CN115002579B - Electric power information acquisition system based on thing networking - Google Patents
Electric power information acquisition system based on thing networking Download PDFInfo
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- CN115002579B CN115002579B CN202210844247.6A CN202210844247A CN115002579B CN 115002579 B CN115002579 B CN 115002579B CN 202210844247 A CN202210844247 A CN 202210844247A CN 115002579 B CN115002579 B CN 115002579B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04Q—SELECTING
- H04Q9/00—Arrangements in telecontrol or telemetry systems for selectively calling a substation from a main station, in which substation desired apparatus is selected for applying a control signal thereto or for obtaining measured values therefrom
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
- G16Y10/00—Economic sectors
- G16Y10/35—Utilities, e.g. electricity, gas or water
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
- G16Y10/00—Economic sectors
- G16Y10/75—Information technology; Communication
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
- G16Y20/00—Information sensed or collected by the things
- G16Y20/30—Information sensed or collected by the things relating to resources, e.g. consumed power
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
- G16Y40/00—IoT characterised by the purpose of the information processing
- G16Y40/10—Detection; Monitoring
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/02—Power saving arrangements
- H04W52/0209—Power saving arrangements in terminal devices
- H04W52/0212—Power saving arrangements in terminal devices managed by the network, e.g. network or access point is master and terminal is slave
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04Q—SELECTING
- H04Q2209/00—Arrangements in telecontrol or telemetry systems
- H04Q2209/20—Arrangements in telecontrol or telemetry systems using a distributed architecture
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04Q—SELECTING
- H04Q2209/00—Arrangements in telecontrol or telemetry systems
- H04Q2209/80—Arrangements in the sub-station, i.e. sensing device
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S40/00—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them
- Y04S40/12—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment
- Y04S40/128—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment involving the use of Internet protocol
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Abstract
The invention discloses an electric power information acquisition system based on the Internet of things, which comprises an Internet of things module; the Internet of things module comprises a wireless sensor node and a control base station; the control base station is used for clustering the wireless sensor nodes in the following modes: dividing the distribution range of the power equipment into a plurality of sub-ranges by adopting a self-adaptive partition mode; clustering the wireless sensor nodes in each sub-range respectively, and dividing the wireless sensor nodes into cluster head nodes and member nodes; the member nodes are used for acquiring power information of the power equipment and transmitting the power information to the cluster head nodes; the cluster head node is used for forwarding the power information to the control base station. Because the partition is firstly carried out, the distribution of the cluster head nodes is not random any more, the distribution of the cluster head nodes is more reasonable, and the workload of substation workers is effectively reduced.
Description
Technical Field
The invention relates to the field of information acquisition, in particular to an electric power information acquisition system based on the Internet of things.
Background
The transformer substation is a place for converting voltage and current, receiving electric energy and distributing electric energy in an electric power system. The substations in the power plant are step-up substations, which are used to boost up the electrical energy generated by the generator and feed it into the high-voltage network. The transformer substation comprises various types of power equipment, and in the operation process, the power information of the power equipment needs to be acquired so as to monitor the states of the power equipment.
In the prior art, the power information of the power equipment is generally acquired through the technology of internet of things, that is, the power information is acquired by forming a wireless sensor network by using wireless sensor nodes. The existing wireless sensor network generally adopts a mode of randomly generating cluster heads to perform clustering processing on wireless sensor nodes in the operation process, and the cluster heads are unreasonably distributed in the clustering mode to influence the service life of the wireless sensor nodes, so that the wireless sensor nodes are required to be subjected to battery replacement operation more frequently, and the workload of transformer substation workers is increased.
Disclosure of Invention
The invention aims to disclose an electric power information acquisition system based on the Internet of things, and the electric power information acquisition system is used for solving the problems that in the prior art, when a wireless sensor network is used for acquiring electric power information of electric power equipment, cluster processing is carried out on wireless sensor nodes in a mode of randomly generating cluster heads, the cluster heads are unreasonably distributed, and the workload of transformer substation workers is increased.
