock blackout time expected value x load capacity of distribution network line.
The second purpose of the invention is to provide a site selection system of the intelligent switching station of the power distribution network; at least comprises the following steps:
the algorithm generation module is used for compiling a distribution network block forming algorithm; defining element sets with the same distribution network load loss on a distribution network as power supply blocks, analyzing the distribution network in the form of the power supply blocks, and further compiling a distribution network block forming algorithm;
the grading module is used for grading the load importance degree of a power supply block of the power distribution network; counting the load size of the block by using a user electricity utilization information acquisition system, and grading according to the load size degree to finally form a heat distribution diagram of the load importance degree of the power supply block;
the statistical module is used for carrying out statistics on elements in each power supply block, evaluating a possibly-occurring element failure event set one by using a FEMA (field emission MA) method, determining the influence of the element failure event set on the power supply blocks, forming a fault mode consequence analysis table and further obtaining a required system reliability index;
and the site selection module is used for determining the site selection position of the intelligent switching station according to the target of reducing the expected value of the power shortage of the system.
The third purpose of the invention is to provide an information data processing terminal for realizing the site selection method of the intelligent switching station of the power distribution network.
A fourth object of the present invention is to provide a computer-readable storage medium, which includes instructions that, when executed on a computer, cause the computer to execute the above-mentioned method for locating an intelligent switching station of a power distribution network.
The invention has the advantages and positive effects that:
the method analyzes indexes such as the reliability of the power supply block by taking the defect amount of the system as a target, quantifies the project of selecting the intelligent switching station for transformation by experience in the past into a site selection strategy with specific indexes and data support, and thus, the purpose of improving the power supply reliability of the power distribution network to the maximum extent under the condition of limited resources is achieved.
The method and the system can quickly evaluate the influence of the intelligent switching stations at different positions on the system power supply reliability, so that the conventional situation of transformation through experience is quantified to be transformed according to the indexes of the system defect amount, the transformation of the intelligent switching stations has a theoretical support basis, and the purpose of improving the power supply reliability of the power distribution network to the maximum extent is achieved under the condition that the working plan is limited or the fund amount is limited.
Drawings
FIG. 1 is a flow chart of a preferred embodiment of the present invention;
FIG. 2 is a simplified diagram of a distribution network in east Li, Tianjin;
FIG. 3 is a distribution system adjacency matrix formed from parent-child nodes;
fig. 4 is a distribution network power supply block distribution diagram obtained through calculation of a distribution network power supply block algorithm;
FIG. 5 is a thermal distribution diagram of power block load importance.
Detailed Description
In order to further understand the contents, features and effects of the present invention, the following embodiments are illustrated and described in detail with reference to the accompanying drawings:
zero trust is a new network security model, does not distinguish internal and external networks, and all entities need authentication and authorization to access resources, so that the zero trust method can be used for networks with increasingly fuzzy protection boundaries.
A site selection method for an intelligent switching station of a power distribution network comprises the following steps:
step 1: compiling a distribution network block forming algorithm: the network structure of the power distribution network has a plurality of branches, switches and isolation switches, and due to the existence of the devices, the faults of some elements on the power distribution network have the same influence on the load loss of the power distribution network, and a set of the elements is defined as a power supply block. The distribution network is analyzed in the form of the power supply block, so that the analysis time of the distribution network can be shortened, and the analysis efficiency is improved.
Step 2: grading the importance degree of the load of a power supply block of the power distribution network: and (4) counting the load size of the block by using a user electricity information acquisition system, and grading according to the load size degree to finally form a heat distribution diagram of the load importance degree of the power supply block.
And step 3: the method comprises the steps of counting elements in each power supply block, evaluating a set of possible element failure events one by using a FEMA method, determining the influence of the set on the power supply block, forming a fault mode consequence analysis table, and further obtaining a required system reliability index.
And 4, step 4: and determining the site selection position of the intelligent switching station according to the target of reducing the expected value of the power shortage of the system.
For the foregoing power distribution network intelligent switching station location strategy, particularly, the step 1 specifically refers to: and analyzing the power distribution network by utilizing the adjacent matrix among the nodes.
