Power distribution network heterogeneous networking scheduling method, equipment and medium

Abstract

The invention relates to a power distribution network heterogeneous networking scheduling method and device and a medium, and belongs to the technical field of power grid communication scheduling, and the method comprises the following steps: setting a scheduling variable and a data transmission time slice variable of a relay terminal, constructing a queue backlog model, and outputting queue backlog; setting a virtual queue based on queue backlog, and obtaining a space domain and time domain state index of the relay terminal so as to obtain a matching preference between the relay terminal and each channel; constructing a target function taking minimization of the space-domain and time-domain state indexes as a target, and formulating corresponding constraint conditions; and solving the target function by adopting a relay terminal matching algorithm to obtain a relay scheduling decision, scheduling the relay terminal based on the relay scheduling decision, and optimizing the time slice variable by adopting an ant algorithm. According to the method, relay scheduling and data transmission time slice variables are jointly optimized, the average end-to-end queuing delay of the network is reduced, and the performance and stability of a power distribution network communication system are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to a power distribution network heterogeneous networking scheduling method, device and medium, belonging to the power grid communication scheduling technical field. BACKGROUND

[0002] With the continuous advancement of new power system construction, the power distribution network is evolving from single-end passive to multi-end active. A large number of distributed energy resources are accessed in the active power distribution network, such as distributed photovoltaic, electric vehicle charging piles, energy storage devices, etc. Transparent real-time data collection and efficient transmission of these distributed resources are crucial for the safe operation and stable regulation of the power grid.

[0003] The prior art such as Chinese patent application for invention with publication number CN104735800B discloses a worst delay-aware cross-layer optimization method in heterogeneous wireless sensor network, which comprises: each node in the network makes a decision behavior according to the queue state of the actual queue in the current time slot and the virtual queue constructed, and then updates the queue state of the current time slot; the source node makes an optimization decision on data collection behavior; the source node and the intermediate node make optimization decisions on data packet loss behavior, routing scheduling and data transmission power allocation according to the data queue and virtual delay queue state in the current time slot; at the same time, each node makes energy collection behavior decision by observing the queue state of the energy queue and combining the electricity price factor. After several iterations, the queue state of the wireless sensor network gradually stabilizes. However, the above-mentioned patent limits the target to minimizing the network packet loss performance and optimizing the throughput utility, and does not fully consider other key business performance indicators such as data transmission delay. This may lead to insufficient support for services that require strict delay guarantees in actual application. SUMMARY

[0004] In order to solve the problems existing in the prior art, the present application provides a power distribution network heterogeneous networking scheduling method, device and medium.

[0005] The technical solution of the present application is as follows: On the one hand, the present application provides a power distribution network heterogeneous networking scheduling method, comprising the following steps: setting a scheduling variable and a data transmission time slicing variable of a relay terminal, constructing a queue backlog model based on the scheduling variable and the data transmission time slicing variable, and outputting the queue backlog of the relay terminal; setting a virtual queue based on the queue backlog, and obtaining the spatial-temporal state index of the relay terminal based on the virtual queue; setting a spatial coverage hole awareness value and a channel resource utilization awareness value of the relay terminal, and updating the spatial coverage hole awareness value and the channel resource utilization awareness value based on a dynamic prediction mechanism; obtaining a matching preference of each relay terminal and each channel based on the spatial coverage hole perception value, the channel resource utilization perception value and the spatial-temporal state index; constructing an objective function aiming at minimizing the spatial-temporal state index and formulating corresponding constraint conditions; solving the objective function by using a relay terminal matching algorithm based on the matching preference to obtain a scheduling variable of each relay terminal and taking the scheduling variable as a relay scheduling decision; scheduling the relay terminal based on the relay scheduling decision.

[0006] Preferably, the data transmission time slicing variable of the relay terminal comprises a relay data transmission time slicing variable and a local data transmission time slicing variable. constructing a relay queue backlog model based on the relay data transmission time slicing variable and the scheduling variable to output a relay queue backlog of the relay terminal; constructing a local queue backlog model based on the local data transmission time slicing variable and the scheduling variable to output a local queue backlog of the relay terminal.