In order to achieve the purpose, the invention adopts the following technical scheme:
an electric power information acquisition system based on the Internet of things comprises an Internet of things module;
the Internet of things module comprises a wireless sensor node and a control base station;
the control base station is used for clustering the wireless sensor nodes in the following modes:
dividing the distribution range of the power equipment into a plurality of sub-ranges by adopting a self-adaptive partition mode;
clustering the wireless sensor nodes in each sub-range respectively, and dividing the wireless sensor nodes into cluster head nodes and member nodes;
the member nodes are used for acquiring power information of the power equipment and transmitting the power information to the cluster head nodes;
the cluster head node is used for forwarding the power information to the control base station.
Preferably, the power information acquisition system based on the internet of things further comprises a data transmission module;
the control base station is used for sending the power information sent by the cluster head node to the data transmission module.
Preferably, the power information acquisition system based on the internet of things further comprises a data storage module;
the data transmission module is used for transmitting the power information transmitted by the control base station to the data storage module.
Preferably, the data transmission module includes a wired transmission unit or a wireless transmission unit.
Preferably, the data storage module is configured to store the power information.
Preferably, the power information includes temperature, voltage, and current.
Preferably, the power equipment comprises a transformer, a high voltage circuit breaker, a disconnector and a bus bar.
Preferably, the dividing the distribution range of the power equipment into a plurality of sub-ranges by using an adaptive partition method includes:
acquiring a minimum circumscribed rectangle of a distribution range of the power equipment;
partitioning for the first time, dividing the minimum circumscribed rectangle into H sub-ranges with the same area, and storing the sub-ranges obtained by the partitioning into a set
；
Respectively judge
Whether each sub-range in (a) enters the next partition, storing the sub-ranges entering the next partition into the set
Storing sub-ranges not entering next partition into the set
；
The nth partition, n is greater than or equal to 2, respectively collecting
Each element in the set is divided into H sub-ranges with the same area, and the sub-ranges obtained by the current partition are stored into a set
；
Respectively judge
Whether each sub-range in (a) enters the next partition, storing the sub-ranges entering the next partition into the set
Storing sub-ranges not entering next partition into the set
；
If it is
If the number of elements in (1) is less than the set number threshold, the elements are aggregated
Element (1) ofAs a sub-range to be finally obtained.
Preferably, whether the sub-range enters the next partition is judged by the following method:
calculating partition coefficients of the sub-ranges:
in the formula (I), the compound is shown in the specification,
the partition coefficients representing the sub-ranges are,
which is indicative of a set scale parameter,
indicating the number of wireless sensor nodes contained within the sub-range,
represents the total number of wireless sensor nodes contained in the internet of things module,
the footprint of a sub-range is indicated,
represents the area of the distribution range of the power equipment,
representing the set of all wireless sensor nodes within a sub-range,
representing the distance between the wireless sensor node within the sub-range and the control base station,
representing the maximum value of the distance between a wireless sensor node in the Internet of things module and a control base station;
and comparing the partition coefficient with a set partition coefficient threshold value, if the partition coefficient is greater than the partition coefficient threshold value, indicating that the sub-range enters the next partition, and if the partition coefficient is less than or equal to the partition coefficient threshold value, indicating that the sub-range does not enter the next partition.
Preferably, the shape of the sub-range is rectangular.
When the wireless sensor nodes are used for acquiring the power information, the method is used for partitioning the distribution range of the power equipment to obtain a plurality of sub-ranges, and then clustering processing is performed on each sub-range to realize clustering processing. Because the partition is firstly carried out, the distribution of the cluster head nodes is not random any more, the distribution of the cluster head nodes is more reasonable, and the workload of substation workers is effectively reduced.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, without inventive effort, further drawings may be derived from the following figures.
Fig. 1 is a diagram of an exemplary embodiment of an internet-of-things-based power information acquisition system according to the present invention.
