Dynamic adjustment method and system for power utilization transmission path of expressway

Abstract

The invention relates to the technical field of expressway power grids, and particularly provides a dynamic adjustment method and system for an expressway power utilization transmission path, and the method comprises the steps: monitoring the state parameters of a power transmission network, and calculating the gradient information of a comprehensive index according to the state data; determining an optimal power transmission path set in the power transmission network in combination with an improved ant colony routing algorithm according to the gradient information; and adjusting the actual power transmission path by adjusting the network topology and installing the optimal power transmission path set. According to the method, a local optimal solution during topological optimization can be avoided, the path optimization rate is improved, and the stability of a power grid is maintained.

Description

Technical Field

[0001] The present invention belongs to the technical field of highway power grids, and in particular relates to a method and system for dynamically adjusting a highway power transmission path. Background Art

[0002] Current highway power transmission networks primarily employ static topologies and fixed routing strategies, relying on manual experience or offline simulations for path planning. Traditional monitoring systems suffer from high response latency, resulting in inefficient fault isolation.

[0003] Some monitoring methods use classic algorithms such as Dijkstra for topological conditions, but they are difficult to handle multi-objective optimization problems and often produce local optimal solutions. Summary of the Invention

[0004] In view of the above-mentioned deficiencies in the prior art, the present invention provides a method and system for dynamically adjusting the power transmission path of highways to solve the above-mentioned technical problems.

[0005] In a first aspect, the present invention provides a method for dynamically adjusting a highway power transmission path, comprising: Monitoring state parameters of the power transmission network and calculating gradient information of the comprehensive index based on the state data; Determining an optimal power transmission path set in the power transmission network based on the gradient information and in combination with an improved ant colony routing algorithm; The actual power transmission path is adjusted by adjusting the network topology and installing the optimal power transmission path set.

[0006] In an optional embodiment, monitoring state parameters of the power transmission network and calculating gradient information of the comprehensive indicator based on the state data includes: Monitor the power generation status data, load demand data, and energy storage status data of each node in the transmission network; Calculate comprehensive indicators based on node monitoring data:

[0007] in, is the vector from one node position to another node position, represents the distributed generation output density between two nodes at time t; represents the load demand density between two nodes at time t, represents the state of charge of the energy storage system between two nodes at time t, represents the line loss gradient tensor between two nodes at time t; Calculate the spatial variation gradient and spatiotemporal variation gradient of the comprehensive indicator.

[0008] In an optional embodiment, the method further comprises: Calculate the spatial variation gradient of the comprehensive index:

[0009] The spatial variation gradient reflects the change in field strength from node i to node j at time t.

[0010] In an optional embodiment, the method further comprises:

[0011] is the spatiotemporal variation gradient of the comprehensive indicator.

[0012] In an optional embodiment, determining an optimal power transmission path set in a power transmission network based on the gradient information and in combination with an improved ant colony routing algorithm includes: By encoding the quantum state of each path node, a superposition state of the path between the nodes is formed:

[0013] in, Indicates the path is closed; Indicates the path conduction state; θ ij represents the path selection probability angle; represents the phase angle; The probability of a path being selected is calculated based on the superposition state of the path and the spatial variation gradient:

[0014] in, represents the set of neighbor nodes of node i, that is, all other nodes directly connected to node i in the transmission network; Adjust the path selection probability angle according to the spatiotemporal gradient, and synchronously update the superposition state of the path; Enter the next round of iterative update based on the superposition state of the updated path; An annealing mechanism is introduced to determine the convergence state, and the optimal power transmission path set under the convergence state is output.

[0015] In an optional embodiment, an annealing mechanism is introduced to determine the convergence state, including: Compute the Hamiltonian:

[0016] Among them, J ij Represents the energy transfer capability or constraint strength between nodes i and j, which is determined by the spatiotemporal gradient and line impedance; Γ(t) controls the tunneling effect of the quantum bit and gradually decreases over time to complete annealing; μ represents the weight of the influence of the time derivative of the field intensity on the system; It represents the rate of change of the comprehensive index E over time, reflecting load fluctuations or changes in the output of new energy sources; is the Pauli-Z operator, acting on the quantum bit at node i, representing its energy eigenstate as on or off; is the Pauli-Z operator acting on the quantum bit at node j; Drive the tunneling effect of quantum bits for the Pauli-X operator to achieve transitions between quantum states; Calculate the ground state energy of the current Hamiltonian and the rate of change of the ground state energy over time. When the rate of change is lower than the threshold, it is determined to have entered the convergence state.

