A power distribution network heterogeneous networking scheduling method and device and medium

Abstract

The present application relates to a kind of power distribution network heterogeneous networking scheduling method, equipment and medium, belong to power grid communication scheduling technical field, include the following steps: setting the scheduling variable of relay terminal and data transmission time slice variable, construct queue backlog model and output queue backlog;Based on queue backlog, set virtual queue, obtain the space-time state index of relay terminal, and then obtain the matching preference of relay terminal and each channel;Construct the objective function with the minimum space-time state index as target, formulate corresponding constraint condition;Using relay terminal matching algorithm to solve the objective function obtains relay scheduling decision, based on the relay scheduling decision scheduling relay terminal, and using ant algorithm to optimize time slice variable.The present application jointly optimizes relay scheduling and data transmission time slice variable, reduces network average end-to-end queuing delay, improves the performance and stability of power distribution network communication system.

Description

TECHNICAL FIELD

[0001] The application relates to a power distribution network heterogeneous networking scheduling method, device and medium, and belongs to the technical field of power grid communication scheduling. 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, such as distributed photovoltaic, electric vehicle charging piles and energy storage devices, are connected to the active power distribution network. 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 a heterogeneous wireless sensor network. The method includes: each node in the network makes a decision based on the actual queue and the constructed virtual queue state of the current time slot, 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 based on the current time slot data queue and virtual delay queue state; 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 multiple iterations, the queue state of the wireless sensor network gradually stabilizes. However, the above-mentioned patent limits the target to minimizing network packet loss performance and optimizing 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 applications. SUMMARY

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

[0005] The technical scheme of the application is as follows:

[0006] On the one hand, the application provides a power distribution network heterogeneous networking scheduling method, which includes the following steps:

[0007] 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;

[0008] Setting a virtual queue based on the queue backlog, and obtaining the spatial and temporal state indicators of the relay terminal based on the virtual queue;

[0009] set a spatial coverage hole awareness value and a channel resource utilization awareness value of the relay terminal, and update the spatial coverage hole awareness value and the channel resource utilization awareness value based on a dynamic prediction mechanism;

[0010] obtain a matching preference of the relay terminal and each channel based on the spatial coverage hole awareness value, the channel resource utilization awareness value, and a spatial-temporal state index;

[0011] construct an objective function aiming at minimizing the spatial-temporal state index, and formulate corresponding constraint conditions;

[0012] solve the objective function based on the matching preference by using a relay terminal matching algorithm to obtain a scheduling variable of each relay terminal and use the scheduling variable as a relay scheduling decision;

[0013] schedule the relay terminal based on the relay scheduling decision.

[0014] 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;

[0015] construct 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;

[0016] construct 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.

[0017] Preferably, a virtual queue is set based on the queue backlogs, and a spatial-temporal state index of the relay terminal is obtained based on the virtual queue, and the specific steps are as follows:

[0018] obtain a temporal state lag index based on the relay queue backlog and the local queue backlog;

[0019] set a maximum tolerable threshold of queuing delay;

[0020] determine a spatial coverage hole indication variable based on the relay queue backlog, the local queue backlog, and the maximum tolerable threshold of queuing delay;

[0021] set a virtual queue based on the spatial coverage hole indication variable;

[0022] obtain the spatial-temporal state index based on the temporal state lag index, the spatial coverage hole indication variable, and the virtual queue.

[0023] Preferably, the matching preference of the relay terminal and each channel is obtained based on the spatial coverage hole awareness value, the channel resource utilization awareness value, and the spatial-temporal state index, and the specific steps are as follows:

[0024] obtaining a matching degree of the relay terminal and the channel based on the spatial coverage hole perception value, the channel resource utilization perception value and the spatial and temporal state index of the channel;

[0025] obtaining a transmission rate average value of the channel, and obtaining a matching preference of the relay terminal and the channel based on the matching degree and the transmission rate average value.

[0026] Preferably, the spatial coverage hole perception value is updated based on a spatial coverage hole perception value step-up and a spatial coverage hole perception value of the relay terminal at the next time.

[0027] Preferably, the channel resource utilization perception value is updated based on a channel resource utilization perception value step-up and an estimated value of the channel resource utilization perception value of the relay terminal at the next time.

