Transformer substation mobile safety management method and system based on edge computing

Abstract

The invention discloses a substation mobile safety management method and system based on edge computing, and the method comprises the steps: monitoring an encrypted signal lamp request which is broadcasted regularly by an automatic guided vehicle through an edge server corresponding to an intersection; the encryption signal lamp request is decrypted when the encryption signal lamp request is received, and if decryption succeeds, a traffic signal is generated and sent to the automatic guided vehicle at the intersection; after each automatic guided vehicle receives the traffic signal, the running state is adjusted according to the traffic signal, if the traffic signal indicates that passing is allowed, the automatic guided vehicle continues to run, and otherwise, the automatic guided vehicle stops and waits until the traffic signal indicating that passing is allowed is received. The invention aims to reduce the delay and bandwidth use required by the traffic control of the automatic guided vehicle, improve the response speed and data processing capability of the automatic guided vehicle in a transformer substation, and improve the safety of the automatic guided vehicle.

Description

Technical Field

[0001] The present invention relates to the field of substation safety management, and in particular to a substation mobile safety management method and system based on edge computing. Background Art

[0002] In recent years, with the rapid development of the industrial internet-of-things (IIoT), many technologies and solutions such as data management, security and privacy, blockchain, and data mining have been innovated. In particular, 5G technology has brought unprecedented connectivity to all sectors of society by connecting a large number of IoT devices. Among these core technologies, the application of edge computing allows applications to be deployed on edge servers near users, providing convenient use of computing resources, storage resources, or bandwidth. In particular, in the field of substation safety management, automated monitoring equipment such as automated guided vehicles (AGVs) has become a frontier of research, dedicated to reducing human operations and thus significantly improving overall social productivity. As an important part of the power system, the safe operation of substations is directly related to the stability of the entire power grid and the prevention of large-scale power outages. Therefore, ensuring the safe operation of substations is an important task facing the power industry. In the safety management of substations, the application of IoT technologies has gradually increased, including not only the use of sensors to monitor the status of equipment, but also the implementation of remote control and automated operations. However, the application of these technologies has also brought new problems in data security and network security. For example, unauthorized access may lead to malicious operation of equipment, and data leakage may expose key operational information. Summary of the invention

[0003] Technical problem to be solved by the present invention: In view of the above-mentioned problems of the prior art, a substation mobile safety management method and system based on edge computing are provided. The present invention aims to reduce the delay and bandwidth usage required for automated guided vehicle traffic control, improve the response speed and data processing capability of automated guided vehicles in substations, and improve the safety of automated guided vehicles.

[0004] In order to solve the above technical problems, the technical solution adopted by the present invention is: A mobile safety management method for a substation based on edge computing comprises the following steps: an edge server corresponding to an intersection monitors encrypted traffic light requests broadcasted regularly from an automatic guided vehicle, and decrypts the encrypted traffic light requests upon receipt, and if the decryption is successful, generates a traffic signal and sends it to the automatic guided vehicle at the intersection; after receiving the traffic signal, each automatic guided vehicle adjusts its operating state according to the traffic signal, and continues to travel if the traffic signal allows passage, otherwise stops and waits until receiving a traffic signal allowing passage.

[0005] Optionally, generating a traffic signal and sending it to an automatic guided vehicle at an intersection includes: Initialize the signal light status of all automated guided vehicles at the intersection to allow passage; Sort all automated guided vehicles by distance to the intersection; Check each AGV one by one: if the signal light status of an AGV is "no passage", set the signal light status of other AGVs in the same lane as the AGV to "no passage"; if the signal light status of an AGV is not "no passage", perform collision detection on the AGV and other AGVs respectively, and set the signal light status of other AGVs that fail the collision detection to "no passage"; The signal light status of each automated guided vehicle generates a corresponding traffic signal and sends it to the automated guided vehicle.

[0006] Optionally, sorting all the automated guided vehicles according to their distances to the intersection includes: S101, initialize loop variable i to 0; S102, determine whether the loop variable i is less than the number of automatic guided vehicles, if so, jump to step S103; otherwise, determine that the sorting is completed, end and return; S103, obtain the running state state1 of the i-th automatic guided vehicle AVGS[i] and its distance Pt2xrd1 to the intersection, and assign the loop variable j to i+1; S104, determine whether the loop variable j is less than the number of automatic guided vehicles AVGS, if so, jump to step S105; otherwise, add 1 to the loop variable i and jump to step S102; S105, obtain the running state state2 of the j-th automatic guided vehicle AVGS[j] and its distance Pt2xrd2 to the intersection; determine whether the distance Pt2xrd2 from the j-th automatic guided vehicle AVGS[j] to the intersection is less than the distance Pt2xrd1 from the ith automatic guided vehicle AVGS[i] to the intersection; if so, swap the positions of the ith automatic guided vehicle AVGS[i] and the j-th automatic guided vehicle AVGS[j], assign the distance Pt2xrd2 from the j-th automatic guided vehicle AVGS[j] to the intersection to the distance Pt2xrd1 from the ith automatic guided vehicle AVGS[i] to the intersection, add 1 to the loop variable i, and jump to step S102; if not, jump to step S106; S106, determine whether the distance Pt2xrd2 from the j-th automatic guided vehicle AVGS[j] to the intersection is equal to the distance Pt2xrd1 from the i-th automatic guided vehicle AVGS[i] to the intersection. If so, jump to step S107; otherwise, add 1 to the loop variable j, add 1 to the loop variable i, and jump to step S102; S107, obtain the ratio of the remaining time of the i-th automatic guided vehicle AVGS[i] to the remaining distance of the path, and the ratio of the remaining time of the j-th automatic guided vehicle AVGS[j] to the remaining distance of the path, wherein the remaining time is the time difference from the current time to the time of arriving at the target position, and the remaining distance of the path is the distance from the current position to the target position; if the ratio of the remaining time of the i-th automatic guided vehicle AVGS[i] to the remaining distance of the path is greater than the ratio of the remaining time of the j-th automatic guided vehicle AVGS[j] to the remaining distance of the path, then swap the positions of the i-th automatic guided vehicle AVGS[i] and the j-th automatic guided vehicle AVGS[j], assign the distance Pt2xrd2 from the j-th automatic guided vehicle AVGS[j] to the intersection to the distance Pt2xrd1 from the i-th automatic guided vehicle AVGS[i] to the intersection, add 1 to the loop variable j, add 1 to the loop variable i, and jump to step S102.