[0017] In an optional embodiment, outputting an optimal power transmission path set in a convergence state includes: Output the probability of the path being selected and the quantum superposition state under the convergence state; A projection measurement operator is constructed and used to measure the quantum superposition state to obtain the optimal power transmission path set with the highest probability of being selected and the largest corresponding space-time change gradient.

[0018] In a second aspect, the present invention provides a system for dynamically adjusting power transmission paths for highways, comprising: A monitoring module, configured to monitor state parameters of the power transmission network and calculate gradient information of the comprehensive index based on the state data; An optimization module, configured to determine an optimal power transmission path set in the power transmission network based on the gradient information and in combination with an improved ant colony routing algorithm; The adjustment module is used to adjust the actual power transmission path by adjusting the network topology and installing the optimal power transmission path set.

[0019] According to a third aspect, a device is provided, comprising: A memory for storing a dynamic adjustment program for a power transmission path for a highway; The processor is configured to implement the steps of the method for dynamically adjusting the highway power transmission path as provided in the first aspect when executing the program for dynamically adjusting the highway power transmission path.

[0020] In a fourth aspect, a computer-readable storage medium is provided, on which a program for dynamically adjusting the power transmission path for a highway is stored. When the program for dynamically adjusting the power transmission path for a highway is executed by a processor, the steps of the method for dynamically adjusting the power transmission path for a highway as provided in the first aspect are implemented.

[0021] The beneficial effects of the present invention lie in the fact that the method and system for dynamically adjusting highway power transmission paths, through real-time monitoring and gradient calculation, shortens the traditional minute-level response time to seconds, significantly improving fault isolation efficiency. An improved ant colony algorithm, incorporating multi-objective optimization, avoids local optimal solutions and improves the path optimization rate. Automated network reconstruction reduces manual intervention, shortens path switching time, and ensures power supply continuity. This invention can avoid local optimal solutions during topology optimization, improve path optimization rates, and maintain grid stability.

[0022] In addition, the present invention has a reliable design principle, a simple structure and a very broad application prospect. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0024] Figure 1 is a schematic flow chart of a method according to an embodiment of the present invention.

[0025] Figure 2 FIG. 4 is a schematic block diagram of a system according to an embodiment of the present invention.

[0026] Figure 3 A schematic structural diagram of a device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the technical solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of 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 making creative efforts should fall within the scope of protection of the present invention.

[0028] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0029] The method for dynamically adjusting the power transmission path for highways provided by the embodiment of the present invention is executed by a computer device. Accordingly, the system for dynamically adjusting the power transmission path for highways runs in the computer device.

[0030] Figure 1 is a schematic flow chart of a method according to an embodiment of the present invention. Figure 1 The execution subject may be a system for dynamically adjusting the power transmission path for a highway. According to different requirements, the order of the steps in the flowchart may be changed, and some steps may be omitted.

[0031] like Figure 1 As shown, the method includes: S1. Monitoring the state parameters of the power transmission network and calculating the gradient information of the comprehensive index based on the state data; S2. Determine the optimal power transmission path set in the transmission network based on the gradient information and the improved ant colony routing algorithm; S3. Adjust the actual power transmission path by adjusting the network topology and installing the optimal power transmission path set.

[0032] In an embodiment of the present invention, based on step S1, a possible embodiment will be given below to illustrate its specific implementation scheme in a non-limiting manner.

[0033] Monitor the power generation status data, load demand data, and energy storage status data of each node in the transmission network; Calculate comprehensive indicators based on node monitoring data:

[0034] in, is the vector from one node position to another node position, represents the distributed generation output density between two nodes at time t; represents the load demand density between two nodes at time t, represents the state of charge of the energy storage system between two nodes at time t, represents the line loss gradient tensor between two nodes at time t; Calculate the spatial variation gradient and spatiotemporal variation gradient of the comprehensive index: Calculate the spatial variation gradient of the comprehensive index:

[0035] The spatial variation gradient reflects the change in field strength from node i to node j at time t.

