CN114444886A - Analysis method based power distribution network damage probability evaluation method under typhoon disaster - Google Patents

Analysis method based power distribution network damage probability evaluation method under typhoon disaster Download PDF

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CN114444886A
CN114444886A CN202111650363.6A CN202111650363A CN114444886A CN 114444886 A CN114444886 A CN 114444886A CN 202111650363 A CN202111650363 A CN 202111650363A CN 114444886 A CN114444886 A CN 114444886A
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typhoon
damage
power
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probability
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吴旭光
赵深
宋金根
刘家齐
龚列谦
李更丰
李勇
苏毅芳
别朝红
陈鹏
张鼎茂
郭子黎
孙思源
张理寅
叶宇鑫
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Wenzhou Power Supply Co of State Grid Zhejiang Electric Power Co Ltd
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Wenzhou Power Supply Co of State Grid Zhejiang Electric Power Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/22—Matching criteria, e.g. proximity measures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
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    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract

The invention discloses an analytical method-based method for evaluating damage probability of a power distribution network under typhoon disasters, which overcomes the defects of the prior art and comprises the following steps: step 1, collecting attribute data of each element affected by typhoon in a power distribution network, and determining the fault probability of each element under the condition of typhoon weather; step 2, determining the power consumption damage degree of the user according to the fault probability of each element under the typhoon weather condition, and then determining the damage condition of the system under the typhoon weather condition; and 3, determining power consumption damage level evaluation according to the power consumption damage degree of the user and the damage condition of the system, matching the power consumption damage level with historical data, and calling measures taken by the same power consumption damage level in the historical data to repair the power consumption damage condition of the user.

Description

Analysis method based power distribution network damage probability evaluation method under typhoon disaster
Technical Field
The invention relates to the technical field of power distribution systems, in particular to an evaluation method for the damage probability of a power distribution network under a typhoon disaster based on an analytic method.
Background
The rapid development of social economy makes the dependence of users on electric power continuously strengthened, and a power distribution system is connected with a power transmission system and the users in a power system and plays an important role in the reliability level of the users. Extreme weather has a great impact on power systems, especially widely distributed power distribution systems. Therefore, it is necessary to evaluate and predict the possible damage to the distribution system in typhoon disaster, and provide a theoretical reference for relevant departments and users such as government and power grid company to take countermeasures. At present, no clear and definite method is used for predicting or evaluating the power failure probability and the damage degree of the user and the system according to the typhoon characteristic information, and meanwhile, from the aspect of probability, no complete and systematic index is used for evaluating the damage conditions of the user and the system. Therefore, how to establish a series of indexes based on the probability for evaluating the damage conditions of the user and the power distribution system and how to evaluate the power failure probability of the user and the disaster degree of the power distribution system according to the typhoon information is a problem worthy of research.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provides an analytic method-based method for evaluating the damage probability of a power distribution network under a typhoon disaster.
The purpose of the invention is realized by the following technical scheme:
the method for evaluating the damage probability of the power distribution network under the typhoon disaster based on the analytic method comprises the following steps:
step 1, collecting attribute data of each element affected by typhoon in a power distribution network, and determining the fault probability of each element under the condition of typhoon weather;
step 2, determining the power consumption damage degree of the user according to the fault probability of each element under the typhoon weather condition, and then determining the damage condition of the system under the typhoon weather condition;
and 3, determining power consumption damage level evaluation according to the power consumption damage degree of the user and the damage condition of the system, matching the power consumption damage level with historical data, and calling measures taken by the same power consumption damage level in the historical data to repair the power consumption damage condition of the user.
Preferably, the step 1 specifically comprises the following substeps:
substep 1, collecting fault data of the power distribution network under the influence of historical typhoons, comprises: fault time period, fault element number and historical typhoon characteristic information;
substep 2, collecting characteristic information of the existing typhoon to be evaluated, matching the characteristic information of the existing typhoon with historical typhoon characteristic information, and searching historical typhoon characteristic information with highest similarity;
substep 3, training fault data in substep 1 by using a random forest algorithm, and predicting hourly fault probability of the elements according to historical typhoon characteristic information;
and substep 4, calculating the fault probability of the element under the influence of the typhoon of the whole field according to the hourly fault probability of the element obtained in substep 3, wherein the calculation formula is as follows:
Figure BDA0003446687950000021
wherein, PjIs the failure probability, P, of the element j under the influence of the typhoon of the whole fieldjkIs the probability of failure of element j during the k hour, and T is the total number of hours that the typhoon impact lasts.
