CN116109295B - Maintenance decision method based on power distribution terminal - Google Patents
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Abstract
The application relates to the technical field of power distribution terminals, in particular to a maintenance decision method based on a power distribution terminal. Comprising the following steps: acquiring real-time evaluation value data of a power distribution terminal, and generating reliable running time of the power distribution terminal, equipment fault rate and predicted fault type according to the real-time evaluation data of the power distribution terminal; setting a fault decision factor according to the equipment fault rate and the predicted fault type, and setting an overhaul time interval according to the fault decision factor; and establishing a maintenance optimizing model, setting a primary maintenance decision according to the reliable running time and maintenance time interval of each power distribution terminal, and correcting the primary maintenance decision according to the maintenance optimizing model to generate a secondary maintenance decision. And (3) according to different overlapping intervals of the overhaul time period of the power distribution terminal, a plurality of overhaul plans are formulated, and optimizing is carried out according to the principle of minimum overhaul time, so that the overhaul time cost is reduced and the overall operation and maintenance cost is saved on the basis of ensuring timely overhaul of the power distribution terminal.
Description
Technical Field
The application relates to the technical field of power distribution terminals, in particular to a maintenance decision method based on a power distribution terminal.
Background
The safety and the maintenance of the power equipment after fault discovery are also the problems that the power system is continuously required to be optimally solved. The traditional power equipment maintenance method mostly adopts a post-maintenance method, which is maintenance after a professional equipment maintenance personnel sends out complete stress feedback of the fault to the power equipment under the condition that the serious deviation control failure or the fault even damage of the state parameters of the power equipment occur.
For secondary equipment such as power distribution terminals, particularly power distribution terminals with low voltage level of a distribution network, the quantity is large, the distribution is wide, the maintenance is generally carried out in accidental fault period and loss fault period, the fault rate can be reduced, and the equipment maintenance cost and economic loss caused by faults are reduced. However, too few repairs will increase the failure rate of the device, increase the cost of repairing the failure, increase the total cost, and too many repairs will result in too high repair costs and increase the assembly, so it is very important how to reasonably arrange the number of repairs, and the period of repair.
Disclosure of Invention
The purpose of the present application is: in order to solve the technical problems, the application provides a maintenance decision method based on a power distribution terminal, which aims to save the whole operation and maintenance cost and ensure the stable operation of the power distribution terminal.
In some embodiments of the present application, a service decision method based on a power distribution terminal is provided, including:
acquiring real-time evaluation value data of a power distribution terminal, and generating reliable running time of the power distribution terminal, equipment fault rate and predicted fault type according to the real-time evaluation data of the power distribution terminal;
setting a fault decision factor according to the equipment fault rate and the predicted fault type, and setting an overhaul time interval according to the fault decision factor;
and establishing a maintenance optimizing model, setting a primary maintenance decision according to the reliable running time and maintenance time interval of each power distribution terminal, and correcting the primary maintenance decision according to the maintenance optimizing model to generate a secondary maintenance decision.
In some embodiments of the present application, setting a fault decision factor according to the equipment fault rate and the predicted fault type includes:
presetting a fault type grade matrix A, and setting A (A1, A2, A3 and A4), wherein A1 is a preset primary fault, A2 is a preset secondary fault, A3 is a preset tertiary fault, and A4 is a preset quaternary fault;
presetting a fault evaluation value matrix B, and setting B (B1, B2, B3 and B4), wherein B1 is a preset first fault evaluation value, B2 is a preset second fault evaluation value, B3 is a preset third fault evaluation value, B4 is a preset fourth fault evaluation value, and B1 is more than B2 and less than B3 and less than B4;
if the predicted fault type is a preset first-level fault, setting a real-time fault evaluation value B to be B1-B < B2;
if the predicted fault type is a preset secondary fault, setting a real-time fault evaluation value B to be B2-B < B3;
if the predicted fault type is a preset three-level fault, setting a real-time fault evaluation value B to be B3-B < B4;
if the predicted fault type is a preset four-level fault, setting a real-time fault evaluation value B as B not less than B4;
acquiring a device failure rate c, and generating a failure decision factor d according to the real-time failure evaluation value b and the device failure rate c;
the fault decision factor d=b×c.
