Energy Internet of Things fusion communication system and method based on swarm intelligence

Abstract

The present invention discloses an energy Internet of Things fusion communication system and method based on swarm intelligence, which belongs to the field of data processing systems for prediction. The present invention imports the acquired operation data of each energy Internet of Things node device into an energy Internet of Things node safety factor assessment model to evaluate the energy Internet of Things node safety factor, imports the acquired communication data importance factor assessment result and the energy Internet of Things node safety factor assessment into a communication resource allocation strategy to output the communication resource allocation plan of each energy Internet of Things node, controls the corresponding network transmission node to allocate network transmission resources according to the communication resource allocation plan, and reasonably allocates network transmission resources through comprehensive analysis of the historical transmission data of the energy Internet of Things node and the operation data of the node device, thereby avoiding the delay of important transmission information and improving the security of the communication process.

Description

Technical Field

[0001] The present invention belongs to the field of data processing systems for prediction, and specifically relates to an energy Internet of Things fusion communication system and method based on swarm intelligence. Background Art

[0002] Energy Internet of Things refers to an application that uses Internet of Things technology to manage and monitor energy systems. By connecting sensors, devices and systems to the Internet, Energy Internet of Things can achieve real-time monitoring, analysis and control of energy data, thereby improving energy utilization efficiency and reducing energy consumption. This technology can be applied to various energy systems, such as power systems, hydraulic systems, solar energy systems, etc., bringing more efficient and intelligent management methods to the energy industry;

[0003] Energy IoT converged communication refers to the combination of communication technology and IoT technology in the energy IoT system to achieve interconnection between energy devices. Through the converged communication technology, the energy IoT can achieve real-time communication and data exchange between devices, thereby achieving more intelligent management and control of the energy system. This converged communication technology can improve the response speed and efficiency of the energy system, making the energy IoT system more intelligent and reliable;

[0004] The existing technology cannot comprehensively analyze the historical transmission data of the energy Internet of Things nodes and the operation data of the node devices during the energy Internet of Things integrated communication process, and then irrationally allocates network transmission resources, resulting in delays in important transmission information and reducing the security of the communication process;

[0005] In order to solve these problems, this application designs an energy Internet of Things fusion communication system and method based on swarm intelligence. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention proposes an energy Internet of Things fusion communication system and method based on swarm intelligence. The present invention obtains energy transmission data and network transmission data of each energy Internet of Things node in the historical period of energy transmission of the energy Internet of Things node, and simultaneously obtains the operation data of each energy Internet of Things node device, imports the energy transmission data and network transmission data of each energy Internet of Things node in the historical period of energy transmission obtained into a communication data importance coefficient evaluation model to perform communication data importance coefficient evaluation, imports the operation data of each energy Internet of Things node device obtained into an energy Internet of Things node safety factor evaluation model to perform energy Internet of Things node safety factor evaluation, imports the obtained communication data importance coefficient evaluation results and energy Internet of Things node safety factor evaluation into a communication resource allocation strategy to output a communication resource allocation plan for each energy Internet of Things node, controls the corresponding network transmission node to allocate network transmission resources according to the communication resource allocation plan, and reasonably allocates network transmission resources through comprehensive analysis of the historical transmission data of the energy Internet of Things node and the operation data of the node device, thereby avoiding the delay of important transmission information and improving the security of the communication process.

[0007] To achieve the above object, the present invention provides the following technical solution: an energy Internet of Things fusion communication method based on swarm intelligence, which includes the following specific steps:

[0008] S1. Obtain the energy transmission data and network transmission data of each energy IoT node in the historical period of energy transmission of the energy IoT node, and at the same time obtain the operation data of each energy IoT node device;

[0009] S2. Importing the energy transmission data and network transmission data of each energy IoT node of the historical period energy transmission into the communication data importance coefficient evaluation model to evaluate the communication data importance coefficient;

[0010] S3, importing the acquired operation data of each energy Internet of Things node device into the energy Internet of Things node safety factor assessment model to conduct energy Internet of Things node safety factor assessment;

[0011] S4, importing the obtained communication data importance coefficient evaluation results and energy Internet of Things node safety coefficient evaluation into the communication resource allocation strategy to output the communication resource allocation plan of each energy Internet of Things node;

[0012] S5. Control the corresponding network transmission node to allocate network transmission resources according to the communication resource allocation plan.