Preferably, the characteristic information of the typhoon in the step 1 comprises typhoon center position coordinates, maximum wind speed, wind power level, moving speed, moving direction, center air pressure, seventh-level wind circle radius, tenth-level wind circle radius and twelfth-level wind circle radius.
Preferably, in the step 2, the determining the power consumption damage degree of the user specifically includes:
the system comprises a plurality of nodes, each node is associated with a plurality of elements, and the damage condition of a certain node i is determined by the following sub-steps:
and substep 5, determining the power loss probability of the node i:
Figure BDA0003446687950000031
wherein, PiThe probability that the node i has a power loss event under the influence of the typhoon in the whole field is S, and S is a set formed by elements capable of causing the node i to lose power after failure;
substep 6, determining the average unavailable time for node i:
Ui＝PiT
wherein, UiAnd (4) influencing the expected value of the unavailable time for the node i in the whole typhoon.
Substep 7 of determining the average power shortage of node i
EENSi＝UiLi
Wherein, EENSiExpected value of electric quantity, L, for node i losing power supply under the whole typhooniIs the average load capacity of node i.
Preferably, the step 2 of determining the damage condition of the system in the typhoon weather specifically comprises the following substeps:
substep 8, calculating the average power failure probability of the system:
Figure BDA0003446687950000041
SAIPI is the average power failure probability of all users of the system, R is the set formed by all nodes of the system, NiThe number of users of the node i;
substep 9, calculating the average power failure time of the system:
Figure BDA0003446687950000042
SAIDI is the average power off time of all users in the system;
substep 10, calculating the system outage load proportion SLLPI:
Figure BDA0003446687950000043
substep 11, calculating average power supply availability ASAI:
Figure BDA0003446687950000044
substep 12, calculating the expected starved power EENS:
Figure BDA0003446687950000045
preferably, in step 3, determining the power damage level evaluation according to the power damage level of the user and the damage condition of the system specifically includes:
substep 3.1, inputting a power distribution network topological structure and node i user information;
substep 3.2, obtaining a minimum path set and a non-minimum path set of each load node i by using breadth search according to the network structure;
substep 3.3, determining the influence level of each line fault on each load node according to the minimum path set and the non-minimum path set obtained in substep 3.2 and the switch configuration condition on the line in the power distribution network;
and 3.4, after determining the elements affecting each load node, calculating the evaluation indexes of the damage conditions of the user and the system by using the calculation formula in the step 2, and finishing the evaluation of the power utilization damage level under the typhoon disaster.
The invention has the beneficial effects that: the method and the system can evaluate the damage conditions of the users and the power distribution system under the typhoon disaster, and reduce the influence of the typhoon disaster on the normal operation of the power distribution system. A two-stage typhoon influence evaluation model is provided, and key features are extracted according to typhoon forecast information in the first stage to predict the fault probability of each element; and a series of probability-based indexes are provided in the second stage and used for evaluating the damage conditions of users and systems, then each index is calculated by using an analysis method according to the fault probability of each element obtained in the first stage, the damage degree of each user and the whole power distribution system under the typhoon of the whole power plant can be judged by analyzing the obtained indexes, and the user nodes with high power loss risk probability can be quickly and accurately identified.
Drawings
FIG. 1 is a flow chart of the present invention.
FIG. 2 is a block diagram of the RBTS-BUS6 system;
fig. 3 is a graph of component failure probability prediction results.
Detailed Description
The invention is further described below with reference to the figures and examples.
Example (b):
the method for evaluating the damage probability of the power distribution network under the typhoon disaster based on the analytic method, as shown in fig. 1, comprises the following steps:
step 1, collecting attribute data of each element affected by typhoon in a power distribution network, and determining the fault probability of each element under the condition of typhoon weather;
step 2, determining the power consumption damage degree of the user according to the fault probability of each element under the typhoon weather condition, and then determining the damage condition of the system under the typhoon weather condition;
and 3, determining power consumption damage level evaluation according to the power consumption damage degree of the user and the damage condition of the system, matching the power consumption damage level with historical data, and calling measures taken by the same power consumption damage level in the historical data to repair the power consumption damage condition of the user.
