CN116911626A - System and method for managing and analyzing post-disaster rush repair of power grid - Google Patents
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Abstract
The invention discloses a system and a method for managing and analyzing post-disaster repair of a power grid, and belongs to the technical field of post-disaster repair of the power grid. The method comprises the following steps: acquiring state information of a post-disaster power grid and state information of maintenance personnel; evaluating the maintenance priority of each maintenance point according to the state information of the post-disaster power grid; sequencing the maintenance sequence of each maintenance point according to the maintenance priority to obtain different sequencing modes; and carrying out predictive analysis on different sequencing modes according to the state information of the maintenance personnel, and determining a maintenance strategy according to the result of the predictive analysis. According to the method, the maintenance orders of all maintenance points are ordered according to the maintenance priority, multiple ordering modes are obtained, prediction analysis is carried out on the multiple ordering modes, the optimal solution is selected according to the result of the prediction analysis, and then the post-disaster power grid rush-repair is carried out according to the maintenance strategy, so that economic losses caused by the post-disaster power grid rush-repair can be reduced as much as possible.
Description
Technical Field
The invention relates to a post-disaster maintenance technology of a power grid, in particular to a post-disaster rush repair management analysis system and method of the power grid.
Background
Under extreme environmental conditions, such as typhoons, freezing disasters, snowy disasters and the like, physical faults, such as equipment faults, tripping of a transformer substation, large-scale power failure and the like, of a power grid easily occur, and in order to ensure normal operation of life production of people, timely rush repair is needed for fault lines and fault equipment after the disasters.
For the fault problems which occur independently, materials and personnel can be concentrated to maintain the fault problems, but for the range fault problems which occur after disaster, the influences of various factors on the rush repair speed and the economic loss are required to be considered; the existing rush-repair strategy is mainly used for distributing the rush-repair tasks according to experience of management staff, and the maintenance tasks are further completed by distributing staff through the fault maintenance points.
The existing rush-repair management mode can maintain each fault maintenance point in time, but is difficult to achieve the optimal solution on maintenance progress, personnel allocation and economic loss caused by the personnel allocation, and further cannot minimize the loss caused by the power grid disaster.
Disclosure of Invention
In view of this, in order to solve or improve the above-mentioned bad phenomenon in the prior art, the present invention provides a system and a method for post-disaster emergency repair management and analysis of a power grid, which can minimize the loss caused by post-disaster analysis and management of the power grid.
In order to achieve the above purpose, the present invention provides a method for managing and analyzing post-disaster rush repair of a power grid, comprising: acquiring state information of a post-disaster power grid and state information of maintenance personnel; evaluating the maintenance priority of each maintenance point according to the state information of the post-disaster power grid; sequencing the maintenance sequence of each maintenance point according to the maintenance priority to obtain different sequencing modes; and carrying out predictive analysis on different sequencing modes according to the state information of the maintenance personnel, and determining a maintenance strategy according to the result of the predictive analysis.
In one possible implementation, the maintenance priority evaluation process is:
calculating the priority value of each maintenance point, comparing the priority value with a preset interval set, and determining the corresponding maintenance priority according to the interval in which the priority value falls;
the calculation formula in the maintenance priority evaluation process is as follows:
wherein P is rt Priority values for each maintenance point; d, d rp The maintenance difficulty value is corresponding to the fault type; v (V) imp The important value corresponding to the maintenance point power equipment is obtained; a is that if A regional scope value for the service point impact; a is that 0 Is a regional scope value reference; n (N) user The number of users affected for the service point; n (N) 0 A reference value for the number of users; alpha 1 、α 2 、α 3 Are all preset weight coefficients。
In one possible implementation, the predictive analysis is performed by:
combining maintenance points corresponding to priority values belonging to the same preset interval, and combining maintenance points of different preset intervals;
predicting maintenance point predicted completion time nodes of different combination modes according to state information of maintenance personnel, and establishing recovery state curves of different combination modes according to the predicted completion time nodes;
calculating recovery state values of different combination modes, and selecting a combination mode corresponding to the maximum recovery state value for maintenance;
the calculation formula in the calculated recovery state values of different combination modes is as follows:
wherein R is i (t) is a recovery state curve, i ε N, N is the total number of combinations; t is t max The longest predicted maintenance time in the combination mode; max is a maximum selection function; s is S i To recover the value.