Firstly, nodes in a power distribution network are divided into two categories, wherein one category is a father node, and the other category is a child node. The definition of parent and child nodes is as follows: node A, B is two nodes directly connected in a power distribution network, and if active power flows from node a to node B, node a is called a parent node of node B, and node B is called a child node of node a. Since the 10kV distribution network is in a tree-shaped operation mode of a closed-loop design, it is determined that any node has one and only one father node (except a substation bus node), but each node may have a plurality of child nodes.
The adjacency matrix L is used for describing the connection relationship between the nodes of the power distribution network, and is recorded as L ═ L (L)ij)n×n。
In the above formula L ij0 indicates that there is no join relationship between nodes i and j, i.e. there is no parent-child relationship; l isij1 indicates that nodes i and j have a parent-child relationship, and a switching device is configured at i, namely a breaker or a disconnector or a fuse is configured at i; l isijAnd 2, showing that the nodes i and j have a parent-child relationship, but no switching device is configured at the position i, and obtaining the adjacent matrix of the distribution network system according to the steps.
For the foregoing power distribution network intelligent switching station site selection strategy, particularly, in the step 2, the "user power consumption information acquisition system" is to realize power consumption monitoring, step pricing, load management and line loss analysis by acquiring and analyzing power consumption data of a distribution transformer and a terminal user, and finally achieve the purposes of automatic meter reading, off-peak power consumption, power consumption inspection (electricity stealing prevention), load prediction, power consumption cost saving and the like.
For the foregoing intelligent switching station location strategy of the power distribution network, particularly, the FMEA method in step 3 belongs to an analytic method, and is one of the most common methods for evaluating reliability of the power distribution network. The method adopts a set of component failure events which possibly occur to be evaluated one by one and determines the influence of the component failure events on a load point, a failure mode consequence analysis table is formed, and then the required system reliability index is obtained.
The calculation procedure of the FEMA method is as follows:
enumerating the shutdown of a single element, and determining the contribution of the shutdown to the outage rate and the outage time of each load point in consideration of the processes of switching on and off, isolating and recovering power supply of a switch.
Secondly, respectively analyzing the outage rate and the power failure time list of each load point after each element is individually shut down, and obtaining the outage rate, the power failure time and other indexes of each load point after the lists are summarized.
Judging whether the power failure occurs at the load point according to the analysis result of the step I, and if the power failure occurs, calculating the expected value lambda of the corresponding power failure rateLPExpected values r of (time/year) and power supply recovery time (power failure duration)LP(h/time) and expected value u of power failure timeLP(h/year).
The expected value calculation formula of the outage rate of the power supply block is as follows:
equipment failure outage rate
The expected value calculation formula of the power failure time of the power supply block fault is as follows: equipment failure outage rate x after failure power supply block load restoration power supply time ═ equipment failure outage rate x (failure location isolation time + failure outage tie-in switch (or upstream switch) switching time)
And thirdly, calculating the reliability index of the system based on the reliability index of each load point.
The average power supply reliability expected value calculation formula of the power supply blocks is as follows: ASAILP＝(1-uLP/8760)
The power shortage expected value calculation formula of the distribution network system is as follows: EENSLPExpected power failure time value of sigma power supply block multiplied by load capacity of distribution network line
As shown in fig. 1, a parent node and a child node in a power distribution network are defined and arranged to form an adjacency matrix L, and a method for forming the adjacency matrix L is as follows:
firstly, only the head end of the branch i-j is provided with a switch device, then Lij＝1，Lji＝2。
② only the tail end of the branch i-j is equipped with a switch device, then Lij＝2，Lji＝1。
③ both ends of branch i-j are provided with switch equipment, then Lij＝Lji＝1。
Fourthly, no switch equipment is arranged at both ends of the branch i-j, then Lij＝Lji＝2。
Fig. 2 is a simplified diagram of a distribution network line in the east-li-city of tianjin, in which the solid line represents an overhead line and the dotted line represents a cable line, and the adjacency matrix of the system of fig. 2 formed according to the above analysis method is shown in fig. 3.
Using the adjacency matrix shown in fig. 3, the power distribution grid system is divided into a number of power supply blocks according to the following algorithm.