In some embodiments of the present application, when setting the overhaul time interval according to the fault decision factor, the method includes:
presetting a fault decision factor value matrix D, and setting D (D1, D2, D3 and D4), wherein D1 is a preset first fault decision factor value, D2 is a preset second fault decision factor value, D3 is a preset third fault decision factor value, D4 is a preset fourth fault decision factor value, and D1 is less than D2 and less than D3 is less than D4;
presetting a maintenance time interval matrix T, and setting T (T1, T2, T3 and T4), wherein T1 is a preset first maintenance time interval, T2 is a preset second maintenance time interval, T3 is a preset third maintenance time interval, T4 is a preset fourth maintenance time interval, and T1 is more than T2 and less than T3 and less than T4;
if D1 is less than or equal to D < D2, setting the overhaul time interval T as a preset first overhaul time interval T1;
if D2 is less than or equal to D < D3, setting the overhaul time interval T as a preset second overhaul time interval T2;
if D3 is less than or equal to D4, setting the overhaul time interval T as a preset third overhaul time interval T3;
if D is more than or equal to D4, setting the overhaul time interval T as a preset fourth overhaul time interval T4.
In some embodiments of the present application, when setting a primary overhaul decision according to a reliable running time and an overhaul time interval of each power distribution terminal, the method includes:
setting overhaulable time periods of the power distribution terminals according to reliable running time and overhauling time intervals of all the power distribution terminals, and setting a plurality of overhauling time nodes according to the overhaulable time periods of all the power distribution terminals;
generating a plurality of maintenance plans for maintenance according to the number of power distribution terminals to be maintained of the maintenance time node, wherein all the power distribution terminals are contained in a single maintenance plan;
and acquiring the maintenance time cost of a single maintenance plan, and generating a primary maintenance decision according to the maintenance time cost.
In some embodiments of the present application, when generating the primary overhaul decision according to the overhaul time cost, the method includes:
presetting a maintenance time cost threshold;
if the overhaul time cost of the overhaul plan is lower than the preset overhaul time cost threshold value, setting the overhaul plan as a feasible overhaul plan;
if the overhaul time cost of the overhaul plan is higher than the preset overhaul time cost threshold, setting the overhaul plan as an infeasible overhaul plan;
the primary service decision includes all of the feasible service plans.
In some embodiments of the present application, when establishing the overhaul optimizing model, the method includes:
acquiring historical maintenance data of a power distribution terminal, and generating a maintenance cost model, a reliability model after maintenance and a fault maintenance model according to the historical maintenance data of the power distribution terminal;
the overhaul cost model is used for generating overhaul cost f of a single overhaul plan;
the reliability model after overhaul is used for generating reliable running time of all power distribution terminals after execution according to a single overhaul plan is completed;
the fault maintenance model is used for generating fault maintenance costs of all power distribution terminals in reliable operation time after the fault maintenance model is executed according to a single maintenance plan.
In some embodiments of the present application, generating a fault maintenance cost for all power distribution terminals during reliable run time includes:
presetting a first type of maintenance and a second type of maintenance;
acquiring one type of maintenance cost e1 of a single distribution terminal and an expected income value g1 after one type of maintenance is performed;
acquiring a second-class maintenance cost e2 of a single power distribution terminal and an expected income value g2 after the second-class maintenance is executed;
if g1> g2, performing a type of maintenance;
if g1 is less than or equal to g2, performing second-class maintenance;
and obtaining one type of maintenance cost e1 or two types of maintenance cost e2 of all the power distribution terminals, and generating the fault maintenance cost e of a single maintenance plan.
In some embodiments of the present application, when the overhaul optimizing model is established, the method further includes:
generating an overall expected cost h of a single overhaul plan according to the overhaul cost f of the single overhaul plan and the fault maintenance cost e of the single overhaul plan;
setting a correction coefficient n according to the maintenance time cost of the maintenance plan;
the overall desired cost of the single service plan h=n×f+e.
In some embodiments of the present application, when setting the correction coefficient n according to the maintenance time cost of the maintenance plan, the method includes:
presetting an overhaul time cost matrix M, and setting M (M1, M2 and M3), wherein M1 is preset first overhaul time cost, M2 is preset second overhaul time cost, M3 is preset third overhaul time cost, and M1 is less than M2 and less than M3;
presetting a correction coefficient value matrix N, and setting N (N1, N2, N3), wherein N1 is a preset first correction coefficient, N2 is a preset second correction coefficient, N3 is a preset third correction coefficient, and 1 is more than N1 and less than N2 is more than N3;
acquiring maintenance time cost m of a maintenance plan and setting a correction coefficient n;
if M1 is more than M and less than or equal to M2, setting a correction coefficient n=n1;
if M2 is more than M and less than or equal to M3, setting a correction coefficient n=n2;
if M is equal to or greater than M3, a correction coefficient n=n3 is set.