[0028] 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:

[0029] S1, initializing a queue backlog, a spatial coverage hole perception value, a channel resource utilization perception value, a scheduling variable of each relay terminal and a matching request quantity of each channel;

[0030] S2, obtaining a matching preference of a relay terminal not initiating a matching request and each channel, initiating a matching request to a channel corresponding to a maximum matching preference from the matching preferences, and increasing the matching request quantity of the channel by 1;

[0031] S3, if the matching request quantity of the channel is less than or equal to 1, executing step S5, otherwise executing step S4;

[0032] S4, comparing the matching preference of the relay terminal initiating the matching request and the matching preference of the relay terminal already matched with the channel, if the matching preference of the relay terminal initiating the matching request is greater than the matching preference of the relay terminal already matched with the channel, setting the scheduling variable of the relay terminal initiating the matching request to 1 and setting the scheduling variable of the relay terminal already matched to 0;

[0033] Otherwise, setting the scheduling variable of the relay terminal initiating the matching request to 0;

[0034] S5, setting the scheduling variable of the relay terminal initiating the matching request to 1;

[0035] S6, updating the spatial coverage hole perception value and the channel resource utilization perception value of each relay terminal at the next time, and selecting a next relay terminal not initiating a matching request to execute step S2 until all relay terminals are executed.

[0036] Preferably, the method further comprises optimizing a data transmission time slicing variable by using an ant algorithm.

[0037] The pheromone amount of the ant algorithm is updated by using a time domain state lag index.

[0038] The specific steps of the ant algorithm are as follows:

[0039] D1, regarding the relay terminal as an ant, initializing the number of ants, a pheromone evaporation factor, an information heuristic factor, an expected heuristic factor, a heuristic function, a termination threshold and a pheromone amount;

[0040] D2, letting an unexecuted ant randomly generate a starting position;

[0041] D3, the ant moves to a next position according to a movement rule;

[0042] The movement rule is formulated based on the pheromone amount, the information heuristic factor, the expected heuristic factor and the heuristic function, and the heuristic function is constructed based on a data transmission time slice variable, and different positions correspond to different data transmission time slice variables;

[0043] The pheromone amount is constructed based on the pheromone evaporation factor;

[0044] D4, step D3 is executed until the heuristic function of a current stay position is less than or equal to the termination threshold or the number of cycles reaches a maximum execution threshold;

[0045] D5, the data transmission time slice variable corresponding to the final stay position of the ant is taken as a new termination threshold;

[0046] D6, a next unexecuted ant is selected to execute step D2 until all ants are executed;

[0047] D7, the data transmission time slice variable corresponding to the heuristic function is taken as an optimal data transmission time slice variable and output.

[0048] In another aspect, the application further 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 application.

[0049] In another aspect, the application further 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 application.

[0050] The application has the following beneficial effects:

[0051] 1、The application constructs a queue backlog model through setting the scheduling variable and data transmission time slicing variable of the relay terminal, and can effectively improve the data transmission integrity and timeliness, and guarantee the real-time and reliability of power grid operation, aiming at the communication island caused by the dispersion of terminal equipment in the power distribution network communication network, and the information time lag caused by the heterogeneity and task priority difference.

[0052] 2、The application sets a virtual queue according to the queue backlog, and obtains the airspace and time domain state index, and then obtains the matching preference of the relay terminal and each channel, and solves the objective function based on the relay terminal matching algorithm and the ant colony algorithm, so that the accurate decision of the scheduling of each relay terminal and the data transmission time slicing is realized, and the communication resource allocation and utilization efficiency is improved.

[0053] 3、The application is different from the existing part of the technology which only pays attention to the network packet loss performance and throughput utility, and the application takes minimizing the airspace and time domain state index as the target, and considers the time delay and jitter of data transmission, so that the service which needs strict time delay guarantee is more fully supported, and the strict requirements of the power distribution network on communication are met.

[0054] 4、The application uses the ant colony algorithm to solve the optimal data transmission time slicing variable, simulates the intelligent optimization mechanism of ant path finding, can efficiently search the global or local optimal solution, and the algorithm has strong adaptability and robustness, and can cope with the dynamic change and uncertainty of the power distribution network communication network.

