Human resource scheduling and distribution methods applied to power systems

Abstract

This invention belongs to the field of human resource allocation and discloses a method for scheduling and distributing human resources in power systems. The method includes: S1, calculating the emergency repair coefficient of power equipment in each power supply station within the scheduling range, including: S10, obtaining historical damage parameters of power equipment in each power supply station within a set time period; S20, calculating a first emergency repair coefficient based on the historical damage parameters; S30, obtaining detection images of power equipment in each power supply station; S40, calculating a second emergency repair coefficient for each power supply station based on the detection images; S50, calculating the emergency repair coefficient of power equipment in each power supply station based on the first and second emergency repair coefficients. S2, generating a set of emergency repair personnel for each power supply station based on the emergency repair coefficients; S3, distributing the set of emergency repair personnel to each power supply station. This invention improves the accuracy of estimating the probability of power equipment damage and achieves more effective human resource scheduling.

Description

Technical Field

[0001] This invention relates to the field of human resource allocation, and more particularly to a method for scheduling and distributing human resources in power systems. Background Technology

[0002] In the process of preventing and responding to power disasters, it is usually necessary to allocate human resources to each power supply station in advance so that when events causing damage to outdoor power equipment occur during disaster-prone periods (such as typhoon seasons or rainy seasons), timely repairs can be carried out. Since the number and probability of power equipment damage events vary depending on the location of the power supply station, current technology typically uses the historical number of power equipment damage events within its jurisdiction as an indicator for allocating human resources for emergency repairs at each power supply station. However, this method of allocating human resources has a drawback: historical data can only be used as a reference and does not represent the probability of subsequent disaster damage to power equipment. This can lead to a significant discrepancy between the dispatch plan obtained when using historical data as an indicator for human resource allocation and the actual degree of matching between the two. For example, power supply stations with a high incidence of power equipment damage may have insufficient personnel for emergency repairs, resulting in many damaged power equipment not being repaired in a timely manner. Summary of the Invention

[0003] The purpose of this invention is to disclose a method for scheduling and distributing human resources in power systems, which addresses the problem of how to improve the accuracy of the estimation results of the probability of damage to power equipment, thereby improving the accuracy of human resource allocation, and thus causing an excessively high probability of events where power equipment cannot be repaired in a timely manner.

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] This invention provides a method for scheduling and distributing human resources in power systems, including:

[0006] S1, calculates the emergency repair coefficient of power equipment in each power supply station within the dispatch range;

[0007] S2 generates a set of emergency repair personnel for each power supply station based on the emergency repair coefficient of power equipment;

[0008] S3, to gather and distribute the emergency repair personnel to various power supply stations;

[0009] The calculation of the emergency repair coefficient for power equipment at each power supply station within the dispatch range includes:

[0010] S10, obtain historical damage parameters of power equipment in each power supply station within a set time period;

[0011] S20, calculate the first emergency repair coefficient based on historical damage parameters;

[0012] S30: Obtain detection images of power equipment in each power supply station;

[0013] S40, calculates the second emergency repair coefficient for each power supply station based on the detected image;

[0014] S50, calculate the emergency repair coefficient of power equipment in each power supply station based on the first emergency repair coefficient and the second emergency repair coefficient.

[0015] Preferably, the historical damage parameters include the number of electrical equipment damaged by disasters within the jurisdiction of the power supply station and the probability of the electrical equipment being damaged by disasters within a set time period.

[0016] Preferably, the first emergency repair coefficient is calculated based on historical damage parameters, including:

[0017] The first emergency repair coefficient is calculated using the following formula:

[0018]

[0019] emerep h,1 numdam represents the first emergency repair coefficient of power supply station h. h This represents the number of electrical devices damaged by a disaster within the jurisdiction of power supply station h during a specified time period. h This indicates the total number of electrical devices within the jurisdiction of power supply station h during a set time period. h This represents the probability that electrical equipment within the jurisdiction of power supply station h will be damaged by a disaster during a set time period. max `dist` represents the maximum distance between power equipment within the jurisdiction of power supply station `h` and power supply station `h` within a specified time period. `splu` represents the maximum distance between all power equipment outside the jurisdiction of power supply station `h` and power supply station `h` whose distance is less than `dist`. max A collection of electrical equipment, dist i numsplu represents the distance between power device i and power supply station h in splu, w1, w2 and w3 represent the quantity weight, probability weight and distance weight set respectively.

[0020] Preferably, acquiring detection images of the power equipment at each power supply station includes:

[0021] Obtain the set of power equipment that needs to be detected and image acquired for each power supply station;

[0022] The appearance of each power device in the set of power devices that need to be inspected for each power supply station is photographed to obtain the inspection image of the power device.