[0007] Preferably, a virtual queue is set based on the queue backlogs and the spatial-temporal state index of the relay terminal is obtained based on the virtual queue, and the specific steps are as follows: obtaining a time domain state lag index based on the relay queue backlog and the local queue backlog; setting a maximum tolerable threshold of queuing delay; determining a spatial coverage hole indication variable based on the relay queue backlog, the local queue backlog and the maximum tolerable threshold of queuing delay; setting a virtual queue based on the spatial coverage hole indication variable; obtaining the spatial-temporal state index based on the time domain state lag index, the spatial coverage hole indication variable and the virtual queue.

[0008] Preferably, the matching preference of each relay terminal and each channel is obtained based on the spatial coverage hole perception value, the channel resource utilization perception value and the spatial-temporal state index, and the specific steps are as follows: obtaining a matching degree of each relay terminal and each channel based on the spatial coverage hole perception value, the channel resource utilization perception value and the spatial-temporal state index; obtaining a transmission rate average of each channel, and obtaining the matching preference of each relay terminal and each channel based on the matching degree and the transmission rate average.

[0009] Preferably, the spatial coverage hole perception value is updated based on a spatial coverage hole perception value increasing step and a next time relay terminal spatial coverage hole perception value.

[0010] Preferably, the channel resource utilization awareness value is updated based on a channel resource utilization awareness value increment step and an estimated value of the channel resource utilization awareness value of the relay terminal at the next time.

[0011] Preferably, the target function is solved by using a relay terminal matching algorithm based on the matching preference, and the specific steps are as follows: S1, initialize the queue backlog, the spatial coverage hole awareness value, the channel resource utilization awareness value, the scheduling variable of each relay terminal, and the matching request quantity of each channel; S2, obtain the matching preference of each channel and the relay terminal which does not initiate a matching request, select the channel corresponding to the maximum matching preference from the matching preference, initiate a matching request, and set the matching request quantity of the channel to 1; S3, if the matching request quantity of the channel is less than or equal to 1, execute step S5, otherwise execute step S4; S4, compare the matching preference of the relay terminal which initiates the matching request and the matched relay terminal with the channel, if the matching preference of the relay terminal which initiates the matching request is greater than the matching preference of the matched relay terminal and the channel, set the scheduling variable of the relay terminal which initiates the matching request to 1, and set the scheduling variable of the matched relay terminal to 0; Otherwise, set the scheduling variable of the relay terminal which initiates the matching request to 0; S5, set the scheduling variable of the relay terminal which initiates the matching request to 1; S6, update the spatial coverage hole awareness value and the channel resource utilization awareness value of each relay terminal at the next time, select the next relay terminal which does not initiate a matching request to execute step S2, and repeat until all relay terminals are executed.

[0012] Preferably, the method further comprises optimizing the data transmission time slicing variable by using an ant algorithm. Wherein, the pheromone quantity of the ant algorithm is updated by using a time domain state lag index. The specific steps of the ant algorithm are as follows: D1, consider the relay terminal as an ant, initialize the number of ants, the pheromone evaporation factor, the information heuristic factor, the expected heuristic factor, the heuristic function, the termination threshold, and the pheromone quantity; D2, let the unexecuted ant randomly generate a starting position; D3, the ant moves to the next position according to the movement rule; Wherein, the movement rule is based on the pheromone quantity, the information heuristic factor, the expected heuristic factor, and the heuristic function, and the heuristic function is constructed based on the data transmission time slicing variable, and different positions correspond to different data transmission time slicing variables. The pheromone amount is constructed based on a pheromone volatility factor; D4, performing step D3 until the heuristic function of the current stay position is less than or equal to a termination threshold or the number of loops reaches a maximum execution threshold; D5, taking the data transmission time slice variable corresponding to the final stay position of the ant as a new termination threshold; D6, selecting the next unexecuted ant to perform step D2 until all ants are executed; D7, taking the data transmission time slice variable corresponding to the heuristic function as an optimal data transmission time slice variable and outputting.

[0013] In still another aspect, the present application also provides an electronic device having a computer program stored thereon, wherein the computer program is executed by a processor to implement the power distribution network heterogeneous networking scheduling method according to any one of the embodiments of the present application.

[0014] In still another aspect, the present application also provides a computer readable storage medium for storing one or more programs, wherein the one or more programs, when executed by one or more processors, cause the one or more processors to implement the power distribution network heterogeneous networking scheduling method according to any one of the embodiments of the present application.