In some embodiments of the present application, when generating a secondary overhaul decision by correcting a primary overhaul decision according to the overhaul optimizing model, the method includes:
acquiring a single feasible maintenance plan, setting a time point when the execution of the feasible maintenance plan is completed as an iteration time node, acquiring real-time evaluation value data of the power distribution terminal again according to the iteration time node, generating a primary maintenance decision, and carrying out iterative calculation;
acquiring expected rejection periods of all power distribution terminals, setting iteration times according to the expected rejection periods, and stopping iteration when the iteration times are reached;
acquiring all feasible overhaul plans of the primary overhaul decision in each iteration period, and generating a secondary overhaul decision, wherein the secondary overhaul decision comprises a plurality of overhaul chains, and the overhaul chains select one feasible overhaul plan in each iteration period;
and generating the overall expected cost of the overhaul chain according to all feasible overhaul plans contained in the overhaul chain, and selecting the overhaul chain with the lowest overall expected cost as an optimizing result.
Compared with the prior art, the overhaul decision method based on the power distribution terminal has the beneficial effects that:
based on historical data, calculating the reliable running time of the power distribution terminals, equipment fault rate and predicted fault types, determining the overhaulable time period of each power distribution terminal, making a plurality of overhauling plans according to different overlapping intervals of the overhauling time periods of the power distribution terminals, optimizing according to the principle of forming the minimum overhauling time, reducing the overhauling time cost and saving the whole operation and maintenance cost on the basis of guaranteeing timely overhauling of the power distribution terminals.
By establishing an overhaul optimizing model, the overall optimizing for the overhaul of the power distribution terminal is realized, but not the partial optimizing is realized, the increase of other partial overhaul cost caused by pursuing the partial optimizing is avoided, the waste of the overall cost is caused, the overall overhaul plans of a plurality of different paths are selected by generating an overhaul chain, the overall optimizing is performed according to the minimum cost principle, and the overall operation and maintenance cost is saved.
Drawings
Fig. 1 is a schematic flow chart of a maintenance decision method based on a power distribution terminal in a preferred embodiment of the application.
Detailed Description
The detailed description of the present application is further described in detail below with reference to the drawings and examples. The following examples are illustrative of the present application, but are not intended to limit the scope of the present application.
In the description of the present application, it should be understood that the terms "center," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like indicate orientations or positional relationships based on the orientation or positional relationships shown in the drawings, merely to facilitate description of the present application and simplify the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and therefore should not be construed as limiting the present application.
The terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. In the description of the present application, unless otherwise indicated, the meaning of "a plurality" is two or more.
In the description of the present application, it should be noted that, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the terms in this application will be understood by those of ordinary skill in the art in a specific context.
As shown in fig. 1, a service decision method based on a power distribution terminal according to a preferred embodiment of the present application includes:
s101: acquiring real-time evaluation value data of a power distribution terminal, and generating reliable running time of the power distribution terminal, equipment fault rate and predicted fault type according to the real-time evaluation data of the power distribution terminal;
s102: setting a fault decision factor according to the equipment fault rate and the predicted fault type, and setting an overhaul time interval according to the fault decision factor;
s103: and establishing a maintenance optimizing model, setting a primary maintenance decision according to the reliable running time and maintenance time interval of each power distribution terminal, and correcting the primary maintenance decision according to the maintenance optimizing model to generate a secondary maintenance decision.
Specifically, the reliability refers to the probability that the device can operate to time t1 without any obstacle, and when the reliability of time t1 is lower than 95%, the time interval from the start of operation to time t1 is a reliable operation time;
specifically, the equipment failure rate refers to the probability of failure per unit time after the operation to time t 1.
Specifically, a corresponding prediction model is generated according to historical operation data of the power distribution terminal, the prediction model calculates reliable operation time and equipment failure rate according to a Weibull distribution formula, and the type of possible failure is predicted according to the historical failure data of the power distribution terminal.