[0023] Preferably, the calculation of the second emergency repair coefficient for each power supply station based on the detected image includes:

[0024] For power supply station h, use aerimgu h This represents the set of power equipment corresponding to power supply station h that requires image acquisition for detection;

[0025] Obtain aerimgu respectively h The defect coefficient of each electrical device in the system;

[0026] Based on aerimgu h The defect coefficient of all electrical equipment is calculated as the second emergency repair coefficient of power supply station h.

[0027] Preferably, aerimgu is obtained respectively. h The defect coefficient for each electrical device in the data includes:

[0028] For aerimgu h Electrical equipment b in the middle, using imgcol b This represents the set of detected images corresponding to power equipment b;

[0029] Get imgcol respectively b The number of defects of a preset type contained in each detected image;

[0030] Based on imgcol b Calculate the defect coefficient of power equipment b by counting the number of defects of the preset type present in all detected images.

[0031] Preferably, imgcol is obtained respectively. b The number of defects of a preset type contained in each detected image, including:

[0032] imgcol b Each detected image is input into a pre-trained defect detection model for identification, and the defect detection model outputs the type of defect present in each detected image and the location of each defect.

[0033] Preferably, based on imgcol b The number of preset types of defects present in all detected images is used to calculate the defect coefficient of power equipment b, including:

[0034] The defect coefficient of power equipment b is calculated using the following formula:

[0035]

[0036] defcef b numdef represents the defect coefficient of electrical equipment b. b imgcol b The total number of defects of the preset type present in all detected images, numpx b imgcol b The maximum number of defects of a preset type present in a single detected image across all detected images, where numd represents imgcol. b The total number of detected images.

[0037] Preferably, based on aerimgu h The defect coefficient of all electrical equipment is calculated, and the second emergency repair coefficient of power supply station h is included, including:

[0038] The second emergency repair coefficient is calculated using the following formula:

[0039]

[0040] emerep h,2 Denotes the second emergency repair coefficient of power supply station h, defcef j Represents aerimgu h The defect coefficient of electrical equipment j in the middle, naerimg u Represents aerimgu h The total number of electrical devices j in the system, varaerimg u Represents aerimgu h The standard deviation of the defect coefficient of electrical equipment in the data, defcef max and defcef mid They represent aerimgu respectively h The maximum and median of the defect coefficients of the power equipment in the data; δ1 and δ2 represent the mean weight and standard deviation weight, respectively.

[0041] Preferably, the emergency repair coefficient for each power supply station is calculated based on the first emergency repair coefficient and the second emergency repair coefficient, including:

[0042] For power supply station h, the formula for calculating its corresponding power equipment emergency repair coefficient is:

[0043]

[0044] emerep h,1 and emerep h,2Let eleequ represent the first and second emergency repair coefficients of power supply station h, respectively, and let eleequ represent the set of all power supply stations within the dispatch range. k,1 and emerep k,2 These represent the first and second emergency repair coefficients of power supply station k, respectively.

[0045] Beneficial effects:

[0046] Compared to existing methods that rely solely on historical damage data of power equipment to represent the probability of equipment damage and then allocate personnel for emergency repairs based on this data, this invention goes beyond simply representing the probability of damage based on historical data. It incorporates the latest technology: calculating a second emergency repair coefficient using captured inspection images. This second and first emergency repair coefficients are then combined to obtain the emergency repair coefficient for each power supply station, improving the accuracy of the probability estimation. The emergency repair coefficient is then used to allocate repair personnel to power supply stations within the dispatch area. This significantly improves the accuracy of the probability of equipment damage, enabling more efficient allocation of human resources for power repair and substantially reducing the probability of damaged power equipment not being repaired in a timely manner. Attached Figure Description

[0047] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] Figure 1 This is a schematic diagram of the human resource scheduling and distribution method of the present invention applied to the power system.

[0049] Figure 2 This is a schematic diagram illustrating the process of the power equipment emergency repair coefficient of the present invention. Detailed Implementation

[0050] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0051] like Figure 1As shown, this invention provides a method for scheduling and distributing human resources in a power system, including:

[0052] S1, calculates the emergency repair coefficient of power equipment in each power supply station within the dispatch range;

[0053] S2 generates a set of emergency repair personnel for each power supply station based on the emergency repair coefficient of power equipment;

[0054] S3, to gather and distribute the emergency repair personnel to various power supply stations;

[0055] Among them, such as Figure 2 As shown, the calculation of the emergency repair coefficient for power equipment at each power supply station within the dispatch range includes:

[0056] S10, obtain historical damage parameters of power equipment in each power supply station within a set time period;

[0057] S20, calculate the first emergency repair coefficient based on historical damage parameters;

[0058] S30: Obtain detection images of power equipment in each power supply station;

[0059] S40, calculates the second emergency repair coefficient for each power supply station based on the detected image;

[0060] S50, calculate the emergency repair coefficient of power equipment in each power supply station based on the first emergency repair coefficient and the second emergency repair coefficient.