[0007] Optionally, the step of inspecting each automated guided vehicle one by one includes: S201, initialize loop variable i to 0; S202, determine whether the loop variable i is less than the number of automated guided vehicles, if so, jump to step S203; otherwise, determine that the automated guided vehicle inspection is completed, end and exit; S203, assign loop variable j to i+1; S204, determine whether the loop variable j is less than the number of automatic guided vehicles AVGS, if so, jump to step S205; otherwise, add 1 to the loop variable i and jump to step S202; S205, determine whether the traffic light status of the i-th automatic guided vehicle AVGS[i] is no-travel, if yes, jump to step S206; otherwise, jump to step S207; S206, determining whether the i-th automatic guided vehicle AVGS[i] and the j-th automatic guided vehicle AVGS[j] are in the same lane, and if so, setting the signal light state of the j-th automatic guided vehicle AVGS[j] to no passage; S207, perform collision detection on the i-th automatic guided vehicle AVGS[i] and the j-th automatic guided vehicle AVGS[j]. The collision detection refers to determining whether there is an intersection between the paths of the i-th automatic guided vehicle AVGS[i] and the j-th automatic guided vehicle AVGS[j]. If there is an intersection, the collision detection is determined to fail; otherwise, the collision detection is determined to pass; if the collision detection fails, the traffic light state of the j-th automatic guided vehicle AVGS[j] is set to no passage; the loop variable j is increased by 1, and the process jumps to step S204.

[0008] Optionally, the generating function expression of the encrypted traffic light request broadcasted by the automatic guided vehicle at regular intervals is: , In the above formula, Encrypt is the encryption function for encrypting the ciphertext requested by the signal light. msg For the original semaphore request, and are two geographic coordinate points, MPK is the primary public key, where is an integer, and the two geographic coordinates are and is generated according to the following formula: , In the above formula, is the position coordinate, is the preset distance, and the position coordinates here refer to the position coordinates of the automatic guided vehicle. is the forward angle of the automatic guided vehicle; the expression for decrypting the encrypted signal light request is: , In the above formula, Decrypt is the decryption function corresponding to the encryption function Encrypt. SK is the decryption key; if the position of the automated guided vehicle And the two decrypted geographic coordinates and satisfy and The decryption function returns the original semaphore request msg , otherwise the encrypted semaphore request is ignored, where is the location coordinate, and the location coordinate here refers to the location coordinate of the edge server.

[0009] Optionally, the encryption function generates the ciphertext of the encryption request including: converting two geographic coordinate points and As the access policy AP of the attribute encryption algorithm CP-ABE based on the ciphertext policy, a random message is generated. M, using the attribute encryption algorithm CP-ABE based on the ciphertext strategy to generate the ciphertext ; The message M Convert the message into a byte sequence M The byte sequence is used as the input of the AES algorithm. The original semaphore request msg As the key of the AES algorithm, use the AES algorithm to generate ciphertext , thus obtaining the ciphertext of the encryption request ; The decryption function decrypts the original signal light request msg Include: Encrypt the ciphertext of the request The ciphertext in and the decryption key SK As the input of the attribute encryption algorithm based on ciphertext policy CP-ABE, the message is decrypted using the attribute encryption algorithm based on ciphertext policy CP-ABE M And access policy AP, access policy AP includes two geographic coordinate points and If two geographic coordinate points and Dissatisfied or Ignore the encrypted traffic light request, remove the AGV from the list of AGVs that need to provide traffic signals on the edge server, end and exit, otherwise send the message M Convert the message into a byte sequence M The byte sequence is used as the input of the AES algorithm, and the ciphertext of the encryption request is encrypted using the AES algorithm. The ciphertext in Decrypt the original semaphore request msg , and add the automated guided vehicle to the list of automated guided vehicles for which the edge server needs to provide traffic signals.

[0010] Optionally, before the edge server corresponding to the intersection monitors the encrypted signal light request broadcasted regularly by the automated guided vehicle, the cloud server receives the security parameter Based on safety parameters Generate a master key pair (MPK, MSK), where MPK is the master public key and MSK is the master private key; the cloud server sends the master private key MSK and the location coordinates of the cloud server As input, a preset key generation algorithm is used to generate a decryption key SK The location coordinates here refer to the location coordinates of the cloud server; the cloud server sends the master public key MPK to each automated guided vehicle and the decryption key SK Send it to each edge server.

[0011] In addition, the present invention also provides a substation mobile safety management system based on edge computing, including an interconnected microprocessor and a memory, and the microprocessor is programmed or configured to execute the substation mobile safety management method based on edge computing.

[0012] In addition, the present invention also provides a computer-readable storage medium, which stores a computer program or instruction, and the computer program or instruction is programmed or configured to execute the edge computing-based substation mobile safety management method through a processor.

[0013] In addition, the present invention also provides a computer program product, including a computer program or instructions, which are programmed or configured to execute the substation mobile safety management method based on edge computing through a processor.

[0014] Compared with the prior art, the present invention mainly has the following advantages: 1. The present invention includes monitoring encrypted traffic light requests broadcast regularly from automated guided vehicles through the edge server corresponding to the intersection, and responding to the encrypted traffic light requests to generate the required traffic signals, and processing data close to the data source through edge computing to reduce latency and bandwidth usage, and improve system response speed and data processing capabilities. In practical applications of substations, this model can realize real-time analysis of sensor data.

[0015] 2. The edge server corresponding to the intersection of the present invention monitors the encrypted traffic light requests broadcast regularly from the automatic guided vehicle, and decrypts the encrypted traffic light requests when they are received. If the decryption is successful, it responds to generate the required traffic signal, and quickly identifies and responds to potential security threats, such as equipment anomalies and unauthorized intrusions.