[0055] 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 can effectively reduce the network average end-to-end queuing delay while guaranteeing the airspace coverage hole rate requirement, and improves the overall performance and stability of the power distribution network communication system. BRIEF DESCRIPTION OF DRAWINGS

[0056] Figure 1 The flowchart of the method of the application is shown.

[0057] Figure 2 The comparison chart of the network airspace coverage hole rate change of the embodiment of the application is shown.

[0058] Figure 3 The comparison chart of the network average end-to-end queuing delay change of the embodiment of the application is shown. DETAILED DESCRIPTION

[0059] The technical solutions in the embodiments of the application will be described clearly and completely in combination with the drawings in the embodiments of the application. Obviously, the described embodiments are only a 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 scope of protection of the application.

[0060] 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.

[0061] It should be understood that the terms used in the specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification and the appended claims of the present application, the singular forms "a", "an" and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0062] The terms "comprise" and "include" indicate the presence of the described features, integers, steps, operations, elements, and / or components, but do not exclude one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0063] The term "and / or" means any combination of one or more of the associated listed items and all possible combinations, and includes these combinations.

[0064] Embodiment one:

[0065] A power distribution network heterogeneous networking includes a perception layer, a relay layer and an edge layer;

[0066] 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;

[0067] 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;

[0068] The channel includes an HPLC channel and a 5G channel;

[0069] 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.

[0070] Referring to Figure 1 , the embodiment provides a power distribution network heterogeneous networking scheduling method, comprising the following steps:

[0071] Setting a scheduling variable and a data transmission time slicing variable of the 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;

[0072] Based on the queue backlog, a virtual queue is set up, and the spatial and temporal status indicators of the relay terminal are obtained based on the virtual queue.

[0073] Set the spatial coverage hole perception value and channel resource utilization perception value of the relay terminal, and update the spatial coverage hole perception value and channel resource utilization perception value based on the dynamic prediction mechanism.

[0074] Based on the spatial coverage hole perception value, channel resource utilization perception value, and spatial time domain status index, the matching preference between the relay terminal and each channel is obtained.

[0075] Construct an objective function that minimizes the spatial and temporal state indices, and define the corresponding constraints.

[0076] The objective function is solved using a relay terminal matching algorithm based on matching preferences, and the scheduling variables of each relay terminal are obtained and used as relay scheduling decisions.

[0077] The relay terminal is scheduled based on the relay scheduling decision.

[0078] Preferably, the data transmission time sharding variable of the relay terminal includes a relay data transmission time sharding variable and a local data transmission time sharding variable;

[0079] A relay queue backlog model is constructed based on relay data transmission time-slicing variables and scheduling variables. The relay queue backlog of the relay terminal is output as a formula:

[0080] ;

[0081] ;

[0082] In the formula, Indicates the first relay terminal exist The relay data queue is backlogged at any given time. Represents the maximum value function. Indicates the first relay terminal exist The relay data queue is backlogged at any given time. Indicates the first relay terminal exist Whether to use the first time Channel scheduling variables, If it is 1, it means the first... relay terminal exist The time is scheduled and passed through the first a channel upload data to edge server, 0 means not scheduled, denotes the relay terminal at time using the channel transmission rate, denotes the relay terminal at time relay data transmission time slice variable, denotes the relay terminal at time relay data amount received, denotes the scheduling period, denotes the time index, denotes the time length of the time, denotes the number of channels, denotes the relay terminal index, denotes the channel index;

[0083] In an embodiment, the HPLC channel and 5G channel transmission rates are 10 Mbps and 200 Mbps, respectively.

[0084] Based on the local data transmission time slice variable and the scheduling variable, a local queue backlog model is constructed, and the local queue backlog of the relay terminal is output, which is expressed by the formula:

[0085] ;

[0086] In the formula, denotes the relay terminal at time local data queue backlog, denotes the maximum function, denotes the relay terminal at time local data queue backlog, denotes the relay terminal at time local data transmission time slice variable, denotes the relay terminal at time local data amount received.