Specifically, when setting the fault decision factor according to the equipment fault rate and the predicted fault type, the method includes:
presetting a fault type grade matrix A, and setting A (A1, A2, A3 and A4), wherein A1 is a preset primary fault, A2 is a preset secondary fault, A3 is a preset tertiary fault, and A4 is a preset quaternary fault;
presetting a fault evaluation value matrix B, and setting B (B1, B2, B3 and B4), wherein B1 is a preset first fault evaluation value, B2 is a preset second fault evaluation value, B3 is a preset third fault evaluation value, B4 is a preset fourth fault evaluation value, and B1 is more than B2 and less than B3 and less than B4;
if the predicted fault type is a preset first-level fault, setting a real-time fault evaluation value B to be B1-B < B2;
if the predicted fault type is a preset secondary fault, setting a real-time fault evaluation value B to be B2-B < B3;
if the predicted fault type is a preset three-level fault, setting a real-time fault evaluation value B to be B3 less than or equal to B4;
if the predicted fault type is a preset four-level fault, setting a real-time fault evaluation value B as B not less than B4;
acquiring a device failure rate c, and generating a failure decision factor d according to the real-time failure evaluation value b and the device failure rate c;
fault decision factor d=b×c.
Specifically, the equipment failure rate refers to the probability of possible failure at the current moment, a failure prediction model is established according to the historical operation parameters of the equipment, and the real-time operation parameters of the equipment are collected by the failure prediction model to predict, so that the real-time equipment failure rate is obtained. The fault prediction model mainly establishes a fault rate maintenance and time model by a risk assessment method to predict the equipment fault rate.
Specifically, the fault type grade matrix is set according to historical fault data of the power distribution terminal, and is mainly determined according to factors such as maintenance difficulty after the occurrence of the fault, influence and loss caused by the fault, duration of the fault, whether the operation parameters of the power distribution terminal have obvious changes before the occurrence of the fault and the like.
Specifically, when setting the maintenance time interval according to the fault decision factor, the method includes:
presetting a fault decision factor value matrix D, and setting D (D1, D2, D3 and D4), wherein D1 is a preset first fault decision factor value, D2 is a preset second fault decision factor value, D3 is a preset third fault decision factor value, D4 is a preset fourth fault decision factor value, and D1 is less than D2 and less than D3 is less than D4;
presetting a maintenance time interval matrix T, and setting T (T1, T2, T3 and T4), wherein T1 is a preset first maintenance time interval, T2 is a preset second maintenance time interval, T3 is a preset third maintenance time interval, T4 is a preset fourth maintenance time interval, and T1 is more than T2 and less than T3 and less than T4;
if D1 is less than or equal to D < D2, setting the overhaul time interval T as a preset first overhaul time interval T1;
if D2 is less than or equal to D < D3, setting the overhaul time interval T as a preset second overhaul time interval T2;
if D3 is less than or equal to D4, setting the overhaul time interval T as a preset third overhaul time interval T3;
if D is more than or equal to D4, setting the overhaul time interval T as a preset fourth overhaul time interval T4.
Specifically, the overhaul time interval refers to that after the power distribution terminal completes the operation of reliable operation time, one overhaul is required to be completed within the overhaul time interval. According to the difference of the equipment fault rate and the predicted fault type of each power distribution terminal, the overhaul time intervals are different, and the greater the probability of faults, the more serious the predicted fault type and the shorter the overhaul time intervals.
Specifically, the present invention relates to a method for manufacturing a semiconductor device. When setting a primary overhaul decision according to the reliable running time and the overhaul time interval of each power distribution terminal, the method comprises the following steps:
setting overhaulable time periods of the power distribution terminals according to reliable running time and overhauling time intervals of all the power distribution terminals, and setting a plurality of overhauling time nodes according to the overhaulable time periods of all the power distribution terminals;
generating a plurality of maintenance plans for maintenance according to the number of power distribution terminals to be maintained of the maintenance time node, wherein all the power distribution terminals are contained in a single maintenance plan;
and acquiring the maintenance time cost of a single maintenance plan, and generating a primary maintenance decision according to the maintenance time cost.