[0036]

[0037] is the spatiotemporal variation gradient of the comprehensive indicator.

[0038] In an embodiment of the present invention, based on step S2, a possible embodiment will be given below to illustrate its specific implementation scheme in a non-limiting manner.

[0039] S201. By encoding the quantum state of each path node, a superposition state of the paths between the nodes is formed:

[0040] in, Indicates the path is closed; Indicates the path conduction state; θ ij represents the path selection probability angle; represents the phase angle; S202. Calculate the probability of a path being selected based on the superposition state of the path and the spatial variation gradient:

[0041] in, represents the set of neighbor nodes of node i, that is, all other nodes directly connected to node i in the transmission network; S203. Adjust the path selection probability angle according to the spatiotemporal gradient, and synchronously update the superposition state of the path; enter the next round of iterative update based on the updated superposition state of the path.

[0042]

[0043] d ij is the direction vector between nodes, τ ij is the pheromone concentration.

[0044] S204. Introduce an annealing mechanism to determine the convergence state, and output the optimal power transmission path set in the convergence state.

[0045] Compute the Hamiltonian:

[0046] Among them, J ij Represents the energy transfer capability or constraint strength between nodes i and j, which is determined by the spatiotemporal gradient and line impedance; Γ(t) controls the tunneling effect of the quantum bit and gradually decreases over time to complete annealing; μ represents the weight of the influence of the time derivative of the field intensity on the system; It represents the rate of change of the comprehensive index E over time, reflecting load fluctuations or changes in the output of new energy sources; is the Pauli-Z operator, acting on the quantum bit at node i, representing its energy eigenstate as on or off; is the Pauli-Z operator acting on the quantum bit at node j; Drive the tunneling effect of quantum bits for the Pauli-X operator to achieve transitions between quantum states; Calculate the ground state energy of the current Hamiltonian and the rate of change of the ground state energy over time. When the rate of change is lower than the threshold, it is determined to have entered the convergence state.

[0047] S205. Output the probability of selection and quantum superposition state of the path in the convergence state; construct a projection measurement operator, use the projection measurement operator to measure the quantum superposition state, and obtain the optimal power transmission path set with the highest probability of selection and the largest corresponding space-time change gradient.

[0048] Specifically, the projection measurement operation M opt The mathematical essence of is to solve the following problem:

[0049] represents the quantum probability amplitude of path k (the probability at convergence); ∇Ek represents the field intensity gradient of path k; K represents the set of high-gradient paths that have passed pre-screening.

[0050] Through quantum measurement, the optimization results implicit in the quantum superposition state are converted into specific path plans.

[0051] 1. The physical process of quantum collapse Initial state: the system is in superposition , all paths coexist.

[0052] Apply M opt : Projected to the optimal path set K, the state becomes:

[0053] Collapse result: measurement causes the system to collapse with probability Collapse into a path , where k′∈K.

[0054] 2. Determination of the optimal path Probability Dominance Principle: In the set K, |c k ∣ 2 The largest path is the current optimal solution.

[0055] Field intensity gradient verification: If |c k ∣ 2 Close, choose ∇E k The largest path.

[0056] Repeated measurement strategy: Through multiple measurements (such as 10 times), the frequently occurring paths are counted as the final solution.

[0057] In an embodiment of the present invention, based on step S3, a possible embodiment will be given below to illustrate its specific implementation scheme in a non-limiting manner.

[0058] Switch control: Utilize intelligent switching devices, such as circuit breakers and disconnectors, to achieve line switching and interconnection, and adjust network topology through remote or automatic control according to the requirements of the optimal power transmission path set. Coordination of distributed power sources and energy storage devices: For power grids containing distributed power sources and energy storage devices, the output power of distributed power sources and the charge and discharge status of energy storage devices should be reasonably controlled to coordinate with network topology adjustments and optimize power transmission paths. Flexible AC transmission system (FACTS) application: FACTS devices, such as static VAR compensators (SVCs) and static synchronous compensators (STATCOMs), are installed on key lines. By adjusting the parameters of the devices, the power flow distribution of the lines can be changed, achieving flexible adjustment of the network topology.

