Post-disaster power communication recovery method and device and storage medium

Abstract

The invention discloses a post-disaster power communication recovery method and device and a storage medium. The method comprises the following steps: dividing a power disaster range into a plurality of areas of power communication to be recovered; determining a base station to be deployed and a plurality of automatic aircrafts in each area; the base station provides a communication service for the plurality of automatic aircrafts, and each automatic aircraft provides a communication service for an automatic switch in a region; moth flame catching under the chaos phenomenon is simulated for the multiple automatic aircrafts, so that the suspension coordinates of the multiple automatic aircrafts in the area are optimized; and fitting the working points of the base stations in the area according to the suspension coordinates of the plurality of automatic aircrafts. According to the embodiment, the chaos optimization algorithm and the moth flame capturing algorithm are combined, so that the local searching capability is improved, and the convergence speed is increased.

Description

Technical Field

[0001] The present invention relates to the field of electric power technology, and in particular to a post-disaster electric power communication recovery method, device and storage medium. Background Art

[0002] Extreme natural disasters occur from time to time in various places, posing a great threat to the safe operation of the power system. For example, eastern Guangdong was affected by heavy rainfall clouds for a period of time, and heavy rainstorms and local torrential rains occurred in a certain area. The continuous heavy rainfall caused serious disasters in many places, and dangerous situations such as landslides, urban and rural waterlogging occurred. The power supply lines and equipment in low-lying areas were severely flooded, and the normal electricity use of more than 400,000 residential users was affected.

[0003] Under the influence of extreme natural disasters, the restoration of power communications provides data support for preliminary surveys, line power restoration arrangements, construction coordination and information collection, and the restoration of the entire distribution network based on distribution automation.

[0004] At present, in post-disaster reconstruction scenarios, the solution for temporarily restoring communications is mostly to drive an emergency communication vehicle to the disaster area, and the emergency communication vehicle provides temporary communication services for the automated switch.

[0005] However, emergency communication vehicles are greatly affected by the terrain and environment, their radiation area is limited, and the number of automatic switches for restoring communications is small. Summary of the invention

[0006] In view of this, the present invention provides a post-disaster power communication recovery method, device and storage medium to improve the radiation area of ​​post-disaster power communication recovery.

[0007] A first aspect of the present invention provides a post-disaster power communication recovery method, comprising:

[0008] Divide the power disaster area into multiple areas where power and communication are to be restored;

[0009] Determining a base station and a plurality of automatic aerial vehicles to be deployed in each of the areas; the base station provides communication services for the plurality of automatic aerial vehicles, and each of the automatic aerial vehicles provides communication services for the automated switches in the area;

[0010] Simulating a moth catching a flame under a chaotic phenomenon for the plurality of said automatic flying vehicles, so as to optimize the coordinates of the plurality of said automatic flying vehicles suspended in the said area;

[0011] The working points of the base station in the area are fitted according to the coordinates of the suspension of the multiple automatic aerial vehicles.

[0012] A second aspect of the present invention provides a post-disaster power communication recovery device, comprising:

[0013] A regional division module is used to divide the power disaster area into multiple areas where power communication is to be restored;

[0014] A device determination module, used to determine a base station and a plurality of automatic aerial vehicles to be deployed in each of the areas; the base station provides communication services for the plurality of automatic aerial vehicles, and each of the automatic aerial vehicles provides communication services for the automatic switches in the area;

[0015] An aircraft coordinate optimization module, used for simulating a moth catching a flame under a chaotic phenomenon for a plurality of the automatic aircraft, so as to optimize the coordinates of the plurality of the automatic aircraft suspended in the area;

[0016] The base station working point fitting module is used to fit the working point of the base station in the area according to the coordinates of the suspension of multiple automatic aerial vehicles.

[0017] A third aspect of the present invention provides an electronic device, the electronic device comprising:

[0018] at least one processor; and

[0019] a memory communicatively connected to the at least one processor; wherein,

[0020] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the post-disaster power communication recovery method as described in the first aspect above.

[0021] A fourth aspect of the present invention provides a computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the post-disaster power communication recovery method as described in the first aspect above.

[0022] A fifth aspect of the present invention provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements the post-disaster power communication recovery method as described in the first aspect above.