Let row i equal to 0, column j equal to 0, and block number k equal to 1;
search for the 1 st element of row i, let LijPressing the branch into a current block k, and turning to the third step; if the row has no 1 element, i is equal to i +1, j is equal to 0, and then the row is rotated;
if L isji1, indicating that the block is formed, and enabling j to be j +1 and k to be k + 1; if L isjiPressing the branch into the current block, continuing to search the jth row 2 element, recording the column number of the 2 element, and after accessing the jth row, accessing the row with the column number by the same method until the block is formed, and turning to (j + 1) and (k + 1). Where k is the number of blocks of the current evaluation system.If the number of the system elements is l, k is less than or equal to l. In general, k is much less than l.
By using the above method for searching, the system of fig. 2 can be divided into the power supply blocks shown in fig. 4, and after the operation is completed, there are 10 power supply blocks, wherein there are 6 power supply blocks with loads.
The power consumption data of all users in the distribution network line are collected through a user power consumption information collection system, a power supply block (II) is obtained through calculation, the active power size is 0.414MW, the active power size of the power supply block (III) is 0.094MW, the active power size of the power supply block (III) is 0.218MW, the active power size of the power supply block (III) is 0.072MW, the active power size of the power supply block (N) is 0.35MW, the active power size of the power supply block (III) is 0.186MW, and finally a power supply block load important degree thermal distribution graph is formed as shown in fig. 5.
And calculating the fault outage rates of the power supply blocks, wherein the fault outage rate of the bare conductor is 12.96 times/(100 km.year), the fault outage rate of the cable line is 1.4 times/(100 km.year), the fault outage rate of the distribution transformer is 0.7 times/(100 machines.year), and the fault rate of the disconnecting link is 1.94 times/(100 machines.year).
Calculating the expected power failure value of each power supply block according to the data, and obtaining that the equipment failure outage rate of the power supply block is 0.6962 (times/year), the failure outage rate of the power supply block is 0.00714 (times/year), the failure outage rate of the power supply block is 0.014 (times/year), the failure outage rate of the power supply block is 0.0862 (times/year), the failure outage rate of the power supply block is 0.59638 (times/year), and the failure outage rate of the power supply block is 0.0147 (times/year).
The expected value of the power failure time of each power supply block is the sum of the influences of power failure of each power supply block caused by each facility, wherein the average fault repair time of an overhead line is 3.44h, the average fault repair time of a cable is 48h, the average fault repair time of a distribution transformer is 4.87h, the average fault repair time of a disconnecting link is 1.83h, the average fault positioning time of a distribution system is 1.83h, and the switching time of a tie switch is 0.54 h.
Therefore, the expected value of the power failure time of the power supply block II is 3.69h, the expected value of the power failure time of the power supply block III is 0.08h, the expected value of the power failure time of the power supply block III is 0.03h, the expected value of the power failure time of the power supply block III is 0.165h, the expected value of the power failure time of the power supply block IV is 1.98h, and the expected value of the power failure time of the power supply block III is 0.059 h.
Calculating the expected value of the power shortage when the system is not provided with the intelligent switching station to be 8 MW/year;
the intelligent switching station has a protection function, can quickly remove a fault line, isolate fault points and ensure normal power supply of a non-fault line.
The expected value of the system power shortage of the intelligent switch station at different positions can be calculated, when the intelligent switch station is selected to be DLK-646, the value of the system power shortage is 3.43 MW/year, when the intelligent switch station is selected to be DLK-229, the expected value of the system power shortage is 3.37MW, when the intelligent switch station is selected to be DLK-230, the expected value of the system power shortage is 3.90 MW/year, and when the intelligent switch station is selected to be DLK-276, the expected value of the system power shortage is 6.93 MW/year.
And finally, determining the optimal position of the intelligent switching station as the DLK-229 switching station according to the principle that the power shortage of the system is minimum.
An address selection system of a power distribution network intelligent switching station; at least comprises the following steps:
the algorithm generation module is used for compiling a distribution network block forming algorithm; defining element sets with the same distribution network load loss on a distribution network as power supply blocks, analyzing the distribution network in the form of the power supply blocks, and further compiling a distribution network block forming algorithm;
the grading module is used for grading the load importance degree of a power supply block of the power distribution network; counting the load size of the block by using a user electricity utilization information acquisition system, and grading according to the load size degree to finally form a heat distribution diagram of the load importance degree of the power supply block;
the statistical module is used for carrying out statistics on elements in each power supply block, evaluating a possibly-occurring element failure event set one by using a FEMA (field emission MA) method, determining the influence of the element failure event set on the power supply blocks, forming a fault mode consequence analysis table and further obtaining a required system reliability index;
and the site selection module is used for determining the site selection position of the intelligent switching station according to the target of reducing the expected value of the power shortage of the system.