[0059] In some embodiments, the system for dynamically adjusting the power transmission path for highways may include a plurality of functional modules composed of computer program segments. The computer program of each program segment in the system for dynamically adjusting the power transmission path for highways may be stored in a memory of a computer device and executed by at least one processor to perform (see Figure 1 Description) Dynamic adjustment of highway power transmission paths.

[0060] In this embodiment, the highway power transmission path dynamic adjustment system can be divided into multiple functional modules according to the functions it performs, such as Figure 2 As shown. The module referred to in the present invention refers to a series of computer program segments that can be executed by at least one processor and can perform fixed functions, which are stored in a memory. In this embodiment, the functions of each module will be described in detail in subsequent embodiments.

[0061] A monitoring module, configured to monitor state parameters of the power transmission network and calculate gradient information of the comprehensive index based on the state data; An optimization module, configured to determine an optimal power transmission path set in the power transmission network based on the gradient information and in combination with an improved ant colony routing algorithm; The adjustment module is used to adjust the actual power transmission path by adjusting the network topology and installing the optimal power transmission path set.

[0062] Figure 3The method for dynamically adjusting the power transmission path for highways provided in the embodiment of the present application can be applied to equipment. Those skilled in the art will understand that the device structure involved in the embodiment of the present invention does not constitute a limitation on the device, and the device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently. In the embodiment of the present invention, the device includes but is not limited to a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices 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 embodiments of the present application described and / or required herein.

[0063] The device 300 may include a processor 310, a memory 320, and a communication unit 330. These components communicate via one or more buses. Those skilled in the art will appreciate that the server structure shown in the figure does not limit the present invention. The server structure may be a bus structure or a star structure, and may include more or fewer components than shown, or combine certain components, or arrange the components differently.

[0064] The memory 320 can be used to store execution instructions of the processor 310. The memory 320 can be implemented by any type of volatile or non-volatile memory device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk. When the execution instructions in the memory 320 are executed by the processor 310, the device 300 can perform some or all of the steps in the above-described method embodiments.

[0065] The processor 310 is the control center of the storage device, which uses various interfaces and lines to connect various parts of the entire electronic device. It executes various functions of the electronic device and / or processes data by running or executing software programs and / or modules stored in the memory 320, and calling data stored in the memory. The processor can be composed of an integrated circuit (IC), for example, it can be composed of a single packaged IC, or it can be composed of multiple packaged ICs with the same or different functions. For example, the processor 310 can only include a central processing unit (CPU). In an embodiment of the present invention, the CPU can be a single computing core or multiple computing cores.

[0066] The communication unit 330 is configured to establish a communication channel so that the storage device can communicate with other devices, receive user data sent by other devices, or send user data to other devices.

[0067] The present invention also provides a computer storage medium, wherein the computer storage medium may store a program that, when executed, may include some or all of the steps of each embodiment provided by the present invention. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0068] Those skilled in the art will clearly understand that the techniques in the embodiments of the present invention can be implemented using software and a necessary general-purpose hardware platform. Based on this understanding, the technical solutions in the embodiments of the present invention, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, among other media capable of storing program code, and includes instructions for causing a computer device (which can be a personal computer, a server, or a second device, a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention.

[0069] In this specification, the same or similar parts between the various embodiments can be referred to each other. In particular, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method embodiment.

[0070] In the several embodiments provided by the present invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For example, the division of the modules is merely a logical function division. In actual implementation, there may be other division methods, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of systems or modules, and can be electrical, mechanical or other forms.

[0071] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected to achieve the purpose of the present embodiment according to actual needs.

[0072] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0073] Although the present invention has been described in detail with reference to the accompanying drawings and in conjunction with preferred embodiments, the present invention is not limited thereto. Without departing from the spirit and essence of the present invention, persons of ordinary skill in the art may make various equivalent modifications or substitutions to the embodiments of the present invention, and such modifications or substitutions shall be within the scope of the present invention. Any changes or substitutions that can be easily conceived by persons skilled in the art within the technical scope disclosed in the present invention shall be within the scope of protection of the present invention.

Claims

1. A method for dynamically adjusting the power transmission path of a highway, characterized in that: include: Monitoring state parameters of the power transmission network and calculating gradient information of the comprehensive index based on the state data; Determining an optimal power transmission path set in the power transmission network based on the gradient information and in combination with an improved ant colony routing algorithm; The actual power transmission path is adjusted by adjusting the network topology and installing the optimal power transmission path set.