[0013] As a preferred technical solution of the energy Internet of Things fusion communication method based on swarm intelligence, S1 includes the following specific steps:

[0014] S11. Obtain energy transmission data of the corresponding historical period of each energy Internet of Things node through the energy transmission collection terminal, and store it in the second storage component, wherein the energy transmission data includes energy transmission quantity data and energy transmission quality data, and the energy transmission quality is the proportion of qualified energy transmission quantity to the total energy transmission quantity, and collect the network occupancy of each energy Internet of Things node through the network transmission collection terminal;

[0015] S12, collecting the operation data of each energy Internet of Things node device through the operation data collection terminal, and storing it in the second storage component;

[0016] As a preferred technical solution for the energy Internet of Things fusion communication method based on swarm intelligence, the communication data importance coefficient evaluation model in S2 includes the following specific contents:

[0017] S21. Obtain the energy transmission data and network occupancy of each energy IoT node in the corresponding historical period, and substitute them into the network importance calculation formula to calculate the network importance of each energy IoT node. The network importance calculation formula of the i-th energy IoT node is: Wherein, m is the number of historical cycles, kij is the network occupancy of the i-th Energy IoT node in the j-th cycle, S is the number of other Energy IoT nodes that transmit energy with the i-th Energy IoT node in the j-th cycle, and Tijz is the energy transmission amount between the z-th Energy IoT node that transmits energy with the i-th Energy IoT node and the i-th Energy IoT node in the j-th cycle;

[0018] S22, obtaining the calculated network importance of all energy Internet of Things nodes, and substituting the obtained network importance of all energy Internet of Things nodes into the communication data importance coefficient calculation formula to calculate the communication data importance coefficient, wherein the communication data importance coefficient calculation formula of the i-th energy Internet of Things node is: Among them, Z is the number of energy IoT nodes, pt is the network importance of the tth energy IoT node;

[0019] As a preferred technical solution for the energy Internet of Things fusion communication method based on swarm intelligence, the energy Internet of Things node safety factor evaluation model in S3 includes the following specific steps:

[0020] S31. Obtain the operation data of the energy Internet of Things node device, and substitute the operation data of the energy Internet of Things node device into the node device security value calculation formula to calculate the node device security value, wherein the node device security value calculation formula of the i-th energy Internet of Things node device is: Among them, U is the number of operating data types of energy Internet of Things node devices, aiu is the proportion coefficient of the u-th operating data type of the i-th energy Internet of Things node device, xui is the specific data of the u-th operating data type of the i-th energy Internet of Things node device, xuim is the median of the safety range of the u-th operating data type of the i-th energy Internet of Things node device, and xuic is the difference between the maximum and minimum values ​​of the safety range of the u-th operating data type of the i-th energy Internet of Things node device. Among them,

[0021] S32, substituting the node device safety value of each energy Internet of Things node device obtained by calculation into the energy Internet of Things node safety factor calculation formula to calculate the energy Internet of Things node safety factor, wherein the energy Internet of Things node safety factor calculation formula of the i-th energy Internet of Things node device is: Wherein, Tt is the energy IoT node safety factor of the t-th energy IoT node device;

[0022] As a preferred technical solution of the energy Internet of Things fusion communication method based on swarm intelligence, the communication resource allocation strategy in S4 includes the following specific steps:

[0023] S41. Obtain the calculated communication data importance coefficient and energy Internet of Things node safety coefficient of each energy Internet of Things node, and substitute them into the communication resource allocation value calculation formula to calculate the communication resource allocation value of each energy Internet of Things node, wherein the communication resource allocation value calculation formula of the i-th energy Internet of Things node is: Among them, Qm is the total amount of communication resources, a is the proportion of communication data importance coefficient, wt is the communication data importance coefficient of the t-th energy Internet of Things node, and dt is the energy Internet of Things node safety factor of the t-th energy Internet of Things node device;

[0024] S42. Obtain the calculated communication resource allocation value of each energy Internet of Things node at the corresponding time, and calculate the allocation plan of the communication resources of each energy Internet of Things node.

