CN113220449B - Vulnerable line identification method and structure based on edge calculation - Google Patents
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Abstract
The invention relates to a fragile line identification technology of an electric power system, in particular to a fragile line identification method and structure based on edge calculation. The method is characterized in that edge calculation is introduced in a physical network in a mode of expanding equipment carriers, so that compatibility and high-efficiency transmission of collected data of different types of equipment are realized, the edge calculation is introduced in an information network in a mode of decomposing information processing, so that decision processing load of a network control center is reduced, real-time control of the physical network by the information network is ensured through decomposition of decision links, the purposes of improving transmission rate, improving processing speed, reducing work load and the like are achieved.
Description
Technical Field
The invention belongs to the technical field of fragile line identification of an electric power system, and particularly relates to a fragile line identification method and structure based on edge calculation.
Background
Along with the continuous innovation of science and technology, the requirements of people on power enterprises are higher and higher, and the traditional power network exposes a plurality of problems in aspects of power transmission, resource allocation, power supply analysis and the like, so that a power information coupling network is generated, and the efficient utilization of power resources is realized by configuring massive advanced equipment and intelligent analysis software. In the process of modifying the traditional power network to the power information coupling network, the power enterprise gradually presents the characteristics of complexity, isomerism, deep fusion, real-time performance, mass performance and the like, but the power enterprise faces risks in links of information transmission, processing, analysis, control and the like due to defects, loopholes and the like of physical equipment and an information network, and the power enterprise is challenged to safely and stably operate:
1. the power information coupling network is connected with massive advanced equipment, and a huge data volume is produced in unit time, so that the transmission of data is not facilitated, the data formats of different equipment are inconsistent, and the processing of the data is not facilitated;
2. when the electric power information coupling network performs data flow and information flow interaction, the real-time performance of data analysis is very high, and once higher time delay occurs, the information network can make unreasonable decisions on the physical network, so that the power supply network is paralyzed;
studies have shown that once a problem arises with the power information coupling network, unpredictable losses will result. Therefore, the application of the edge computing science in the electric power information coupling network has very important research significance.
Disclosure of Invention
Aiming at the problems existing in the background technology, the invention provides a fragile line identification method and system based on edge calculation.
In order to solve the technical problems, the invention adopts the following technical scheme: the fragile line identification method based on edge calculation is characterized in that a physical network, edge calculation and information network transmission process interacts with a network control center through network node acquisition equipment, edge node fusion equipment, edge node processing equipment and a power transmission line; the method comprises the following steps:
step 1, data acquisition; acquiring various types of data by network node acquisition equipment, wherein the data comprise voltage, current, phase angle and power under various communication protocols, and forming user electricity utilization information at intervals of 15 minutes;
step 2, parameter supplementation; mixing the data by the edge node fusion equipment, extracting data check bits, line numbers, user numbers, voltages, currents, phase angles and power according to field characteristics of different communication protocols, filtering inferior information through the data check bits, and forming voltage, current, phase angles, power and time information which are orderly sequenced according to the line numbers-the user numbers according to actual acquisition time;
step 3, data processing; processing the data in unit time by using the edge node processing equipment with 60 minutes as unit time and 15 minutes as time length;
step 4, data interaction; the network control center analyzes the load data all the day, and takes a line with the largest load fluctuation in the power transmission line as a fragile line under the condition of meeting the minimum network fluctuation load;
step 5, service decomposition; when the network control center processes daily service, the load level of the network node is perceived by the edge node, when the service is decomposed to the network node, the load level is not changed greatly, so that the service can be distributed to the network node at the moment, and otherwise, the service is distributed to other network nodes.
In the fragile line identification method based on edge calculation, the sampling time in the step 3 is supplemented into electricity utilization information acquired by a physical network, normalization is carried out on the electricity utilization information, and classification marking is carried out on data samples before the edge node interacts with an information network.