2. The method according to claim 1, characterized in that Monitoring the state parameters of the power transmission network and calculating the gradient information of the comprehensive index based on the state data, including: Monitor the power generation status data, load demand data, and energy storage status data of each node in the transmission network; Calculate comprehensive indicators based on node monitoring data: in, is the vector from one node position to another node position, represents the distributed generation output density between two nodes at time t; represents the load demand density between two nodes at time t, represents the state of charge of the energy storage system between two nodes at time t, represents the line loss gradient tensor between two nodes at time t; Calculate the spatial variation gradient and spatiotemporal variation gradient of the comprehensive indicator.

3. The method according to claim 2, characterized in that The method further comprises: Calculate the spatial variation gradient of the comprehensive index: The spatial variation gradient reflects the change in field strength from node i to node j at time t.

4. The method according to claim 2, characterized in that The method further comprises: is the spatiotemporal variation gradient of the comprehensive indicator.

5. The method according to claim 3, characterized in that Determining an optimal power transmission path set in a power transmission network based on the gradient information and in combination with an improved ant colony routing algorithm includes: By encoding the quantum state of each path node, a superposition state of the path between the nodes is formed: in Indicates the path is closed; Indicates the path conduction state; θ ij represents the path selection probability angle; represents the phase angle; The probability of a path being selected is calculated based on the superposition state of the path and the spatial variation gradient: in, represents the set of neighbor nodes of node i, that is, all other nodes directly connected to node i in the transmission network; Adjust the path selection probability angle according to the spatiotemporal gradient, and synchronously update the superposition state of the path; Enter the next round of iterative update based on the superposition state of the updated path; An annealing mechanism is introduced to determine the convergence state, and the optimal power transmission path set under the convergence state is output.

6. The method according to claim 5, characterized in that The annealing mechanism is introduced to determine the convergence state, including: Compute the Hamiltonian: Among them, J ij Represents the energy transfer capability or constraint strength between nodes i and j, which is determined by the spatiotemporal gradient and line impedance; Γ(t) controls the tunneling effect of the quantum bit and gradually decreases over time to complete annealing; μ represents the weight of the influence of the time derivative of the field intensity on the system; It represents the rate of change of the comprehensive index E over time, reflecting load fluctuations or changes in the output of new energy sources; is the Pauli-Z operator, acting on the quantum bit at node i, representing its energy eigenstate as on or off; is the Pauli-Z operator acting on the quantum bit at node j; Drive the tunneling effect of quantum bits for the Pauli-X operator to achieve transitions between quantum states; Calculate the ground state energy of the current Hamiltonian and the rate of change of the ground state energy over time. When the rate of change is lower than the threshold, it is determined to have entered the convergence state.

7. The method according to claim 5, characterized in that The optimal power transmission path set under the output convergence state includes: Output the probability of the path being selected and the quantum superposition state under the convergence state; A projection measurement operator is constructed and used to measure the quantum superposition state to obtain the optimal power transmission path set with the highest probability of being selected and the largest corresponding space-time change gradient.

8. A system for dynamically adjusting the power transmission path of a highway, characterized in that: include: A monitoring module, configured to monitor state parameters of the power transmission network and calculate gradient information of the comprehensive index based on the state data; An optimization module, configured to determine an optimal power transmission path set in the power transmission network based on the gradient information and in combination with an improved ant colony routing algorithm; The adjustment module is used to adjust the actual power transmission path by adjusting the network topology and installing the optimal power transmission path set.

9. A device, characterized in that include: A memory for storing a dynamic adjustment program for a power transmission path for a highway; A processor is configured to implement the steps of the method for dynamically adjusting the highway power transmission path as described in any one of claims 1 to 7 when executing the program for dynamically adjusting the highway power transmission path.

10. A computer-readable storage medium storing a computer program, characterized in that: The readable storage medium stores a dynamic adjustment program for the power transmission path for highways. When the dynamic adjustment program for the power transmission path for highways is executed by the processor, the steps of the dynamic adjustment method for the power transmission path for highways as described in any one of claims 1 to 7 are implemented.

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