Fig. 2 is a diagram illustrating an exemplary embodiment of a clustering process according to the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
As shown in fig. 1, an embodiment of the present invention provides an electric power information obtaining system based on internet of things, which includes
An electric power information acquisition system based on the Internet of things comprises an Internet of things module;
the Internet of things module comprises a wireless sensor node and a control base station;
the control base station is used for clustering the wireless sensor nodes in the following way:
dividing the distribution range of the power equipment into a plurality of sub-ranges in a self-adaptive partitioning mode;
clustering the wireless sensor nodes in each sub-range respectively, and dividing the wireless sensor nodes into cluster head nodes and member nodes;
the member nodes are used for acquiring power information of the power equipment and transmitting the power information to the cluster head nodes;
the cluster head node is used for forwarding the power information to the control base station.
When the wireless sensor nodes are used for acquiring the power information, the method is used for partitioning the distribution range of the power equipment to obtain a plurality of sub-ranges, and then clustering processing is performed on each sub-range to realize clustering processing. Because the partition is firstly carried out, the distribution of the cluster head nodes is not random any more, the distribution of the cluster head nodes is more reasonable, and the workload of the transformer substation workers is effectively reduced.
Preferably, the power information acquisition system based on the internet of things further comprises a data transmission module;
the control base station is used for sending the power information sent by the cluster head node to the data transmission module.
Preferably, the power information acquisition system based on the internet of things further comprises a data storage module;
the data transmission module is used for transmitting the power information transmitted by the control base station to the data storage module.
Preferably, the data transmission module includes a wired transmission unit or a wireless transmission unit.
The wired transmission unit may include a fiber optic communication network, while the wireless sensor unit may include a 4G communication network, a 5G communication network, and the like.
Preferably, the data storage module is configured to store the power information.
The storage module may be a cloud server.
Preferably, the power information includes temperature, voltage, and current.
The power information is only an example, and the power information required to be acquired by different types of power devices is not the same, and therefore, the present invention is not limited to acquiring only the type of power information of the distance.
Preferably, the power equipment comprises a transformer, a high-voltage circuit breaker, a disconnector and a bus bar.
There are many types of electrical equipment other than those listed above, and the equipment in the substation may be part of the electrical equipment.
Preferably, the dividing the distribution range of the power equipment into a plurality of sub-ranges by using an adaptive partition method includes:
acquiring a minimum circumscribed rectangle of a distribution range of the power equipment;
partitioning for the first time, dividing the minimum circumscribed rectangle into H sub-ranges with the same area, and storing the sub-ranges obtained by the partitioning into a set
；
Respectively judge
Whether each sub-range in (a) enters the next partition, storing the sub-ranges entering the next partition into the set
Storing sub-ranges not entering next partition into the set
；
The nth sub-area, n is more than or equal to 2, respectivelyWill be assembled
Each element in the set is divided into H sub-ranges with the same area, and the sub-ranges obtained by the current partition are stored into a set
；
Respectively judge
Whether each sub-range in (a) enters the next partition, storing the sub-ranges entering the next partition into the set
Storing the sub-ranges not entering the next partition into the set
；
If it is
If the number of elements in (1) is less than the set number threshold, the elements are aggregated
As the sub-ranges finally obtained.
The final sub-range is obtained by a multi-time partition mode, and the distribution range of the power equipment is not directly divided into a plurality of sub-ranges with the same size. By the arrangement mode, the situation that the obtained sub-range does not contain the wireless sensor node, invalid partition is caused, and the calculation force is wasted can be avoided. In addition, the size of the sub-range is adaptive to the actual distribution condition of the wireless sensor nodes, and the practicability of the wireless sensor node distribution method is improved.
Preferably, whether the sub-range enters the next partition is judged by the following method:
calculating partition coefficients of the sub-ranges:
in the formula (I), the compound is shown in the specification,
the partition coefficients representing the sub-ranges,
which is indicative of a set scale parameter,
indicating the number of wireless sensor nodes contained within the sub-range,
represents the total number of wireless sensor nodes contained in the internet of things module,
the footprint of a sub-range is indicated,
represents the area of the distribution range of the power equipment,
representing the set of all wireless sensor nodes within a sub-range,
indicating the distance between the wireless sensor node within the sub-range and the control base station,
representing the maximum value of the distance between a wireless sensor node in the Internet of things module and a control base station;
and comparing the partition coefficient with a set partition coefficient threshold value, if the partition coefficient is greater than the partition coefficient threshold value, indicating that the sub-range enters the next partition, and if the partition coefficient is less than or equal to the partition coefficient threshold value, indicating that the sub-range does not enter the next partition.