[0025] The energy Internet of Things fusion communication system based on swarm intelligence is implemented based on the above-mentioned energy Internet of Things fusion communication method based on swarm intelligence, and specifically includes:

[0026] The data acquisition module is used to obtain the energy transmission data and network transmission data of each energy IoT node in the historical period of energy transmission of the energy IoT node, and at the same time obtain the operation data of each energy IoT node device;

[0027] A communication data importance coefficient evaluation module is used to import the energy transmission data and network transmission data of each energy IoT node in the historical period energy transmission into the communication data importance coefficient evaluation model to evaluate the communication data importance coefficient;

[0028] An energy Internet of Things node safety factor evaluation module is used to import the acquired operation data of each energy Internet of Things node device into the energy Internet of Things node safety factor evaluation model to perform energy Internet of Things node safety factor evaluation;

[0029] A communication resource allocation module is used to import the acquired communication data importance coefficient evaluation results and energy Internet of Things node safety coefficient evaluation into the communication resource allocation strategy to output the allocation plan of communication resources for each energy Internet of Things node;

[0030] A network transmission allocation module, used to control the corresponding network transmission node to allocate network transmission resources according to the communication resource allocation scheme;

[0031] The control module is used to control the operation of the data acquisition module, the communication data importance coefficient evaluation module, the energy Internet of Things node safety factor evaluation module, the communication resource allocation module and the network transmission allocation module.

[0032] An electronic device comprises: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0033] The processor executes the above-mentioned energy Internet of Things fusion communication method based on collective intelligence by calling the computer program stored in the memory.

[0034] A computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the above-mentioned energy Internet of Things fusion communication method based on swarm intelligence.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] The present invention obtains energy transmission data and network transmission data of each energy Internet of Things node in the historical period energy transmission of the energy Internet of Things node, and simultaneously obtains the operation data of each energy Internet of Things node device, imports the energy transmission data and network transmission data of each energy Internet of Things node in the historical period energy transmission into a communication data importance coefficient evaluation model to perform communication data importance coefficient evaluation, imports the operation data of each energy Internet of Things node device into an energy Internet of Things node safety factor evaluation model to perform energy Internet of Things node safety factor evaluation, imports the acquired communication data importance coefficient evaluation results and energy Internet of Things node safety factor evaluation into a communication resource allocation strategy to output a communication resource allocation plan for each energy Internet of Things node, controls the corresponding network transmission node to allocate network transmission resources according to the communication resource allocation plan, and reasonably allocates network transmission resources through comprehensive analysis of the historical transmission data of the energy Internet of Things node and the operation data of the node device, thereby avoiding the delay of important transmission information and improving the security during the communication process. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0038] Figure 1 It is a schematic diagram of the overall process of the energy Internet of Things fusion communication method based on collective intelligence of the present invention;

[0039] Figure 2 It is a schematic flow chart of the steps of the communication data importance coefficient evaluation model in the energy Internet of Things integrated communication method based on swarm intelligence of the present invention;

[0040] Figure 3 It is a schematic flow chart of the steps of the energy Internet of Things node safety factor assessment model in the energy Internet of Things fusion communication method based on swarm intelligence of the present invention;

[0041] Figure 4 It is a schematic diagram of the overall framework of the energy Internet of Things fusion communication system based on swarm intelligence of the present invention;

[0042] Figure 5 A schematic diagram of the allocation of network transmission resources of the present invention; DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0044] In the following description, many specific details are set forth to facilitate a full understanding of the present application, but the present application may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present application. Therefore, the present application is not limited to the specific embodiments disclosed below.