[0061] The aforementioned human resource dispatching process not only represents the probability of power equipment damage based on historical data, but also incorporates the latest maintenance images obtained through photography to calculate a second emergency repair coefficient. This second and first emergency repair coefficients are then combined to obtain the power equipment emergency repair coefficient for each power supply station, improving the accuracy of the probability estimation. Subsequently, repair personnel are allocated to power supply stations within the dispatching area based on these emergency repair coefficients. In this way, because the accuracy of the probability of power equipment damage is effectively improved, more efficient dispatching of human resources for power repair is achieved, significantly reducing the probability of damaged power equipment not being repaired in a timely manner.

[0062] Preferably, in this invention, electrical equipment refers to primary equipment located outdoors. Primary equipment refers to equipment that directly participates in the production, transmission and distribution of electrical energy. They are the core part of the power system and are in direct contact with high-voltage and high-current electricity.

[0063] Primary equipment mainly includes:

[0064] Generator: A device that converts mechanical energy into electrical energy.

[0065] Transformer: A device used to increase or decrease voltage.

[0066] Circuit breaker: Used to control the opening and closing of circuits and protect circuits from overload or short circuit damage.

[0067] Disconnecting switch: Used to switch circuits when there is no load.

[0068] Busbar: A conductor used to connect various electrical devices.

[0069] Cables and transmission lines: used to transmit electrical energy.

[0070] Power capacitors and reactors: used to improve the power factor and stability of power systems.

[0071] Preferably, the dispatching range refers to the area under the jurisdiction of the power company in the prefecture-level city.

[0072] Preferably, the historical damage parameters include the number of electrical equipment damaged by disasters within the jurisdiction of the power supply station and the probability of the electrical equipment being damaged by disasters within a set time period.

[0073] The probability of electrical equipment being damaged by a disaster is obtained by dividing the number of electrical equipment damaged by the disaster by the total number of electrical equipment within the jurisdiction of the power supply station.

[0074] Preferably, the time period is the most recent five years.

[0075] For example, if the date of running this invention is June 1, 2024, then the time period is set from June 1, 2019 to June 1, 2024.

[0076] Preferably, the first emergency repair coefficient is calculated based on historical damage parameters, including:

[0077] The first emergency repair coefficient is calculated using the following formula:

[0078]

[0079] emerep h,1 numdam represents the first emergency repair coefficient of power supply station h. h This represents the number of electrical devices damaged by a disaster within the jurisdiction of power supply station h during a specified time period. h This indicates the total number of electrical devices within the jurisdiction of power supply station h during a set time period. h This represents the probability that electrical equipment within the jurisdiction of power supply station h will be damaged by a disaster during a set time period. max`dist` represents the maximum distance between power equipment within the jurisdiction of power supply station `h` and power supply station `h` within a specified time period. `splu` represents the maximum distance between all power equipment outside the jurisdiction of power supply station `h` and power supply station `h` whose distance is less than `dist`. max A collection of electrical equipment, dist i numsplu represents the distance between power device i and power supply station h in splu, w1, w2 and w3 represent the quantity weight, probability weight and distance weight set respectively.

[0080] The first emergency repair coefficient of this invention is calculated comprehensively from three aspects: the number of damages, the probability of damage, and the distance between the power equipment and other power supply stations within their jurisdiction. The larger the number of damages, the higher the probability of damage, and the closer the distance to other power supply stations' equipment, the larger the first emergency repair coefficient, indicating greater emergency repair pressure on the power supply station and the need for more repair personnel through dispatch. Unlike general calculation methods, this invention also incorporates the distance to power equipment outside its jurisdiction when calculating the first emergency repair coefficient reflecting the emergency repair pressure faced by the power supply station. Thus, when a disaster occurs and the emergency repair pressure within the power supply station's jurisdiction is relatively low, while the pressure on neighboring power supply stations is relatively high, this invention, through its dispatching process, directs repair personnel to locations closer to the disaster-affected power equipment, thereby improving the efficiency of normal emergency repairs to the affected power equipment.