[0023] In this embodiment, the power disaster area is divided into multiple areas to be restored power communication; base stations and multiple automatic aircraft to be deployed are determined in each area; the base station provides communication services for multiple automatic aircraft, and each automatic aircraft provides communication services for the automatic switches in the area; the moth catching flame under the chaotic phenomenon is simulated for multiple automatic aircraft to optimize the coordinates of the multiple automatic aircraft suspended in the area; the working point of the base station in the area is fitted according to the coordinates of the multiple automatic aircraft suspended. In this embodiment, after the disaster, the communication is restored based on the coordination of the automatic aircraft and the base station. The automatic aircraft is less affected by the terrain and environment, has a highly reliable line-of-sight link and the ability to be flexibly deployed, and can adapt to the characteristics of a large number of automatic switches in the distribution network, a wide distribution, and a complex environment. It effectively improves the radiation surface of post-disaster power communication recovery, cooperates with the medium-voltage feeder of the distribution network to realize automatic switch control, automatic isolation and self-healing, and can use a wireless private network for data transmission to ensure high reliability, economy and flexibility requirements. In addition, the combination of the chaotic optimization algorithm and the moth catching flame algorithm improves the local search capability and accelerates the convergence speed.

[0024] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0026] Figure 1 This is a flowchart of a post-disaster power communication recovery method provided in Example 1 of the present invention.

[0027] Figure 2 It is a structural schematic diagram of a post-disaster power communication recovery device provided in Embodiment 2 of the present invention.

[0028] Figure 3 It is a structural schematic diagram of an electronic device provided in Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present invention described herein can cover sequential implementations other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0031] Embodiment 1

[0032] See also Figure 1 , shows a flowchart of a post-disaster power communication restoration method provided by Embodiment 1 of the present invention, the method can be executed by a post-disaster power communication restoration device, the post-disaster power communication restoration device can be implemented in the form of hardware and / or software, and the post-disaster power communication restoration device can be configured in an electronic device. Figure 1 As shown, the method includes:

[0033] Step 101: Divide the power disaster-affected area into multiple areas where power communication is to be restored.

[0034] In this embodiment, the local power system damaged by extreme natural disasters may be referred to as a power disaster-affected area, and the power disaster-affected area may be divided into a plurality of areas where power communication is to be restored.

[0035] In the specific implementation, the geographic information (longitude and latitude) and administrative units (such as towns, villages, streets, etc.) of each automatic switch are queried within the power disaster area.

[0036] Unsupervised clustering algorithms such as K-means (K means) and DBSCAN (Density-Based Spatial Clustering of Applications with Noise) are used to cluster the automation switches according to geographic information to obtain multiple clusters, so that the geographic locations of the automation switches in the same cluster are close.

[0037] Adjust the parameters in the unsupervised clustering algorithm (such as the K value and center point in K-means) and re-cluster to obtain multiple clustering results.

[0038] In the results of each clustering, the number of administrative units to which the automation switches belong is counted for each cluster.

[0039] The automated switches belonging to the same cluster and having the least number of administrative units are grouped into the same area where power communication is to be restored.

[0040] Step 102: Determine the base stations and multiple automatic aerial vehicles to be deployed in each area.

[0041] A certain number of base stations and automatic aerial vehicles are deployed in each area. The base stations provide communication services for multiple automatic aerial vehicles, and each automatic aerial vehicle provides communication services for the automatic switches in the area when hovering.

[0042] In each area, unmanned aerial vehicles (UAVs) are used to coordinate with base stations to quickly restore emergency communications at the distribution network after a disaster. UAVs are less affected by terrain and environment, have highly reliable line-of-sight links and flexible deployment capabilities.

[0043] The implementation of post-disaster emergency repair work gives the load downstream of the faulty line a chance to recover. Using automatic aerial vehicles as emergency communication media makes the automatic switch controllable. By operating the automatic switch, the self-healing strategy can be quickly executed to restore the load downstream of the power supply. At the same time, the power of the non-fault section is restored to provide power services to the communication nodes downstream of the faulty section, so that the power supply of the automated nodes due to backup power supply can be restored, thereby better optimizing the flow of electricity and enabling limited power generation resources after the disaster to supply critical loads more effectively.