[0087] In one embodiment, local data queue backlog. and relay data queue backlog The initial value is set to 0, and the relay data transmission time-slicing variable is... and local data transfer time sharding variables Set it to 0.5.

[0088] Building queue backlogs can quantify network congestion and drive load balancing. Using a maximum value function (max) avoids distortion from negative values ​​and ensures scheduling stability. Furthermore, when the amount of data that can be sent at any given time exceeds the backlog, the excess bandwidth is automatically allocated to other queues.

[0089] Preferably, a virtual queue is set up based on the queue backlog, and the spatial and temporal status indicators of the relay terminal are obtained based on the virtual queue. The specific steps are as follows:

[0090] 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:

[0091] ;

[0092] In the formula, This represents the time-domain state lag index of the relay layer. Indicates the time index. Indicates the first relay terminal exist The amount of relay data received at any given time. Indicates the first relay terminal exist The amount of local data received at any given time. Indicates the number of relay terminals;

[0093] Set the maximum tolerable threshold for queuing delay;

[0094] The airspace coverage hole indicator variable is determined based on the relay queue backlog, local queue backlog, and the maximum tolerable queuing delay threshold, expressed by the formula:

[0095] ;

[0096] In the formula, Indicates the first relay terminal exist Spatial coverage hole indicator variable at time, Indicates the first relay terminal The maximum tolerable threshold for queuing delay. denotes an indicator function, outputs 1 if the inequality holds, and outputs 0 otherwise;

[0097] In the embodiment, when researching the power distribution network heterogeneous networking problem of minimizing the space-time state index, the network space coverage hole rate and the network average end-to-end queuing delay are minimized by jointly optimizing relay scheduling and time slicing under the constraint of space coverage hole rate. The optimization problem can be modeled as:

[0098]

[0099] In the formula, denotes a minimum function, denotes a preset weight coefficient, denotes the jth relay terminal, a scheduling variable of the jth relay terminal, whether the jth channel is used at the kth moment, a scheduling variable of the jth relay terminal, a relay data transmission time slicing variable of the jth relay terminal at the kth moment, a local data transmission time slicing variable of the jth relay terminal at the kth moment; The following constraint conditions are set, which are expressed in formulas as follows: In the formula, denotes a constraint condition, denotes an expected function, denotes the maximum tolerable average space coverage hole rate of the jth relay terminal;

[0100] Because the short-term relay scheduling and time slicing are coupled with the long-term space coverage hole rate constraint, the optimization problem is difficult to solve directly. Therefore, a virtual queue is set based on the space coverage hole indicator variable;

[0101] Based on the time domain state lag index, the space coverage hole indicator variable and the virtual queue, a space-time state index is obtained, the space coverage hole rate constraint is converted into a queue stability constraint by introducing the concept of virtual queue, and the above optimization problem is modeled and converted into a solvable objective function;

[0102]

[0103] Because the short-term relay scheduling and time slicing are coupled with the long-term space coverage hole rate constraint, the optimization problem is difficult to solve directly. Therefore, a virtual queue is set based on the space coverage hole indicator variable;

[0104] Based on the time domain state lag index, the space coverage hole indicator variable and the virtual queue, a space-time state index is obtained, the space coverage hole rate constraint is converted into a queue stability constraint by introducing the concept of virtual queue, and the above optimization problem is modeled and converted into a solvable objective function;

[0105] ​​​​​​​​​​​Construct a target function aiming at minimizing the space-time state index, and formulate corresponding constraint conditions;

[0106] ;

[0107] In the formula, The minimum value function is represented by, The target function is represented by, The preset weight coefficient is represented by, The virtual queue of the i-th relay terminal at the j-th time is represented by, The virtual queue at the j-th time is represented by, The corresponding constraint condition is represented by a formula:

[0108]

[0109] ;

[0110] The virtual queue is represented by a formula:

[0111] ;

[0112] In the formula, The virtual queue of the i-th relay terminal at the j-th time is represented by, The virtual queue at the j-th time is represented by, The space coverage hole indication variable of the i-th relay terminal at the j-th time is represented by, The maximum tolerable average space coverage hole rate of the i-th relay terminal is represented by,

[0113] In an embodiment, the initial value of the virtual queue is 0.