[0081] Preferably, the quantity weight, probability weight, and distance weight are respectively and

[0082] In this invention, jurisdiction refers to the area with jurisdiction over electricity.

[0083] Preferably, acquiring detection images of the power equipment at each power supply station includes:

[0084] Obtain the set of power equipment that needs to be detected and image acquired for each power supply station;

[0085] The appearance of each power device in the set of power devices that need to be inspected for each power supply station is photographed to obtain the inspection image of the power device.

[0086] In this invention, the acquisition of detection images can be achieved using means such as drones. The acquisition can take place up to one week prior to obtaining a human resource scheduling plan for emergency repairs.

[0087] Preferably, when photographing the appearance of power equipment, multiple detection images with a certain overlap between adjacent positions are captured to achieve full coverage of the appearance of the power equipment.

[0088] Preferably, the overlap ratio is 10%.

[0089] Preferably, the set of power equipment corresponding to each power supply station that needs to have its images acquired is obtained, including:

[0090] For power supply station h, obtain the set of power equipment belonging to the primary equipment in power supply station h, elemah. h ;

[0091] Obtain a plan view P containing the complete jurisdiction of power supply station h. h ;

[0092] In P h In the diagram, the boundary of the jurisdiction of power supply station h is marked as a closed area. h ;

[0093] In P h Get Cloare h The minimum bounding rectangle of bourec h ;

[0094] bourec h Divide the first range into multiple preset sizes, and delete the first range that does not include the jurisdiction of the power supply station h;

[0095] Obtain the damage characteristic parameters of the power equipment in each first range;

[0096] The first range is merged based on the characteristic parameters of power equipment damage to obtain the second range;

[0097] Each of the second ranges contains the electrical equipment for which image acquisition is required;

[0098] All power devices within the second range that require image acquisition are saved to the set of power devices requiring image acquisition corresponding to power supply station h.

[0099] Since different power supply stations have varying jurisdictions and the number of power devices affected by disasters within their jurisdictions differ, relying solely on the size of the jurisdiction or the number of power devices within it as the basis for capturing detection images can easily result in capturing too many invalid detection images in areas with a low probability of power device damage, thus affecting the efficiency of image acquisition. Therefore, this invention obtains a first range and then a second range based on the power device damage characteristic parameters. This avoids capturing detection images of all power devices, improving efficiency. Furthermore, it avoids determining the number of power devices to be photographed solely based on the number of devices and the size of the jurisdiction, improving the representativeness of the calculation results when calculating the second emergency repair coefficient based on the captured detection images.

[0100] Preferably, bourec h The first range is divided into multiple preset sizes, including:

[0101] Using L respectively h and W h indicates bourec h Length and width;

[0102] bourec h Divided into multiple sizes The first range.

[0103] H is a pre-set positive integer, which is related to the maximum area of ​​the jurisdiction of all power supply stations within the dispatch range. The larger the maximum area, the larger H is.

[0104] Preferably, H is 20.

[0105] Preferably, the damage characteristic parameters of the power equipment in each first range are obtained, including:

[0106] For the first range z;

[0107] Get the values ​​within the range of z that belong to elemah. h A collection of electrical equipment elemh z ;

[0108] Get elemh respectively z The operation and maintenance records for each power device within a set time period include the type of fault that occurred in the power device and the time when the fault occurred.

[0109] Within the set time period, elemh z Among all electrical equipment, the fault that occurs most frequently and the month with the most faults are used as the electrical equipment damage characteristic parameters for z.

[0110] The purpose of obtaining the damage characteristic parameters of power equipment is to subsequently obtain the second range. When the damage characteristic parameters of power equipment in multiple adjacent first ranges are similar, only one power equipment needs to be selected as the target for the detection image. This can effectively reduce the number of detection images that need to be captured and improve the representativeness of the detection images, enabling the present invention to determine the maintenance pressure of different power supply stations more quickly.

[0111] Preferably, the first range is merged based on the characteristic parameters of power equipment damage to obtain a second range, including:

[0112] The first step is to store all the first ranges into the collection firloc;

[0113] The second step is to randomly select a first range from firloc as the current range and save the current range to the temporary set of the second range.

[0114] The third step is to save all first ranges adjacent to the current range in firloc to the adjacent set;

[0115] The fourth step is to determine whether the adjacent set is empty. If it is, proceed to the fifth step; otherwise, proceed to the seventh step.