In one possible implementation, the repair point predicted completion time node includes:
determining the number of simultaneous maintenance of the maintenance points and the number of maintenance personnel of each maintenance point according to the number of current personnel and the fault type of the maintenance points;
and predicting the predicted completion time node of the maintenance point according to the number of maintenance personnel and the fault type of the maintenance point.
In one possible implementation manner, the process of acquiring the recovery state curve is:
determining a recovery user number function through a time node of which the maintenance point is expected to finish, and obtaining an average yield value of a recovery user according to the recovery user number function; then calculating a recovery state curve;
the calculation formula in the calculated recovery state curve is as follows:
R i (t)＝Q i (t)*v i (t)
wherein R is i (t) is a recovery state curve; q (Q) i (t) is a recovery user number function; v i (t) recovering the user average yield value.
In one possible implementation, after the maintenance points are assembled, the order of the assembled maintenance points is adjusted according to the expected delivery time of the materials.
In one possible implementation, the adjusting process is:
judging whether the arrival time of the materials can meet the maintenance requirements of the maintenance points according to the sequence of the combined maintenance points;
if yes, carrying out predictive analysis according to the combined maintenance point sequence;
otherwise, the maintenance points which do not meet the maintenance requirements are sequentially postponed backwards, and the adjustment process is repeated until all maintenance points meet the maintenance requirements.
The invention provides a system for managing and analyzing post-disaster rush repair of a power grid, which comprises the following components: the first module is used for acquiring the state information of the post-disaster power grid and the state information of maintenance personnel; the second module is used for evaluating the maintenance priority of each maintenance point according to the state information of the post-disaster power grid; the third module is used for sequencing the maintenance sequence of each maintenance point according to the maintenance priority to obtain different sequencing modes; and carrying out predictive analysis on different sequencing modes according to the state information of the maintenance personnel, and determining a maintenance strategy according to the result of the predictive analysis.
In one possible implementation, the maintenance priority evaluation process is:
calculating the priority value of each maintenance point, comparing the priority value with a preset interval set, and determining the corresponding maintenance priority according to the interval in which the priority value falls;
the calculation formula in the maintenance priority evaluation process is as follows:
wherein d rp The maintenance difficulty value is corresponding to the fault type; v (V) imp The important value corresponding to the maintenance point power equipment is obtained; a is that if A regional scope value for the service point impact; a is that 0 Is a regional scope value reference; n (N) user The number of users affected for the service point; n (N) 0 A reference value for the number of users; alpha 1 、α 2 、α 3 Are all preset weight coefficients.
In one possible implementation, the predictive analysis is performed by:
combining maintenance points corresponding to priority values belonging to the same preset interval, and combining maintenance points of different preset intervals;
predicting maintenance point predicted completion time nodes of different combination modes according to state information of maintenance personnel, and establishing recovery state curves of different combination modes according to the predicted completion time nodes;
calculating recovery state values of different combination modes, and selecting a combination mode corresponding to the maximum recovery state value for maintenance;
the calculation formula in the calculated recovery state values of different combination modes is as follows:
wherein R is i (t) is a recovery state curve, i ε N, N is the total number of combinations; t is t max The longest predicted maintenance time in the combination mode; max is a maximum selection function; s is S i To recover the value.
Advantageous effects
Compared with the prior art, the technical scheme of the invention has the advantages that: according to the invention, the maintenance orders of the maintenance points are ordered according to the maintenance priority, a plurality of ordering modes are obtained, the prediction analysis is carried out on the plurality of ordering modes, the optimal solution is selected according to the result of the prediction analysis, and then the post-disaster power grid rush-repair is carried out according to the maintenance strategy, so that the economic loss caused by the post-disaster power grid rush-repair can be reduced as much as possible.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments of the present invention will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present invention, and other drawings may be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a post-disaster rush repair management analysis method of the power grid of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It will be apparent that the described embodiments are only some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. are based on the directions or positional relationships shown in the drawings, are merely for convenience of describing the present invention and simplifying 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 thus should not be construed as limiting the present invention.