[0044] Step 103: simulate the moth catching flame under the chaotic phenomenon for multiple automatic aerial vehicles to optimize the coordinates of the multiple automatic aerial vehicles suspended in the area.

[0045] In practical applications, the coordinates of an automatic aircraft when it is suspended belong to the optimal location problem, which is essentially a nonlinear optimal path planning problem. This embodiment is based on the moth-catching-flame algorithm and adds a new strategy based on a chaotic operator, which gives full play to the ergodicity and randomness of the two, effectively improves the global search capability, and finds the coordinates of multiple automatic aircraft suspended in the area.

[0046] Furthermore, in order to search for the coordinates of multiple autonomous aerial vehicles hovering in the area, assumptions are added to the optimization scenario to restrict it, wherein the assumptions are as follows:

[0047] Assuming that the endurance of the automatic aircraft is not limited, the operator manually operates the automatic aircraft near the work point, visits the work points one by one, and then the automatic aircraft returns.

[0048] Assume that the power consumed by communication is not taken into account, and the power consumption under the two working conditions of hovering and patrolling is considered, and the power consumption values ​​in the two states are the same.

[0049] Assuming that the data transmission rate of each automated switch of the medium voltage line is the same, the automated aircraft can bear the data transmission requirements of the automated switch when the data transmission capacity of the automated aircraft is certain.

[0050] It is assumed that the automated switch can be covered by the base station and communication can be restored, without considering communication issues of other factors.

[0051] It is assumed that before the medium voltage distribution network is restored, the current distribution network system status has been obtained through on-site investigation and system information.

[0052] The emergency communication resources are optimally deployed with the coverage capability and data transmission capacity of the base station emergency communication of the automatic aerial vehicle as boundary conditions. The coverage target of the automatic aerial vehicle is the intersection of the communication nodes of multiple automatic switches in the distribution network system. The boundary conditions are used to find the positioning of the automatic aerial vehicle with the least configuration and the widest coverage.

[0053] In this regard, a quantification of the coverage capability of the automatic aerial vehicle is performed to reduce interference between automatic aerial vehicles. It can be assumed that each automatic aerial vehicle has an antenna whose elevation angle is θ with the horizontal plane, that is: tanθ = h / r, where h is the hovering height of the automatic aerial vehicle and r is the communication radius of the automatic aerial vehicle.

[0054] When the automatic aerial vehicle is at a certain hovering height, its maximum communication coverage radius is a fixed value, and the communication nodes outside the coverage range are not interfered by the base station communication.

[0055] It is assumed that the hovering height of all autopilots is the same and fixed, and all automation switches within the coverage area of ​​the autopilot can communicate with it.

[0056] The data throughput of all automated switch status within the coverage area of ​​the base station is within the data capacity of the base station, preventing the base station from being overloaded.

[0057] In one embodiment of the present invention, step 103 may include the following steps:

[0058] S31. Initialize the moth swarm.

[0059] In this embodiment, the parameters in the moth-catching flame algorithm can be initialized, for example, the moth swarm, the maximum number of iterations (i.e., the threshold, such as 20), etc., wherein the moths in the moth swarm represent automatic aircraft, and the positions of the moths represent the coordinates of the automatic aircraft suspended in the area. Then, the number of moth swarms is the number of automatic aircraft deployed in an area, such as 20, and the coordinates are longitude and latitude, and the coordinates can be set using random methods or the like.

[0060] S32, calculating the fitness of the moths, sorting the positions of the moths in increasing order of fitness and assigning them to the flames.

[0061] In this embodiment, the fitness function is used to calculate the fitness of each moth, and after the positions of the moths are sorted in order of increasing fitness, the position with the best fitness is selected and assigned to the flame as the position of the flame in the first generation.

[0062] S33. Determine whether the current number of iterations is 1; if so, execute S34; if not, execute S35.

[0063] S34, using the parallel light linear flame catching mode under the chaotic phenomenon to update the position of the moth when it flies towards the flame, and executing S37.

[0064] After initialization (i.e., the current number of iterations is 1), the moths search more independently and exchange less information. At this time, the chaos operator is used to simulate the chaotic phenomenon, and on this basis, the parallel light linear flame catching mode is used to update the position of the moth when it flies towards the flame.