An information data processing terminal for realizing a site selection method of an intelligent switching station of a power distribution network comprises the following steps:
step 1: compiling a distribution network block forming algorithm: the network structure of the power distribution network has a plurality of branches, switches and isolation switches, and due to the existence of the devices, the faults of some elements on the power distribution network have the same influence on the load loss of the power distribution network, and a set of the elements is defined as a power supply block. The distribution network is analyzed in the form of the power supply block, so that the analysis time of the distribution network can be shortened, and the analysis efficiency is improved.
Step 2: grading the importance degree of the load of a power supply block of the power distribution network: and (4) counting the load size of the block by using a user electricity information acquisition system, and grading according to the load size degree to finally form a heat distribution diagram of the load importance degree of the power supply block.
And step 3: the method comprises the steps of counting elements in each power supply block, evaluating a set of possible element failure events one by using a FEMA method, determining the influence of the set on the power supply block, forming a fault mode consequence analysis table, and further obtaining a required system reliability index.
And 4, step 4: and determining the site selection position of the intelligent switching station according to the target of reducing the expected value of the power shortage of the system.
A computer-readable storage medium comprising instructions that, when executed on a computer, cause the computer to perform a method for locating a power distribution network intelligent switching station, the method for locating a power distribution network intelligent switching station comprising:
step 1: compiling a distribution network block forming algorithm: the network structure of the power distribution network has a plurality of branches, switches and isolation switches, and due to the existence of the devices, the faults of some elements on the power distribution network have the same influence on the load loss of the power distribution network, and a set of the elements is defined as a power supply block. The distribution network is analyzed in the form of the power supply block, so that the analysis time of the distribution network can be shortened, and the analysis efficiency is improved.
Step 2: grading the importance degree of the load of a power supply block of the power distribution network: and (4) counting the load size of the block by using a user electricity information acquisition system, and grading according to the load size degree to finally form a heat distribution diagram of the load importance degree of the power supply block.
And step 3: the method comprises the steps of counting elements in each power supply block, evaluating a set of possible element failure events one by using a FEMA method, determining the influence of the set on the power supply block, forming a fault mode consequence analysis table, and further obtaining a required system reliability index.
And 4, step 4: and determining the site selection position of the intelligent switching station according to the target of reducing the expected value of the power shortage of the system.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When used in whole or in part, can be implemented in a computer program product that includes one or more computer instructions. When loaded or executed on a computer, cause the flow or functions according to embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL), or wireless (e.g., infrared, wireless, microwave, etc.)). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that includes one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
The above-mentioned embodiments are only for illustrating the technical ideas and features of the present invention, and the purpose thereof is to enable those skilled in the art to understand the contents of the present invention and to carry out the same, and the present invention shall not be limited to the embodiments, i.e. the equivalent changes or modifications made within the spirit of the present invention shall fall within the scope of the present invention.
Claims (8)
1. A site selection method for an intelligent switching station of a power distribution network; characterized in that it at least comprises:
s1, compiling a distribution network block forming algorithm; defining element sets with the same distribution network load loss on a distribution network as power supply blocks, analyzing the distribution network in the form of the power supply blocks, and further compiling a distribution network block forming algorithm;
s2, grading the load importance of the power supply block of the power distribution network; counting the load size of the block by using a user electricity utilization information acquisition system, and grading according to the load size degree to finally form a heat distribution diagram of the load importance degree of the power supply block;
s3, counting the elements in each power supply block, evaluating a set of possible element failure events one by using a FEMA method, determining the influence of the set on the power supply block, forming a failure mode consequence analysis table and further obtaining a required system reliability index;
and S4, determining the site selection position of the intelligent switch station according to the target of reducing the expected value of the power shortage of the system.
2. The method of claim 1, wherein in step S3, the expected power shortage of each power supply block is used as a criterion.