[0016] 3. The edge server corresponding to the intersection of the present invention monitors the encrypted signal light requests broadcast regularly from the automatic guided vehicle. By encrypting the signal light requests, the problem of data privacy leakage caused by the broadcast environment of the substation can be solved. Moreover, the location-based encryption (LBE) algorithm can be further used to protect the security of key information. The LBE algorithm is adapted from the ciphertext-policy attribute-based encryption (CP-ABE) and uses location coordinates as attribute values. It not only enhances the security of the data, but also implements a one-to-many encryption method to ensure that only authorized edge servers can access and process the data. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1Schematic diagram of the basic flow of the method of the embodiment of the present invention.

[0018] Figure 2 The figure is a schematic diagram of the process of generating and sending a traffic signal in the method of an embodiment of the present invention.

[0019] Figure 3 Schematic diagram of the system structure of the method of the embodiment of the present invention.

[0020] Figure 4 Schematic diagram of the process of the sorting method in the embodiment of the present invention.

[0021] Figure 5 The figure is a schematic diagram of the working process of the edge server in the embodiment of the present invention.

[0022] Figure 6 The figure is a schematic diagram of the encryption and decryption process in an embodiment of the present invention.

[0023] Figure 7 Schematic diagram of a complete solution flow in an embodiment of the present invention. DETAILED DESCRIPTION

[0024] like Figure 1 As shown, the substation mobile safety management method based on edge computing in this embodiment includes the following steps: the edge server corresponding to the intersection monitors the encrypted traffic light request broadcasted regularly from the automatic guided vehicle, and decrypts the encrypted traffic light request when receiving the encrypted traffic light request. If the decryption is successful, a traffic signal is generated and sent to the automatic guided vehicle at the intersection; after each automatic guided vehicle receives the traffic signal, it adjusts its operating status according to the traffic signal. If the traffic signal allows passage, it continues to drive; otherwise, it stops and waits until it receives a traffic signal allowing passage.

[0025] like Figure 2 As shown, in this embodiment, the automatic guided vehicle generating the traffic signal and sending it to the intersection includes: Initialize the signal light status of all automated guided vehicles at the intersection to allow passage (in this embodiment, a green light is used to indicate that passage is allowed, and other signs may also be used to indicate this); Sort all automated guided vehicles by distance to the intersection; Check each automated guided vehicle one by one: if the signal light status of an automated guided vehicle is no passage (in this embodiment, a red light is used to indicate no passage, and other signs may also be used to indicate no passage), the signal light status of other automated guided vehicles in the same lane as the automated guided vehicle is set to no passage; if the signal light status of an automated guided vehicle is not no passage, collision detection is performed on the automated guided vehicle and other automated guided vehicles respectively, and the signal light status of other automated guided vehicles that fail the collision detection is set to no passage; The signal light status of each automated guided vehicle generates a corresponding traffic signal and sends it to the automated guided vehicle.

[0026] As an optional implementation, the system in this embodiment includes: Cloud Server: The cloud server is a center responsible for system setup and key management. It holds the LBE master key privately and issues decryption keys to edge servers.

[0027] Automated Guided Vehicle (AGV): An automated monitoring device with an anonymous identity authenticated by a cloud server, capable of performing LBE encryption and broadcasting messages. It moves from one location to another within the substation area to monitor and maintain facility security. All monitoring devices know the LBE master public key.

[0028] intersection ): An intersection is where a longitude road and a latitude road meet. If two or more AGVs arrive at an intersection at the same time, they may collide. But note that there is no physical traffic signal equipment at the intersection.

[0029] Traffic lights: Traffic lights are virtual signals for AGVs arriving at a specific intersection. This means that two AGVs heading in the same direction may "see" different traffic signal results at the same intersection. Traffic signals for multiple AGVs at an intersection are generated by an edge server. However, an edge server may be responsible for setting traffic signals for multiple intersections. Edge server: An edge server is a worker server that coordinates the AGVs near the substation. Each edge server holds a LBE decryption key (decryption key, ).

[0030] Figure 3 The horizontal and vertical coordinates of the automatic guided vehicle AGV are given. , moving north (i.e. the angle is 90 degrees), Figure 3 The schematic diagram of the system structure of the method of this embodiment, where a represents the edge server, b represents the intersection, c represents the area broadcast by the automated guided vehicle, (x, y) is the position coordinate, specifically the position coordinate of the automated guided vehicle (AGV), α and β are the forward angles of different automated guided vehicles, and all edge servers in the circle can receive the encrypted message broadcast by the automated guided vehicle AGV. As needed, only the edge servers in the gray rectangle can decrypt the message. Finally, if the edge servers receive the original message from the AGV, they will generate a traffic light for the automated guided vehicle AGV.