[0065] In the specific implementation, the parallel light linear flame capture mode under the chaotic phenomenon includes:

[0066]

[0067] Among them, M i is the position of the i-th moth, M j is the position of the jth moth, i≠j, J is the moth with the highest fitness, r n is the chaotic optimization coefficient in the nth iteration, r n-1 is the chaos optimization coefficient in the n-1th iteration.

[0068] This embodiment adopts a multi-elite position combination strategy, selects multiple excellent moth individuals, and performs chaotic linear combination with each moth, which helps to improve the global search capability.

[0069] S35. Selecting a parallel light linear flame catching mode or a divergent light spiral flame catching mode under a chaotic phenomenon according to the relationship between the number of flames and the current number of iterations to update the position of the moth when it flies toward the flame.

[0070] In this embodiment, the number of flames can be adaptively adjusted to take into account the advantages of both the parallel light linear flame catching mode and the divergent light spiral flame catching mode in the optimization process, effectively avoiding the discreteness of the automatic aerial vehicle and the base station from falling into the local optimum, which helps to search for the global optimal solution.

[0071] In a specific implementation, the number of flames is compared with the current iteration number.

[0072] If the number of flames is less than the current number of iterations, the parallel light straight line flame catching mode under chaotic phenomenon is used to update the position of the moth when it flies towards the flame.

[0073] Among them, the parallel light linear flame capture modes under chaotic phenomena include:

[0074]

[0075] Among them, M i is the position of the i-th moth, M j is the position of the jth moth, i≠j, J is the moth with the highest fitness, r n is the chaotic optimization coefficient in the nth iteration, r n-1 is the chaos optimization coefficient in the n-1th iteration.

[0076] If the number of flames is greater than or equal to the current number of iterations, the position of the moth as it flies toward the flame is updated using the divergent light spiral flame catching mode.

[0077] Among them, the divergent light spiral flame capture mode includes:

[0078] S(M i ,F j )=D i ·e bt cos(2πt)+F j

[0079] D i =|M i -F j |

[0080] Among them, M i For the i-th moth, F iis the jth flame, S(M i ,F j ) is the position of the i-th moth flying towards the j-th flame, D i M i With F i The distance between them, b is the logarithmic spiral shape constant, and t is the path coefficient.

[0081] S36, merge the moth swarm of the current generation with the moth swarm of the previous generation into the moth swarm of the next generation, and execute S37.

[0082] In this embodiment, the moth colony of the current generation is subjected to selection operation, crossover operation, compilation operation and other genetic related operations with the moth colony of the previous generation to obtain the next generation moth colony.

[0083] S37, reduce the flame and add 1 to the current number of iterations.

[0084] If each position update of each moth is based on a different position in the search space, the local search ability of the moth-catching-flame algorithm will be reduced. In order to solve this problem, an adaptive mechanism is proposed for the number of flames, so that the number of flames can be adaptively reduced during the iteration process, thereby balancing the global search ability and local development ability of the moth-catching-flame algorithm in the search space.

[0085] Exemplarily, the number of flames is: Flame=round(Nn×(N-1) / m), where Flame is the number of flames, round is a rounding function, n is the current number of iterations, N is the maximum number of flames, and m is the maximum number of iterations.

[0086] S38. Determine whether the current number of iterations is less than a preset threshold; if so, return to execute S32; if not, execute S39.

[0087] S39. Output the position of the moth as the coordinate of the automatic flying vehicle hovering in the area.

[0088] In each round of iteration, it can be determined whether the current number of iterations is less than a preset threshold (ie, the maximum number of iterations).

[0089] If the current number of iterations is less than a preset threshold (ie, the maximum number of iterations), the process returns to S32 to enter the next round of iterations.

[0090] If the current number of iterations is greater than or equal to a preset threshold (ie, the maximum number of iterations), the iteration is stopped, the position of each moth is output, and the coordinates of each automatic flying vehicle suspended in the area are obtained.

[0091] Step 104: Fit the working points of the base station in the area according to the coordinates of the suspension of multiple automatic aerial vehicles.

[0092] The working points of the base station in the area is a position set coverage problem, which belongs to a continuous model. When the coordinates of multiple suspended automatic aerial vehicles are determined, the area is discretized into a point set, and a continuous model is converted into a discrete model. Then, the working points of the base station in the area can be fitted according to the coordinates of multiple suspended automatic aerial vehicles.