In the fragile line identification method based on edge calculation, the implementation of step 4 includes:
step 4.1, establishing a macroscopic relation between network power supply load and consumption load and a microscopic relation between a power transmission line and an edge node and a network node, and providing an influence coefficient to realize the relation between the edge node and the power transmission line load, wherein when the network node load belongs to a normal level, the power transmission line load is stable, and when the network node load changes drastically, the redundant load is regulated to the power transmission line;
step 4.2, identifying the load type of the network node through the coefficient adjustment weight, wherein the influence coefficient is negative when the network node is under low-level load, and the influence coefficient is positive when the network node is under high-level load;
and 4.3, when the overall load fluctuation of the network in unit time is minimum, and the power transmission line is a fragile line when the maximum load fluctuation occurs.
The utility model provides a power information coupling network structure for fragile line identification method based on edge calculation, includes network node, edge node, transmission line, network control center, and the physical carrier of network node is generator, transformer and safety device for observe this node power flow, load distribution, and reserve terminal interface and be used for the upgrading and the transformation of equipment; the edge node comprises novel equipment for expanding and accessing the network node, and is used for expanding the functional application range of the network node and carrying out fine-granularity and high-density secondary perception on the multi-dimensional data types; the power transmission line comprises various power transmission lines which are used as transmission channels of data flow and information flow and are used for adjusting current flow and load distribution in a network; the network control center comprises a port driver, a communication protocol, an intelligent algorithm and a visual interaction interface, and realizes the perception and real-time feedback of the network state through bidirectional interaction with the edge node.
Compared with the prior art, the invention has the beneficial effects that: 1. introducing edge calculation in a physical network in a mode of expanding equipment carriers, and realizing compatibility and efficient transmission of collected data of different types of equipment; 2. introducing edge calculation in an information network in a mode of decomposing information processing, and reducing decision processing load of a network control center; 3. the aims of improving the transmission rate, improving the processing speed, reducing the workload and the like are achieved by decomposing and simplifying the decision links and realizing accurate sensing and real-time feedback of the network state.
Drawings
FIG. 1 is a network implementation architecture diagram of one embodiment of the present invention;
FIG. 2 is a diagram of an actual network architecture of one embodiment of the present invention;
FIG. 3 is a simplified diagram of network transmission according to one embodiment of the present invention;
the system comprises 1-network nodes, 2-edge nodes, 3-power transmission lines and a 4-network control center; 1-1-network node acquisition equipment, 2-1-edge node fusion equipment and 2-2-edge node processing equipment.
Detailed Description
The technical solutions of the embodiments of the present invention will be clearly and completely described in the following in conjunction with the embodiments of the present invention, and it is obvious that the described embodiments are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be noted that, without conflict, the embodiments of the present invention and features of the embodiments may be combined with each other.
The invention will be further illustrated, but is not limited, by the following examples.
As shown in fig. 1, in this embodiment, edge computation is introduced into a physical network and an information network, the physical network provides basic data support for the information network, the information network provides reliable technical support for the physical network, the edge computation is introduced into the physical network in a manner of expanding a device carrier, so as to realize data collection compatibility of different types of devices, and an advanced communication manner is introduced to ensure efficient transmission of data, the edge computation is introduced into the information network in a manner of decomposing information processing, so as to reduce decision processing load of a network control center, and real-time control of the physical network by the information network is ensured through decomposition of decision links and simplification of fusion and cooperation of the physical network, the edge computation and the information network, so as to construct an electric power information coupling network system based on the edge computation, thereby achieving the purposes of improving transmission rate, improving processing speed, reducing workload and the like, finally realizing overall optimization of the electric power network, and meeting various demands of people on electric power enterprises.
As shown in fig. 2, the embodiment builds an electric power information coupling network architecture based on edge calculation, including a network node 1, an edge node 2, a power transmission line 3 and a network control center 4, wherein main physical carriers of the network node 1 are a generator, a transformer and a safety device, so that power flow and load distribution of the node can be effectively observed, terminal interfaces and the like are reserved for upgrading and modifying equipment, the edge node 2 mainly includes novel equipment for expanding and accessing the network node 1, the functional application range of the network node 1 is expanded, fine granularity and high-density secondary perception is carried out on multi-dimensional data types, the power transmission line 3 includes various power transmission lines as transmission channels of data flow and information flow, current flow and load distribution in a network are regulated, and the like, and the network control center 4 serves as an important core component and mainly includes port driving, a communication protocol, an intelligent algorithm and a visual interaction interface, and through bidirectional interaction with the edge node 2, accurate sensing and real-time feedback of network state are realized.