[0031] In this embodiment, the purpose of sorting all automated guided vehicles by distance to the intersection is to prioritize the AGVs when approaching the intersection, ensure smooth traffic flow and reduce the risk of collision. Figure 4 As shown, in this embodiment, sorting all automatic guided vehicles according to the distance to the intersection includes: S101, initialize loop variable i to 0; S102, determine whether the loop variable i is less than the number of automatic guided vehicles, if so, jump to step S103; otherwise, determine that the sorting is completed, end and return; S103, obtain the running state state1 of the i-th automatic guided vehicle AVGS[i] and its distance Pt2xrd1 to the intersection, and assign the loop variable j to i+1; S104, determine whether the loop variable j is less than the number of automatic guided vehicles AVGS, if so, jump to step S105; otherwise, add 1 to the loop variable i and jump to step S102; S105, obtain the running state state2 of the j-th automatic guided vehicle AVGS[j] and its distance Pt2xrd2 to the intersection; determine whether the distance Pt2xrd2 from the j-th automatic guided vehicle AVGS[j] to the intersection is less than the distance Pt2xrd1 from the ith automatic guided vehicle AVGS[i] to the intersection; if so, swap the positions of the ith automatic guided vehicle AVGS[i] and the j-th automatic guided vehicle AVGS[j], assign the distance Pt2xrd2 from the j-th automatic guided vehicle AVGS[j] to the intersection to the distance Pt2xrd1 from the ith automatic guided vehicle AVGS[i] to the intersection, add 1 to the loop variable i, and jump to step S102; if not, jump to step S106; S106, determine whether the distance Pt2xrd2 from the j-th automatic guided vehicle AVGS[j] to the intersection is equal to the distance Pt2xrd1 from the i-th automatic guided vehicle AVGS[i] to the intersection. If so, jump to step S107; otherwise, add 1 to the loop variable j, add 1 to the loop variable i, and jump to step S102; S107, obtain the ratio of the remaining time of the i-th automatic guided vehicle AVGS[i] to the remaining distance of the path, and the ratio of the remaining time of the j-th automatic guided vehicle AVGS[j] to the remaining distance of the path, wherein the remaining time is the time difference from the current time to the time of arriving at the target position, and the remaining distance of the path is the distance from the current position to the target position; if the ratio of the remaining time of the i-th automatic guided vehicle AVGS[i] to the remaining distance of the path is greater than the ratio of the remaining time of the j-th automatic guided vehicle AVGS[j] to the remaining distance of the path, then swap the positions of the i-th automatic guided vehicle AVGS[i] and the j-th automatic guided vehicle AVGS[j], assign the distance Pt2xrd2 from the j-th automatic guided vehicle AVGS[j] to the intersection to the distance Pt2xrd1 from the i-th automatic guided vehicle AVGS[i] to the intersection, add 1 to the loop variable j, add 1 to the loop variable i, and jump to step S102.

[0032] This sequencing method effectively manages the travel priority of AGVs as they approach intersections by dynamically adjusting their order, thereby optimizing traffic flow and reducing the risk of accidents.

[0033] like Figure 5 As shown, in this embodiment, checking each automated guided vehicle one by one includes: S201, initialize loop variable i to 0; S202, determine whether the loop variable i is less than the number of automated guided vehicles, if so, jump to step S203; otherwise, determine that the automated guided vehicle inspection is completed, end and exit; Figure 5 Return res in the above code, which means returning the signal light status of each automated guided vehicle to generate the corresponding traffic signal; S203, assign loop variable j to i+1; S204, determine whether the loop variable j is less than the number of automatic guided vehicles AVGS, if so, jump to step S205; otherwise, add 1 to the loop variable i and jump to step S202; S205, determine whether the traffic light status of the i-th automatic guided vehicle AVGS[i] is no-travel, if yes, jump to step S206; otherwise, jump to step S207; S206, determining whether the i-th automatic guided vehicle AVGS[i] and the j-th automatic guided vehicle AVGS[j] are in the same lane, and if so, setting the signal light state of the j-th automatic guided vehicle AVGS[j] to no passage; S207, perform collision detection on the i-th automatic guided vehicle AVGS[i] and the j-th automatic guided vehicle AVGS[j]. The collision detection refers to determining whether there is an intersection between the paths of the i-th automatic guided vehicle AVGS[i] and the j-th automatic guided vehicle AVGS[j]. If there is an intersection, the collision detection is determined to fail; otherwise, the collision detection is determined to pass; if the collision detection fails, the traffic light state of the j-th automatic guided vehicle AVGS[j] is set to no passage; the loop variable j is increased by 1, and the process jumps to step S204.

[0034] In this embodiment, the algorithm for checking each automated guided vehicle one by one effectively prevents collisions at intersections by dynamically adjusting the signal light status of each automated guided vehicle AGV, ensuring smooth and safe traffic. As an optional implementation, in this embodiment, the collision detection function is encapsulated as an isCollide function. When three or more automated guided vehicles AGVs come to the intersection, they are first sorted according to priority, and then the isCollide function is called to detect whether two automated guided vehicles AGVs may collide at the intersection. This sCollide function determines whether two automated guided vehicles AGVs may intersect in the same lane or on the path about to enter the intersection based on the given state information, so as to determine whether a collision will occur. If a possible collision is detected, the function returns a flag, usually true, indicating that the driving paths of the two automated guided vehicles AGVs have an intersection, which may cause a collision. This design is to enhance the system's early warning capability for potential dangerous situations and ensure that AGVs can travel safely at intersections without signals. It should be noted that whether there is an intersection in the path is an existing known method, so its specific details are not described in detail here.

[0035] In this embodiment, the generating function expression of the encrypted traffic light request broadcasted by the automatic guided vehicle at regular intervals is: , In the above formula, Encrypt is the encryption function for encrypting the ciphertext requested by the signal light. msg For the original semaphore request, and are two geographic coordinate points, MPK is the primary public key, where is an integer, and the two geographic coordinates are and is generated according to the following formula: , In the above formula, is the position coordinate, is the preset distance, and the position coordinates here refer to the position coordinates of the automatic guided vehicle. is the forward angle of the automatic guided vehicle; it should be noted that the preset distance can be set according to actual needs, such as Figure 3 As shown, as an optional implementation, the preset distance in this embodiment is 50, so: ; The expression for decrypting the encrypted signal light request is: , In the above formula, Decrypt is the decryption function corresponding to the encryption function Encrypt. SK is the decryption key; if the position of the automated guided vehicle And the two decrypted geographic coordinates and satisfy and The decryption function returns the original semaphore request msg , otherwise the encrypted semaphore request is ignored, where is the location coordinate, and the location coordinate here refers to the location coordinate of the edge server. Location-based encryption (LBE) is an encryption scheme designed to protect mobile communications by limiting the area where the intended recipient can decrypt the message. Formally, LBE can be defined as follows: Set the algorithm ( ): Initialize the algorithm to receive security parameters , and output the master key pair (MPK, MSK). Key generation algorithm ( ): The key generation algorithm uses the master private key MSK and location is the input, where and belongs to the integer Z. The algorithm outputs a decryption key .

[0036] Encryption algorithm ( ): The encryption algorithm receives the master public key MPK and a message and two geographic coordinate points and ,in belongs to the integer Z. The algorithm generates ciphertext .