[0093] In a specific implementation, on the one hand, the number of working points of the base station in the area can be counted as an objective function, and on the other hand, constraints can be added to the base station according to the coordinates of the automatic aerial vehicle's suspension.

[0094] Exemplarily, the objective function is:

[0095]

[0096] The constraints include:

[0097]

[0098] Among them, S FTU is the set of communication nodes in the automation switch, S UAV is a collection of autonomous aircraft. When point k is selected as the working point of the base station in the region, p k =1, when point k is not selected as the working point of the base station in the area, p k =0, at c ,k ≥0, x c,k =1, at d c,k <0, x c,k =0, r is the communication radius of the automatic aircraft, (x c ,y c ) is the coordinate of the communication node in the automation switch, (x k ,y k ) is the coordinate of point k.

[0099] The first constraint condition indicates that the communication node is covered by at least one base station, and the second constraint condition indicates that the number of communication nodes that can be accommodated by the base station is limited. This constraint condition is applied when there are many and densely populated communication nodes in the distribution network.

[0100] Under the constraints, with the goal of minimizing (i.e., min function) the objective function, commercial solvers such as Gurobi or heuristic algorithms such as particle swarm optimization can be used to find the operating point of the base station in the area.

[0101] In this embodiment, the power disaster area is divided into multiple areas to be restored power communication; base stations and multiple automatic aircraft to be deployed are determined in each area; the base station provides communication services for multiple automatic aircraft, and each automatic aircraft provides communication services for the automatic switches in the area; the moth catching flame under the chaotic phenomenon is simulated for multiple automatic aircraft to optimize the coordinates of the multiple automatic aircraft suspended in the area; the working point of the base station in the area is fitted according to the coordinates of the multiple automatic aircraft suspended. In this embodiment, after the disaster, the communication is restored based on the coordination of the automatic aircraft and the base station. The automatic aircraft is less affected by the terrain and environment, has a highly reliable line-of-sight link and the ability to be flexibly deployed, and can adapt to the characteristics of a large number of automatic switches in the distribution network, a wide distribution, and a complex environment. It effectively improves the radiation surface of post-disaster power communication recovery, cooperates with the medium-voltage feeder of the distribution network to realize automatic switch control, automatic isolation and self-healing, and can use a wireless private network for data transmission to ensure high reliability, economy and flexibility requirements. In addition, the combination of the chaotic optimization algorithm and the moth catching flame algorithm improves the local search capability and accelerates the convergence speed.

[0102] Embodiment 2

[0103] See also Figure 2 , shows a schematic diagram of the structure of a post-disaster power communication restoration device provided by Embodiment 2 of the present invention. Figure 2 As shown, the device comprises:

[0104] The area division module 201 is used to divide the power disaster area into a plurality of areas where power communication is to be restored;

[0105] The device determination module 202 is used to determine a base station and a plurality of automatic aerial vehicles to be deployed in each of the areas; the base station provides communication services for the plurality of automatic aerial vehicles, and each of the automatic aerial vehicles provides communication services for the automatic switches in the area;

[0106] The aircraft coordinate optimization module 203 is used to simulate the moth catching flame under the chaotic phenomenon for the multiple automatic aircrafts to optimize the coordinates of the multiple automatic aircrafts suspended in the area;

[0107] The base station working point fitting module 204 is used to fit the working point of the base station in the area according to the coordinates of the suspension of multiple automatic aerial vehicles.

[0108] In one embodiment of the present invention, the region division module 201 is further used for:

[0109] Query geographic information and administrative units for each automatic switch within the power disaster area;

[0110] Clustering the automation switches according to the geographic information to obtain a plurality of clusters;

[0111] The automation switches that belong to the same cluster and to which the least number of administrative units belong are divided into the same area where power communication is to be restored.

[0112] In one embodiment of the present invention, the aircraft coordinate optimization module 203 is further used for:

[0113] S31, initializing a moth swarm; the moths in the moth swarm represent the automatic flying vehicle;

[0114] S32, calculating the fitness of the moths, sorting the positions of the moths in ascending order of the fitness and assigning them to flames;

[0115] S33, determine whether the current number of iterations is 1; if so, execute S34, if not, execute S35;

[0116] S34, using a parallel light straight line flame catching mode under a chaotic phenomenon to update the position of the moth when it flies toward the flame, and executing S37;

[0117] S35, selecting a parallel light linear flame catching mode or a divergent light spiral flame catching mode under a chaotic phenomenon according to the relationship between the number of flames and the current number of iterations to update the position of the moth when it flies toward the flame.