[0116] Fifth step: Create a new second-range set, save the elements in the second-range temporary set to the second-range set, delete the elements in the second-range temporary set from firloc, clear the second-range temporary set, and clear the adjacent set;

[0117] Step 6: Determine if firloc is an empty set. If it is, output all the second range sets, and form a second range by the elements in each second range set; otherwise, proceed to step 2.

[0118] Step 7: Calculate the similarity between each first range in the adjacent set and the current range based on the power equipment damage characteristic coefficients;

[0119] Step 8: Determine if the maximum similarity is greater than the preset similarity. If yes, proceed to step 9; otherwise, proceed to step 12.

[0120] Step 9: Save the first range corresponding to the maximum similarity to the second range temporary set, and delete the first range corresponding to the maximum similarity from firloc;

[0121] Step 10: Determine if firloc is an empty set. If it is, output all the second range sets, and form a second range by the elements in each second range set. If not, proceed to step 11.

[0122] Step 11: Take the first range corresponding to the maximum similarity as the new current range, clear the adjacent set, and proceed to step 3;

[0123] Step 12: Create a new second-range set, save the elements in the second-range temporary set to the second-range set, clear the second-range temporary set, and clear the adjacent set;

[0124] Step 13: Determine if firloc is an empty set. If it is, output all the second range sets, and form a second range by the elements in each second range set. If not, proceed to step 2.

[0125] In the aforementioned merging process, this invention merges first regions with similar damaged characteristic parameters of power equipment, thereby reducing the number of power devices that need to be photographed. Furthermore, during the merging process, this invention continuously expands the range of the second region based on similarity, avoiding gaps within the second region and improving the effectiveness of subsequently acquiring images of the power equipment requiring photographing and detection based on the second region.

[0126] Preferably, the similarity between each first range in the adjacent set and the current range is calculated based on the power equipment damage characteristic coefficient, including:

[0127] For the first range A and the current range B in the adjacent set;

[0128] The formula for calculating the similarity between A and B is:

[0129]

[0130] sim A,B Jug represents the similarity between A and B. A，B The judgment value represents the fault type. If the most frequent fault types in A and B are the same, then jug A，B If it is 1, otherwise, jug A，B For 11, mon A and mon B These represent the months with the highest number of failures in A and B, respectively.

[0131] Similarity is calculated from two perspectives: the type of fault and the month with the most faults. When the types of faults are the same and the months with the most faults are close, the higher the similarity, the closer the probability that the power equipment in the two ranges will be affected by the disaster.

[0132] Preferably, the preset similarity is 0.8.

[0133] Preferably, the process involves acquiring images of the electrical equipment requiring detection within each second range, including:

[0134] Calculate the acquisition coefficient of power equipment;

[0135] The power equipment with the highest acquisition coefficient is selected as the power equipment for which image acquisition is required.

[0136] In this invention, the emergency repair pressure of power equipment in the second range can be effectively represented by a detection image of the power equipment, reducing the number of detection images taken and improving the speed of obtaining a scheduling plan.

[0137] Preferably, the formula for calculating the coefficient is as follows:

[0138]

[0139] obtcof v Desyear represents the acquisition coefficient of power equipment v. v This indicates the number of years in which electrical equipment v will be replaced; wrkyear indicates the number of years electrical equipment v has been in operation; distzs v Distzs represents the distance between the center of the electrical equipment v and the center of the second range. max This represents the farthest distance between the center of the second range and the edge of the second range.

[0140] The fewer years the power equipment has been in operation and the greater the distance between it and the center of the second range, the lower the probability of it being selected as the subject of the detection image. This calculation method can effectively improve the representativeness of the detection images.

[0141] Preferably, the calculation of the second emergency repair coefficient for each power supply station based on the detected image includes:

[0142] For power supply station h, use aerimgu h This represents the set of power equipment corresponding to power supply station h that requires image acquisition for detection;

[0143] Obtain aerimgu respectively h The defect coefficient of each electrical device in the system;

[0144] Based on aerimgu h The defect coefficient of all electrical equipment is calculated as the second emergency repair coefficient of power supply station h.

[0145] Preferably, aerimgu is obtained respectively. h The defect coefficient for each electrical device in the data includes:

[0146] For aerimgu hElectrical equipment b in the middle, using imgcol b This represents the set of detected images corresponding to power equipment b;

[0147] Get imgcol respectively b The number of defects of a preset type contained in each detected image;

[0148] Based on imgcol b Calculate the defect coefficient of power equipment b by counting the number of defects of the preset type present in all detected images.

[0149] Preferably, the preset type of defects includes rust, foreign matter adhesion, cracks, dents, and bending.