[0045] Example 1

[0046] See also Figure 1 , Figure 2 , Figure 3 and Figure 5 , an embodiment provided by the present invention: the technical problem solved by this embodiment is: the prior art cannot comprehensively analyze the historical transmission data of the energy Internet of Things nodes and the operation data of the node devices during the energy Internet of Things converged communication process, thereby irrationally allocating network transmission resources, resulting in a delay in important transmission information and reducing the security of the communication process;

[0047] The energy Internet of Things fusion communication method based on swarm intelligence includes the following specific steps:

[0048] S1. Obtain the energy transmission data and network transmission data of each energy IoT node in the historical period of energy transmission of the energy IoT node, and at the same time obtain the operation data of each energy IoT node device;

[0049] S2. Importing the energy transmission data and network transmission data of each energy IoT node of the historical period energy transmission into the communication data importance coefficient evaluation model to evaluate the communication data importance coefficient;

[0050] S3, importing the acquired operation data of each energy Internet of Things node device into the energy Internet of Things node safety factor assessment model to conduct energy Internet of Things node safety factor assessment;

[0051] S4, importing the obtained communication data importance coefficient evaluation results and energy Internet of Things node safety coefficient evaluation into the communication resource allocation strategy to output the communication resource allocation plan of each energy Internet of Things node;

[0052] S5. Control the corresponding network transmission node to allocate network transmission resources according to the communication resource allocation scheme;

[0053] In this embodiment, it should be specifically explained that S1 includes the following specific steps:

[0054] S11. Obtain energy transmission data of the corresponding historical period of each energy Internet of Things node through the energy transmission collection terminal, and store it in the second storage component, wherein the energy transmission data includes energy transmission quantity data and energy transmission quality data, and the energy transmission quality is the proportion of qualified energy transmission quantity to the total energy transmission quantity, and collect the network occupancy of each energy Internet of Things node through the network transmission collection terminal;

[0055] S12. Collect the operation data of each energy Internet of Things node device through the operation data collection terminal and store it in the second storage component, wherein the types of operation data of the energy Internet of Things node device mainly include the following:

[0056] Equipment status data: including real-time data such as the equipment's operating status, temperature, pressure, flow, and equipment fault alarm data; Production data: including data on the production process, such as the equipment's power, voltage, current and other electrical parameters, as well as product quality and output data during the production process; Environmental data: including environmental parameters such as temperature, humidity, pressure, light, and other data;

[0057] It should be specifically explained in this embodiment that the communication data importance coefficient evaluation model in S2 includes the following specific contents:

[0058] S21. Obtain the energy transmission data and network occupancy of each energy IoT node in the corresponding historical period, and substitute them into the network importance calculation formula to calculate the network importance of each energy IoT node. The network importance calculation formula of the i-th energy IoT node is: Wherein, m is the number of historical cycles, kij is the network occupancy of the i-th Energy IoT node in the j-th cycle, S is the number of other Energy IoT nodes that transmit energy with the i-th Energy IoT node in the j-th cycle, and Tijz is the energy transmission amount between the z-th Energy IoT node that transmits energy with the i-th Energy IoT node and the i-th Energy IoT node in the j-th cycle;

[0059] S22, obtaining the calculated network importance of all energy Internet of Things nodes, and substituting the obtained network importance of all energy Internet of Things nodes into the communication data importance coefficient calculation formula to calculate the communication data importance coefficient, wherein the communication data importance coefficient calculation formula of the i-th energy Internet of Things node is: Among them, Z is the number of energy IoT nodes, pt is the network importance of the tth energy IoT node;

[0060] It should be specifically explained in this embodiment that the energy Internet of Things node safety factor assessment model in S3 includes the following specific steps:

[0061] S31. Obtain the operation data of the energy Internet of Things node device, and substitute the operation data of the energy Internet of Things node device into the node device security value calculation formula to calculate the node device security value, wherein the node device security value calculation formula of the i-th energy Internet of Things node device is: Among them, U is the number of operating data types of energy Internet of Things node devices, aiu is the proportion coefficient of the u-th operating data type of the i-th energy Internet of Things node device, xui is the specific data of the u-th operating data type of the i-th energy Internet of Things node device, xuim is the median of the safety range of the u-th operating data type of the i-th energy Internet of Things node device, and xuic is the difference between the maximum and minimum values ​​of the safety range of the u-th operating data type of the i-th energy Internet of Things node device. Among them,

[0062] S32, substituting the node device safety value of each energy Internet of Things node device obtained by calculation into the energy Internet of Things node safety factor calculation formula to calculate the energy Internet of Things node safety factor, wherein the energy Internet of Things node safety factor calculation formula of the i-th energy Internet of Things node device is: Among them, Tt is the energy Internet of Things node safety factor of the tth energy Internet of Things node device.