[0118] S36, merging the moth swarm of the current generation with the moth swarm of the previous generation into the moth swarm of the next generation, and executing S37;

[0119] S37, reducing the flame, and adding 1 to the current number of iterations;

[0120] S38. Determine whether the current number of iterations is less than a preset threshold; if so, return to execute S32; if not, execute S39.

[0121] S39, output the position of the moth as the coordinates of the automatic flying vehicle hovering in the area.

[0122] In one embodiment of the present invention, the region division module 201 is further used for:

[0123] If the number of flames is less than the current number of iterations, the parallel light straight line flame catching mode under the chaotic phenomenon is used to update the position of the moth when it flies towards the flame;

[0124] If the number of flames is greater than or equal to the current number of iterations, the divergent light spiral flame catching mode is used to update the position of the moth when it flies toward the flame.

[0125] In one embodiment of the present invention, the parallel light linear flame capture mode under the chaotic phenomenon includes:

[0126]

[0127] Among them, M i is the position of the i-th moth, M j is the position of the jth moth, i≠j, J is the moth with the highest fitness, r n is the chaotic optimization coefficient in the nth iteration, r n-1 is the chaos optimization coefficient in the n-1th iteration.

[0128] In one embodiment of the present invention, the divergent light spiral flame capture mode includes:

[0129] S(M i ,F j )=D i ·e bt cos(2πt)+F j

[0130] D i =|M i -F j |

[0131] Among them, M i is the i-th moth, F i is the jth flame, S(M i ,F j ) is the position of the i-th moth flying towards the j-th flame, D i M i With F i The distance between them, b is the logarithmic spiral shape constant, and t is the path coefficient.

[0132] In one embodiment of the present invention, the base station operating point fitting module 204 is further used for:

[0133] Counting the number of working points of the base station in the area as an objective function;

[0134] Adding constraint conditions to the base station according to the coordinates of the automatic aerial vehicle being suspended;

[0135] Under the constraint of the constraint condition, the working point of the base station in the area is found with the goal of minimizing the objective function.

[0136] In one embodiment of the present invention, the objective function is:

[0137]

[0138] The constraints include:

[0139]

[0140] Among them, S FTU is the set of communication nodes in the automatic switch, S UAV is the set of the automatic aircraft, when point k is selected as the working point of the base station in the area, p k =1, when point k is not selected as the working point of the base station in the area, p k =0, at d c,k ≥0, x c,k =1, at d c,k <0, x c,k =0, r is the communication radius of the automatic aircraft, (x c ,y c ) is the coordinate of the communication node in the automatic switch, (x k ,y k ) is the coordinate of point k.

[0141] The post-disaster power communication recovery device provided in the embodiment of the present invention can execute the post-disaster power communication recovery method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the post-disaster power communication recovery method.

[0142] Embodiment 3

[0143] See also Figure 3 , showing a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0144] like Figure 3As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0145] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0146] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the post-disaster power communication restoration method.

[0147] In some embodiments, the post-disaster power communication recovery method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the post-disaster power communication recovery method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the post-disaster power communication recovery method in any other appropriate manner (e.g., by means of firmware).

[0148] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0149] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0150] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0151] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0152] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0153] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0154] Embodiment 4

[0155] An embodiment of the present invention further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the post-disaster power communication recovery method provided by any embodiment of the present invention is implemented.

[0156] In the process of implementation, the computer program product can be written in one or more programming languages ​​or a combination thereof to perform the computer program code of the present invention, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0157] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0158] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A post-disaster power communication recovery method, characterized in that: include: Divide the power disaster area into multiple areas where power and communication are to be restored; Determining a base station and a plurality of automatic aerial vehicles to be deployed in each of the areas; The base station provides communication services for a plurality of the automatic aircrafts, and each of the automatic aircrafts provides communication services for the automatic switches in the area; Simulating a moth catching a flame under a chaotic phenomenon for the plurality of said automatic flying vehicles, so as to optimize the coordinates of the plurality of said automatic flying vehicles suspended in the said area; The working points of the base station in the area are fitted according to the coordinates of the suspension of the multiple automatic aerial vehicles.