[0015] The present application has the following beneficial effects: 1. The present application sets the scheduling variable and the data transmission time slice variable of the relay terminal to construct a queue backlog model and other series of operations, and can effectively improve the data transmission integrity and timeliness, and guarantee the real-time and reliability of power grid operation, in view of the communication islands caused by the dispersion of terminal devices in the power distribution network communication network, and the information time lag caused by the heterogeneity and task priority difference.

[0016] 2. The present application sets a virtual queue according to the queue backlog, and obtains the airspace and time domain state indicators, and then obtains the matching preferences of the relay terminal and each channel, and solves the objective function based on the relay terminal matching algorithm and the ant colony algorithm, to realize the accurate decision of the scheduling of each relay terminal and the data transmission time slice, and improve the communication resource allocation and utilization efficiency.

[0017] 3. The present application differs from the existing part of the technology which only focuses on the network packet loss performance and throughput utility, and the present application takes the minimization of the airspace and time domain state indicators as the target, and simultaneously considers the time delay and jitter of data transmission, and supports the services requiring strict time delay guarantee more fully, to meet the strict requirements of various key services of the power distribution network on communication.

[0018] 4. The present application uses the ant colony algorithm to solve the optimal data transmission time slice variable, simulates the intelligent optimization mechanism of ant pathfinding, can efficiently search the global or local optimal solution, and the algorithm has strong adaptability and robustness, and can cope with the dynamic changes and uncertainties of the power distribution network communication network.

[0019] 5、The application converts the airspace coverage hole rate constraint into the queue stability constraint by jointly optimizing the relay scheduling and time slicing, so that the system effectively reduces the network average end-to-end queuing delay while ensuring the airspace coverage hole rate requirement, and improves the overall performance and stability of the power distribution network communication system. BRIEF DESCRIPTION OF DRAWINGS

[0020] Figure 1 The method embodiment flowchart of the application is shown.

[0021] Figure 2 The network airspace coverage hole rate change comparison chart of the embodiment of the application is shown.

[0022] Figure 3 The network average end-to-end queuing delay change comparison chart of the embodiment of the application is shown. DETAILED DESCRIPTION

[0023] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the application.

[0024] It should be understood that the step numbers used herein are only for the convenience of description, and are not limited to the execution sequence of the steps.

[0025] It should be understood that the terms used in the specification of the application are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in the specification and the appended claims of the application, unless otherwise clear from the context, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0026] The terms "comprise" and "include" indicate the presence of the described features, whole, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, whole, steps, operations, elements, components and / or sets thereof.

[0027] The term "and / or" means any combination of one or more of the associated listed items and all possible combinations, and includes these combinations.

[0028] Embodiment one: A power distribution network heterogeneous networking includes a perception layer, a relay layer and an edge layer. The perception layer is provided with at least one collection terminal deployed on distributed photovoltaic, electric vehicle charging pile, distributed energy storage and other power equipment, for acquiring real-time collected voltage, active power, reactive power and other data and transmitting to the relay layer through high-speed radio frequency communication (HRF), long range radio (LoRa) and other methods; The relay layer is provided with at least two relay terminals for receiving relay data uploaded by the perception layer, and forwarding the relay data and local data collected by the relay terminal locally to the edge server of the edge layer through a channel; The channel includes an HPLC channel and a 5G channel; The edge layer is provided with an edge server for processing data uploaded by the relay terminal, supporting power business operation such as equipment monitoring, load control, distributed power regulation, etc.

[0029] Referring to Figure 1 The embodiment provides a power distribution network heterogeneous networking scheduling method, including the following steps: A scheduling variable and a data transmission time slicing variable of the relay terminal are set, a queue backlog model is constructed based on the scheduling variable and the data transmission time slicing variable, and a queue backlog of the relay terminal is output; A virtual queue is set based on the queue backlog, and a space-time state index of the relay terminal is obtained based on the virtual queue; A space coverage hole perception value and a channel resource utilization rate perception value of the relay terminal are set, and the space coverage hole perception value and the channel resource utilization rate perception value are updated based on a dynamic prediction mechanism; A matching preference of the relay terminal and each channel is obtained based on the space coverage hole perception value, the channel resource utilization rate perception value and the space-time state index; A target function with the minimum space-time state index as the target is constructed, and corresponding constraint conditions are formulated; The target function is solved by using a relay terminal matching algorithm based on the matching preference, the scheduling variable of each relay terminal is obtained, and the scheduling variable is used as a relay scheduling decision; The relay terminal is scheduled based on the relay scheduling decision.