[0063] As a preferred technical solution for the energy Internet of Things convergence communication method based on swarm intelligence, the proportion coefficient of the u-th operating data type of energy Internet of Things node devices may be different for different energy Internet of Things node devices. Here, a method for taking the value of the proportion coefficient of the u-th operating data type of energy Internet of Things node devices is proposed: at least 5000 groups of operating data corresponding to energy Internet of Things node devices are obtained and imported into the node device safety value calculation formula for calculation, and 50 experts are hired to inspect the node devices corresponding to the operating data of the energy Internet of Things node devices and rank their damage degrees. The sorting results and the node device safety value calculation results are imported into the fitting software to output the value of the proportion coefficient of the u-th operating data type of the energy Internet of Things node device that meets the highest damage degree sorting accuracy.

[0064] It should be specifically explained in this embodiment that the communication resource allocation strategy in S4 includes the following specific steps:

[0065] S41. Obtain the calculated communication data importance coefficient and energy Internet of Things node safety coefficient of each energy Internet of Things node, and substitute them into the communication resource allocation value calculation formula to calculate the communication resource allocation value of each energy Internet of Things node, wherein the communication resource allocation value calculation formula of the i-th energy Internet of Things node is: Among them, Qm is the total amount of communication resources, a is the proportion of communication data importance coefficient, wt is the communication data importance coefficient of the t-th energy Internet of Things node, and dt is the energy Internet of Things node safety factor of the t-th energy Internet of Things node device;

[0066] S42. Obtain the calculated communication resource allocation value of each energy Internet of Things node at the corresponding time, and calculate the allocation plan of the communication resources of each energy Internet of Things node.

[0067] It should be noted here that the value of the communication data importance coefficient ratio is obtained in the following way: the energy transmission data and network transmission data of each energy IoT node in the historical period energy transmission of at least 5,000 groups of energy IoT nodes are obtained, and the operation data of each energy IoT node device is obtained and imported into the communication resource allocation value calculation formula for calculation, and 50 experts are hired to sort the order of energy IoT nodes that need to ensure smooth communication, and the obtained sorting results and communication resource allocation value calculation results are imported into the fitting software to output the value of the communication data importance coefficient ratio that meets the highest communication smoothness order accuracy rate;

[0068] It should be specifically noted here that the highest damage degree ranking accuracy and the highest communication smoothness order accuracy here are calculated by the shortest distance calculation formula, such as the Euclidean distance and Manhattan distance calculation formula;

[0069] It should be noted here that the advantages of this embodiment over the prior art are: obtaining the energy transmission data and network transmission data of each energy Internet of Things node in the historical period of energy transmission of the energy Internet of Things node, and at the same time obtaining the operating data of each energy Internet of Things node device, importing the energy transmission data and network transmission data of each energy Internet of Things node in the historical period of energy transmission obtained into the communication data importance coefficient evaluation model to perform communication data importance coefficient evaluation, importing the operating data of each energy Internet of Things node device obtained into the energy Internet of Things node safety factor evaluation model to perform energy Internet of Things node safety factor evaluation, importing the obtained communication data importance coefficient evaluation results and energy Internet of Things node safety factor evaluation into the communication resource allocation strategy to output the communication resource allocation plan of each energy Internet of Things node, controlling the corresponding network transmission node to allocate network transmission resources according to the communication resource allocation plan, and reasonably allocating network transmission resources through comprehensive analysis of the historical transmission data of the energy Internet of Things nodes and the operating data of the node devices, thereby avoiding the delay of important transmission information and improving the security of the communication process.