[0037] Decryption algorithm ( ): The decryption algorithm receives the master public key MPK and the ciphertext and a decryption key Only if and , the algorithm will decrypt the ciphertext and return the message , here Used to generate Otherwise, it will output (Indicates invalid). In this scenario, only the edge server close to the automated guided vehicle AGV in the substation needs to generate the correct signal light for the key node. More specifically, only the signal lights near the front of the automated guided vehicle in the substation are considered. Obviously, each automated guided vehicle can use its current position for message encrypting instead of using the public key of the decryptor. Therefore, the proposed LBE scheme enables the automated guided vehicle to broadcast its encrypted information anywhere without any handshake process with the edge server. Therefore, the paradigm of the present technical solution is centered on the automated guided vehicle AGV, and the communication rounds are efficient. As Figure 3 As shown, the automated guided vehicle is located at point, and it is facing north, i.e. At the current time, rectangle c is the target area represented by the access policy.

[0038] The Ciphertext Policy-Based Attribute Encryption (CP-ABE) scheme embeds an access policy (AP) in its ciphertext. The access policy AP consists of a series of attributes written in Boolean or threshold gate expressions. The CP-ABE scheme allows a user to decrypt a ciphertext only if its attributes satisfy the access policy AP of the ciphertext. Therefore, the user encrypts the message using attributes, and in the CP-ABE scheme, there may be multiple decryptors for a ciphertext. The CP-ABE scheme can be formally defined using the following four algorithms: Set Algorithm ( :Set up the algorithm to receive security parameters and output the master key pair (MPK, MSK). The authorized institution privately holds the master secret key (MSK) and publishes the master public key (MPK). Key generation algorithm ( ): The key generation algorithm uses the master private key MSK and a set of attributes that describe the key. As input, output a decryption key . Encryption algorithm ( ): The encryption algorithm receives the master public key MPK, the message and access policy AP. Algorithm to encrypt messages , and generate a ciphertext (ciphertext, ), only users whose attribute sets satisfy the access policy can decrypt this message. Decryption algorithm ( ): The decryption algorithm receives the master public key MPK and the ciphertext (Including access policy ) and the decryption key (From the attribute set generated). If satisfy , the algorithm will decrypt the ciphertext and return the message Otherwise, it will output , indicating invalid. In addition, the attributes in the CP-ABE access policy support integer comparison. AES is a symmetric encryption scheme that can protect information of any bytes. The AES scheme generally includes the following two algorithms: AES encryption algorithm ( ): The AES encryption algorithm receives a random or pseudo-random number seed for generating a key ( ) is used to generate a symmetric key, and a plaintext message (message, ). It outputs the ciphertext . AES decryption algorithm ( ): The AES decryption algorithm receives a and a ciphertext As input, it outputs the plaintext message To be able to encrypt an arbitrary string (the original semaphore request msg ), this embodiment needs to combine AES encryption with the CP-ABE scheme, that is, integrate AES encryption into the CP-ABE scheme. Therefore, the encryption and decryption algorithms of CP-ABE are redefined. Figure 6 As shown in (a) in the figure, the encryption function in this embodiment generates the ciphertext of the encryption request including: converting two geographic coordinate points and As the access policy AP of the attribute encryption algorithm CP-ABE based on the ciphertext policy, a random message is generated. M , using the attribute encryption algorithm CP-ABE based on the ciphertext strategy to generate the ciphertext ; The message M Convert the message into a byte sequence M The byte sequence is used as the input of the AES algorithm. The original semaphore request msg As the key of the AES algorithm, use the AES algorithm to generate ciphertext , thus obtaining the ciphertext of the encryption request .like Figure 6 As shown in (b) in the figure, the decryption function in this embodiment decrypts the original traffic light request msg Include: Encrypt the ciphertext of the request The ciphertext in and the decryption key SK As the input of the attribute encryption algorithm based on ciphertext policy CP-ABE, the message is decrypted using the attribute encryption algorithm based on ciphertext policy CP-ABE M And access policy AP, access policy AP includes two geographic coordinate points and If two geographic coordinate points and Dissatisfied or Ignore the encrypted traffic light request, remove the AGV from the list of AGVs that need to provide traffic signals on the edge server, end and exit, otherwise send the message M Convert the message into a byte sequence M The byte sequence is used as the input (key) of the AES algorithm, and the ciphertext of the encryption request is encrypted using the AES algorithm. The ciphertext in Decrypt the original semaphore request msg , and add the automated guided vehicle to the list of automated guided vehicles for which the edge server needs to provide traffic signals.

[0039] like Figure 7 As shown, the edge server corresponding to the intersection monitors the encrypted signal light request broadcasted by the automated guided vehicle at regular intervals, and also includes: the cloud server receives the security parameter Based on safety parameters Generate a master key pair (MPK, MSK), where MPK is the master public key and MSK is the master private key; the cloud server sends the master private key MSK and the location coordinates of the cloud server As input, a preset key generation algorithm is used to generate a decryption key SK The location coordinates here refer to the location coordinates of the cloud server; the cloud server sends the master public key MPK to each automated guided vehicle and the decryption key SK It is sent to each edge server. If there are multiple devices near the edge server, the edge server will analyze the status of all devices and sort them. This embodiment defines a sorting algorithm by adjusting the sequential flow chart of the automated guided vehicle. The sorting algorithm sorts the devices at key nodes according to the point, remaining time, and path, with the highest priority at the front of the sorting list. Thereafter, the edge server will run the program for setting traffic lights based on this sorting result to generate corresponding virtual traffic lights for each key node. The input of this process is the operating status information of the equipment, and the output is the traffic light indication of each device at the key node to ensure orderly and safe traffic. Therefore, the paradigm workflow proposed by the method of this embodiment is as follows: 1. The cloud server sets up the system once. It runs the LBE algorithm, and the master public key (MPK) is saved by all AGVs. Then, it runs , where ES is the edge server point on the map; is a key generation function that uses the master private key (MSK) and a set of attributes to generate a decryption key. The master private key here is generated and kept secret by the cloud server when the system is initialized; the attributes : These attributes represent the location coordinates of the edge server, X and Y are the attribute names, and and These attributes correspond to the specific location coordinates of the edge server, which means that the generated decryption key will be associated with these specific location coordinates; the generated edge server decryption key :This is a key specially generated according to the specific location of the edge server. Only the edge server at this location can use this key to decrypt the encrypted information. The cloud server will output 2. At each fixed time interval, each AGV obtains its current operating state. Then, the AGV is based on the position parameters defined in Formula 1. To call the encryption function ,in Represents an AGV-based coordinate , and the orientation angle The access policy here It can be calculated from x, y and path in the running status data structure. It is an encryption function, and its input includes the state information to be encrypted, the access policy And the master public key MPK. Finally, AGV broadcasts the ciphertext and 3. After receiving the ciphertext Then, the nearby edge server tries to decrypt them. If the output of the decryption algorithm is (indicates decryption failure), the edge server will ignore the ciphertext. Otherwise, it will run the signal light algorithm flowchart for each intersection and send each result to the corresponding AGV. 4. If the device receives a "red light" signal at the intersection, it will slow down and stop before reaching the intersection. Otherwise, it will go directly through the intersection. It can be seen that no matter where the AGV is, it can get the traffic light result in just one round without any handshake process.