[0030] Preferably, the data transmission time slicing variable of the relay terminal includes a relay data transmission time slicing variable and a local data transmission time slicing variable; A relay queue backlog model is constructed based on the relay data transmission time slicing variable and the scheduling variable, and a relay queue backlog of the relay terminal is output, which is expressed by the following formula: ; ; In the formula, represents the relay terminal at the relay data queue backlog at time, denotes the maximum function, denotes the relay terminal at the relay data queue backlog at time, denotes the relay terminal at whether the channel is used by the relay terminal at time, denotes whether the relay terminal is scheduled and uploads data to the edge server through the channel at time, denotes the transmission rate of the channel used by the relay terminal at time, denotes the transmission rate of the channel used by the relay terminal at time, denotes the relay data transmission time slicing variable of the relay terminal at time, denotes the amount of relay data received by the relay terminal at time, denotes the scheduling period, denotes the time index, denotes the time length of the time index, denotes the relay terminal index, denotes the channel index. In an embodiment, the HPLC channel and the 5G channel transmission rate are 10 Mbps and 200 Mbps, respectively.

[0031] The local queue backlog model is constructed based on the local data transmission time slicing variable and the scheduling variable, and the local queue backlog of the relay terminal is output, which is expressed by the formula: ; In the formula, denotes the relay terminal at local data queue backlog at time t, max represents a maximum function, represents the relay terminal receives local data at time t, local data queue backlog at time t, represents the relay terminal receives local data at time t, local data transmission time slice variable at time t, represents the relay terminal receives local data at time t, local data amount received by the

[0032] In an embodiment, the initial values of the local data queue backlog and the relay data queue backlog are set to 0, and the relay data transmission time slice variable and the local data transmission time slice variable are set to 0.5.

[0033] Building a queue backlog can quantify the degree of network congestion and drive load balancing. Through the maximum function max, negative distortion can be avoided, and scheduling stability can be ensured. At the same time, when the amount of data that can be sent at the current time exceeds the backlog data, the excess bandwidth is automatically allocated to other queues.

[0034] Preferably, a virtual queue is set based on the queue backlog, and a space-time state index of the relay terminal is obtained based on the virtual queue, and the specific steps are as follows: The time-domain state lag index is obtained based on the relay queue backlog and the local queue backlog, and is expressed by the formula: ; In the formula, represents the time-domain state lag index of the relay layer, represents a time index, represents the relay terminal receives relay data at time t, represents the relay terminal receives local data at time t, represents the relay terminal receives local data at time t, represents the number of relay terminals; The maximum tolerable threshold of queuing delay is set; The space-time coverage hole indicating variable is determined based on the relay queue backlog, the local queue backlog, and the maximum tolerable threshold of queuing delay, and is expressed by the formula: ; wherein, denotes the relay terminal at time denotes the spatial coverage hole indicator variable at time denotes the relay terminal maximum tolerable queuing delay threshold, denotes the indicator function, outputs 1 if the inequality is true, otherwise outputs 0; In the research of the minimum spatial-temporal state index of the heterogeneous networking problem of the power distribution network, under the constraint of the spatial coverage hole rate, the relay scheduling and time slicing are jointly optimized to minimize the weighted sum of the network spatial coverage hole rate and the network average end-to-end queuing delay. The optimization problem can be modeled as: ; wherein, denotes the minimum function, denotes the preset weight coefficient, denotes the relay terminal whether the channel is used by the relay terminal at time denotes the relay terminal relay data transmission time slicing variable at time denotes the relay terminal local data transmission time slicing variable at time ; And the following constraint conditions are set, which are expressed in formulas as: ; wherein, denotes the constraint condition, denotes the expected function, denotes the maximum tolerable average spatial coverage hole rate of the relay terminal ; Because the short-term relay scheduling and time slicing are coupled with the long-term spatial coverage hole rate constraint, the optimization problem is difficult to solve directly. Therefore, a virtual queue is set based on the spatial coverage hole indicator variable; Based on the time-domain state lag index, the spatial coverage hole indicator variable and the virtual queue, the spatial-temporal state index is obtained, and the spatial coverage hole rate constraint is introduced by introducing the concept of virtual queue Convert into a queue stability constraint, and convert the above optimization problem modeling into a solvable objective function; Construct an objective function with the goal of minimizing the airspace-time state index, and formulate the corresponding constraint condition; ; In the formula, Indicates the minimum value function, Indicates the objective function, Indicates the preset weight coefficient, Indicates the virtual queue of the nth relay terminal At the time t; The corresponding constraint condition is expressed by the formula: ; The virtual queue is expressed by the formula: ; In the formula, Indicates the virtual queue of the nth relay terminal At the time t, Indicates the airspace coverage hole indicating variable of the nth relay terminal At the time t, Indicates the maximum tolerable average airspace coverage hole rate of the nth relay terminal .