Specifically, the overhaulable time period refers to the time period when overhauling needs to be completed, and as the overhaulable time periods of different power distribution terminals overlap, a plurality of different overhauling plans can be generated. For example, assume that there are three distribution terminals, terminal one, terminal two, terminal three, three service time nodes are selected, wherein a first time node may service terminal one and terminal three, a second time node may service terminal two and terminal three, a third time node may service terminal two,
the current time node being overhaulable means that the time node is included in an overhaulable period of the equipment.
A service plan one may be generated: the first time node overhauls the terminal I and the terminal III, and the third time node overhauls the terminal II. Maintenance plan two: the first time node can be used for overhauling the first terminal, the second time node and the third time node can be used for overhauling the second terminal and the third terminal, and the like, and all overhauling plans can be obtained by using an exhaustion method.
Specifically, the maintenance schedule includes a maintenance time and a maintenance method for each power distribution terminal.
Specifically, the maintenance time cost comprises maintenance working time and preparation time, and the preparation time refers to the time for reaching the power distribution terminal to be maintained and returning.
Specifically, when generating a primary overhaul decision according to an overhaul time cost, the method comprises the following steps:
presetting a maintenance time cost threshold;
if the maintenance time cost of the maintenance plan is lower than the preset maintenance time cost threshold value, setting the maintenance plan as a feasible maintenance plan;
if the maintenance time cost of the maintenance plan is higher than the preset maintenance time cost threshold, setting the maintenance plan as an infeasible maintenance plan;
the primary service decision includes all possible service plans.
Specifically, the maintenance time cost is generated according to historical fault maintenance parameters in the equipment, and mainly refers to the time for executing one maintenance plan, maintenance labor cost, maintenance distance and other costs. The maintenance time cost threshold can be set according to the requirements of enterprises, namely the maximum time cost that the enterprises are willing to pay for a single maintenance plan.
It may be appreciated that in the above embodiment, based on the historical data, the reliable operation time, the equipment fault rate and the predicted fault type of the power distribution terminal are calculated, so that the overhaulable time period of each power distribution terminal is determined, a plurality of overhauling plans are formulated according to different overlapping intervals of the overhauling time period of the power distribution terminal, and the optimization is performed according to the principle of forming the minimum overhauling time, so that the overhauling time cost is reduced and the overall operation and maintenance cost is saved on the basis of ensuring timely overhauling of the power distribution terminal.
In a preferred embodiment of the present application, when establishing an overhaul optimizing model, the method includes:
acquiring historical maintenance data of the power distribution terminal, and generating a maintenance cost model, a reliability model and a fault maintenance model after maintenance according to the historical maintenance data of the power distribution terminal;
the overhaul cost model is used for generating overhaul cost f of a single overhaul plan;
the reliability model after overhaul is used for generating reliable running time of all power distribution terminals after execution according to a single overhaul plan is completed;
the fault maintenance model is used to generate fault maintenance costs for all power distribution terminals within a reliable run time after execution according to a single maintenance schedule.
Specifically, generating fault maintenance costs for all power distribution terminals during reliable run time includes:
presetting a first type of maintenance and a second type of maintenance;
acquiring one type of maintenance cost e1 of a single distribution terminal and an expected income value g1 after one type of maintenance is performed;
acquiring a second-class maintenance cost e2 of a single power distribution terminal and an expected income value g2 after the second-class maintenance is executed;
if g1> g2, performing a type of maintenance;
if g1 is less than or equal to g2, performing second-class maintenance;
and obtaining one type of maintenance cost e1 or two types of maintenance cost e2 of all the power distribution terminals, and generating the fault maintenance cost e of a single maintenance plan.
Specifically, one type of maintenance refers to maintenance of equipment, the second type of maintenance refers to direct replacement of equipment, and the type of maintenance is selected according to an expected benefit value, so that local maintenance cost is the lowest, wherein the expected benefit value refers to the total benefit value minus the cost of maintaining or replacing the equipment.
Specifically, according to a single distribution terminal, the expected benefit value is to build a prediction model according to a plurality of parameters such as the expected service life of equipment, the historical operation parameters of the equipment and the like, so as to predict.
Specifically, when establishing the maintenance optimizing model, the method further comprises the following steps:
generating the overall expected cost h of the single overhaul plan according to the overhaul cost f of the single overhaul plan and the fault maintenance cost e of the single overhaul plan;
setting a correction coefficient n according to the maintenance time cost of the maintenance plan;
the overall expected cost of a single service plan h=n×f+e.