3. The site selection method for the intelligent switching station of the power distribution network according to claim 1, wherein the S1 specifically comprises: analyzing the power distribution network by using the adjacent matrix among the nodes;
firstly, dividing nodes in a power distribution network into two major classes, wherein one class is a father node, and the other class is a child node; the definition of parent and child nodes is as follows: node A, B is two nodes directly connected in a power distribution network, and if active power flows from node a to node B, node a is called a parent node of node B, and node B is a child node of node a; since the 10kV distribution network is in a tree-shaped operation mode with a closed-loop design, it is determined that any node has one and only one father node, but each node may have a plurality of child nodes;
the adjacency matrix L is used for describing the connection relationship between the nodes of the power distribution network, and is recorded as L ═ L (L)ij)n×n；
In the above formula Lij0 indicates that there is no join relationship between nodes i and j, i.e. there is no parent-child relationship; l isij1 indicates that nodes i and j have a parent-child relationship, and a switching device is configured at i, namely a breaker or a disconnector or a fuse is configured at i; l isijAnd 2, showing that the nodes i and j have a parent-child relationship, but no switching device is configured at the position i, and obtaining the adjacent matrix of the distribution network system according to the steps.
4. The site selection method for the intelligent switching station of the power distribution network according to claim 1, wherein in S2, the user power consumption information acquisition system acquires and analyzes power consumption data of the distribution transformer and the end user to realize power consumption monitoring, implementation of ladder pricing, load management and line loss analysis, and finally achieves automatic meter reading, off-peak power consumption, power consumption inspection, load prediction and power consumption cost saving.
5. The method for locating the intelligent switching stations of the power distribution network according to claim 1, wherein the FEMA method comprises the following calculation steps:
enumerating the outage of a single element, and determining the contribution of the outage to the outage rate and the outage time of each load point in consideration of the processes of switching on and off, isolating and recovering power supply of a switch;
respectively analyzing the outage rate and the power failure time list of each load point after each element is independently shut down, and obtaining the outage rate and the power failure time index of each load point after the lists are summarized;
judging whether the power failure occurs at the load point according to the analysis result of the step I, and if the power failure occurs, calculating the expected value lambda of the corresponding power failure rateLPExpected value r of power supply recovery timeLPAnd expected value u of power failure timeLP；
The expected value calculation formula of the outage rate of the power supply block is as follows:
equipment failure outage rate;
the expected value calculation formula of the power failure time of the power supply block fault is as follows: the product of the equipment failure outage rate and the power supply block load restoration power supply time after the failure is equal to the equipment failure outage rate x;
thirdly, calculating a system reliability index based on the reliability indexes of the load points;
the average power supply reliability expected value calculation formula of the power supply blocks is as follows: ASAILP＝(1-uLP/8760)
The power shortage expected value calculation formula of the distribution network system is as follows: EENSLPThe expected value of the power failure time of the sigma power supply block is multiplied by the load capacity of the distribution network line.
6. An address selection system of a power distribution network intelligent switching station; characterized in that it at least comprises:
the algorithm generation module is used for compiling a distribution network block forming algorithm; defining element sets with the same distribution network load loss on a distribution network as power supply blocks, analyzing the distribution network in the form of the power supply blocks, and further compiling a distribution network block forming algorithm;
the grading module is used for grading the load importance degree of a power supply block of the power distribution network; counting the load size of the block by using a user electricity utilization information acquisition system, and grading according to the load size degree to finally form a heat distribution diagram of the load importance degree of the power supply block;
the statistical module is used for carrying out statistics on elements in each power supply block, evaluating a possibly-occurring element failure event set one by using a FEMA (field emission MA) method, determining the influence of the element failure event set on the power supply blocks, forming a fault mode consequence analysis table and further obtaining a required system reliability index;
and the site selection module is used for determining the site selection position of the intelligent switching station according to the target of reducing the expected value of the power shortage of the system.
7. An information data processing terminal for implementing the site selection method of the intelligent switching station of the power distribution network according to any one of claims 1 to 5.
8. A computer-readable storage medium comprising instructions that, when executed on a computer, cause the computer to perform the method of addressing a distribution grid intelligent switching station of any of claims 1-5.
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