[0114] Preferably, the matching preference of the relay terminal and each channel is obtained based on the space-time state index, and the specific steps are as follows:

[0115] The initial values of the space coverage hole awareness value and the channel resource utilization awareness value of the relay terminal are set, and an updating rule is formulated to update the space coverage hole awareness value and the channel resource utilization awareness value at the next time;

[0116] In an embodiment, the initial values of the space coverage hole awareness value and the channel resource utilization awareness value of the relay terminal are both set to 0.

[0117] The matching degree of the relay terminal and the channel is obtained based on the space coverage hole awareness value, the channel resource utilization awareness value, and the space-time state index, and is represented by a formula:​​​​​​​​​​

[0118] ;

[0119] In the formula, Indicates the first relay terminal 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 variables at any given moment;

[0120] The average transmission rate of the channel is obtained, expressed by the formula:

[0121] ;

[0122] 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 in the time and the first channel transmission rate mean;

[0123] Based on the matching degree and the transmission rate mean, the matching preference of the relay terminal and the channel is obtained, which is expressed by the formula:

[0124] ;

[0125] In the formula, indicates the matching preference of the first relay terminal in the time and the first channel .

[0126] The communication island awareness value and the resource utilization rate are introduced into the matching preference, the matching request of the relay terminal with large local cache data queuing delay is preferentially met when the matching conflict occurs, the generation of the communication island is effectively reduced, the remaining channel resources are avoided, and the long-term stability of the network is ensured.

[0127] Preferably, the spatial coverage hole awareness value is updated based on the spatial coverage hole awareness value promotion step and the spatial coverage hole awareness value of the relay terminal at the next time, which is expressed by the formula:

[0128] ;

[0129] In the formula, indicates the spatial coverage hole awareness value of the first relay terminal in the time, indicates the spatial coverage hole awareness value promotion step of the first relay terminal , indicates the spatial discount factor, indicates the number of future times, indicates the spatial coverage hole awareness estimated value of the first relay terminal in the next time, which is preset by the technician according to experience; The spatial coverage hole awareness value promotion step is expressed by the formula:

[0130]

[0131] ;

[0132] 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;

[0133] The number of future moments is expressed by the formula:

[0134] ;

[0135] In the formula, Represents the maximum value function. This represents the minimum threshold number of times. This represents the adjustment coefficient, used to control the sensitivity of volatility to the number of time intervals. Indicates in Moment-isolated perception value volatility Indicates benchmark volatility;

[0136] The volatility of the isolated sensing value is expressed by the formula:

[0137] ;

[0138] In the formula, Indicates in The mean value of the spatial domain coverage void perception value at any given time.

[0139] Preferably, the channel resource utilization perception value is updated based on the channel resource utilization perception value increase step size and the estimated value of the relay terminal's channel resource utilization perception value at the next time moment, expressed by the formula:

[0140] ;

[0141] In the formula, Indicates the first relay terminal exist Time and the Channel The perceived value of channel resource utilization. Indicates the first relay terminal With the Channel The step size for increasing the perceived value of channel resource utilization. Indicates the first Channel The maximum tolerable data transfer threshold. Represents the resource discount factor. Indicates the first relay terminal I am the channel resource utilization awareness value of the jth channel at the ith time instant; The channel resource utilization awareness value is preset by the technician according to experience;

[0142] The channel resource utilization awareness value step-up is expressed by a formula as follows:

[0143] ;

[0144] In the formula, the channel resource utilization awareness value step-up factor is represented by , and the channel resource utilization awareness value of the jth channel at the ith time instant is represented by the channel resource utilization awareness value of the jth channel at the ith time instant;

[0145] Preferably, the relay terminal matching algorithm is used to solve the objective function based on the matching preferences, and the specific steps are as follows:

[0146] S1, initialize 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 quantity of each channel;

[0147] 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 quantity of each channel is set to 0 during initialization;

[0148] S2, obtain the matching preferences of the relay terminal which has not initiated a matching request and each channel, select the channel corresponding to the maximum matching preference from the matching preferences, initiate a matching request for the channel, and increase the matching request quantity of the channel by 1;

[0149] S3, if the matching request quantity of the channel is less than or equal to 1, execute step S5, otherwise execute step S4;