[0040] In order to verify the substation mobile safety management method based on edge computing in this embodiment, in terms of system simulation verification, Java and CP-ABE toolkit are used to implement the proposed substation safety management paradigm. Java programs are used to simulate sites, intersections, and AGVs, and the CP-ABE toolkit is used to encrypt or decrypt the output of Java programs. Entity storage evaluation: First, the storage requirements of each entity in the paradigm are evaluated. The cloud server stores the master key pair and the location of all edge servers. Each edge server only holds its decryption key, and each AGV only stores the public keys MPK and GPK. Encryption performance evaluation: Only four attributes are used for integer comparison in the LBE encryption algorithm, namely , , and The cost of the CP-ABE encryption algorithm is linear with the number of attributes in the access policy. In our scenario, the venue is , so the integer range is 1 to 300. The cost of the CP-ABE key generation algorithm is also linearly related to the size of the attribute set S. However, the attribute set of each edge server only includes its location coordinates. Time cost evaluation: The cloud server issues the key in about 800ms; the AGV encrypts its running status in 200-350ms; the edge server decrypts the ciphertext in 30-50ms. In addition, the speed of the AGV is about 30km / h, so it travels about 2.9m every 350ms, which has little effect on the accuracy of its location. Running status and encryption algorithm performance: The running status of the AGV is a fixed data structure containing a dynamic "path" size, usually within a few megabytes. Edge server processing power test: Multiple AGVs may arrive at the intersection at the same time. To test the processing power of the edge server, in an extreme case, if there are 10 AGVs at an intersection at the same time, the edge server takes about 524ms to process all AGVs. In addition, the decryption algorithms of different AGVs can be completed at the same time. Therefore, if equipped with 2 processors, the edge server can respond to the AGV within 274ms in extreme cases. It can be seen that this embodiment successfully developed a substation mobile safety management system based on edge computing, which is based on automated guided vehicles (AGVs) and advanced encryption technology to improve the operation safety and data protection inside the substation. By introducing the virtual traffic light mechanism and location-based encryption (LBE) strategy, the collision problem of automated guided vehicles at key intersections is effectively solved, and the privacy of broadcast information is protected. In the implementation of the system, the edge server, as a key data processing node, realizes real-time monitoring and management of the operating status of AGVs, controls the movement of AGVs through dynamically generated traffic lights, and optimizes the safety and efficiency of equipment movement. In addition, combined with CP-ABE and AES encryption technology, this system not only strengthens the security of data transmission, but also ensures that only authorized edge servers can access key data through precise access control, effectively preventing unauthorized access and data leakage. The test and evaluation results of the system show that the proposed security management scheme can operate stably in a high-density equipment environment, quickly respond to various security threats, and significantly improve the automation and intelligence level of the substation. Overall, the system design meets the needs of modern power systems and provides an innovative and effective solution for substation safety management, which has broad application prospects and practical value.

[0041] The substation mobile security management method based on edge computing in this embodiment focuses on the following technical solutions to enhance the security protection and data security of the substation: Design and implementation of edge computing architecture: This system takes the edge server as the core to build a dynamic data processing system to process the location and status information of each monitoring device in the substation in real time to improve the response speed and processing efficiency. The cloud server is responsible for the overall initialization of the system and the management of the edge server, optimizes resource allocation, and improves the operation and maintenance efficiency of the system without directly participating in daily data processing. Implementation of security protection mechanism: Introduce an intelligent security monitoring system based on edge computing, use advanced data analysis technology, dynamically generate early warning signals based on the real-time data of substation equipment, and effectively monitor and prevent any potential security threats. The system optimizes the equipment movement path and scheduling through intelligent algorithms to ensure the safety and continuity of key equipment operation. Data security and privacy protection: Combine CP-ABE and advanced encryption standard (AES) encryption technology to protect the security and privacy of substation monitoring data during transmission and storage. Through location-based encryption (LBE) technology, it is ensured that only authorized edge servers can access and process sensitive data in a specific geographical location, which strengthens the security and fine-grained control of data access. System simulation verification and evaluation: By simulating the actual operating environment of the substation, a comprehensive computer simulation test is carried out to verify the effectiveness of the system design and the reliability of the actual operation. The test results show that the system can effectively prevent safety accidents and ensure the security and privacy of data in a high-density equipment environment. The implementation of the substation mobile security management method based on edge computing in the field of substation security management in this embodiment significantly enhances the security monitoring and data protection capabilities of the substation by integrating edge computing and location-based encryption (LBE) technology. It mainly has the following advantages: 1. Strengthening data security and privacy protection: Using CP-ABE and AES technology, the system ensures the secure transmission and storage of monitoring data. These encryption measures provide a solid data protection barrier for the substation, effectively prevent data leakage and unauthorized access, and ensure the absolute privacy of sensitive information. 2. Instant response and reduced delay: Using the fast data processing capability of edge computing, the system can respond to various security threats in real time, such as intrusions, system failures and other emergencies. Fast data processing significantly reduces response delays and enhances the handling speed and efficiency of substations in the face of security incidents. 3. Real-time monitoring and intelligent early warning system: The system automatically detects and identifies potential risks by continuously monitoring the key operating parameters and environmental variables of the substation. When an abnormality or potential threat is detected, the system immediately initiates early warning and automated safety response measures to effectively prevent and mitigate the occurrence of safety accidents. 4. Resource optimization and technical support: Through efficient resource management and optimized configuration, the present invention not only improves the operating efficiency of the monitoring system, but also ensures the continuous stability and high reliability of the system.This provides strong technical support for the intelligent and automated management of substations and enhances the overall security of the power system. In summary, the substation mobile security management method based on edge computing in this embodiment provides a comprehensive substation security management solution, which significantly improves the security protection capability and management efficiency of substations through advanced technical means, and has important strategic significance for the safe operation of the power industry.