Specifically, when setting the correction coefficient n according to the maintenance time cost of the maintenance schedule, the method includes:
presetting an overhaul time cost matrix M, and setting M (M1, M2 and M3), wherein M1 is preset first overhaul time cost, M2 is preset second overhaul time cost, M3 is preset third overhaul time cost, and M1 is less than M2 and less than M3;
presetting a correction coefficient value matrix N, and setting N (N1, N2, N3), wherein N1 is a preset first correction coefficient, N2 is a preset second correction coefficient, N3 is a preset third correction coefficient, and 1 is more than N1 and less than N2 is more than N3;
acquiring maintenance time cost m of a maintenance plan and setting a correction coefficient n;
if M1 is more than M and less than or equal to M2, setting a correction coefficient n=n1;
if M2 is more than M and less than or equal to M3, setting a correction coefficient n=n2;
if M is equal to or greater than M3, a correction coefficient n=n3 is set.
Specifically, the maintenance time cost is used for generating a correction coefficient to correct the maintenance cost, so that the balance of the whole maintenance time and the maintenance cost can be realized, the situation that the maintenance time is too short due to the fact that the personnel cost is increased or the maintenance cost is too low due to the fact that the maintenance time is too long is avoided, the workload of maintenance personnel is too large, and the maintenance quality is prevented from being reduced.
Specifically, when the primary overhaul decision is corrected according to the overhaul optimizing model to generate the secondary overhaul decision, the method comprises the following steps:
acquiring a single feasible overhaul plan, setting a time point when the execution of the feasible overhaul plan is completed as an iteration time node, acquiring real-time evaluation value data of the power distribution terminal again according to the iteration time node, generating a primary overhaul decision, and carrying out iterative calculation;
acquiring expected rejection periods of all power distribution terminals, setting iteration times according to the expected rejection periods, and stopping iteration when the iteration times are reached;
acquiring all feasible overhaul plans of the primary overhaul decision in each iteration period, generating a secondary overhaul decision, wherein the secondary overhaul decision comprises a plurality of overhaul chains, and the overhaul chains select one feasible overhaul plan in each iteration period;
and generating the overall expected cost of the overhaul chain according to all feasible overhaul plans contained in the overhaul chain, and selecting the overhaul chain with the lowest overall expected cost as an optimizing result.
Specifically, all maintenance chains are obtained by using an exhaustion method, wherein the maintenance chains are generated by a local time cost optimization principle, the overall maintenance time is guaranteed to be optimal, and global optimization is performed according to a maintenance cost minimum principle, so that the overall operation and maintenance cost is reduced, the local optimization is abandoned, and the overall stability is guaranteed.
It can be understood that in the above embodiment, by establishing the overhaul optimizing model, the overall optimizing for the overhaul of the power distribution terminal is realized, but not the partial optimizing, so that the increase of the overhaul cost of other parts caused by pursuing the partial optimizing is avoided, the waste of the overall cost is avoided, the overall overhaul plans of a plurality of different paths are selected by generating an overhaul chain, the overall optimizing is performed according to the principle of minimum cost, and the overall operation and maintenance cost is saved.
The foregoing is merely a preferred embodiment of the present application, and it should be noted that modifications and substitutions can be made by those skilled in the art without departing from the technical principles of the present application, and these modifications and substitutions should also be considered as being within the scope of the present application.