[0150] S4, compare the matching preferences of the relay terminal which has initiated a matching request and the matched relay terminal and the channel, if the matching preference of the relay terminal which has initiated a 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 has initiated a matching request to 1, and set the scheduling variable of the matched relay terminal to 0;

[0151] Otherwise, set the scheduling variable of the relay terminal which has initiated a matching request to 0;

[0152] S5, set the scheduling variable of the relay terminal which has initiated a matching request to 1; ​​​​​​

[0153] S6, updating the spatial coverage hole perception value and the channel resource utilization perception value of each relay terminal at the next time, and selecting the next relay terminal which does not initiate a matching request to perform step S2 until all relay terminals are executed.

[0154] Preferably, the method further comprises optimizing the data transmission time slicing variable by using an ant algorithm;

[0155] wherein the pheromone amount of the ant algorithm is updated by using a time domain state lag index, which is expressed by a formula as follows:

[0156] ;

[0157] In the formula, p represents a proportional coefficient, represents a pheromone increment;

[0158] The pheromone increment is expressed by a formula as follows:

[0159] ;

[0160] In the formula, p represents a proportional coefficient, represents a pheromone increment factor.

[0161] Preferably, the specific steps of the ant algorithm are as follows:

[0162] D1, regarding the relay terminal as an ant, initializing the number of ants, a pheromone evaporation factor, an information heuristic factor, an expected heuristic factor, a heuristic function, a termination threshold, and a pheromone amount;

[0163] 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 expected 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 when initialized;

[0164] D2, letting an unexecuted ant randomly generate a starting position;

[0165] D3, the ant moves to the next position according to a movement rule;

[0166] In the formula, the movement rule is based on the pheromone amount, the information heuristic factor, the expected heuristic factor, and the heuristic function.

[0167] ;

[0168] In the formula, p represents a proportional coefficient, represents the next position of the movement of the i-th ant, represents the next position of the movement of the i-th ant, represents the next position of the movement of the i-th ant, ​corresponding to the maximum , information indicating the position amount of pheromone, denotes a heuristic function, denotes an information heuristic factor, denotes an expected heuristic factor;

[0169] The heuristic function is constructed based on a data transmission time slicing variable, and different positions correspond to different data transmission time slicing variables;

[0170] The amount of pheromone is constructed based on a pheromone volatility factor;

[0171] 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 cycles reaches a maximum execution threshold;

[0172] D5, taking the data transmission time slicing variable corresponding to the final stay position of the ant as a new termination threshold;

[0173] D6, selecting the next unexecuted ant to perform step D2 until all ants are executed;

[0174] D7, taking the data transmission time slicing variable corresponding to the heuristic function as the optimal data transmission time slicing variable and outputting.

[0175] 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; When relaying, the communication island perception value and resource utilization are not optimized at the same time, affecting the island suppression effect. The improved ant colony algorithm is used to optimize the time slicing in the application, and the pheromone update method of time domain state lag perception is used to speed up the convergence speed and improve the optimization accuracy.

[0176] By optimizing the data transmission time slicing variable, different transmission time slots are allocated to relay terminals of different communication systems to avoid channel conflict. At the same time, combined with the backlog data of the relay terminal queue, the flow routing path is dynamically adjusted to preferentially guide data to the relay terminal with low backlog. Both low-latency transmission of business data and load balancing to avoid local network congestion are ensured.

[0177] 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:

[0178] Figure 2 and Figure 3The network space coverage hole rate and the network average end-to-end queuing delay under different algorithms are shown respectively. The network space coverage hole rate of the algorithm provided in the application is reduced by 37.5% compared with the comparative algorithm 1 and reduced by 58.3% compared with the comparative algorithm 2. The network average end-to-end queuing delay of the algorithm provided in the application is reduced by 3% compared with the comparative algorithm 1 and reduced by 4.9% compared with the comparative algorithm 2.

[0179] Embodiment two:

[0180] The embodiment provides an electronic device, and a computer program is stored on the electronic device. The computer program is executed by a processor to implement the power distribution network heterogeneous networking scheduling method in any embodiment of the application.