The step 1 specifically comprises the following substeps:
substep 1, collecting fault data of the power distribution network under the influence of historical typhoons, comprising: fault time period, fault element number and historical typhoon characteristic information;
substep 2, collecting characteristic information of the existing typhoon to be evaluated, matching the characteristic information of the existing typhoon with historical typhoon characteristic information, and searching historical typhoon characteristic information with highest similarity;
substep 3, training the fault data in substep 1 by using a random forest algorithm, and predicting hourly fault probability of the element according to historical typhoon characteristic information;
and substep 4, calculating the fault probability of the element under the influence of the typhoon of the whole field according to the hourly fault probability of the element obtained in substep 3, wherein the calculation formula is as follows:
Figure BDA0003446687950000061
wherein, PjIs the failure probability, P, of the element j under the influence of the typhoon of the whole fieldjkIs the probability of failure of element j during the k hour, and T is the total number of hours that the typhoon impact lasts.
The characteristic information of the typhoon in the step 1 comprises a typhoon center position coordinate, a maximum wind speed, a wind power level, a moving speed, a moving direction, a central air pressure, a seven-level wind ring radius, a ten-level wind ring radius and a twelve-level wind ring radius.
In the step 2, the determining of the power consumption damage degree of the user specifically includes:
the system comprises a plurality of nodes, each node is associated with a plurality of elements, and the damage condition of a certain node i is determined by the following sub-steps:
and substep 5, determining the power loss probability of the node i:
Figure BDA0003446687950000071
wherein, PiThe probability that the node i has a power loss event under the influence of the typhoon in the whole field is S, and S is a set formed by elements capable of causing the node i to lose power after failure;
substep 6, determining the average unavailable time for node i:
Ui＝PiT
wherein, UiAnd (4) influencing the expected value of the unavailable time for the node i in the whole typhoon.
Substep 7, determining the average power shortage of node i
EENSi＝UiLi
Wherein, EENSiExpected value of electric quantity, L, for node i losing power supply under the whole typhooniIs the average load capacity of node i.
The step 2 of determining the damage condition of the system in the typhoon weather specifically comprises the following substeps:
substep 8, calculating the average power failure probability of the system:
Figure BDA0003446687950000081
SAIPI is the average outage probability of all users of the system, R is the set formed by all nodes of the system, NiThe number of users of the node i;
substep 9, calculating the average power failure time of the system:
Figure BDA0003446687950000082
SAIDI is the average power off time of all users in the system;
substep 10, calculating the system outage load proportion SLLPI:
Figure BDA0003446687950000083
substep 11, calculating average power supply availability ASAI:
Figure BDA0003446687950000084
substep 12, calculating the expected starved power EENS:
Figure BDA0003446687950000085
in the step 3, determining the power consumption damage level evaluation according to the power consumption damage degree of the user and the damage condition of the system specifically comprises:
substep 3.1, inputting a power distribution network topological structure and node i user information;
substep 3.2, obtaining a minimum path set and a non-minimum path set of each load node i by using breadth search according to the network structure;
substep 3.3, determining the influence level of each line fault on each load node according to the minimum path set and the non-minimum path set obtained in substep 3.2 and the switch configuration condition on the line in the power distribution network;
the impact grades are divided into three types:
(1) and losing power for a long time.
The long-term power loss refers to that a load node needs to wait for the restoration of a fault element and then can supply power again, and the long-term power loss situation includes: for a load node with only one power supply path, an element on the power supply path fails; the load node has a plurality of power supply paths, but a fault line cannot be isolated through a switch; the non-supply path element fails but is closely tied to the load node without the corresponding switch to isolate.
(2) Short-term power loss.
Short-term power loss means that the load node can recover power supply only by waiting for the time of switching operation, and the short-term power loss situation includes: the load is provided with a plurality of power supply paths, the elements on the main power supply path fail, the corresponding switch is subjected to switching operation, and the standby power supply path is used for supplying power to the load node; the element failure on the power supply path, the load is connected to other power supply paths through the interconnection switch; the element on the non-supply path fails, but a switching operation of the switch is required to isolate the failed element.