Claims (7)
1. The overhaul decision method based on the power distribution terminal is characterized by comprising the following steps of:
acquiring real-time evaluation value data of a power distribution terminal, and generating reliable running time of the power distribution terminal, equipment fault rate and predicted fault type according to the real-time evaluation data of the power distribution terminal;
setting a fault decision factor according to the equipment fault rate and the predicted fault type, and setting an overhaul time interval according to the fault decision factor;
establishing a maintenance optimizing model, setting a primary maintenance decision according to the reliable running time and maintenance time interval of each power distribution terminal, and correcting the primary maintenance decision according to the maintenance optimizing model to generate a secondary maintenance decision;
when the primary overhaul decision is set according to the reliable running time and the overhaul time interval of each power distribution terminal, the method comprises the following steps:
setting overhaulable time periods of the power distribution terminals according to reliable running time and overhauling time intervals of all the power distribution terminals, and setting a plurality of overhauling time nodes according to the overhaulable time periods of all the power distribution terminals;
generating a plurality of maintenance plans for maintenance according to the number of power distribution terminals to be maintained of the maintenance time node, wherein all the power distribution terminals are contained in a single maintenance plan;
obtaining the maintenance time cost of a single maintenance plan, and generating a primary maintenance decision according to the maintenance time cost;
when generating a primary overhaul decision according to the overhaul time cost, the method comprises the following steps:
presetting a maintenance time cost threshold;
if the overhaul time cost of the overhaul plan is lower than the preset overhaul time cost threshold value, setting the overhaul plan as a feasible overhaul plan;
if the overhaul time cost of the overhaul plan is higher than the preset overhaul time cost threshold, setting the overhaul plan as an infeasible overhaul plan;
the primary overhaul decision includes all of the feasible overhaul plans;
when the overhaul optimizing model is established, the method comprises the following steps:
acquiring historical maintenance data of a power distribution terminal, and generating a maintenance cost model, a reliability model after maintenance and a fault maintenance model according to the historical maintenance data of the power distribution terminal;
the overhaul cost model is used for generating overhaul cost f of a single overhaul plan;
the reliability model after overhaul is used for generating reliable running time of all power distribution terminals after execution according to a single overhaul plan is completed;
the fault maintenance model is used for generating fault maintenance costs of all power distribution terminals in reliable operation time after the fault maintenance model is executed according to a single maintenance plan.
2. The distribution terminal-based service decision method according to claim 1, wherein when setting a fault decision factor according to the equipment fault rate and the predicted fault type, comprising:
presetting a fault type grade matrix A, and setting A (A1, A2, A3 and A4), wherein A1 is a preset primary fault, A2 is a preset secondary fault, A3 is a preset tertiary fault, and A4 is a preset quaternary fault;
presetting a fault evaluation value matrix B, and setting B (B1, B2, B3 and B4), wherein B1 is a preset first fault evaluation value, B2 is a preset second fault evaluation value, B3 is a preset third fault evaluation value, B4 is a preset fourth fault evaluation value, and B1 is more than B2 and less than B3 and less than B4;
if the predicted fault type is a preset first-level fault, setting a real-time fault evaluation value B to be B1-B < B2;
if the predicted fault type is a preset secondary fault, setting a real-time fault evaluation value B to be B2-B < B3;
if the predicted fault type is a preset three-level fault, setting a real-time fault evaluation value B to be B3-B < B4;
if the predicted fault type is a preset four-level fault, setting a real-time fault evaluation value B as B not less than B4;
acquiring a device failure rate c, and generating a failure decision factor d according to the real-time failure evaluation value b and the device failure rate c;
the fault decision factor d=b×c.
3. The service decision method based on the power distribution terminal according to claim 2, wherein when setting a service time interval according to the fault decision factor, comprising:
presetting a fault decision factor value matrix D, and setting D (D1, D2, D3 and D4), wherein D1 is a preset first fault decision factor value, D2 is a preset second fault decision factor value, D3 is a preset third fault decision factor value, D4 is a preset fourth fault decision factor value, and D1 is less than D2 and less than D3 is less than D4;
presetting a maintenance time interval matrix T, and setting T (T1, T2, T3 and T4), wherein T1 is a preset first maintenance time interval, T2 is a preset second maintenance time interval, T3 is a preset third maintenance time interval, T4 is a preset fourth maintenance time interval, and T1 is more than T2 and less than T3 and less than T4;
if D1 is less than or equal to D < D2, setting the overhaul time interval T as a preset first overhaul time interval T1;
if D2 is less than or equal to D < D3, setting the overhaul time interval T as a preset second overhaul time interval T2;
if D3 is less than or equal to D4, setting the overhaul time interval T as a preset third overhaul time interval T3;
if D is more than or equal to D4, setting the overhaul time interval T as a preset fourth overhaul time interval T4.
4. The overhaul decision method based on the power distribution terminal as claimed in claim 3, wherein when the overhaul optimizing model is built, the method comprises the following steps:
acquiring historical maintenance data of a power distribution terminal, and generating a maintenance cost model, a reliability model after maintenance and a fault maintenance model according to the historical maintenance data of the power distribution terminal;
the overhaul cost model is used for generating overhaul cost f of a single overhaul plan;
the reliability model after overhaul is used for generating reliable running time of all power distribution terminals after execution according to a single overhaul plan is completed;
the fault maintenance model is used for generating fault maintenance costs of all power distribution terminals in reliable operation time after the fault maintenance model is executed according to a single maintenance plan.