[0035] In an embodiment, the initial value of the virtual queue is 0.

[0036] Preferably, the matching preference of the relay terminal and each channel is obtained based on the airspace-time state index, and the specific steps are as follows: Set the initial values of the airspace coverage hole awareness value and the channel resource utilization awareness value of the relay terminal, and formulate an updating rule to update the airspace coverage hole awareness value and the channel resource utilization awareness value at the next time; In an embodiment, the initial values of the airspace coverage hole awareness value and the channel resource utilization awareness value of the relay terminal are both set to 0; The matching degree of the relay terminal and the channel is obtained based on the airspace coverage hole awareness value, the channel resource utilization awareness value, and the airspace-time state index, and is expressed by the formula: ; In the formula, Indicates the matching degree of the nth relay terminal and the channel, ​​​​​​​exist Time and the Channel The degree of matching, Here, it refers to the directly calculated spatial and temporal state indices, which can also be understood as the objective function that has not yet been solved. Indicates the weight of the perception value for airspace coverage holes. The perceived value weight represents the channel resource utilization rate. , Adjustments can be made according to the actual situation. Indicates the first relay terminal exist The spatial coverage void perception value at any given moment. Indicates the first relay terminal exist Time and the Channel The perceived value of channel resource utilization. Indicates the first relay terminal exist Whether to use the first time Channel scheduling variables, Indicates the first relay terminal exist The relay data transmission time-slicing variable at a given moment. Indicates the first relay terminal exist Local data transmission time-slicing variable at any given moment; The average transmission rate of the channel is obtained, expressed by the formula: ; In the formula, Indicates the time index. Indicates the first relay terminal exist Use the first time Channel transmission rate, Indicates the first relay terminal exist Time and the Channel The average transmission rate; The matching preference between the relay terminal and the channel is obtained based on the matching degree and the average transmission rate, expressed by the formula: ; In the formula, Indicates the first relay terminal exist Time and the Channel Matching preferences.

[0037] By incorporating communication island awareness and resource utilization into the matching preference, when a matching conflict occurs, the matching requests of relay terminals with large local cache data queuing delays are prioritized, effectively reducing the generation of communication islands, avoiding channel resource surplus, and ensuring the long-term stability of the network.

[0038] Preferably, the airspace coverage hole sensing value is updated based on the airspace coverage hole sensing value improvement step size and the relay terminal airspace coverage hole sensing value at the next moment, as expressed by the formula: ; In the formula, Indicates the first relay terminal exist The spatial coverage void perception value at any given moment. Indicates the first relay terminal The step size for increasing the airspace coverage hole perception value. Indicates the spatial discount factor. Indicates the quantity at future time points. Indicates the first relay terminal I am The estimated value of airspace coverage void perception at any given moment is preset by technical personnel based on experience. The step size for increasing the perceived value of airspace coverage voids is expressed by the formula: ; In the formula, This represents the step size adjustment factor for improving the perception value of airspace coverage holes. Indicates the first relay terminal exist The perceived value of the spatial coverage void at any given moment; The number of future moments is expressed by the formula: ; In the formula, Represents the maximum value function. This represents the minimum threshold quantity at any given time. This represents the adjustment coefficient, used to control the sensitivity of volatility to the number of time intervals. Indicates in the time instant, a reference fluctuation; the island awareness fluctuation is expressed by a formula as follows: ; in the formula, represents the mean value of the spatial coverage hole awareness value at the time instant.