[0042] In summary, the substation mobile safety management method based on edge computing in this embodiment implements a substation mobile safety management mechanism based on edge computing. The mechanism uses advanced location-based encryption technology (LBE) to enhance information security and privacy protection, and ensure the security of the substation when performing key operations and the stability of the network. The mechanism processes the data of the substation monitoring equipment in real time and uses the edge computing architecture to improve the speed and efficiency of data processing. At the same time, the cloud server is responsible for the overall initialization and key management of the system to ensure the continuity and security of the system operation. By implementing a dynamic security monitoring mechanism, the mechanism can not only prevent potential safety accidents, but also prevent equipment failures through intelligent analysis. Using a virtual signal system and a refined control algorithm, the system can accurately control the movement of equipment in the substation, optimize the operating efficiency of the equipment, and ensure rapid response in emergency situations. In general, the substation mobile safety management method based on edge computing in this embodiment provides a multifunctional safety management system that integrates data protection, equipment control and real-time monitoring. Its design uses edge computing to achieve efficient data processing and rapid response, ensuring the stable operation and safety of the substation. In addition, the flexibility and adaptability of the system enable it to cope with various complex environments, significantly improving the automation and intelligence level of substations and providing an innovative safety management solution for modern power systems.

[0043] In addition, this embodiment also provides a substation mobile safety management system based on edge computing, including an interconnected microprocessor and a memory, and the microprocessor is programmed or configured to execute the substation mobile safety management method based on edge computing.

[0044] In addition, this embodiment also provides a computer-readable storage medium, which stores a computer program or instructions, and the computer program or instructions are programmed or configured to execute the edge computing-based substation mobile safety management method through a processor.

[0045] In addition, this embodiment also provides a computer program product, including a computer program or instructions, which are programmed or configured to execute the substation mobile safety management method based on edge computing through a processor.

[0046] Those skilled in the art should understand that the technical solutions provided by the embodiments of the present application may be in the form of methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the process Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the functions specified in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing the process in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0047] The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. A substation mobile safety management method based on edge computing, characterized in that: The method comprises the following steps: an edge server corresponding to an intersection monitors encrypted traffic light requests broadcast periodically from an automated guided vehicle, and decrypts the encrypted traffic light requests upon receipt, and if the decryption is successful, generates a traffic signal and sends it to the automated guided vehicle at the intersection; after receiving the traffic signal, each automated guided vehicle adjusts its operating status according to the traffic signal, and continues to drive if the traffic signal allows passage, otherwise stops and waits until receiving a traffic signal allowing passage.

2. The substation mobile safety management method based on edge computing according to claim 1 is characterized in that: The method of generating a traffic signal and sending it to the automatic guided vehicle at the intersection includes: Initialize the signal light status of all automated guided vehicles at the intersection to allow passage; Sort all automated guided vehicles by distance to the intersection; Check each AGV one by one: if the signal light status of an AGV is "no passage", set the signal light status of other AGVs in the same lane as the AGV to "no passage"; if the signal light status of an AGV is not "no passage", perform collision detection on the AGV and other AGVs respectively, and set the signal light status of other AGVs that fail the collision detection to "no passage"; The signal light status of each automated guided vehicle generates a corresponding traffic signal and sends it to the automated guided vehicle.

3. The substation mobile safety management method based on edge computing according to claim 2 is characterized in that: The step of sorting all the automated guided vehicles by distance to the intersection includes: S101, initialize loop variable i to 0; S102, determine whether the loop variable i is less than the number of automatic guided vehicles, if so, jump to step S103; otherwise, determine that the sorting is completed, end and return; S103, obtain the running state state1 of the i-th automatic guided vehicle AVGS[i] and its distance Pt2xrd1 to the intersection, and assign the loop variable j to i+1; S104, determine whether the loop variable j is less than the number of automatic guided vehicles AVGS, if so, jump to step S105; otherwise, add 1 to the loop variable i and jump to step S102; S105, obtain the running state state2 of the j-th automatic guided vehicle AVGS[j] and its distance Pt2xrd2 to the intersection; determine whether the distance Pt2xrd2 from the j-th automatic guided vehicle AVGS[j] to the intersection is less than the distance Pt2xrd1 from the ith automatic guided vehicle AVGS[i] to the intersection; if so, swap the positions of the ith automatic guided vehicle AVGS[i] and the j-th automatic guided vehicle AVGS[j], assign the distance Pt2xrd2 from the j-th automatic guided vehicle AVGS[j] to the intersection to the distance Pt2xrd1 from the ith automatic guided vehicle AVGS[i] to the intersection, add 1 to the loop variable i, and jump to step S102; if not, jump to step S106; S106, determine whether the distance Pt2xrd2 from the j-th automatic guided vehicle AVGS[j] to the intersection is equal to the distance Pt2xrd1 from the i-th automatic guided vehicle AVGS[i] to the intersection. If so, jump to step S107; otherwise, add 1 to the loop variable j, add 1 to the loop variable i, and jump to step S102; S107, obtain the ratio of the remaining time of the i-th automatic guided vehicle AVGS[i] to the remaining distance of the path, and the ratio of the remaining time of the j-th automatic guided vehicle AVGS[j] to the remaining distance of the path, wherein the remaining time is the time difference from the current time to the time of arriving at the target position, and the remaining distance of the path is the distance from the current position to the target position; if the ratio of the remaining time of the i-th automatic guided vehicle AVGS[i] to the remaining distance of the path is greater than the ratio of the remaining time of the j-th automatic guided vehicle AVGS[j] to the remaining distance of the path, then swap the positions of the i-th automatic guided vehicle AVGS[i] and the j-th automatic guided vehicle AVGS[j], assign the distance Pt2xrd2 from the j-th automatic guided vehicle AVGS[j] to the intersection to the distance Pt2xrd1 from the i-th automatic guided vehicle AVGS[i] to the intersection, add 1 to the loop variable j, add 1 to the loop variable i, and jump to step S102.