In the description of the present invention, a number means one or more, a number means two or more, and greater than, less than, exceeding, etc. are understood to not include the present number, and above, below, within, etc. are understood to include the present number. The terms "first," "second," "third," and the like, if any, are used for descriptive purposes only and for distinguishing between technical features and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated or implicitly indicating the precedence of the technical features indicated.
In the description of the present invention, 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 above terms in the present invention will be understood in specific cases by those of ordinary skill in the art. In addition, the technical features of the different embodiments of the present invention described below may be combined with each other as long as they do not collide with each other.
Referring to fig. 1, in one embodiment, a method for analyzing post-disaster rush repair management of a power grid is provided, where the method includes steps S1 to S3:
s1, acquiring state information of a post-disaster power grid and state information of maintenance personnel;
s2, evaluating the maintenance priority of each maintenance point according to the state information of the post-disaster power grid;
s3, sorting the maintenance sequence of each maintenance point according to the maintenance priority, and obtaining different sorting modes; and carrying out predictive analysis on different sequencing modes according to the state information of the maintenance personnel, and determining a maintenance strategy according to the result of the predictive analysis.
Through the technical scheme, the post-disaster power grid state information and the maintenance personnel state information are obtained, the maintenance priority of each maintenance point is evaluated according to the post-disaster power grid state information, the maintenance orders of the maintenance points are ordered according to the maintenance priority, multiple ordering modes are obtained, prediction analysis is carried out on the multiple ordering modes, the optimal solution is selected according to the result of the prediction analysis, further post-disaster power grid rush repair is carried out through the maintenance strategy, and economic loss caused by the post-disaster power grid rush repair can be reduced as much as possible.
As one embodiment of the present invention, the maintenance priority determining process is as follows:
by the formulaCalculating the priority value P of each maintenance point rt Will give priority to the value P rt Comparing with the preset interval set, and according to the priority value P rt Determining corresponding maintenance priority in the falling interval;
wherein P is rt Priority values for each maintenance point; d, d rp The maintenance difficulty value is corresponding to the fault type; v (V) imp The important value corresponding to the maintenance point power equipment is obtained; a is that if A regional scope value for the service point impact; a is that 0 Is a regional scope value reference; n (N) user The number of users affected for the service point; n (N) 0 A reference value for the number of users; alpha 1 、α 2 、α 3 Are all preset weight coefficients.
Through the technical scheme, the method for determining the maintenance priority is provided, specifically, comprehensive judgment is carried out according to the fault type, the importance parameter of the maintenance point and the maintenance difficulty, and the method is characterized by comprising the following steps ofCalculating the priority value P of each maintenance point rt The method comprises the steps of carrying out a first treatment on the surface of the Wherein d rp The maintenance difficulty value is corresponding to the fault type; v (V) imp For the corresponding importance value of the maintenance point power equipment, < >>Then the area coverage condition affected by the service point is indicated; />The user condition affected by the service point is indicated; therefore, the maintenance priority of the maintenance point can be judged by integrating a plurality of factors through a formula; then by passing the priority value P rt Comparing with the preset interval set, and according to the priority value P rt The section that falls into determines the corresponding maintenance priority.
The maintenance difficulty value d rp Is determined according to the fault type and different fault typesCorresponding maintenance difficulty value d rp Presetting; important value V corresponding to maintenance point power equipment imp According to the type of the power equipment, determining the importance value V corresponding to different power equipment types imp Presetting; preset weight coefficient alpha 1 、α 2 、α 3 Selectively set based on empirical data, not described in detail herein; it should be noted that, the intervals in the preset interval set are set according to the empirical data, and pass through the priority value P rt And comparing and judging with a preset interval set.