The partition coefficient is mainly considered comprehensively from the three aspects of the number of the wireless sensor nodes, the occupied area of the sub-range and the distance between the wireless sensor nodes in the sub-range and the control base station, and the probability of entering the next partition is higher when the number is larger, the occupied area is larger, and the distance between the wireless sensor nodes in the sub-range and the control base station is smaller. The setting mode can make the area of the sub-range which is farther from the control base station larger as much as possible, and the area of the sub-range which is closer to the control base station smaller, so that the number of cluster head nodes in the area which is closer to the control base station is more, the situation that the area which is close to the control base station consumes the electric quantity quickly due to the too small number and quits the work is avoided, the power change operation needs to be carried out on the wireless sensor nodes more frequently, and the workload of substation workers is increased.
Preferably, the shape of the sub-range is rectangular.
Preferably, as shown in fig. 2, the clustering the wireless sensor nodes in each sub-range to divide the wireless sensor nodes into cluster head nodes and member nodes includes:
calculating the clustering probability value of each wireless sensor node in the sub-range;
calculating the number of cluster head nodes within a sub-range
；
Rank the clustering probability values ahead
The wireless sensor nodes of the bits are used as cluster head nodes, and the rest wireless sensor nodes are used as member nodes.
The invention does not only have one cluster head node in a sub-range, but adaptively determines the number of cluster head nodes according to the distribution of the wireless sensor nodes, and the number and the distribution change. The method is favorable for avoiding the problem that a single cluster head node needs to be responsible for too many data forwarding tasks, so that the energy consumption is too fast.
Preferably, the clustering probability value of the wireless sensor node is calculated by adopting the following formula:
in the formula (I), the compound is shown in the specification,
and
respectively representing the remaining energy and the initial energy of the wireless sensor node,
representing the minimum distance between the wireless sensor node and the edge of the sub-range,
represents a preset first distance criterion value,
representing the distance between the wireless sensor node and the control base station,
representing a preset second distance criterion value.
The clustering probability value is related to the residual energy, the minimum distance between the residual energy and the edge and the distance between the control base stations, and the clustering probability value is larger when the residual energy is more, the minimum distance between the residual energy and the edge is smaller, and the distance between the residual energy and the control base stations is smaller. Therefore, the wireless sensor nodes which are close to the control base station, close to the edge of the sub-range and have more residual energy can be selected as cluster head nodes. The energy consumed by the data forwarding of the cluster head nodes is less, and the success rate of one-hop communication with the cluster head nodes in other sub-ranges is also obviously improved.
Preferably, the number of cluster head nodes
The following formula is adopted for calculation:
in the formula (I), the compound is shown in the specification,
indicating the number of wireless sensor nodes contained within the sub-range,
the footprint of a sub-range is indicated,
represents a preset density standard value and a preset density standard value,
representing a preset quantity standard value.
The number of cluster head nodes is mainly related to the distribution density of the wireless sensor nodes, and the larger the density is, the larger the number of cluster head nodes is. The number of cluster head nodes can be adaptively changed along with the actual distribution of the wireless sensor nodes.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
In the foregoing description of the specification, reference to the description of "one embodiment/example," "another embodiment/example," or "certain embodiments/examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.