[0150] Preferably, imgcol is obtained respectively. b The number of defects of a preset type contained in each detected image, including:

[0151] imgcol b Each detected image is input into a pre-trained defect detection model for identification, and the defect detection model outputs the type of defect present in each detected image and the location of each defect.

[0152] The detection model can accurately output the type and location of defects.

[0153] Preferably, the pre-trained defect detection model is an R-CNN model.

[0154] Preferably, based on imgcol b The number of preset types of defects present in all detected images is used to calculate the defect coefficient of power equipment b, including:

[0155] The defect coefficient of power equipment b is calculated using the following formula:

[0156]

[0157] defcef b numdef represents the defect coefficient of electrical equipment b. b imgcol b The total number of defects of the preset type present in all detected images, numpx b imgcol b The maximum number of defects of a preset type present in a single detected image across all detected images, where numd represents imgcol. b The total number of detected images.

[0158] The more defects there are, the higher the defect coefficient, indicating greater pressure for emergency repairs.

[0159] Preferably, based on aerimgu h The defect coefficient of all electrical equipment is calculated, and the second emergency repair coefficient of power supply station h is included, including:

[0160] The second emergency repair coefficient is calculated using the following formula:

[0161]

[0162] emerep h,2 Denotes the second emergency repair coefficient of power supply station h, defcef j Represents aerimgu h The defect coefficient of electrical equipment j in the middle, naerimg u Represents aerimgu h The total number of electrical devices j in the system, varaerimg u Represents aerimgu h The standard deviation of the defect coefficient of electrical equipment in the data, defcef max and defcef mid They represent aerimgu respectively h The maximum and median of the defect coefficients of the power equipment in the data; δ1 and δ2 represent the mean weight and standard deviation weight, respectively.

[0163] The second emergency repair coefficient is calculated from both the mean and variance of the defect coefficient. This avoids the influence of individual power equipment with excessively large defect coefficients on the final second emergency repair coefficient, which would otherwise reduce the accuracy of representing the emergency repair pressure on power equipment within the jurisdiction of the power supply station.

[0164] Preferably, the mean weight and the standard deviation weight are respectively and

[0165] Preferably, the emergency repair coefficient for each power supply station is calculated based on the first emergency repair coefficient and the second emergency repair coefficient, including:

[0166] For power supply station h, its corresponding emergency repair coefficient for power equipment is eleemerep h The calculation formula is:

[0167]

[0168] emerep h,1 and emerep h,2Let eleequ represent the first and second emergency repair coefficients of power supply station h, respectively, and let eleequ represent the set of all power supply stations within the dispatch range. k,1 and emerep k,2 These represent the first and second emergency repair coefficients of power supply station k, respectively.

[0169] The power equipment emergency repair coefficient combines a first emergency repair coefficient based on historical data and a second emergency repair coefficient based on the latest detection images. This makes the probability of power equipment damage within the jurisdiction of the power supply station more accurate, which can improve the accuracy of human resource allocation and reduce the probability of power equipment not being repaired in a timely manner.

[0170] Preferably, a set of emergency repair personnel for each power supply station is generated based on the power equipment emergency repair coefficient, including:

[0171] Let eleequ represent the set of all power supply stations within the dispatch range, and calculate the number of emergency repair personnel assigned to each power supply station in eleequ based on the power equipment emergency repair coefficient;

[0172] The following calculations are performed for each power supply station within the dispatch range to obtain the set of emergency repair personnel for each power supply station:

[0173] For power supply station h, use numcal h The number of emergency repair personnel assigned to power supply station h is represented by numori. h This indicates the number of emergency repair personnel originally present at power supply station h;

[0174] Save the existing emergency repair personnel at power supply station h to the emergency repair personnel assembly at power supply station h;

[0175] If numcal h Less than numori h Then the number of repair personnel in the power station h will be... h -numcal h The emergency repair personnel were placed in a temporary assembly area.

[0176] If numcal h Greater than numori h Then, select numcal from the temporary personnel set. h -numori h One repairman joined the repair team of power supply station h;

[0177] If numcal h equals numori h Then the assembly of emergency repair personnel at power station h remains unchanged.

[0178] The above-described scheduling process is controlled based on the power equipment emergency repair coefficient calculated by this invention, which improves the accuracy of scheduling.

[0179] Preferably, the number of emergency repair personnel assigned to each power supply station in eleequ is calculated based on the power equipment emergency repair coefficient, including:

[0180] Let numpeo represent the total number of emergency repair personnel existing in all power stations in eleequ;

[0181] For power supply station h, the number of emergency repair personnel assigned to it is numdis h The calculation formula is:

[0182]

[0183] eleemerep k This represents the emergency repair coefficient for power equipment at power supply station k.