[0070] Example 2

[0071] like Figure 4As shown, the energy Internet of Things fusion communication system based on swarm intelligence is implemented based on the above-mentioned energy Internet of Things fusion communication method based on swarm intelligence, which specifically includes: a data acquisition module, which is used to obtain the energy transmission data and network transmission data of each energy Internet of Things node in the historical period of energy transmission of the energy Internet of Things node, and at the same time obtain the operation data of each energy Internet of Things node device;

[0072] A communication data importance coefficient evaluation module is used to import the energy transmission data and network transmission data of each energy IoT node in the historical period energy transmission into the communication data importance coefficient evaluation model to evaluate the communication data importance coefficient;

[0073] An energy Internet of Things node safety factor evaluation module is used to import the acquired operation data of each energy Internet of Things node device into the energy Internet of Things node safety factor evaluation model to perform energy Internet of Things node safety factor evaluation;

[0074] A communication resource allocation module is used to import the acquired communication data importance coefficient evaluation results and energy Internet of Things node safety coefficient evaluation into the communication resource allocation strategy to output the allocation plan of communication resources for each energy Internet of Things node;

[0075] A network transmission allocation module, used to control the corresponding network transmission node to allocate network transmission resources according to the communication resource allocation scheme;

[0076] The control module is used to control the operation of the data acquisition module, the communication data importance coefficient evaluation module, the energy Internet of Things node safety factor evaluation module, the communication resource allocation module and the network transmission allocation module.

[0077] Example 3

[0078] This embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0079] The processor executes the above-mentioned energy Internet of Things fusion communication method based on collective intelligence by calling the computer program stored in the memory.

[0080] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors (Central Processing Units, CPU) and one or more memories, wherein the memory stores at least one computer program, which is loaded and executed by the processor to implement the energy Internet of Things converged communication method based on swarm intelligence provided by the above method embodiment.

[0081] Example 4

[0082] This embodiment provides a computer-readable storage medium having a rewritable computer program stored thereon;

[0083] When the computer program runs on a computer device, the computer device executes the above-mentioned energy Internet of Things fusion communication method based on swarm intelligence.

[0084] For example, the computer readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, etc.