2. The method according to claim 1, characterized in that The power disaster area is divided into multiple areas where power communication needs to be restored, including: Query geographic information and administrative units for each automatic switch within the power disaster area; Clustering the automation switches according to the geographic information to obtain a plurality of clusters; The automation switches that belong to the same cluster and to which the least number of administrative units belong are divided into the same area where power communication is to be restored.

3. The method according to claim 1, characterized in that The step of simulating a moth catching a flame under a chaotic phenomenon for the plurality of automatic flying vehicles to optimize the coordinates of the plurality of automatic flying vehicles suspended in the area includes: S31, initializing a moth swarm; the moths in the moth swarm represent the automatic flying vehicle; S32, calculating the fitness of the moths, sorting the positions of the moths in ascending order of the fitness and assigning them to flames; S33, determine whether the current number of iterations is 1; if so, execute S34, if not, execute S35; S34, using a parallel light straight line flame catching mode under a chaotic phenomenon to update the position of the moth when it flies toward the flame, and executing S37; S35, selecting a parallel light linear flame catching mode or a divergent light spiral flame catching mode under a chaotic phenomenon according to the relationship between the number of flames and the current number of iterations to update the position of the moth when it flies toward the flame. S36, merging the moth swarm of the current generation with the moth swarm of the previous generation into the moth swarm of the next generation, and executing S37; S37, reducing the flame, and adding 1 to the current number of iterations; S38. Determine whether the current number of iterations is less than a preset threshold; if so, return to execute S32; if not, execute S39. S39, output the position of the moth as the coordinates of the automatic flying vehicle hovering in the area.

4. The method according to claim 3, characterized in that The step of selecting a parallel light linear flame catching mode or a divergent light spiral flame catching mode under a chaotic phenomenon according to the relationship between the number of flames and the current number of iterations to update the position of the moth when it flies toward the flame comprises: If the number of flames is less than the current number of iterations, the parallel light straight line flame catching mode under the chaotic phenomenon is used to update the position of the moth when it flies towards the flame; If the number of flames is greater than or equal to the current number of iterations, the divergent light spiral flame catching mode is used to update the position of the moth when it flies toward the flame.

5. The method according to claim 3 or 4, characterized in that: The parallel light linear flame capture mode under the chaotic phenomenon includes: Among them, M i is the position of the i-th moth, M j is the position of the jth moth, i≠j, J is the moth with the highest fitness, r n is the chaotic optimization coefficient in the nth iteration, r n-1 is the chaos optimization coefficient in the n-1th iteration.

6. The method according to claim 3 or 4, characterized in that: The divergent light spiral flame catching mode includes: S(M i ,F j )=D i ·e bt cos(2πt)+F j D i =|M i -F j | Among them, M i is the i-th moth, F i is the jth flame, S(M i ,F j ) is the position of the i-th moth flying towards the j-th flame, D i M i With F i The distance between them, b is the logarithmic spiral shape constant, and t is the path coefficient.

7. The method according to any one of claims 1 to 4, characterized in that The step of fitting the working point of the base station in the area according to the coordinates of the plurality of suspended automatic aerial vehicles comprises: Counting the number of working points of the base station in the area as an objective function; Adding constraint conditions to the base station according to the coordinates of the automatic aerial vehicle being suspended; Under the constraint of the constraint condition, the working point of the base station in the area is found with the goal of minimizing the objective function.

8. The method according to claim 7, characterized in that The objective function is: The constraints include: Among them, S FTU is the set of communication nodes in the automatic switch, S UAV is the set of the automatic aircraft, when point k is selected as the working point of the base station in the area, p k =1, when point k is not selected as the working point of the base station in the area, p k =0, at d c,k ≥0, x c,k =1, at d c,k <0, x c,k =0, r is the communication radius of the automatic aircraft, (x c ,y c ) is the coordinate of the communication node in the automatic switch, (x k ,y k ) is the coordinate of point k.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the post-disaster power communication restoration method according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the post-disaster power communication recovery method according to any one of claims 1 to 8 is implemented.

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