[0184] Preferably, the emergency repair personnel are assembled and distributed to various power supply stations, including:

[0185] All emergency repair personnel from the power supply stations were assembled and dispatched to each power supply station.

[0186] After receiving the emergency repair personnel from all power supply stations, the power supply station first obtains the emergency repair personnel set corresponding to its own power supply station. If all the existing emergency repair personnel are in the emergency repair personnel set, it means that the emergency repair personnel of that power supply station do not need to be dispatched.

[0187] If some of the existing emergency repair personnel are not in the corresponding emergency repair personnel set of this power supply station, the dispatch plan for these emergency repair personnel will be determined by querying the emergency repair personnel sets of other stations; that is, determining which power supply station each of these emergency repair personnel has been dispatched to.

[0188] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for human resource scheduling and distribution applied to power systems, characterized in that, include: S1, calculates the emergency repair coefficient of power equipment in each power supply station within the dispatch range; S2 generates a set of emergency repair personnel for each power supply station based on the emergency repair coefficient of power equipment; S3, to gather and distribute the emergency repair personnel to various power supply stations; The calculation of the emergency repair coefficient for power equipment at each power supply station within the dispatch range includes: S10, obtain historical damage parameters of power equipment in each power supply station within a set time period; S20, calculate the first emergency repair coefficient based on historical damage parameters; S30: Obtain detection images of power equipment in each power supply station; S40, calculates the second emergency repair coefficient for each power supply station based on the detected image; S50, calculate the emergency repair coefficient of power equipment in each power supply station based on the first emergency repair coefficient and the second emergency repair coefficient; Historical damage parameters include the number of electrical devices damaged by disasters within the jurisdiction of the power supply station and the probability of such damage occurring within a set time period. The first emergency repair coefficient is calculated based on historical damage parameters, including: The first emergency repair coefficient is calculated using the following formula: emerep h,1 numdam represents the first emergency repair coefficient of power supply station h. h This represents the number of electrical devices damaged by a disaster within the jurisdiction of power supply station h during a specified time period. h This indicates the total number of electrical devices within the jurisdiction of power supply station h during a set time period. h This represents the probability that electrical equipment within the jurisdiction of power supply station h will be damaged by a disaster during a set time period. max `dist` represents the maximum distance between power equipment within the jurisdiction of power supply station `h` and `h` within a specified time period. `splu` represents the maximum distance between all power equipment outside the jurisdiction of power supply station `h` and `h` whose distance is less than `dist`. max A collection of electrical equipment, dist i numsplu represents the distance between power device i and power supply station h in splu, w1, w2 and w3 represent the set quantity weight, probability weight and distance weight respectively; Obtain inspection images of the power equipment at each power supply station, including: Obtain the set of power equipment that needs to be detected and image acquired for each power supply station; The appearance of each power device in the set of power devices that need to be inspected for each power supply station is photographed to obtain the inspection image of the power device. Obtain the set of power equipment corresponding to each power supply station that needs to be image acquired, including: For power supply station h, obtain the set of power equipment belonging to the primary equipment in power supply station h, elemah. h ; Obtain a plan view P containing the complete jurisdiction of power supply station h. h ; In P h In the diagram, the boundary of the jurisdiction of power supply station h is marked as a closed area. h ; In P h Get Cloare h The minimum bounding rectangle of bourec h ; bourec h Divide the first range into multiple preset sizes, and delete the first range that does not include the jurisdiction of the power supply station h; Obtain the damage characteristic parameters of the power equipment in each first range; The first range is merged based on the characteristic parameters of power equipment damage to obtain the second range; Each of the second ranges contains the electrical equipment for which image acquisition is required; All power devices within the second range that require image acquisition are saved to the set of power devices requiring image acquisition corresponding to power supply station h; Obtain the damage characteristic parameters of the power equipment for each of the first ranges, including: For the first range z; Get the values ​​within the range of z that belong to elemah. h A collection of electrical equipment elemh z ; Get elemh respectively z The operation and maintenance records for each power device within a set time period include the type of fault that occurred in the power device and the time when the fault occurred. Within the set time period, elemh z Among all power equipment, the fault that occurs most frequently and the month with the most frequent faults are used as the power equipment damage characteristic parameters for z. The first range is merged based on the characteristic parameters of power equipment damage to obtain the second range, which includes: The first step is to store all the first ranges into the collection firloc; The second step is to randomly select a first range from firloc as the current range and save the current range to the temporary set of the second range. The third step is to save all first ranges adjacent to the current range in firloc to the adjacent set; The fourth step is to determine whether the adjacent set is empty. If it is, proceed to the fifth step; otherwise, proceed to the seventh step. Fifth step: Create a new second-range set, save the elements in the second-range temporary set to the second-range set, delete the elements in the second-range temporary set from firloc, clear the second-range temporary set, and clear the adjacent set; Step 6: Determine if firloc is an empty set. If it is, output all the second range sets, and form a second range by the elements in each second range set; otherwise, proceed to step 2. Step 7: Calculate the similarity between each first range in the adjacent set and the current range based on the power equipment damage characteristic coefficients; Step 8: Determine if the maximum similarity is greater than the preset similarity. If yes, proceed to step 9; otherwise, proceed to step 12. Step 9: Save the first range corresponding to the maximum similarity to the second range temporary set, and delete the first range corresponding to the maximum similarity from firloc; Step 10: Determine if firloc is an empty set. If it is, output all the second range sets, and form a second range by the elements in each second range set. If not, proceed to step 11. Step 11: Take the first range corresponding to the maximum similarity as the new current range, clear the adjacent set, and proceed to step 3; Step 12: Create a new second-range set, save the elements in the second-range temporary set to the second-range set, clear the second-range temporary set, and clear the adjacent set; Step 13: Determine if firloc is an empty set. If it is, output all the second range sets, and form a second range by the elements in each second range set. If not, proceed to step 2.