(3) Instantaneous power failure
The instantaneous power failure means that the load can be supplied with power again in a short time after power loss, and the normal power utilization of a user is not influenced usually. The instant power outage scenarios are: the switching of the main power supply path and the standby power supply path is completed by an automatic device in a moment; when an element on the non-power supply path fails, a protection device such as a fuse operates to remove the failure in a short time. In the reliability evaluation, two consideration modes are provided for the influence of the instantaneous power failure, wherein one mode is to directly not consider the influence of the instantaneous power failure on the node load and the system; in the other method, the influence of the instantaneous fault is taken into account only in the fault frequency index, and the influence of the instantaneous power failure is ignored in the reliability index related to the power failure time.
And 3.4, after determining the elements affecting each load node, calculating the evaluation indexes of the damage conditions of the user and the system by using the calculation formula in the step 2, and finishing the evaluation of the power utilization damage level under the typhoon disaster.
The process of the present invention is further illustrated below with reference to specific examples:
taking the RBTS-BUS6 system as an example, as shown in fig. 2, the system has 4 feeders, and is composed of 40 load nodes and 64 branches, the total load of the system is 10.72MW, the total number of users is 2938, and the start of the system branches is configured with fusible links (not shown in the figure).
Historical data is collected, including typhoon signature data and power distribution system component fault data. The typhoon characteristics include: the center longitude, the center latitude, the center air pressure, the moving speed, the maximum wind speed, the wind power top level, the typhoon level, the seven-level wind circle radius, the ten-level wind circle radius and the twelve-level wind circle radius; the power distribution system component data is the hourly number of failed components of the power distribution system during the typhoon exposure period.
And (4) performing regression on the historical data by using a random forest algorithm, and determining the relation between the typhoon characteristics and the element fault probability.
Typhoon time sequence characteristic information is input, and the hourly fault probability of the power distribution system elements is predicted by using a trained random forest algorithm, and the result is shown in fig. 3.
The failure probability of the element under the influence of the typhoon of the whole field is calculated to be 0.0973%.
The minimum path set of each node is determined by using breadth search, and the minimum path set and the non-minimum path set of part of nodes are shown in a table 1.
TABLE 1
Figure BDA0003446687950000101
Figure BDA0003446687950000111
And judging the load nodes and the influence consequences which are influenced after each line fault according to the network structure and the switch configuration condition, traversing all line fault situations, and calculating the node damage condition evaluation indexes, wherein the indexes of partial nodes are shown in the table 2.
TABLE 2
Figure BDA0003446687950000112
As can be seen from tables 1 and 2, the node 32 has a greater power loss probability due to more line elements on the power supply path, and is more serious in damage risk under typhoon, the power loss event has a probability of 0.38%, the average unavailable time is 1.8197 hours, the expected power shortage amount is 0.3501MW · h, and the power grid related department should pay attention to the user with the greater power loss probability in typhoon.
After the indexes of the nodes are obtained through calculation, the evaluation indexes of the damaged condition of the system are obtained through calculation, and the result is shown in table 3.
TABLE 3
Figure BDA0003446687950000113
Figure BDA0003446687950000121
The average power failure probability of all users of the system is 1.48%, the average power failure time is 0.71 hour, the average power loss user proportion is 1.78%, the average power loss load proportion is 1.48%, the average availability is 98.52%, and the average power shortage amount is 9.13. The indexes can be used as pre-disaster prediction to provide theoretical reference for the power grid to take countermeasures; and the method can also be used for evaluation after disaster, and is used for thinking, summarizing and promoting so as to better cope with the next typhoon accident.
The above-described embodiment is a preferred embodiment of the present invention, and is not intended to limit the present invention in any way, and other variations and modifications may be made without departing from the spirit and scope of the invention as defined in the appended claims.

Claims (6)

1. The method for evaluating the damage probability of the power distribution network under the typhoon disaster based on the analytic method is characterized by comprising the following steps of:
step 1, collecting attribute data of each element influenced by typhoon in a power distribution network, and determining the fault probability of each element under the condition of typhoon weather;
step 2, determining the power consumption damage degree of the user according to the fault probability of each element under the typhoon weather condition, and then determining the damage condition of the system under the typhoon weather condition;
and 3, determining power consumption damage level evaluation according to the power consumption damage degree of the user and the damage condition of the system, matching the power consumption damage level with historical data, and calling measures taken by the same power consumption damage level in the historical data to repair the power consumption damage condition of the user.