[0181] Embodiment three:

[0182] The embodiment provides a computer readable storage medium for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the power distribution network heterogeneous networking scheduling method in any embodiment of the application.

[0183] In the embodiments of the application, "at least one" means one or more, and "multiple" means two or more. The "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.

[0184] Those skilled in the art can realize that the units and algorithm steps described in the embodiments disclosed herein can be realized by electronic hardware, computer software and combination of electronic hardware and computer software. Whether the functions are realized by 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 application.

[0185] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system, device and unit described above can refer to the corresponding process in the foregoing method embodiments, which will not be described here.

[0186] In several embodiments provided in the present application, any function, if 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 or the parts of the technical solutions that essentially contribute to the prior art or the 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 plurality 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 various embodiments of the present application. The aforementioned 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.

[0187] The above description is only some embodiments 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, based on the content of the specification and drawings of the present application, are also included in the patent protection scope of the present application.

Claims

1. A heterogeneous networking scheduling method for power distribution network, characterized in that, The method comprises the following steps: setting a scheduling variable and a data transmission time slice variable of a relay terminal, 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; constructing a relay queue backlog model based on the relay data transmission time slice variable and the scheduling variable, and outputting a relay queue backlog of the relay terminal; constructing a local queue backlog model based on the local data transmission time slice variable and the scheduling variable, and outputting a local queue backlog of the relay terminal; obtaining a time domain state lag index based on the relay queue backlog and the local queue backlog; setting a maximum tolerable threshold of a queuing delay; determining a space domain coverage hole indication variable based on the relay queue backlog, the local queue backlog and the maximum tolerable threshold of the queuing delay; setting a virtual queue based on the space domain coverage hole indication variable; obtaining a space domain time domain state index based on the time domain state lag index, the space domain coverage hole indication variable and the virtual queue; setting a space domain coverage hole perception value and a channel resource utilization rate perception value of the relay terminal, and updating the space domain coverage hole perception value and the channel resource utilization rate perception value based on a dynamic prediction mechanism; obtaining a matching degree of the relay terminal and a channel based on the space domain coverage hole perception value, the channel resource utilization rate perception value and the space domain time domain state index; obtaining a matching preference of the relay terminal and the channel based on the matching degree and a transmission rate average of the channel; constructing an objective function with a minimum space domain time domain state index as a target, and formulating corresponding constraint conditions; solving the objective function by using a relay terminal matching algorithm based on the matching preference, to obtain the scheduling variable of each relay terminal and use the scheduling variable as a relay scheduling decision, and the specific steps are as follows: S1, initializing the queue backlog, the space domain 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 preference of the relay terminal not initiating a matching request and each channel, selecting a channel corresponding to a maximum matching preference from the matching preference to initiate a matching request, and adding 1 to the matching request quantity of the channel; S3, if the matching request quantity 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 initiating the matching request and the matched relay terminal with the channel, if the matching preference of the relay terminal initiating the matching request is greater than the matching preference of the matched relay terminal with the channel, setting the scheduling variable of the relay terminal initiating the matching request as 1 and setting the scheduling variable of the matched relay terminal as 0; otherwise, setting the scheduling variable of the relay terminal initiating the matching request as 0; S5, setting the scheduling variable of the relay terminal initiating the matching request as 1; S6, updating the space domain coverage hole perception value and the channel resource utilization rate perception value of each relay terminal at the next time, selecting the next relay terminal not initiating the matching request to execute step S2 until all the relay terminals are executed; scheduling the relay terminal based on the relay scheduling decision.

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

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

4. The power distribution network heterogeneous networking scheduling method of claim 1, wherein, The method further comprises optimizing the data transmission time slicing variable by using an ant algorithm. 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, pheromone evaporation factor, information heuristic factor, expected heuristic factor, heuristic function, termination threshold, and pheromone amount; D2, letting an unexecuted ant randomly generate a starting position; D3, the ant moves to the next position according to a movement rule; The movement rule is formulated based on the pheromone amount, information heuristic factor, expected heuristic factor, and 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 stay position is less than or equal to the termination threshold or the number of cycles reaches the maximum execution threshold; D5, taking the data transmission time slicing variable corresponding to the final stay 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.

5. 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 4.

6. 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 4.

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