4. The substation mobile safety management method based on edge computing according to claim 2 is characterized in that: The step of inspecting each automated guided vehicle one by one includes: S201, initialize loop variable i to 0; S202, determine whether the loop variable i is less than the number of automated guided vehicles, if so, jump to step S203; otherwise, determine that the automated guided vehicle inspection is completed, end and exit; S203, assign loop variable j to i+1; S204, determine whether the loop variable j is less than the number of automatic guided vehicles AVGS, if so, jump to step S205; otherwise, add 1 to the loop variable i and jump to step S202; S205, determine whether the traffic light status of the i-th automatic guided vehicle AVGS[i] is no-travel, if yes, jump to step S206; otherwise, jump to step S207; S206, determining whether the i-th automatic guided vehicle AVGS[i] and the j-th automatic guided vehicle AVGS[j] are in the same lane, and if so, setting the signal light state of the j-th automatic guided vehicle AVGS[j] to no passage; S207, perform collision detection on the i-th automatic guided vehicle AVGS[i] and the j-th automatic guided vehicle AVGS[j]. The collision detection refers to determining whether there is an intersection between the paths of the i-th automatic guided vehicle AVGS[i] and the j-th automatic guided vehicle AVGS[j]. If there is an intersection, the collision detection is determined to fail; otherwise, the collision detection is determined to pass; if the collision detection fails, the traffic light state of the j-th automatic guided vehicle AVGS[j] is set to no passage; the loop variable j is increased by 1, and the process jumps to step S204.

5. The substation mobile safety management method based on edge computing according to claim 1 is characterized in that: The generating function expression of the encrypted signal light request broadcasted by the automatic guided vehicle at regular intervals is: ， In the above formula, Encrypt is the encryption function for encrypting the ciphertext requested by the signal light. msg For the original semaphore request, and are two geographic coordinate points, MPK is the primary public key, where is an integer, and the two geographic coordinates are and is generated according to the following formula: ， In the above formula, is the position coordinate, is the preset distance, and the position coordinates here refer to the position coordinates of the automatic guided vehicle. is the forward angle of the automatic guided vehicle; the expression for decrypting the encrypted signal light request is: ， In the above formula, Decrypt is the decryption function corresponding to the encryption function Encrypt. SK is the decryption key; if the position of the automated guided vehicle And the two decrypted geographic coordinates and satisfy and The decryption function returns the original semaphore request msg , otherwise the encrypted semaphore request is ignored, where is the location coordinate, and the location coordinate here refers to the location coordinate of the edge server.

6. The substation mobile safety management method based on edge computing according to claim 5 is characterized in that: The encryption function generates the ciphertext of the encryption request including: converting two geographic coordinate points and As the access policy AP of the attribute encryption algorithm CP-ABE based on the ciphertext policy, a random message is generated. M , using the attribute encryption algorithm CP-ABE based on the ciphertext strategy to generate the ciphertext ; The message M Convert the message into a byte sequence M The byte sequence is used as the input of the AES algorithm. The original semaphore request msg As the key of the AES algorithm, use the AES algorithm to generate ciphertext , thus obtaining the ciphertext of the encryption request ; The decryption function decrypts the original signal light request msg Include: Encrypt the ciphertext of the request The ciphertext in and the decryption key SK As the input of the attribute encryption algorithm based on ciphertext policy CP-ABE, the message is decrypted using the attribute encryption algorithm based on ciphertext policy CP-ABE M And access policy AP, access policy AP includes two geographic coordinate points and If two geographic coordinate points and Dissatisfied or Ignore the encrypted traffic light request, remove the AGV from the list of AGVs that need to provide traffic signals on the edge server, end and exit, otherwise send the message M Convert the message into a byte sequence M The byte sequence is used as the input of the AES algorithm, and the ciphertext of the encryption request is encrypted using the AES algorithm. The ciphertext in Decrypt the original semaphore request msg , and add the automated guided vehicle to the list of automated guided vehicles for which the edge server needs to provide traffic signals.

7. The substation mobile safety management method based on edge computing according to claim 5 is characterized in that: The edge server corresponding to the intersection monitors the encrypted signal light request broadcasted regularly by the automatic guided vehicle, and the cloud server receives the security parameter Based on safety parameters Generate a master key pair (MPK, MSK), where MPK is the master public key and MSK is the master private key; the cloud server sends the master private key MSK and the location coordinates of the cloud server As input, a preset key generation algorithm is used to generate a decryption key SK The location coordinates here refer to the location coordinates of the cloud server; the cloud server sends the master public key MPK to each automated guided vehicle and the decryption key SK Send it to each edge server.

8. A mobile safety management system for a substation based on edge computing, comprising an interconnected microprocessor and a memory, characterized in that: The microprocessor is programmed or configured to execute the substation mobile safety management method based on edge computing as described in any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program or instruction stored therein, characterized in that: The computer program or instruction is programmed or configured to execute the substation mobile safety management method based on edge computing as described in any one of claims 1 to 7 through a processor.

10. A computer program product comprising a computer program or instructions, characterized in that The computer program or instruction is programmed or configured to execute the substation mobile safety management method based on edge computing as described in any one of claims 1 to 7 through a processor.

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