As one embodiment of the present invention, the process of performing predictive analysis is:
combining maintenance points of which the priority values belong to the same preset interval, and combining maintenance points of different preset intervals;
predicting maintenance point predicted completion time nodes of different combination modes according to maintenance personnel state information, and establishing recovery state curves R of different combination modes according to the predicted completion time nodes i (t), i E N, N is the total number of combination modes;
by the formulaCalculating recovery values S of different combination modes i Selecting max (S i ) Maintaining the corresponding combination mode;
wherein R is i (t) is a recovery state curve, i ε N, N is the total number of combinations; t is t max The longest predicted maintenance time in the combination mode; max is a maximum selection function; s is S i To recover the value.
Through the above technical solution, this embodiment provides a method for performing prediction analysis, first, the method includes combining the repair points corresponding to the priority value of a preset interval according to the repair points belonging to the same preset interval, and then combining the repair points of different preset intervals, so as to obtain multiple repair sequence combination schemes, and predicting the predicted completion time nodes of each repair point in different combination modes according to the number of current repair personnel, so as to establish recovery state curves of different combination modes according to the predicted completion time nodesLine R i (t); wherein the state curve R is restored i (t) may be one or more combinations of parameters of the number of recovered users, the area of the power recovery area, etc., thus passing through the formulaCan calculate the recovery state value S of different combination modes i Obviously restore the state value S i The larger the value, the better the recovery effect, so max (S i ) And the corresponding combination mode is maintained, so that the optimal solution can be obtained, and the loss caused by the combination mode is minimized.
As one embodiment of the present invention, the predicted process of the maintenance point predicted completion time node is:
determining the number of simultaneous maintenance of the maintenance points and the number of maintenance personnel of each maintenance point according to the number of current personnel and the fault type of the maintenance points;
and predicting the predicted completion time node of the maintenance point according to the number of maintenance personnel and the fault type of the maintenance point.
Through the technical scheme, the embodiment provides a predicting process of the predicted completion time node of the maintenance point, wherein the number of maintenance points for simultaneous maintenance and the number of maintenance personnel of each maintenance point are firstly determined according to the number of current personnel and the fault type of the maintenance point, and then the predicted completion time node of the maintenance point is predicted according to the number of maintenance personnel and the fault type of the maintenance point.
It should be noted that, the distribution of the number of maintenance personnel is determined according to the average personnel demand number and the total number corresponding to the fault type, and the predicted completion time node is determined according to the fault type and the number of maintenance personnel based on the empirical data, which will not be described in detail herein.
As one embodiment of the present invention, the recovery state curve obtaining process is as follows:
determining a recovery user number function Q by a time node of a maintenance point predicted to be completed i (t) according to Q i (t) obtaining a recovered user average yield value v i (t)；
By the formula R i (t)＝Q i (t)*v i (t) obtaining recoveryComplex state curve R i (t)。
Through the above technical solution, the present embodiment provides a process for obtaining a recovery state curve, which is determined according to the number of users and the output value related to the users, and determines the recovery user number function Q through the time node of the expected completion of the maintenance point i (t) by recovering the user number function Q i (t) determining the average yield function v of the recovery user i (t) thus passing through the formula R i (t)＝Q i (t)*v i (t) obtaining a recovery State Curve R i (t) further comprehensively recovering the number of users and judging the phase-change economic damage condition caused by the users, and further passing through a formulaAnd calculating a combination mode with the fastest recovery user number and minimum economic loss.
As one embodiment of the present invention, after completion of the combination of the maintenance points, the order of the maintenance points after the combination is adjusted according to the estimated delivery time of the materials.
The adjusting process comprises the following steps:
judging whether the arrival time of the materials can meet the maintenance requirements of the maintenance points according to the sequence of the combined maintenance points;
if yes, carrying out predictive analysis according to the combined maintenance point sequence;
otherwise, the maintenance points which do not meet the maintenance requirements are sequentially postponed backwards, and the adjustment process is repeated until all maintenance points meet the maintenance requirements.
The embodiment also provides a system for managing and analyzing the post-disaster rush-repair of the power grid, which comprises the following steps: the first module is used for acquiring the state information of the post-disaster power grid and the state information of maintenance personnel; the second module is used for evaluating the maintenance priority of each maintenance point according to the state information of the post-disaster power grid; the third module is used for sequencing the maintenance sequence of each maintenance point according to the maintenance priority to obtain different sequencing modes; and carrying out predictive analysis on different sequencing modes according to the state information of the maintenance personnel, and determining a maintenance strategy according to the result of the predictive analysis.