5. The method for determining maintenance based on a power distribution terminal as set forth in claim 4, wherein when the maintenance optimizing model is established, further comprising:
generating an overall expected cost h of a single overhaul plan according to the overhaul cost f of the single overhaul plan and the fault maintenance cost e of the single overhaul plan;
setting a correction coefficient n according to the maintenance time cost of the maintenance plan;
the overall desired cost of the single service plan h=n×f+e.
6. The maintenance decision method based on the power distribution terminal according to claim 5, wherein when setting the correction coefficient n according to the maintenance time cost of the maintenance plan, comprising:
presetting an overhaul time cost matrix M, and setting M (M1, M2 and M3), wherein M1 is preset first overhaul time cost, M2 is preset second overhaul time cost, M3 is preset third overhaul time cost, and M1 is less than M2 and less than M3;
presetting a correction coefficient value matrix N, and setting N (N1, N2, N3), wherein N1 is a preset first correction coefficient, N2 is a preset second correction coefficient, N3 is a preset third correction coefficient, and 1 is more than N1 and less than N2 is more than N3;
acquiring maintenance time cost m of a maintenance plan and setting a correction coefficient n;
if M1 is more than M and less than or equal to M2, setting a correction coefficient n=n1;
if M2 is more than M and less than or equal to M3, setting a correction coefficient n=n2;
if M is equal to or greater than M3, a correction coefficient n=n3 is set.
7. The service decision method based on the power distribution terminal according to claim 5, wherein when the first-level service decision is modified according to the service optimizing model to generate the second-level service decision, comprising:
acquiring a single feasible maintenance plan, setting a time point when the execution of the feasible maintenance plan is completed as an iteration time node, acquiring real-time evaluation value data of the power distribution terminal again according to the iteration time node, generating a primary maintenance decision, and carrying out iterative calculation;
acquiring expected rejection periods of all power distribution terminals, setting iteration times according to the expected rejection periods, and stopping iteration when the iteration times are reached;
acquiring all feasible overhaul plans of the primary overhaul decision in each iteration period, and generating a secondary overhaul decision, wherein the secondary overhaul decision comprises a plurality of overhaul chains, and the overhaul chains select one feasible overhaul plan in each iteration period;
and generating the overall expected cost of the overhaul chain according to all feasible overhaul plans contained in the overhaul chain, and selecting the overhaul chain with the lowest overall expected cost as an optimizing result.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108182485A (en) * | 2017-12-05 | 2018-06-19 | 中国电力科学研究院有限公司 | A kind of power distribution network maintenance opportunity optimization method and system |
| CN110110933A (en) * | 2019-05-10 | 2019-08-09 | 西南交通大学 | A kind of maintenance circle optimization method of intelligent substation protection system |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7774169B2 (en) * | 2006-06-29 | 2010-08-10 | Toshiba Tec Kabushiki Kaisha | Maintenance system and method |
| CN109376959A (en) * | 2018-12-05 | 2019-02-22 | 广东电网有限责任公司 | A kind of distribution terminal repair time predictor method and device |
| CN109670550B (en) * | 2018-12-20 | 2021-08-24 | 南方电网电力科技股份有限公司 | Power distribution terminal maintenance decision method and device |
| CN113708493B (en) * | 2021-08-26 | 2023-07-28 | 广东电网有限责任公司 | Cloud edge cooperation-based power distribution terminal operation and maintenance method and device and computer equipment |
-
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108182485A (en) * | 2017-12-05 | 2018-06-19 | 中国电力科学研究院有限公司 | A kind of power distribution network maintenance opportunity optimization method and system |
| CN110110933A (en) * | 2019-05-10 | 2019-08-09 | 西南交通大学 | A kind of maintenance circle optimization method of intelligent substation protection system |
Non-Patent Citations (2)
| Title |
|---|
| "Optimal overhaul intervals with imperfect inspection and repair";RICHARD A. DAGG等;《IMA Journal of Management Mathematics ( Volume: 9, Issue: 4, October 1998)》;第1-4页 * |
| "电力市场下发电机组计划检修模型";冯长有等;《电力系统自动化》;第97-104页 * |
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