[0039] Preferably, the channel resource utilization awareness value is updated based on a channel resource utilization awareness value increment step and an estimated value of the channel resource utilization awareness value of the relay terminal at the next time instant, and is expressed by a formula as follows: ; in the formula, represents the channel resource utilization awareness value of the i-th relay terminal at the time instant t and the j-th channel, represents the channel resource utilization awareness value increment step of the i-th relay terminal and the j-th channel, represents the maximum tolerable transmission data amount threshold of the j-th channel, represents the resource discount factor, represents the estimated value of the channel resource utilization awareness value of the i-th relay terminal and the j-th channel at the next time instant, which is preset by a technician according to experience; the channel resource utilization awareness value increment step is expressed by a formula as follows: ; in the formula, represents the channel resource utilization awareness value increment step factor,

[0040] Preferably, the relay terminal matching algorithm is used to solve the objective function based on matching preference, and the specific steps are as follows: ​​​​​​​​​​​​​​​​​​​​​​​S1, initializing the spatial coverage hole awareness value, the channel resource utilization awareness value, the scheduling variable, the local data queue backlog and the relay data queue backlog of each relay terminal, and the matching request number of the channel; In an embodiment, the spatial coverage hole awareness value and the channel resource utilization awareness value of each relay terminal are set to 0, the scheduling variable is set to 0, and the matching request number of the channel is set to 0 at initialization; S2, obtaining the matching preference of the relay terminal which does not initiate the matching request and each channel, selecting the channel corresponding to the maximum matching preference from the matching preference to initiate the matching request, and adding 1 to the matching request number of the channel; S3, if the matching request number of the channel is less than or equal to 1, executing step S5, otherwise executing step S4; S4, comparing the matching preference of the relay terminal which initiates the matching request and the matched relay terminal and the channel, if the matching preference of the relay terminal which initiates the matching request and the channel is greater than the matching preference of the matched relay terminal and the channel, setting the scheduling variable of the relay terminal which initiates the matching request to 1, and setting the scheduling variable of the matched relay terminal to 0; Otherwise, setting the scheduling variable of the relay terminal which initiates the matching request to 0; S5, setting the scheduling variable of the relay terminal which initiates the matching request to 1; S6, updating the spatial coverage hole awareness value and the channel resource utilization awareness value of each relay terminal at the next time, selecting the next relay terminal which does not initiate the matching request to execute step S2, until all relay terminals are executed.

[0041] Preferably, the method further comprises optimizing the data transmission time slicing variable by using the ant algorithm; Wherein, the pheromone amount of the ant algorithm is updated by using the time domain state lag index, which is expressed by the formula as follows: ; In the formula, represents a proportional coefficient, represents a pheromone increment; The pheromone increment is expressed by the formula as follows: ; In the formula, represents a pheromone increment factor.

[0042] Preferably, the specific steps of the ant algorithm are as follows: D1, regarding the relay terminal as an ant, initializing the number of ants, the pheromone evaporation factor, the information heuristic factor, the expected heuristic factor, the heuristic function, the termination threshold, and the pheromone amount; In an embodiment, the number of ants is set to 50, the pheromone evaporation factor is set to 0.7, the information heuristic factor is set to 1, the expectation heuristic factor is set to 2.5, the heuristic function is set to 100, the termination threshold is set to 100, and the pheromone amount is set to 0; D2, randomly generating a starting position for the unexecuted ant; D3, moving the ant to the next position according to the movement rule; The movement rule is based on the pheromone amount, the information heuristic factor, the expectation heuristic factor, and the heuristic function, and is expressed by the formula: ; In the formula, represents the next position of the movement of the i-th ant, represents the corresponding position when the pheromone amount reaches the maximum value, represents the corresponding position when the pheromone amount reaches the maximum value, represents the corresponding position when the pheromone amount reaches the maximum value, , represents the pheromone amount of the position, represents the heuristic function, represents the information heuristic factor, represents the expectation heuristic factor; The heuristic function is constructed based on the data transmission time slice variable, and different positions correspond to different data transmission time slice variables; The pheromone amount is constructed based on the pheromone evaporation factor; D4, executing step D3 until the heuristic function of the current stop position is less than or equal to the termination threshold or the number of loops reaches the maximum execution threshold; D5, taking the data transmission time slice variable corresponding to the final stop position of the ant as a new termination threshold; D6, selecting the next unexecuted ant to execute step D2 until all ants are executed; D7, taking the data transmission time slice variable corresponding to the heuristic function as the optimal data transmission time slice variable and outputting it. The existing ant colony algorithm does not consider the influence of information time delay on pheromone update, resulting in slow convergence and easy to fall into local optimum; In relay scheduling, the communication island perception value and resource utilization rate are not optimized at the same time, affecting the island suppression effect. The improved ant colony algorithm is used to optimize the time slice, and the pheromone update method of time domain state lag perception is used to speed up the convergence speed and improve the optimization accuracy.