In one possible embodiment, the maintenance priority evaluation process is:
calculating the priority value of each maintenance point, comparing the priority value with a preset interval set, and determining the corresponding maintenance priority according to the interval in which the priority value falls;
the calculation formula in the maintenance priority evaluation process is as follows:
wherein d rp The maintenance difficulty value is corresponding to the fault type; v (V) imp The important value corresponding to the maintenance point power equipment is obtained; a is that if A regional scope value for the service point impact; a is that 0 Is a regional scope value reference; n (N) user The number of users affected for the service point; n (N) 0 A reference value for the number of users; alpha 1 、α 2 、α 3 Are all preset weight coefficients.
In one possible embodiment, the predictive analysis is performed by:
combining maintenance points corresponding to priority values belonging to the same preset interval, and combining maintenance points of different preset intervals;
predicting maintenance point predicted completion time nodes of different combination modes according to state information of maintenance personnel, and establishing recovery state curves of different combination modes according to the predicted completion time nodes;
calculating recovery state values of different combination modes, and selecting a combination mode corresponding to the maximum recovery state value for maintenance;
the calculation formula in the calculated recovery state values of different combination modes is as follows:
wherein R is i (t) is a recovery state curve, i ε N, NIs the total number of the combination modes; t is t max The longest predicted maintenance time in the combination mode; max is a maximum selection function; s is S i To recover the value.
Those of ordinary skill in the art will appreciate that the elements of the examples described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the elements of the examples have been described generally in terms of functionality in the foregoing description to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the division of the units is merely a logic function division, and there may be other division manners in actual implementation, for example, multiple units may be combined into one unit, one unit may be split into multiple units, or some features may be omitted.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-0nlyMemory (ROM), a random access memory (RAM, randomAccessMemory), a removable hard disk, a magnetic disk, or an optical disk, or the like, which can store program codes.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention, and are intended to be included within the scope of the appended claims and description.
Claims (10)
1. The method for managing and analyzing the post-disaster rush repair of the power grid is characterized by comprising the following steps of:
acquiring state information of a post-disaster power grid and state information of maintenance personnel;
evaluating the maintenance priority of each maintenance point according to the state information of the post-disaster power grid;
sequencing the maintenance sequence of each maintenance point according to the maintenance priority to obtain different sequencing modes; and carrying out predictive analysis on different sequencing modes according to the state information of the maintenance personnel, and determining a maintenance strategy according to the result of the predictive analysis.
2. The method for post-disaster repair management analysis of a power grid according to claim 1, wherein the evaluation process of the maintenance priority is as follows:
calculating the priority value of each maintenance point, comparing the priority value with a preset interval set, and determining the corresponding maintenance priority according to the interval in which the priority value falls;
the calculation formula in the maintenance priority evaluation process is as follows:
wherein P is rt Priority values for each maintenance point; d, d rp The maintenance difficulty value is corresponding to the fault type; v (V) imp The important value corresponding to the maintenance point power equipment is obtained; a is that if A regional scope value for the service point impact; a is that 0 Is a regional scope value reference; n (N) user The number of users affected for the service point; n (N) 0 A reference value for the number of users; alpha 1 、α 2 、α 3 Are all preset weight coefficients.
3. The method for post-disaster rush repair management analysis of a power grid according to claim 1, wherein the predictive analysis process is as follows:
combining maintenance points corresponding to priority values belonging to the same preset interval, and combining maintenance points of different preset intervals;
predicting maintenance point predicted completion time nodes of different combination modes according to state information of maintenance personnel, and establishing recovery state curves of different combination modes according to the predicted completion time nodes;
calculating recovery state values of different combination modes, and selecting a combination mode corresponding to the maximum recovery state value for maintenance;
the calculation formula in the calculated recovery state values of different combination modes is as follows:
wherein R is i (t) is a recovery state curve, i ε N, N is the total number of combinations; t is t max The longest predicted maintenance time in the combination mode; max is a maximum selection function; s is S i To recover the value.