As shown in fig. 3, in the method for identifying a fragile line based on edge calculation, in a physical network-edge calculation-information network transmission process, interaction is performed with a network control center 4 through a network node acquisition device 1-1, an edge node fusion device 2-1, an edge node processing device 2-2 and a power transmission line 3, and the method comprises the following steps:
step 1) data acquisition. The network node 1-1 acquisition equipment acquires various types of data, mainly comprising voltage, current, phase angle and power under various communication protocols, and user electricity utilization information is formed at intervals of 15 minutes.
And 2) supplementing parameters. The edge node 2-1 fusion equipment mixes the data, extracts data check bits, line numbers, user numbers, voltage, current, phase angle and power according to different communication protocol field characteristics, filters inferior information through the data check bits, and forms voltage, current, phase angle, power and time information which are orderly sequenced according to the line numbers-user numbers according to actual acquisition time.
Step 3) data processing. The edge node processing device 2-2 processes the data in unit time with 60 minutes as unit time and 15 minutes as time length:
{A}＝[U a I a θ a P a T a ] b (1)
a＝1,2,3,4b＝1,2,...24
(2)
B＝(c 1、2、3 ,[A 1 、A 2 、…]) (4)
{C}＝[U a I a θ a P a T a c 1、2、3 ] b (5)
in the formulae (1) - (5) { A } represents the set of the fusion data, a represents the number of data packets per unit time, b represents the unit time length per day, U a 、I a 、θ a 、P a 、T a Sequentially representing voltage, current, phase angle, power and time information in the data group, wherein A represents normalization processing of data in the set { A }, and classification marking of load data in unit time to form load transition sets B and c 1 Representing a lower power load during this period c 2 Representing normal power supply load in the period of time c 3 Representing the overflow of the power supply load in the time period, and forming an all-day load set { C } according to the division conditions of different time periods.
In step 3), the embodiment supplements the sampling time in the electricity utilization information acquired by the physical network, normalizes the electricity utilization information, reduces the influence of amplitude fluctuation, ensures the compatibility and consistency of different acquired data, sorts and marks the data samples before the edge node interacts with the information network, and reduces the complexity of overall network calculation.
And 4) data interaction. The network control center 4 analyzes the load data all the day, and takes the line with the largest load fluctuation in the power transmission line as a fragile line under the condition of meeting the minimum network fluctuation load:
D＝C+α (6)
L＝d(U、I、θ) (8)
sub(ΔD) min 、(ΔL) max (11)
in the formulas (6) - (11), D represents the power supply load of the network node, C represents the load consumption of the user, α represents the load consumption of other devices, E represents the load of the whole network, n represents the number of all nodes of the network, m represents the number of all lines of the network, L represents the load flowing on the transmission line, β represents the dielectric loss and noise loss of the transmission channel of the network, D represents the influence coefficients of the node devices and the transmission line, (U, I, θ) represents the matrix of the node devices, E represents the coefficient adjustment weight, Δd represents the power supply load variation of the nodes in the network in unit time, and Δl represents the power transmission line load variation in unit time.
In step 4), the relation between macroscopic network power supply load and consumption load and the relation between microscopic power transmission lines and between edge nodes and network nodes are established, and the relation between the edge nodes and the power transmission line load is realized by introducing influence coefficients; in the embodiment, the load type of the network node is identified through the coefficient adjustment weight, the influence coefficient is negative when the network node is in low-level load, and the influence coefficient is positive when the network node is in high-level load; when the load fluctuation of the whole network in unit time is minimum, the transmission line is considered as a fragile line when the maximum load fluctuation occurs, and a reference basis is provided for the load scheduling and distribution of the whole network by the network control center.