[0043]

[0044] ​By optimizing the data transmission time slicing variable, the relay terminal of different communication system is allocated with differentiated transmission time slots, so as to avoid channel conflict. Meanwhile, in combination with the queue backlog data of the relay terminal, the flow routing path is dynamically adjusted, and the data is preferentially guided to the relay terminal with low backlog. Both low-delay transmission of service data and load balancing to avoid local network congestion are ensured.

[0045] Referring to Figures 2-3 The comparison algorithm 1 is a Q-learning algorithm, and the comparison algorithm 2 is a simulated annealing algorithm, and the comparison results are as follows: Figure 2 and Figure 3 The network airspace coverage hole rate and the network average end-to-end queuing delay under different algorithms are shown. The network airspace coverage hole rate of the algorithm provided in the application is reduced by 37.5% compared with the comparison algorithm 1, and reduced by 58.3% compared with the comparison algorithm 2. The network average end-to-end queuing delay of the algorithm provided in the application is reduced by 3% compared with the comparison algorithm 1, and reduced by 4.9% compared with the comparison algorithm 2.

[0046] Embodiment two: The embodiment provides an electronic device, which has a computer program stored thereon, and the computer program is executed by a processor to implement the power distribution network heterogeneous networking scheduling method according to any one of the embodiments of the application.

[0047] Embodiment three: The embodiment provides a computer readable storage medium for storing one or more programs, and when the one or more programs are executed by one or more processors, the one or more processors implement the power distribution network heterogeneous networking scheduling method according to any one of the embodiments of the application.

[0048] In the embodiments of the application, “at least one” means one or more, and “multiple” means two or more. “And / or” describes the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B, which means that A exists alone, A and B exist together, and B exists alone. Wherein A and B can be singular or plural. The character “ / ” generally represents an “or” relationship between the associated objects before and after it. “At least one of the following” and the like means any combination of these items, including any combination of single or multiple items. For example, at least one of a, b and c can mean: a, b, c, a and b, a and c, b and c, or a and b and c, wherein a, b, and c can be single or multiple.

[0049] Those skilled in the art can clearly understand that the units and algorithm steps described in the embodiments disclosed herein can be realized by electronic hardware, computer software and a combination of the two. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0050] Those skilled in the art can clearly understand that, for the convenience and brevity of the description, the specific working processes of the above-described system, device and unit can refer to the corresponding processes in the foregoing method embodiments, which will not be described here.

[0051] In several embodiments provided in the present application, any function realized in the form of a software function unit and sold or used as an independent product can be stored in a computer-readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the parts that make contributions to the prior art or parts of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0052] The above is only an embodiment of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation, or direct or indirect application in other related technical fields, is also included in the patent protection scope of the present application.

Claims

1. A power distribution network heterogeneous networking scheduling method, characterized in that, The method comprises the following steps: Setting a scheduling variable and a data transmission time slice variable of the relay terminal, constructing a queue backlog model based on the scheduling variable and the data transmission time slice variable, and outputting a queue backlog of the relay terminal; setting a virtual queue based on the queue backlog, and obtaining a space-time state index of the relay terminal based on the virtual queue; setting a space coverage hole perception value and a channel resource utilization rate perception value of the relay terminal, and updating the space coverage hole perception value and the channel resource utilization rate perception value based on a dynamic prediction mechanism; obtaining a matching preference of the relay terminal and each channel based on the space coverage hole perception value, the channel resource utilization rate perception value and the space-time state index; constructing a target function with the minimum space-time state index as the target, and formulating corresponding constraint conditions; solving the target function based on the matching preference by using a relay terminal matching algorithm to obtain the scheduling variable of each relay terminal and take it as a relay scheduling decision; and scheduling the relay terminal based on the relay scheduling decision.

2. The power distribution network heterogeneous networking scheduling method of claim 1, wherein, The data transmission time slice variable of the relay terminal comprises a relay data transmission time slice variable and a local data transmission time slice variable; A relay queue backlog model is constructed based on the relay data transmission time slice variable and the scheduling variable, and a relay queue backlog of the relay terminal is outputted. A local queue backlog model is constructed based on the local data transmission time slice variable and the scheduling variable, and a local queue backlog of the relay terminal is outputted.