4. The method of claim 3, wherein the maintenance point predicted completion time node comprises:
determining the number of simultaneous maintenance of the maintenance points and the number of maintenance personnel of each maintenance point according to the number of current personnel and the fault type of the maintenance points;
and predicting the predicted completion time node of the maintenance point according to the number of maintenance personnel and the fault type of the maintenance point.
5. The method for post-disaster repair management analysis of a power grid according to claim 3, wherein the process of obtaining the recovery state curve is as follows:
determining a recovery user number function through a time node of which the maintenance point is expected to finish, and obtaining an average yield value of a recovery user according to the recovery user number function; then calculating a recovery state curve;
the calculation formula in the calculated recovery state curve is as follows:
R i (t)＝Q i (t)*v i (t)
wherein R is i (t) is a recovery state curve; q (Q) i (t) is a recovery user number function; v i (t) recovering the user average yield value.
6. The method for post-disaster repair management analysis of power grid according to claim 3, wherein after completion of the combination of maintenance points, the order of the maintenance points after combination is adjusted according to the estimated delivery time of the materials.
7. The method for post-disaster repair management analysis of a power grid according to claim 3, wherein the adjusting process is as follows:
judging whether the arrival time of the materials can meet the maintenance requirements of the maintenance points according to the sequence of the combined maintenance points;
if yes, carrying out predictive analysis according to the combined maintenance point sequence;
otherwise, the maintenance points which do not meet the maintenance requirements are sequentially postponed backwards, and the adjustment process is repeated until all maintenance points meet the maintenance requirements.
8. The utility model provides a power grid post-disaster rush repair management analysis system which is characterized in that the system comprises:
the first module is used for acquiring the state information of the post-disaster power grid and the state information of maintenance personnel;
the second module is used for evaluating the maintenance priority of each maintenance point according to the state information of the post-disaster power grid;
the third module is used for sequencing the maintenance sequence of each maintenance point according to the maintenance priority to obtain different sequencing modes; and carrying out predictive analysis on different sequencing modes according to the state information of the maintenance personnel, and determining a maintenance strategy according to the result of the predictive analysis.
9. The system for post-disaster repair management analysis of a power grid according to claim 8, wherein the evaluation process of the maintenance priority is as follows:
calculating the priority value of each maintenance point, comparing the priority value with a preset interval set, and determining the corresponding maintenance priority according to the interval in which the priority value falls;
the calculation formula in the maintenance priority evaluation process is as follows:
wherein d rp The maintenance difficulty value is corresponding to the fault type; v (V) imp The important value corresponding to the maintenance point power equipment is obtained; a is that if A regional scope value for the service point impact; a is that 0 Is a regional scope value reference; n (N) user The number of users affected for the service point; n (N) 0 A reference value for the number of users; alpha 1 、α 2 、α 3 Are all preset weight coefficients.
10. The system for post-disaster repair management analysis of a power grid according to claim 8, wherein the predictive analysis process is as follows:
combining maintenance points corresponding to priority values belonging to the same preset interval, and combining maintenance points of different preset intervals;
predicting maintenance point predicted completion time nodes of different combination modes according to state information of maintenance personnel, and establishing recovery state curves of different combination modes according to the predicted completion time nodes;
calculating recovery state values of different combination modes, and selecting a combination mode corresponding to the maximum recovery state value for maintenance;
the calculation formula in the calculated recovery state values of different combination modes is as follows:
wherein R is i (t) is a recovery state curve, i ε N, N is the total number of combinations; t is t max The longest predicted maintenance time in the combination mode; max is a maximum selection function; s is S i To recover the value.
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| CN117310394A (en) * | 2023-11-29 | 2023-12-29 | 天津市英环信诚科技有限公司 | Big data-based power failure detection method and device, electronic equipment and medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117310394A (en) * | 2023-11-29 | 2023-12-29 | 天津市英环信诚科技有限公司 | Big data-based power failure detection method and device, electronic equipment and medium |
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