Claims

1. An energy Internet of Things fusion communication method based on swarm intelligence, characterized in that: It includes the following specific steps: S1. Obtain the energy transmission data and network transmission data of each energy IoT node in the historical period of energy transmission of the energy IoT node, and at the same time obtain the operation data of each energy IoT node device; S2. Importing the energy transmission data and network transmission data of each energy IoT node of the historical period energy transmission into the communication data importance coefficient evaluation model to evaluate the communication data importance coefficient; S3, importing the acquired operation data of each energy Internet of Things node device into the energy Internet of Things node safety factor assessment model to conduct energy Internet of Things node safety factor assessment; S4, importing the obtained communication data importance coefficient evaluation results and energy Internet of Things node safety coefficient evaluation into the communication resource allocation strategy to output the communication resource allocation plan of each energy Internet of Things node; S5. Control the corresponding network transmission node to allocate network transmission resources according to the communication resource allocation scheme; The S1 includes the following specific steps: S11. Obtain energy transmission data of the corresponding historical period of each energy Internet of Things node through the energy transmission collection terminal, and store it in the second storage component, wherein the energy transmission data includes energy transmission quantity data and energy transmission quality data, and the energy transmission quality is the proportion of qualified energy transmission quantity to the total energy transmission quantity, and collect the network occupancy of each energy Internet of Things node through the network transmission collection terminal; S12, collecting the operation data of each energy Internet of Things node device through the operation data collection terminal, and storing it in the second storage component; The communication data importance coefficient evaluation model in S2 includes the following specific contents: S21. Obtain the energy transmission data and network occupancy of each energy IoT node in the corresponding historical period, and substitute them into the network importance calculation formula to calculate the network importance of each energy IoT node. The network importance calculation formula of the i-th energy IoT node is: Wherein, m is the number of historical cycles, kij is the network occupancy of the i-th Energy IoT node in the j-th cycle, S is the number of other Energy IoT nodes that transmit energy with the i-th Energy IoT node in the j-th cycle, and Tijz is the energy transmission amount between the z-th Energy IoT node that transmits energy with the i-th Energy IoT node and the i-th Energy IoT node in the j-th cycle; S22, obtaining the calculated network importance of all energy Internet of Things nodes, and substituting the obtained network importance of all energy Internet of Things nodes into the communication data importance coefficient calculation formula to calculate the communication data importance coefficient, wherein the communication data importance coefficient calculation formula of the i-th energy Internet of Things node is: Among them, Z is the number of energy IoT nodes, pt is the network importance of the tth energy IoT node; The energy IoT node safety factor assessment model in S3 includes the following specific steps: S31. Obtain the operation data of the energy Internet of Things node device, and substitute the operation data of the energy Internet of Things node device into the node device security value calculation formula to calculate the node device security value, wherein the node device security value calculation formula of the i-th energy Internet of Things node device is: Among them, U is the number of operating data types of energy Internet of Things node devices, aiu is the proportion coefficient of the u-th operating data type of the i-th energy Internet of Things node device, xui is the specific data of the u-th operating data type of the i-th energy Internet of Things node device, xuim is the median of the safety range of the u-th operating data type of the i-th energy Internet of Things node device, and xuic is the difference between the maximum and minimum values ​​of the safety range of the u-th operating data type of the i-th energy Internet of Things node device. Among them, S32, substituting the node device safety value of each energy Internet of Things node device obtained by calculation into the energy Internet of Things node safety factor calculation formula to calculate the energy Internet of Things node safety factor, wherein the energy Internet of Things node safety factor calculation formula of the i-th energy Internet of Things node device is: Wherein, Tt is the energy IoT node safety factor of the t-th energy IoT node device; The communication resource allocation strategy in S4 includes the following specific steps: S41. Obtain the calculated communication data importance coefficient and energy Internet of Things node safety coefficient of each energy Internet of Things node, and substitute them into the communication resource allocation value calculation formula to calculate the communication resource allocation value of each energy Internet of Things node, wherein the communication resource allocation value calculation formula of the i-th energy Internet of Things node is: Among them, Qm is the total amount of communication resources, a is the proportion of communication data importance coefficient, wt is the communication data importance coefficient of the t-th energy Internet of Things node, and dt is the energy Internet of Things node safety factor of the t-th energy Internet of Things node device; S42. Obtain the calculated communication resource allocation value of each energy Internet of Things node at the corresponding time, and calculate the allocation plan of the communication resources of each energy Internet of Things node.

2. An energy Internet of Things fusion communication system based on swarm intelligence, which is implemented based on the energy Internet of Things fusion communication method based on swarm intelligence as claimed in claim 1, characterized in that: Specifically include: The data acquisition module is used to obtain the energy transmission data and network transmission data of each energy IoT node in the historical period of energy transmission of the energy IoT node, and at the same time obtain the operation data of each energy IoT node device; A communication data importance coefficient evaluation module is used to import the energy transmission data and network transmission data of each energy IoT node in the historical period energy transmission into the communication data importance coefficient evaluation model to evaluate the communication data importance coefficient; An energy Internet of Things node safety factor evaluation module is used to import the acquired operation data of each energy Internet of Things node device into the energy Internet of Things node safety factor evaluation model to perform energy Internet of Things node safety factor evaluation; A communication resource allocation module is used to import the acquired communication data importance coefficient evaluation results and energy Internet of Things node safety coefficient evaluation into the communication resource allocation strategy to output the allocation plan of communication resources for each energy Internet of Things node; A network transmission allocation module, used to control the corresponding network transmission node to allocate network transmission resources according to the communication resource allocation scheme; The control module is used to control the operation of the data acquisition module, the communication data importance coefficient evaluation module, the energy Internet of Things node safety factor evaluation module, the communication resource allocation module and the network transmission allocation module.

3. An electronic device, comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; It is characterized in that the processor executes the energy Internet of Things fusion communication method based on collective intelligence as claimed in claim 1 by calling the computer program stored in the memory.

4. A computer-readable storage medium, characterized in that: Instructions are stored, and when the instructions are executed on a computer, the computer executes the energy Internet of Things fusion communication method based on collective intelligence as claimed in claim 1.

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