3. The power distribution network heterogeneous networking scheduling method of claim 2, wherein, The virtual queue is set based on the queue backlog, and the space-time state index of the relay terminal is obtained based on the virtual queue, and the specific steps are as follows: A time domain state lag index is obtained based on the relay queue backlog and the local queue backlog; A maximum tolerable threshold of queuing delay is set; A space coverage hole indication variable is determined based on the relay queue backlog, the local queue backlog and the maximum tolerable threshold of queuing delay; The virtual queue is set based on the space coverage hole indication variable; The space-time state index is obtained based on the time domain state lag index, the space coverage hole indication variable and the virtual queue.

4. The power distribution network heterogeneous networking scheduling method of claim 3, wherein, The matching preference of the relay terminal and each channel is obtained based on the space coverage hole perception value, the channel resource utilization rate perception value and the space-time state index, and the specific steps are as follows: A matching degree of the relay terminal and the channel is obtained based on the space coverage hole perception value, the channel resource utilization rate perception value and the space-time state index. A transmission rate average of the channel is obtained, and the matching preference of the relay terminal and the channel is obtained based on the matching degree and the transmission rate average.

5. The power distribution network heterogeneous networking scheduling method of claim 1, wherein, The space coverage hole perception value is updated based on a space coverage hole perception value step length and a relay terminal space coverage hole perception value at a next time.

6. The power distribution network heterogeneous networking scheduling method of claim 1, wherein, The channel resource utilization rate perception value is updated based on a channel resource utilization rate perception value step length and an estimated value of a relay terminal resource utilization rate perception value on the channel at a next time.

7. The power distribution network heterogeneous networking scheduling method of claim 4, wherein, The target function is solved based on the matching preference by using the relay terminal matching algorithm, and the specific steps are as follows: S1, initializing the queue backlog, the space coverage hole perception value, the channel resource utilization rate perception value, the scheduling variable of each relay terminal and the matching request quantity of each channel; S2, obtaining the matching preferences of the relay terminals which do not initiate the matching request and each channel, selecting the channel corresponding to the maximum matching preference from the matching preferences to initiate the matching request, and adding 1 to the matching request number of the channel; S3, if the matching request number of the channel is less than or equal to 1, executing step S5, otherwise executing step S4; S4, comparing the matching preferences of the relay terminal which initiates the matching request and the matched relay terminal and the channel, if the matching preference of the relay terminal which initiates the matching request and the channel is greater than the matching preference of the matched relay terminal and the channel, setting the scheduling variable of the relay terminal which initiates the matching request to 1 and setting the scheduling variable of the matched relay terminal to 0; otherwise, setting the scheduling variable of the relay terminal which initiates the matching request to 0; S5, setting the scheduling variable of the relay terminal which initiates the matching request to 1; S6, updating the spatial coverage hole perception value and the channel resource utilization rate perception value of each relay terminal at the next time, and selecting the next relay terminal which does not initiate the matching request to execute step S2 until all relay terminals are executed.

8. The power distribution network heterogeneous networking scheduling method of claim 3, wherein, The method further comprises optimizing the data transmission time slicing variable by using an ant algorithm; wherein the pheromone amount of the ant algorithm is updated by using a time domain state lag index; The specific steps of the ant algorithm are as follows: D1, regarding the relay terminal as an ant, initializing the number of ants, the pheromone evaporation factor, the information heuristic factor, the expected heuristic factor, the heuristic function, the termination threshold, and the pheromone amount; D2, letting the unexecuted ant randomly generate a starting position; D3, the ant moves to the next position according to the movement rule; wherein the movement rule is based on the pheromone amount, the information heuristic factor, the expected heuristic factor, and the heuristic function, the heuristic function is constructed based on the data transmission time slicing variable, and different positions correspond to different data transmission time slicing variables; the pheromone amount is constructed based on the pheromone evaporation factor; D4, executing step D3 until the heuristic function of the current position is less than or equal to the termination threshold or the number of loops reaches the maximum execution threshold; D5, taking the data transmission time slicing variable corresponding to the final position of the ant as a new termination threshold; D6, selecting the next unexecuted ant to execute step D2 until all ants are executed; D7, taking the data transmission time slicing variable corresponding to the heuristic function as the optimal data transmission time slicing variable and outputting it.

9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the program to implement the power distribution network heterogeneous networking scheduling method of any one of claims 1 to 8.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the power distribution network heterogeneous networking scheduling method of any one of claims 1 to 8. The program is executed by the processor to implement the power distribution network heterogeneous networking scheduling method of any one of claims 1 to 8.

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