While the preferred embodiments of the present invention have been illustrated and described, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (8)
1. An electric power information acquisition system based on the Internet of things is characterized by comprising an Internet of things module;
the Internet of things module comprises a wireless sensor node and a control base station;
the control base station is used for clustering the wireless sensor nodes in the following modes:
dividing the distribution range of the power equipment into a plurality of sub-ranges in a self-adaptive partitioning mode;
clustering the wireless sensor nodes in each sub-range respectively, and dividing the wireless sensor nodes into cluster head nodes and member nodes;
the member nodes are used for acquiring power information of the power equipment and transmitting the power information to the cluster head nodes;
the cluster head node is used for forwarding the power information to the control base station;
the distribution range of the power equipment is divided into a plurality of sub-ranges by adopting a self-adaptive partition mode, and the method comprises the following steps:
acquiring a minimum circumscribed rectangle of a distribution range of the power equipment;
partitioning for the first time, dividing the minimum circumscribed rectangle into H sub-ranges with the same area, and storing the sub-ranges obtained by the partitioning into a set
；
Respectively judge
Whether each sub-range in (2) enters the next partition, storing the sub-range entering the next partition into the set
Storing sub-ranges not entering next partition into the set
；
The nth partition, n is greater than or equal to 2, respectively collecting
Each element in the set is divided into H sub-ranges with the same area, and the sub-ranges obtained by the current partition are stored into a set
；
Respectively judge
Whether each sub-range in (2) enters the next partition will enter the next partitionSub-range storage of regions into sets
Storing sub-ranges not entering next partition into the set
；
If it is
If the number of elements in (1) is less than the set number threshold, the elements are aggregated
As the finally obtained subrange;
judging whether the sub-range enters the next partition or not by the following method:
calculating partition coefficients for the subranges:
in the formula (I), the compound is shown in the specification,
the partition coefficients representing the sub-ranges,
which is indicative of a set scale parameter,
indicating the number of wireless sensor nodes contained within the sub-range,
represents the total number of wireless sensor nodes contained in the internet of things module,
the footprint of a sub-range is indicated,
an area representing a distribution range of the electric power equipment,
representing the set of all wireless sensor nodes within a sub-range,
representing the distance between the wireless sensor node within the sub-range and the control base station,
representing the maximum value of the distance between a wireless sensor node in the Internet of things module and a control base station;
and comparing the partition coefficient with a set partition coefficient threshold value, if the partition coefficient is greater than the partition coefficient threshold value, indicating that the sub-range enters the next partition, and if the partition coefficient is less than or equal to the partition coefficient threshold value, indicating that the sub-range does not enter the next partition.
2. The system for acquiring the power information based on the internet of things as claimed in claim 1, further comprising a data transmission module;
the control base station is used for sending the power information sent by the cluster head node to the data transmission module.
3. The system for acquiring the power information based on the internet of things as claimed in claim 2, further comprising a data storage module;
the data transmission module is used for transmitting the power information transmitted by the control base station to the data storage module.
4. The Internet of things-based power information acquisition system as claimed in claim 2, wherein the data transmission module comprises a wired transmission unit or a wireless transmission unit.
5. The internet-of-things-based power information acquisition system according to claim 3, wherein the data storage module is configured to store the power information.
6. The internet-of-things-based power information acquisition system according to claim 1, wherein the power information comprises temperature, voltage and current.
7. The internet of things-based power information acquisition system according to claim 1, wherein the power equipment comprises a transformer, a high-voltage circuit breaker, a disconnecting switch and a bus.
8. The system for acquiring power information based on the internet of things as claimed in claim 1, wherein the shape of the sub-range is rectangular.
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| CN115955491B (en) * | 2022-11-30 | 2024-03-08 | 山东和同信息科技股份有限公司 | Heating power station operation monitoring system based on internet of things technology |
| CN115866554B (en) * | 2023-03-02 | 2023-05-12 | 吉林省信息技术研究所 | Information security transmission system of Internet of things |
| CN116488336B (en) * | 2023-04-14 | 2024-05-24 | 荣森茂(深圳)科技有限公司 | Energy storage battery safety monitoring system based on Internet of things |
| CN116539096A (en) * | 2023-05-12 | 2023-08-04 | 广东康德威电气股份有限公司 | Transformer state monitoring system based on Internet of things |
| CN117042008B (en) * | 2023-08-18 | 2024-04-12 | 国网四川省电力公司电力应急中心 | Power equipment control system based on wireless sensor network |
| CN117320112B (en) * | 2023-10-26 | 2024-05-03 | 陕西思极科技有限公司 | Dual-mode communication network energy consumption balancing method and system |
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