2. The method for human resource scheduling and distribution in a power system according to claim 1, characterized in that, The second emergency repair coefficient for each power supply station is calculated based on the detected images, including: For power supply station h, use aerimgu h This represents the set of power equipment corresponding to power supply station h that requires image acquisition for detection; Obtain aerimgu respectively h The defect coefficient of each electrical device in the system; Based on aerimgu h The defect coefficient of all electrical equipment is calculated as the second emergency repair coefficient of power supply station h.

3. The method for human resource scheduling and distribution in a power system according to claim 2, characterized in that, Obtain aerimgu respectively h The defect coefficient for each electrical device in the data includes: For aerimgu h Electrical equipment b in the middle, using imgcol b This represents the set of detection images corresponding to power equipment b; Get imgcol respectively b The number of defects of a preset type contained in each detected image; Based on imgcol b Calculate the defect coefficient of power equipment b by counting the number of defects of the preset type present in all detected images.

4. The method for human resource scheduling and distribution in a power system according to claim 3, characterized in that, Get imgcol respectively b The number of defects of a preset type contained in each detected image, including: imgcol b Each detected image is input into a pre-trained defect detection model for identification, and the defect detection model outputs the type of defect present in each detected image and the location of each defect.

5. The method for human resource scheduling and distribution in a power system according to claim 3, characterized in that, Based on imgcol b The number of preset types of defects present in all detected images is used to calculate the defect coefficient of power equipment b, including: The defect coefficient of power equipment b is calculated using the following formula: defcef b numdef represents the defect coefficient of electrical equipment b. b imgcol b The total number of defects of the preset type present in all detected images, numpx b imgcol b The maximum number of defects of a preset type present in a single detected image across all detected images, where numd represents imgcol. b The total number of detected images.

6. The method for human resource scheduling and distribution in a power system according to claim 3, characterized in that, Based on aerimgu h The defect coefficient of all electrical equipment is calculated, and the second emergency repair coefficient of power supply station h is included, including: The second emergency repair coefficient is calculated using the following formula: emerep h,2 Denotes the second emergency repair coefficient of power supply station h, defcef j Represents aerimgu h The defect coefficient of electrical equipment j in the middle, naerimg u Represents aerimgu h The total number of electrical devices j in the system, varaerimg u Represents aerimgu h The standard deviation of the defect coefficient of electrical equipment in the data, defcef max and defcef mid They represent aerimgu respectively h The maximum and median of the defect coefficients of the power equipment in the data; δ1 and δ2 represent the mean weight and standard deviation weight, respectively.

7. The method for human resource scheduling and distribution in a power system according to claim 1, characterized in that, The emergency repair coefficients for power equipment at each power supply station are calculated based on the first and second emergency repair coefficients, including: For power supply station h, the formula for calculating its corresponding power equipment emergency repair coefficient is: emerep h,1 and emerep h,2 Let eleequ represent the first and second emergency repair coefficients of power supply station h, respectively, and let eleequ represent the set of all power supply stations within the dispatch range. k,1 and emerep k,2 These represent the first and second emergency repair coefficients of power supply station k, respectively.

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