Step 5) service decomposition. When the network control center processes daily business, the load level of the network node is perceived through the edge node, when the business is decomposed to the network node, the load level change is not large, so that the business can be distributed to the network node at the moment, otherwise, the business is distributed to other network nodes, so that tasks are distributed to the network node reasonably and efficiently, and the processing speed and the control instantaneity of the whole network are improved. In particular, the present embodiment does not explicitly specify evaluation indexes, such as node operation efficiency, energy consumption, traffic consumption, task delay, execution time, and the like.
The foregoing is merely illustrative of the preferred embodiments of the present invention and is not intended to limit the embodiments and scope of the present invention, and it should be appreciated by those skilled in the art that equivalent substitutions and obvious variations may be made using the teachings of the present invention, which are intended to be included within the scope of the present invention.
Claims (4)
1. A fragile line identification method based on edge calculation is characterized by comprising the following steps: the transmission process of the physical network, the edge calculation and the information network is interacted with the network control center through the network node acquisition equipment, the edge node fusion equipment, the edge node processing equipment and the power transmission line; the method comprises the following steps:
step 1, data acquisition; acquiring various types of data by network node acquisition equipment, wherein the data comprise voltage, current, phase angle and power under various communication protocols, and forming user electricity utilization information at intervals of 15 minutes;
step 2, parameter supplementation; mixing the data by the edge node fusion equipment, extracting data check bits, line numbers, user numbers, voltages, currents, phase angles and power according to field characteristics of different communication protocols, filtering inferior information through the data check bits, and forming voltage, current, phase angles, power and time information which are orderly sequenced according to the line numbers-the user numbers according to actual acquisition time;
step 3, data processing; processing the data in unit time by using the edge node processing equipment with 60 minutes as unit time and 15 minutes as time length;
step 4, data interaction; the network control center analyzes the load data all the day, and takes a line with the largest load fluctuation in the power transmission line as a fragile line under the condition of meeting the minimum network fluctuation load;
step 5, service decomposition; when the network control center processes daily service, the load level of the network node is perceived through the edge node, when the service is decomposed to the network node, the load level change is not large, so that the service can be distributed to the network node at the current moment, and otherwise, the service is distributed to other network nodes.
2. The edge computation-based frangible line identification method of claim 1, wherein: and (3) supplementing the sampling time in the step (3) into electricity utilization information acquired by a physical network, normalizing the electricity utilization information, and classifying and marking the data samples before the edge nodes interact with the information network.
3. The edge computation-based frangible line identification method of claim 1, wherein: the implementation of the step 4 comprises the following steps:
step 4.1, establishing a macroscopic relation between network power supply load and consumption load and a microscopic relation between a power transmission line and an edge node and a network node, and providing an influence coefficient to realize the relation between the edge node and the power transmission line load, wherein when the network node load belongs to a normal level, the power transmission line load is stable, and when the network node load changes drastically, the redundant load is regulated to the power transmission line;
step 4.2, identifying the load type of the network node through the coefficient adjustment weight, wherein the influence coefficient is negative when the network node is under low-level load, and the influence coefficient is positive when the network node is under high-level load;
and 4.3, when the overall load fluctuation of the network in unit time is minimum, and the power transmission line is a fragile line when the maximum load fluctuation occurs.
4. A power information coupling network structure for use in an edge computation based frangible line identification method of claim 1, characterized in that: the system comprises a network node, an edge node, a power transmission line and a network control center, wherein physical carriers of the network node are a generator, a transformer and safety equipment, the physical carriers are used for observing the power flow and load distribution of the network node, and terminal interfaces are reserved for upgrading and reconstruction of equipment; the edge node comprises novel equipment for expanding and accessing the network node, and is used for expanding the functional application range of the network node and carrying out fine-granularity and high-density secondary perception on the multi-dimensional data types; the power transmission line comprises various power transmission lines which are used as transmission channels of data flow and information flow and are used for adjusting current flow and load distribution in a network; the network control center comprises a port driver, a communication protocol, an intelligent algorithm and a visual interaction interface, and realizes the perception and real-time feedback of the network state through bidirectional interaction with the edge node.
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