2. The analytic-method-based method for evaluating the damage probability of the power distribution network in the typhoon disaster according to claim 1, wherein the step 1 specifically comprises the following substeps:
substep 1, collecting fault data of the power distribution network under the influence of historical typhoons, comprises: fault time period, fault element number and historical typhoon characteristic information;
substep 2, collecting characteristic information of the existing typhoon to be evaluated, matching the characteristic information of the existing typhoon with historical typhoon characteristic information, and searching historical typhoon characteristic information with highest similarity;
substep 3, training the fault data in substep 1 by using a random forest algorithm, and predicting hourly fault probability of the element according to historical typhoon characteristic information;
and substep 4, calculating the fault probability of the element under the influence of the typhoon of the whole field according to the hourly fault probability of the element obtained in substep 3, wherein the calculation formula is as follows:
Figure FDA0003446687940000011
wherein, PjIs the failure probability, P, of the element j under the influence of the typhoon of the whole fieldjkIs the probability of failure of element j during the k hour, and T is the total number of hours that the typhoon impact lasts.
3. The method according to claim 2, wherein the characteristic information of the typhoon in the step 1 includes a typhoon center position coordinate, a maximum wind speed, a wind power level, a moving speed, a moving direction, a center air pressure, a seven-level wind circle radius, a ten-level wind circle radius and a twelve-level wind circle radius.
4. The method for evaluating the damage probability of the power distribution network in the typhoon disaster according to the claim 1, wherein in the step 2, the power consumption damage degree of the user is determined as follows:
the system comprises a plurality of nodes, each node is associated with a plurality of elements, and the damage condition of a certain node i is determined by the following sub-steps:
and substep 5, determining the power loss probability of the node i:
Figure FDA0003446687940000021
wherein, PiThe probability that the node i has a power loss event under the influence of the typhoon in the whole field is S, and S is a set formed by elements capable of causing the node i to lose power after failure;
substep 6, determining the average unavailable time for node i:
Ui＝PiT
wherein, UiThe expected value of the unavailable time of the node i under the influence of the typhoon in the whole field is obtained;
substep 7, determining the average power shortage of node i
EENSi＝UiLi
Wherein, EENSiExpected value of electric quantity, L, for node i losing power supply under the whole typhooniIs the average load capacity of node i.
5. The method for evaluating the damage probability of the power distribution network under the typhoon disaster based on the analytic method as claimed in claim 4, wherein the step 2 of determining the damage condition of the system under the typhoon weather specifically comprises the following substeps:
substep 8, calculating the average power failure probability of the system:
Figure FDA0003446687940000031
SAIPI is the average outage probability of all users of the system, R is the set formed by all nodes of the system, NiThe number of users of the node i;
substep 9, calculating the average power failure time of the system:
Figure FDA0003446687940000032
SAIDI is the average power off time of all users in the system;
substep 10, calculating the system outage load proportion SLLPI:
Figure FDA0003446687940000033
substep 11, calculating average power supply availability ASAI:
Figure FDA0003446687940000034
substep 12, calculating the expected starved power EENS:
Figure FDA0003446687940000035
6. the analytic-method-based assessment method for power distribution network damage probability in typhoon disasters according to claim 5, wherein in the step 3, the determining of the power damage level assessment according to the power damage degree of the user and the damage condition of the system specifically comprises:
substep 3.1, inputting a power distribution network topological structure and node i user information;
substep 3.2, obtaining a minimum path set and a non-minimum path set of each load node i by using breadth search according to the network structure;
substep 3.3, determining the influence level of each line fault on each load node according to the minimum path set and the non-minimum path set obtained in substep 3.2 and the switch configuration condition on the line in the power distribution network;
and 3.4, after determining the elements affecting each load node, calculating the evaluation indexes of the damage conditions of the user and the system by using the calculation formula in the step 2, and finishing the evaluation of the power utilization damage level under the typhoon disaster.
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